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Genes and hormonal factors involved in the development or recurrence of breast cancer
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Genes and hormonal factors involved in the development or recurrence of breast cancer
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Content
GENES AND HORMONAL FACTORS INVOLVED IN THE DEVELOPMENT
OR RECURRENCE OF BREAST CANCER
by
Eunjung Lee
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(EPIDEMIOLOGY)
May 2008
Copyright 2008 Eunjung Lee
ii
TABLE OF CONTENTS
LIST OF TABLES iii
LIST OF FIGURES iv
Chapter 1. Introduction 1
1.1 Genes and hormonal factors involved in the development of breast cancer 1
1.2 Genes involved in the recurrence of breast cancer 5
Chapter 2. Evaluation of unclassified variants (UVs) in the breast cancer
susceptibility genes BRCA1 and BRCA2 using five methods 8
2.1 Summary 8
2.2 Background 9
2.3 Methods 12
2.4 Results 21
2.5 Discussion 28
2.6 Conclusions 34
Chapter 3. The effect of oral contraceptives and reproductive factors on breast
cancer risk in BRCA1/2 mutation carriers and non-carriers 35
3.1 Summary 35
3.2 Background 36
3.3 Methods 39
3.4 Results 44
3.5 Discussion 53
Chapter 4. GRP78 as a novel predictor of responsiveness to chemotherapy in
breast cancer 60
4.1 Summary 60
4.2 Background 61
4.3 Materials & Methods 63
4.4 Results 68
4.5 Discussion 77
Bibliography 80
Appendices 92
Appendix A. Supplemental methods: sequencing of BRCA1 and BRCA2 genes 92
Appendix B. Sequences used for cross-species comparison of BRCA1/2 96
Appendix C. Classification of significance of BRCA1/2 variants identified
among early onset breast cancer patients in Los Angeles and comparison with
classification according to BIC (Version updated April 05, 2007). 97
Appendix D. Specific detection of GRP78 by H129 antibody 121
Appendix E. Multivariable analyses stratified by each of the covariates. 122
iii
LIST OF TABLES
Table 2.1 Mean Grantham matrix score of BRCA1/2 variants (UVs) according
to classification using allele-frequency, Polyphen, and sequence conservation 23
Table 2.2 Joint distribution of BRCA1/2 variants (UVs) according to
classification using allele-frequency, Polyphen, and sequence conservation 24
Table 2.3 Association between family history of breast or ovarian cancer and
BRCA1 or BRCA2 status of breast cancer patients 25
Table 2.4 Association between family history of breast or ovarian cancer and
BRCA1 or BRCA2 status of breast cancer patients 29
Table 3.1 Characteristics of study subjects according to their disease status and
BRCA1/2 mutation status 45
Table 3.2 Association between hormone-related factors and breast cancer by
BRCA1/2 mutation status 48
Table 3.3 Association between use of combined oral contraceptives (OC) and
breast cancer risk 51
Table 3.4 The role of high-dose and low-dose OC use on breast cancer risk by
age 52
Table 4.1 Association of patient characteristics with tumor block availability or
time to recurrence 69
Table 4.2 Association between GRP78 expression and patient characteristics 73
Table 4.3 Relative risk of recurrence associated with GRP78 expression 76
iv
LIST OF FIGURES
Figure 2.1 Illustration of the classification scheme of BRCA1/2 variants 19
Figure 4.1 Photomicrographs of immunohistochemical staining of GRP78 72
Figure 4.2 Probability of remaining recurrence-free according to GRP78
expression in patients treated with adriamycin-based adjuvant chemotherapy 75
v
ABSTRACT
BRCA1 and BRCA2 (BRCA1/2) genes are well-established breast cancer
susceptibility genes. A large number of variants in these genes has been reported,
including variants with clearly deleterious effects and variants with unknown
significance on breast cancer risk. Classification of such unclassified variants
(UVs) is an area of growing interest, but no study has systematically assessed
whether the various classification methods are biologically meaningful. Further,
given that not all BRCA1/2 deleterious mutation carriers develop breast cancer,
environmental modifiers of breast cancer risk in BRCA1/2 mutation carriers need to
be identified. In this dissertation, I present results from a population-based case-
control study of young breast cancer patients to investigate these issues.
In my first paper, I used sequencing data of BRCA1/2 genes in 1,469 breast cancer
patients. There were 262 distinct BRCA1/2 variants, including 147 UVs.
Application of various methods to classify each variant showed that the BRCA1 UV
carriers, but not BRCA2 UV carriers, who were classified as ‘high risk’ using each
classification method were more likely to have a family history than those
classified as ‘low risk’.
vi
In a second paper, I examined potential modifiers of the effect of BRCA1/2 on
breast cancer risk. An increasing number of full-term pregnancies was associated
with a decreased breast cancer risk, regardless of BRCA1/2 status. Breastfeeding
was protective in the BRCA1/2 mutation non-carriers but not in the carriers. OC
use overall was not associated with risk of breast cancer, regardless of BRCA1/2
status.
There is a critical need for a new prognostic and predictive marker of breast cancer
treatment. Additional work to investigate treatment outcome of BRCA1/2 mutation
carriers would have been an important next step in this population-based sample of
young breast cancer patients, but survival and treatment data of this study
population were not collected. However, in the third paper of my dissertation, I
explored the question of treatment response in a separate breast cancer population
with regard to 78kD glucose-regulated protein (GRP78), which has been shown to
confer chemoresistance to human breast cancer cells. Our results from a
retrospective cohort of 127 breast cancer patients treated with adriamycin-based
chemotherapy showed that GRP78 positive expression, evaluated by
immunohistochemistry, was associated with a shorter time to recurrence (HR=1.78;
p=0.16). Interestingly, our subgroup analyses showed that there is a potential
interaction between GRP78 and taxane-addition. The use of GRP78 as a predictor
for chemoresponsiveness warrant larger studies.
1
Chapter 1. Introduction
1.1 Genes and hormonal factors involved in the development of breast cancer
1.1.1 Genetic susceptibilities to breast cancer and BRCA1/2
Breast cancer susceptibility genes
It has been reported that women who have a first-degree relative diagnosed with breast
cancer are twice as likely to develop breast cancer as those without a family history, and
this figure increases with an increasing number of first-degree relatives with the disease
(2001). This familial aggregation of breast cancer could be due to either genetic factors
or shared environmental factors, but the results of twin studies suggest that the genetic
factors play a substantial role (Ahlbom et al. 1997; Lichtenstein et al. 2000; Mack et al.
2002; Antoniou and Easton 2006). BRCA1 and BRCA2 genes were identified as the
first breast cancer susceptibility genes in mid 1990’s, and about 15% of breast cancer
patients who have a first-degree relative with breast cancer have mutations in BRCA1/2
(Peto et al. 1999; 2000). Several other genes including TP53, PTEN, LKB1, ATM, and
CHEK2 have been reported as breast cancer susceptibility genes. Recent genome-wide
association studies have further identified several candidate genes that are associated
with a moderate risk of breast cancer (Cox et al. 2007; Easton et al. 2007). Of all these
genes, BRCA1 and BRCA2 are among the genes with the highest breast cancer
penetrance: according to a recent US study, the cumulative risk of breast cancer by age
70 among carriers of germline deleterious mutation in these genes were estimated as
46% and 43%, respectively (Chen et al. 2006).
2
Functions of BRCA1/2
BRCA1/2 as tumor suppressor genes: According to Knudson’s two-hit hypothesis, for a
tumor suppressor gene to cause a cancer in a genetically predisposed individual (who
inherited a mutated copy of the gene), it is necessary that the individual lose the
function of the remaining wild-type copy (Knudson 1985). BRCA1/2 has been
proposed as tumor suppressor genes based on the observation that the majority of breast
cancer patients who carry a germline deleterious mutation of BRCA1 or BRCA2 gene
have lost the function of the remaining wild-type copy through loss of heterozygosity
(~90% of patients) or DNA methylation of the wild-type BRCA1 allele (Esteller et al.
2001; Osorio et al. 2002). It is assumed that germline mutation carriers of BRCA1/2,
who inherited only one copy of mutated BRCA1/2, acquire the second hit somatically in
their breasts and develop breast cancer (or acquire the second hit in their ovary for
ovarian cancer patients).
Cellular functions of BRCA1/2: BRCA1 is involved in DNA repair (Scully et al. 1997;
Moynahan et al. 1999), transcription (Chapman and Verma 1996; Anderson et al. 1998),
and the cell cycle checkpoint in the DNA damage response (Somasundaram et al. 1997;
Williamson et al. 2002; Yarden et al. 2002). BRCA2 is also involved in DNA repair
(Chen et al. 1998; Yu et al. 2000; Davies et al. 2001; Moynahan et al. 2001), but its role
in transcription and cell cycle checkpoint is less clear (Lee et al. 1999; Greenblatt et al.
2001; Yoshida and Miki 2004).
3
1.1.2 Variants of unknown significance in BRCA1/2
The prevalence of deleterious mutations in BRCA1/2 among breast cancer patients is
estimated to be about 2-3% (Wooster and Weber 2003). However, a large number of
variants of unknown significance have also been reported, affecting about 9% of breast
cancer patients. Understanding the significance of these unclassified variants (UVs) is a
great challenge not only to researchers of familial breast cancer but also to clinicians
consulting patients and their families carrying these UVs. Various methods have been
proposed to determine the significance of UVs, but no study has systematically assessed
whether women carrying the suspected deleterious UVs have characteristics commonly
seen among women carrying known deleterious or disease-causing mutations in
BRCA1/2. If this was the case, it would suggest that the UV identified as deleterious
using this method may be truly deleterious.
In Chapter 2, I present results from a systematic analysis to identify and classify UVs in
BRCA1/2 genes from a large number of population-based young breast cancer patients.
We used various classification systems and systematically associated such classification
categories with risk characteristics of the carrier women. This work has been published
(Lee et al. 2008).
1.1.3 Gene-environment interactions with BRCA1/2
Evidence for gene-environment interactions
4
Although BRCA1/2 genes have much higher breast cancer penetrance than all the
recently identified breast cancer susceptibility genes (Thompson and Easton 2004; Cox
et al. 2007; Easton et al. 2007; Stacey et al. 2007), it is clear that not all BRCA1/2
mutation carriers, even within a family, develop breast cancer. The effect of a specific
BRCA1/2 mutation appears to vary from individual to individual. It is therefore
possible that other genes, endogenous factors, or environmental risk factors will play a
role in breast cancer risk in BRCA1/2 mutation carrying women (Narod et al. 1995).
Evidence for gene-hormonal factor interactions
Individuals with a BRCA1/2 mutation are more likely to develop cancers of the breast
and ovary, and possibly of the colon and prostate (Ford et al. 1994). Since hormones
are considered to play a role in the etiology of these cancers, it seems likely that
BRCA1/2 may be important regulators of growth and differentiation in hormonally
responsive epithelial cells. Consistently, it has been shown that expression of BRCA1/2
is elevated in highly proliferating and differentiating cells at puberty and pregnancy
(Marquis et al. 1995; Rajan et al. 1997). Estrogen and progesterone stimulate breast
cell proliferation (Yager and Davidson 2006). Considering that BRCA1/2 is involved
in DNA repair, and that unrepaired DNA damage in proliferating cells can be
tumorigenic, the effect of estrogen and progesterone on breast cancer risk might be even
stronger among BRCA1/2 mutation carriers than among the general population. In 1999,
a study based on genetic testing centers reported that having children increases breast
cancer risk in carriers of BRCA1/2 mutations (Jernstrom et al. 1999). However, results
5
from an analyses involving a larger number of patients of the same study was
inconsistent with the original findings (Cullinane et al. 2005). Other groups have
investigated the role of reproductive factors and use of exogenous hormones such as
oral contraceptives (OCs) among the BRCA1/2 mutation carriers, but results have been
mixed (Narod et al. 1995; Jernstrom et al. 1999; Rebbeck et al. 2001; Hartge et al. 2002;
King et al. 2003; Tryggvadottir et al. 2003; Jernstrom et al. 2004; Cullinane et al. 2005;
Kotsopoulos et al. 2005; Andrieu et al. 2006; Antoniou et al. 2006; Chang-Claude et al.
2007) (Ursin et al. 1997; Narod et al. 2002; Milne et al. 2005; Haile et al. 2006).
In Chapter 3, I present results from an investigation of the role of select reproductive
and hormonal factors among BRCA1/2 mutation carriers as well as among BRCA1/2
mutation non-carriers in our population-based case-control study of young breast cancer
patients.
1.2 Genes involved in the recurrence of breast cancer
1.2.1 Breast cancer recurrence and the need for a new predictive marker
Adjuvant therapy for early breast cancer improves survival of patients. However, a
substantial proportion of women develop recurrence even within 5 years, and drug
resistance is considered a major contributing factor (Early Breast Cancer Trialists'
Collaborative Group 1998). There is critical need for a novel predictive factor of
chemo-responsiveness which will help clinicians choose chemotherapeutic drugs and
ultimately lead to improved survival of breast cancer patients.
6
It would be important to investigate prognosis and response to chemotherapy of the
breast cancer patients with mutations in BRCA1/2. Unfortunately, we do not have data
on treatment outcome, survival, and the treatment information in our population-based
study of young breast cancer patients. The 78 kDa glucose-regulated protein (GRP78)
is another promising candidate of a predictive marker: in vitro studies have shown that
GRP78 is associated with resistance to topoisomerase-targeting chemotherapeutic drugs
(Reddy et al. 2003; Dong et al. 2005; Li and Lee 2006; Ranganathan et al. 2006).
However, the predictive value of GRP78 in human breast cancer has not been
investigated. Therefore, in Chapter 4, we investigated the question of treatment
response according to GRP78 expression level in a separate population of breast cancer
patients. This work has been published (Lee et al. 2006).
1.2.2 GRP78 as a novel predictive marker of chemo-responsiveness of breast
cancer patients
Physiological function of GRP78
The 78 kDa glucose-regulated protein (GRP78) is a central regulator of endoplasmic
reticulum function, and plays roles in protein folding and assembly (Lee 2001). GRP78
is induced when cells are stressed under adverse physiological conditions such as during
glucose or oxygen starvation. GRP78 functions as a sensor of endoplasmic reticulum
stress and delivers signals preventing apoptosis (Rutkowski and Kaufman 2004).
7
The role of GRP78 in chemo-resistance
In vitro experiments have suggested that GRP78 is associated with resistance to
topoisomerase-targeting chemotherapeutic drugs (Reddy et al. 2003; Dong et al. 2005;
Li and Lee 2006; Ranganathan et al. 2006). However, the predictive value of GRP78 in
human breast cancer has not been investigated. In Chapter 4, I present results from an
investigation of whether GRP78 predicts chemo-responsiveness of breast cancer
patients treated with topoisomerase-targeting chemotherapy. For this study, I worked
with a medical oncologist to identify 209 stage II/III breast cancer patients at
USC/Norris Comprehensive Cancer Center, and assembled a dataset including detailed
information on demographic, clinical, and histopathologic data, as well as treatments
and recurrence outcomes. My roles also include participation in pathological
assessment procedures, data analysis, and manuscript preparation.
1.2.3 Summary
In summary, this project addresses questions regarding the roles of genetic and
environmental risk factors on breast cancer development and recurrence, specifically
exploring the roles of unclassified variants of BRCA1/2 and reproductive and hormonal
factors on breast cancer risk, and the role of GRP89 on breast cancer recurrence. The
exploration of genetic markers and lifestyle factors that influence susceptibility or
treatment response may contribute to progress in breast cancer prevention and treatment.
8
Chapter 2. Evaluation of unclassified variants (UVs) in the breast
cancer susceptibility genes BRCA1 and BRCA2 using five methods
2.1 Summary
BACKGROUND: Efforts are ongoing to determine the significance of unclassified
variants (UVs) in the breast cancer susceptibility genes BRCA1/2, but no study has
systematically assessed whether women carrying the suspected deleterious UVs have
characteristics commonly seen among women carrying known deleterious or disease-
causing mutations in BRCA1/2.
METHODS: We sequenced BRCA1/2 genes in 1,469 population-based female breast
cancer patients diagnosed between the ages of 20-49. We used existing literature to
classify variants into known deleterious mutations, polymorphic variants, and UVs.
The UVs were further classified as high or low risk based on 5 methods: allele
frequency, Polyphen, sequence conservation, Grantham scores, and a combination of
the Grantham score and sequence conservation. Furthermore, we examined whether
patients who carry the variants classified as ‘high risk’ using these methods have risk
characteristics similar to patients with known deleterious BRCA1/2 mutations (early age
at diagnosis, family history of breast or ovarian cancer, and negative ER/PR).
9
RESULTS: We identified 262 distinct BRCA1/2 variants, including 147 UVs, in our
study population. The BRCA1 UV carriers, but not BRCA2 UV carriers, who were
classified as ‘high risk’ using each classification method were more similar to the
deleterious mutation carriers with respect to family history than those classified as ‘low
risk’. For example, the odds ratio (OR) of having a first-degree family history for the
‘high-risk’ women classified using Polyphen was 3.39 (95%CI=1.16-9.94) compared to
normal/polymorphic BRCA1 carriers. The corresponding OR of ‘low-risk’ women was
1.53 (95%CI=1.07-2.18). The OR for ‘high-risk’ women defined by allele frequency
was 2.00 (95%CI=1.14-3.51), and that of ‘low-risk’ women was 1.30 (95%CI=0.87-
1.93).
CONCLUSIONS: The results suggest that the 5 classification methods yielded similar
results. Polyphen was particularly better at isolating BRCA1 UV carriers likely to have
a family history, and may therefore help to classify BRCA1 UVs. Our study suggests
that these methods may not be as successful in classifying BRCA2 UVs.
2.2 Background
2.2.1 Function of BRCA1 and BRCA2 genes
In the early 1990’s, the breast cancer susceptibility genes BRCA1 and BRCA2 were
identified through linkage analyses (Hall et al. 1990; Miki et al. 1994; Wooster et al.
1994; Wooster et al. 1995). BRCA1, located on chromosome 17q12-q21, consists of 24
exons encoding a protein of 1863 amino acids and is involved in DNA repair (Scully et
10
al. 1997; Moynahan et al. 1999), transcription (Chapman and Verma 1996; Anderson et
al. 1998), and cell cycle checkpoint in DNA damage response (Somasundaram et al.
1997; Williamson et al. 2002; Yarden et al. 2002). BRCA2, located on chromosome
13q12-q13, consists of 27 exons encoding a protein of 3418 amino acids and is also
involved in DNA repair (Chen et al. 1998; Yu et al. 2000; Davies et al. 2001;
Moynahan et al. 2001), but its role in transcription and cell cycle checkpoint is less
clear (Yoshida and Miki 2004).
2.2.2 Variants of BRCA1 and BRCA2 genes
Since the discovery of the BRCA1 and BRCA2 genes, a total of 1643 and 1856 distinct
variants have been reported in the Breast Cancer Information Core Database (BIC
Database, http://research.nhgri.nih.gov/projects/bic) for BRCA1 and BRCA2 as of April,
2007. Among them, frameshift mutations, nonsense mutations, splice variants and a
few well-documented missense mutations are considered deleterious (Shattuck-Eidens
et al. 1997) while synonymous variants have been considered benign or polymorphic.
A large number of missense or intronic variants of BRCA1 or BRCA2 remain of
unknown significance. The proportion of breast cancer patients who carry these
unclassified variants (UV) is about 9% (Chenevix-Trench et al. 2006). Given that only
2-3% of breast cancer patients have deleterious mutations in BRCA1 or BRCA2 (Malone
et al. 2006), understanding the clinical significance of this relatively large number of
UVs is of great importance.
11
2.2.3 Approaches to classifying UVs
Functional studies can provide direct insight into whether the UV has biological
consequences, but few of these studies have been done (Vallon-Christersson et al. 2001;
Phelan et al. 2005). Other approaches have been applied to classify the significance of
UVs including: (i) comparisons of allele frequencies (Shattuck-Eidens et al. 1997); (ii)
algorithms such as Polyphen (see Materials and Methods) (Ramensky et al. 2002); (iii)
examination of sequence conservation across species (Fleming et al. 2003; Abkevich et
al. 2004; Burk-Herrick et al. 2006); and (iv) characterization of the physicochemical
nature of the amino acid substitutions (Grantham scores) (Grantham 1974; Abkevich et
al. 2004). A combination approach of (iii) and (iv) method was applied to classify a
large number of UVs (Abkevich et al. 2004). However, no systematic evaluation has
been conducted to determine whether patients who carry the variants classified as ‘high
risk’ using these methods have similar characteristics as patients with known
deleterious BRCA1/2 mutations, which would suggest that these ‘high-risk’ UVs are
deleterious.
2.2.4 Characteristics of BRCA1/2 mutation carrier women as used to evaluate the
classification scheme
Breast cancer patients with a known deleterious mutation in BRCA1/2 are more likely to
have a family history of breast or ovarian cancer (Berry et al. 2002) and an earlier age
of diagnosis than non-carrier patients (Shattuck-Eidens et al. 1997; Eerola et al. 2005).
In addition, BRCA1 deleterious mutation carriers are more likely to have estrogen
12
receptor (ER) and progesterone receptor (PR) negative tumors, than women without
such mutations (Eerola et al. 2005). In the current analyses, we classified BRCA1/2
UVs using the 4 methods listed above and a combination of Grantham scores and
sequence-conservation. We then evaluated the validity and usefulness of each method
by comparing the risk categories of UV carriers with respect to these three well-defined
characteristics of BRCA1/2 deleterious mutation carriers.
2.3 Methods
2.3.1 Subjects
Data collection methods for this study have previously been described (Ma et al. 2006).
In brief, female patients diagnosed with histologically-confirmed first primary invasive
breast cancer were identified through the Los Angeles County Cancer Surveillance
Program (CSP), a population-based Surveillance, Epidemiology and End Results
registry supported by the State of California and the National Cancer Institute. Eligible
cases were: (1) US-born and English speaking, (2) white (including Hispanic) or
African-American, (3) aged 20-49 years at diagnosis, and (4) Los Angeles County
residents at diagnosis. A total of 2,882 eligible cases were identified (2,534 whites and
348 African-Americans) between February, 1998 and May, 2003. Recruitment of
African-Americans began after the initiation of the study with eligible African-
American cases diagnosed from January, 2000 to May, 2003.
13
Among the 2,882 potentially eligible cases, 1,794 (62%) were interviewed (1,585 white,
209 African-American). Reasons for non-participation were patient refusal (n=428), no
longer a resident of Los Angeles County (n=37), not located (n=88), death (n=38),
serious illness or disability (n=18), physician refusal (n=50), or inability to schedule the
interview within 18 months of diagnosis (n=429). The study was approved by the
Institutional Review Board of the University of Southern California. All participants
provided written informed consent.
2.3.2 Data and blood specimen collection
An in-person interview was completed using a modified version of the structured
questionnaire used in the Women's Contraceptive and Reproductive Experiences
(CARE) Study (Marchbanks et al. 2002). The questionnaire included detailed
information on demographic characteristics, family history of breast or ovarian cancer,
ethnic origin, and environmental factors such as oral contraceptive use, reproductive
history, alcohol use, smoking history, and radiation exposure. We obtained information
up to the date of breast cancer diagnosis. Blood specimens were collected from 1519
participants (85%) and transported to the Norris Cancer Center Genetics Core
Laboratory in Styrofoam containers on frozen ice packs. For the first 50 samples, buffy
coat was immediately extracted and stored, and for the remaining samples we stored
whole blood.
14
2.3.3 Sequencing of BRCA1 and BRCA2 genes
All BRCA1 and BRCA2 exons (except BRCA1 exons 1 and 4 and BRCA2 exon 1) as
well as all exon-intron boundaries were sequenced. Exon 1 was not sequenced for
either gene because it is located upstream of the translation start site in both genes.
BRCA1 exon 4 was not sequenced because it is not found in the normal BRCA1 mRNA
transcript. DNA extraction, amplification and sequencing were done in the USC
Genomics Core Laboratory using a protocol similar to that previously described
(McKean-Cowdin et al. 2005). The detailed procedures are described in Supplemental
Methods (see Appendix A). We sequenced BRCA1/2 genes for 1469 out of 1519 blood
specimens. We were unable to sequence the remaining 50 specimens due to insufficient
DNA. Thirty-three randomly selected, blinded samples were re-sequenced for quality
control purposes. The discordance rate was 0.19%: 16 discordant sequencing results
out of the total 8646 variant sites sequenced (262 variant sites for each of the 33
samples). In addition, 166 subjects who had non-informative sequencing results on one
or more variant sites were re-sequenced or genotyped using TaqMan assay (for I2490T,
N372H, and N991D) as previously described (Freedman et al. 2004).
2.3.4 Epidemiologic and histologic variables
Age at diagnosis was categorized as <35, 35-39, 40-44, and 45-49 years. We classified
women based on their family history of breast or ovarian cancer as follows: (1) first-
degree relatives (mother and full sisters); (2) second-degree relatives (mother’s or
father’s full sisters, and grandmothers); (3) none; (4) unknown first-degree family
15
history. We considered unknown second-degree family history as no family history.
ER and PR status of the breast cancer was obtained by abstracting pathology reports
collected by CSP. Among the 1469 subjects, ER/PR information was available for
1216 patients (83%). For the ER/PR analyses, we excluded 63 patients who had
borderline ER/PR status and 101 patients whose ER/PR status was +/- or -/+, leaving
1052 patients with +/+ or -/- receptor status.
2.3.5 Classification of BRCA1/2 mutation status
We classified each identified BRCA1/2 variant according to its predicted functional and
biological significance as follows: (1) definitely-disease-causing variants (DDCVs),
including frameshift mutations, nonsense mutations, splice variants that were previously
reported to affect splicing or located at the exon/intron boundary, and missense variants
that were previously shown to be deleterious; (2) UVs, including in-frame
deletion/insertions, intronic variants that might affect splicing by creating a splice
donor/acceptor site, variants next to the exon/intron boundary, and most missense
variants; (3) benign polymorphic variants, including synonymous variants, intronic
variants that are unlikely to affect splicing, and a few missense mutations that were
reported to be benign (See Appendix B for a list of all variants identified in this study
with their classification and reasons and references for such classification).
2.3.6 Further classification of BRCA1 and BRCA2 UVs
We further classified BRCA1/2 UVs using the following methods.
16
1. Classification based on allele frequency
We divided the UVs into high-frequency UV (HFUV) versus low-frequency UV
(LFUV) depending on the minor allele frequency ( ≥1% versus <1%) in each ethnic
group (142 African-Americans, 222 Hispanic whites, 1105 non-Hispanic whites): if the
minor allele frequency is ≥1% in one or more ethnic groups, the UV was categorized as
HFUV. This categorization was based on the assumption that variants with high
frequency would be less likely to be disease-causing compared to variants with very
low frequency.
2. Polyphen-based classification
Polyphen (http://coot.embl.de/PolyPhen) is an algorithm that classifies the functional
effect of each missense variant into three catgories (probably damaging, possibly
damaging, and benign) . This classification is based on the chemical characteristics of
the substitution site (eg. disulfide bond, transmembrane region), alignment of
homologous sequences, and protein 3-D structures (Ramensky et al. 2002). UVs other
than missense variants are not classified by Polyphen. Polyphen classification in this
report is based on access to the algorithm in March, 2007.
3. Classification based on sequence conservation across mammalian species.
A variant that occurs at a site with high-degree conservation is considered more likely
to be deleterious than a variant occurring at a site with low-degree conservation (Ng and
Henikoff 2006). For cross-species comparisons of the BRCA1/2 sequences, we selected
17
only mammals since the function of these two proteins could be different in mammals
than in other animals. We selected all mammalian species whose BRCA1/2 sequences
were reported in the NCBI gene database or whose complete coding sequences were
reported in the NCBI nucleotide sequence database. Ten species for BRCA1 and 5
species for BRCA2 met these criteria (see Appendix C). Sequence alignment was
performed using the Clustal W method (Thompson et al. 1994) and the MegAlign
software (DNASTAR, Inc, WI).
We classified BRCA1/2 missense variants into three categories (high, moderate, low-
degree conservation) depending on the number of the species that had a different amino
acid from that of human at the site of variation. For each UV in BRCA1, we considered
differences in 0~1 species out of the 10 examined to represent high-degree conservation,
differences in 2~3 species to represent moderate conservation, and difference in 4 or
more species to represent low conservation. For BRCA2, we compared sequences of 5
species: no difference in all 5 species was considered high-degree conservation, 1~2
differences were considered moderate, 3 or more was considered low.
4. Classification based on Grantham Matrix Score (GMS).
GMS is a composite measure of the degree of amino acid substitution, taking into
account the side-chain composition, polarity, and molecular volume of the two amino
acids (Grantham 1974). We dichotomized GMS at 60, a criterion that was previously
used to define neutral missense variants (Abkevich et al. 2004).
18
5. Integration of sequence conservation and GMS.
We adopted a previously-reported classification scheme integrating the sequence
conservation and GMS (Abkevich et al. 2004). Briefly, if the variant was located at a
fully conserved site or led to a non-conservative substitution at a conserved site, it was
considered deleterious. If the variant amino acid is observed in other species or led to
conservative substitution, it was considered neutral. See Appendix A for further details.
2.3.7 Classification of women who carry UVs in BRCA1/2
Each subject was categorized hierarchically based on their BRCA1 and BRCA2 mutation
status (Figure 2.1). This means that anyone successfully classified by the first criterion
would not be further classified by the criteria that followed. This hierarchical
classification leads to mutually exclusive categories (DDCV carriers, UV carriers,
normal/polymorphic carriers, and patients with unknown mutation status) as follows:
(1) A patient was classified as a DDCV carrier if she had one or more of the DDCV(s);
(2) If the patient did not belong to the DDCV group and had a non-informative result at
any of the identified DDCV sites, she was classified as unknown; (3) If the patient did
not belong to (1) or (2) and carried one or more of the UVs, she was classified as a UV
carrier; (4) If the patient did not belong to (1)~(3) and any of the sequencing results at
the identified UV sites was non-informative for the subject, she was classified as
unknown; (5) If the patient did not belong to (1)~(4), she was classified as a
polymorphic or normal genotype carrier.
19
Figure 2.1 Illustration of the classification scheme of BRCA1/2 variants
20
UV carriers were further classified hierarchically into mutually exclusive categories of
‘high risk’, ‘moderate risk’, ‘low risk’, and ‘unknown risk’ according to the various UV
classifications. For example, when applying the allele frequency method, a UV carrier
was classified as ‘high risk’ if the subject carried one or more of the LFUV; ‘Unknown
risk’ if any of the sequencing results at the LFUV site was non-informative for the
subject; ‘low risk’ if the subject carried one or more of the HFUV; ‘Unknown risk’ if
any of the sequencing results at the HFUV site was non-informative for the subject.
Classification using other methods such as Polyphen, GMS, or sequence conservation
followed the same hierarchical logic. Six BRCA1 UV carriers and six BRCA2 UV
carriers with a possible splice variant or in-frame deletion were categorized only by
allele frequency since Polyphen, GMS, and the integrated GMS/conservation methods
are not applicable to these splice variants and in-frame deletions. Therefore, these
women were excluded from the analyses using Polyphen, GMS, conservation, and the
integrated GMS/conservation methods.
2.3.8 Statistical analyses
We compared UV classification methods of allele-frequency, Polyphen, sequence
conservation, and GMS by examining the pairwise joint distribution of BRCA1/2 UVs
as classified using each method. Tests for linear trend in GMS across the three UV
categories classified using Polyphen and the sequence conservation method were
conducted in linear regression models. T-tests were used to compare mean GMS across
two UV categories using allele frequency. We assessed whether UV classifications
21
using allele frequency, Polyphen and the sequence-conservation method are correlated
using an exact Mantel-Haenszel chi-square test. We performed case-case analyses to
examine the association between BRCA1 or BRCA2 carrier status categorized using
each method (exposure variable) and outcome variables (clinical and disease
characteristics). Case-case analyses were conducted using polychotomous logistic
regression when the outcome variable was family history of breast or ovarian cancer.
The association with ER/PR status was analyzed using logistic regression. We used
linear regression where the outcome variable was age at diagnosis of breast cancer.
When examining BRCA1, results were adjusted for BRCA2 mutation status (DDCV,
non-DDCV, unknown) and vice versa. All p-values reported are 2-sided. SAS 9.1 was
used for all analyses (SAS Institute, NC).
2.4 Results
A total of 105 distinct BRCA1 variants (including 32 DDCV) and 157 distinct BRCA2
variants (including 27 DDCV) were identified in the 1469 breast cancer patients (See
Appendix C). Among those, 22 BRCA1 and 30 BRCA2 variants had not been reported
in the BIC as of April, 2007.
2.4.1 Correlated classifications using various approaches
Classification using Polyphen appeared to be correlated both with GMS and
conservation method: BRCA1/2 missense variants classified as high risk (probably-
damaging) using Polyphen had a higher mean GMS than those classified as low risk
22
(benign missense variants) (Table 2.1). BRCA1/2 missense variants classified as benign
missense variants using Polyphen were generally located at sites with low degree of
sequence conservation while probably-damaging missense variants tended to be located
in highly-conserved regions (Table 2.2). However, GMS was not strongly correlated
with level of conservation across species (Table 2.1). Given the small number of
HFUVs of BRCA1/2, the classification using the allele-frequency method seemed to be
associated with the classifications using other methods, although not all of these
analyses achieved statistical significance.
2.4.2 Classification of case patients with regard to BRCA1 or BRCA2 status
Among the 1469 case patients in this study, 61 women carried a BRCA1 DDCV, and 34
women carried a BRCA2 DDCV. Among the remaining women, 307 and 860 women
were UV carriers in BRCA1 and BRCA2, respectively.
2.4.3 Classification of BRCA1/2 status in relation to epidemiologic and histologic
outcome variables
Family history of breast or ovarian cancer
BRCA1 DDCV carriers were substantially more likely to have a first-degree family
history of breast or ovarian cancer than the normal/polymorphic BRCA1 carriers
(OR=11.3, Table 2.3) after adjusting for BRCA2 mutation status. The UV carriers were
also significantly, though to a smaller extent, more likely to have a first-degree family
history than normal/polymorphic BRCA1 carriers (OR=1.54). The high-risk UV
23
Table 2.1 Mean Grantham matrix score of BRCA1/2 variants (UVs) according to
classification using allele-frequency, Polyphen, and sequence conservation
Gene Classification Level Number Grantham matrix score
*
Method of variants Mean SD Min Max
BRCA1
Allele-
frequency Low risk (HFUV) 5 38.2 20.7 10 56
High risk (LFUV) 39 69.7 45.0 10 194
P-value (t test) 0.13
Polyphen Benign missense 28 55.0 42.3 10 180
Possible-damaging 9 65.3 29.4 10 101
Probably-damaging 7 111.9 40.5 71 194
p for trend
§
0.002
Sequence
conservation Low 14 53.6 44.7 10 180
Moderate 14 70.9 43.5 10 154
High 16 73.0 44.2 10 194
p for trend
§
0.24
BRCA2
Allele-
frequency Low risk (HFUV) 18 67.7 39.7 5 149
High risk (LFUV) 77 87.0 52.9 10 205
P-value (t test) 0.15
Polyphen Benign missense 44 58.1 41.3 5 194
Possible-damaging 25 91.4 41.7 21 180
Probably-damaging 26 118.3 52.3 27 205
p for trend
§
<0.001
Sequence
conservation Low 33 71.5 49.4 10 194
Moderate 29 92.1 55.6 5 205
High 33 87.5 47.8 21 194
p for trend
§
0.20
* SD: standard deviation, Min: Minimum, Max: Maximum.
§
Based on F-test in a linear regression model.
Abbreviations: UV: unclassified variants; LFUV: low-frequency UV; HFUV: high-frequency UV.
24
Table 2.2 Joint distribution of BRCA1/2 variants (UVs) according to classification using
allele-frequency, Polyphen, and sequence conservation
Classification
Level Conservation Frequency
Gene
method
Low Moderate High HFUV LFUV
BRCA1 Frequency Low risk (HFUV) 3 1 1
High risk (LFUV) 11 13 15
p-value
§
0.26
Polyphen Benign missense 12 10 6 4 24
Possible-damaging 2 3 4 1 8
Probably-damaging 0 1 6 0 7
p-value
§
0.002 0.39
BRCA2 Frequency Low risk (HFUV) 10 6 2
High risk (LFUV) 23 23 31
p-value
§
0.018
Polyphen Benign missense 26 11 7 11 33
Possible-damaging 5 10 10 5 20
Probably-damaging 2 8 16 2 24
p-value
§
<0.001 0.089
§
Based on exact Mantel-Haenszel chi-square test.
25
Table 2.3 Association between family history of breast or ovarian cancer and BRCA1 or
BRCA2 status of breast cancer patients
Mutation/UV status None First degree
Second degree
n
§
n
§
OR (95% CI)
*
P
†
n
§
OR (95% CI)
*
P
†
BRCA1
||
Normal/polymorphism (reference) 600 166 1
282 1
DDCV 13 35 11.3 (5.73 - 22.5) <0.001
11 1.89 (0.83 - 4.31) 0.13
UV 156 67 1.54 (1.10 - 2.15) 0.012
75 1.02 (0.74 - 1.39) 0.90
UV classification using:
Allele frequency
High risk (LFUV) 39 21 2.00 (1.14 - 3.51) 0.016
22 1.20 (0.70 - 2.06) 0.52
Low risk (HFUV) 115 42 1.30 (0.87 - 1.93) 0.20
52 0.96 (0.67 - 1.37) 0.82
Polyphen
¶
Probably damaging missense 7 7 3.39 (1.16 - 9.94) 0.026
6 1.80 (0.60 - 5.40) 0.30
Possibly damaging missense 9 1 0.44 (0.06 - 3.54) 0.44
5 1.19 (0.40 - 3.60) 0.75
Benign missense 133 57 1.53 (1.07 - 2.18) 0.021
61 0.97 (0.70 - 1.36) 0.87
Sequence conservation
¶
High or Moderate
**
50 23 1.68 (0.99 - 2.85) 0.053
32 1.35 (0.85 - 2.16) 0.20
High 6 3 1.88 (0.46 - 7.63) 0.38
8 2.85 (0.98 - 8.30) 0.055
Moderate 44 20 1.66 (0.95 - 2.91) 0.076
23 1.10 (0.65 - 1.86) 0.72
Low 99 40 1.43 (0.95 - 2.16) 0.085
41 0.88 (0.60 - 1.31) 0.53
GMS
¶
High (>60) 15 10 2.38 (1.04 - 5.45) 0.039
10 1.42 (0.63 - 3.20) 0.40
Low ( ≤60) 134 55 1.46 (1.02 - 2.10) 0.039
63 1.00 (0.72 - 1.39) 0.98
GMS/ conservation
¶
Deleterious 4 2 1.74 (0.32 - 9.64) 0.52
3 1.63 (0.36 - 7.33) 0.53
Intermediate (Unclassified) 46 22 1.75 (1.02 - 3.01) 0.043
25 1.15 (0.69 - 1.91) 0.60
Neutral 99 40 1.44 (0.95 - 2.16) 0.083
44 0.95 (0.65 - 1.39) 0.78
BRCA2
‡
Normal/polymorphism (reference) 279 87 1
137 1
DDCV 11 13 3.69 (1.57 - 8.68) 0.003
10 1.83 (0.76 - 4.42) 0.18
UV 462 162 1.07 (0.79 - 1.46) 0.66
213 0.93 (0.72 - 1.21) 0.59
UV classification using:
Allele frequency
High risk (LFUV) 71 18 0.81 (0.45 - 1.45) 0.48
40 1.15 (0.74 - 1.78) 0.54
Low risk (HFUV) 385 138 1.09 (0.79 - 1.50) 0.59
168 0.88 (0.67 - 1.16) 0.36
Polyphen
¶
Probably damaging missense 32 7 0.73 (0.31 - 1.74) 0.48
17 1.09 (0.58 - 2.03) 0.79
Possibly damaging missense 108 28 0.79 (0.48 - 1.29) 0.34
42 0.78 (0.52 - 1.18) 0.24
Benign missense 310 118 1.15 (0.83 - 1.60) 0.41
146 0.95 (0.72 - 1.26) 0.73
Sequence conservation
¶
High or Moderate 157 42 0.80 (0.52 - 1.23) 0.31
61 0.78 (0.55 - 1.12) 0.18
High 96 30 0.92 (0.56 - 1.51) 0.75
41 0.86 (0.57 - 1.31) 0.48
Moderate 61 12 0.61 (0.31 - 1.21) 0.15
20 0.66 (0.38 - 1.14) 0.13
Low 292 113 1.18 (0.84 - 1.65) 0.33
142 0.98 (0.74 - 1.31) 0.91
GMS
¶
High (>60) 450 155 1.05 (0.77 - 1.43) 0.76
205 0.92 (0.71 - 1.20) 0.53
Low ( ≤60) 9 3 0.98 (0.25 - 3.85) 0.98
5 1.11 (0.37 - 3.39) 0.85
26
Table 2.3, Continued
GMS/ conservation¶
Deleterious 124 34 0.83 (0.52 - 1.31) 0.42
51 0.83 (0.56 - 1.22) 0.34
Intermediate (Unclassified) 66 14 0.67 (0.35 - 1.27) 0.22
28 0.87 (0.53 - 1.41) 0.56
Neutral 259 107 1.24 (0.89 - 1.75) 0.21
124 0.97 (0.72 - 1.30) 0.82
§
22 and 55 women with unknown BRCA1 and BRCA2 status were included as a separate category for corresponding
analyses. Numbers do not add up when further classifying UVs using the classification methods since the UV
carriers who had missing values for higher-risk UV categories could not be categorized into high or low risk group
and thus added to the unknown group.
*
Odds ratio (95% confidence interval). Family history of breast or ovarian cancer is the outcome (no family history
(reference), first degree, and second degree). Family history unknown cases were deleted from analysis. All
analyses were adjusted for age at diagnosis (<35, 35~<40, 40~<45, 45+).
†
P-values are based on chi-square test.
||
When analyzing BRCA1, the model was further adjusted for BRCA2 mutation status (DDCV, non-DDCV,
unknown).
¶
Splice/in frame deletion carriers of BRCA1 were excluded when analyzing BRCA1. Splice/in frame deletion carriers
of BRCA2 were excluded when analyzing BRCA2.
**
Numbers do not add up due to one additional subject classified after combining high and moderate group who were
in the unknown BRCA1 status before combining.
‡
When analyzing BRCA2, the model was further adjusted for BRCA1 mutation status (DDCV, non-DDCV, unknown).
Abbreviations: UV: unclassified variants; DDCV: definitely-disease causing variant; LFUV: low-frequency UV;
HFUV: high-frequency UV; GMS: Grantham matrix score.
27
carriers were, in general, significantly more likely to have a first-degree family history
than normal/polymorphic women whereas the low-risk UV carriers were not. For
example, the high-risk UV carriers identified using allele frequency (LFUV) or
Polyphen (probably-damaging) were more likely to have a first-degree family history
(OR=2.00 and 3.39, respectively) than normal/polymorphic BRCA1 carriers. Similar
trend was observed using the sequence conservation or GMS method although
differences between the categories of UV carriers were smaller. The integrated method
of GMS/conservation classified only 9 subjects as high risk and their OR was not
different from that of the women who remained unclassified.
BRCA2 DDCV carriers were also at a higher risk of having a first-degree family history
compared to the normal/polymorphic BRCA2 carriers (OR=3.69) after adjusting for
BRCA1 mutation status. The association was weaker than that of BRCA1 DDCV
carriers. Regardless of the classification method, the high-risk UV carriers were not
statistically significantly different from the normal/polymorphic BRCA2 carriers with
regard to family history (Table 2.3).
Age at diagnosis and ER/PR status
As expected, compared to the carriers of normal/polymorphic BRCA1, BRCA1 DDCV
carriers had a much earlier age at diagnosis (by 4.1 years; p<0.001) and more ER/PR
negative tumor (OR=7.24, 95%CI=3.56-14.7). However, case patients with high-risk
UVs did not have such characteristics regardless of the method of UV classification.
28
BRCA2 DDCV or UV status was not associated with early age at diagnosis or ER/PR
negativity (data not shown).
2.4.4 Comparisons of the classifications using the methods in this study and the
BIC
The recent update of the BIC includes the assessment of the ‘clinical importance’ of
each variant. This assessment is based on several criteria, including epidemiological,
segregation, and co-occurrence data. Among the UVs in this study, 1 BRCA1 UV
(IVS5-11T>G) was classified as clinically important whereas 3 BRCA1 and 19 BRCA2
UVs were classified as clinically non-important. IVS5-11T>G was classified as high-
risk UV using allele frequency (LFUV). Since this variant is not a missense variant,
other methods were not applicable. Table 2.4 shows how each UV that was considered
non-important in BIC was classified by the 5 UV classification methods. The allele
frequency and GMS method classified a large number of variants that were considered
non-important by BIC as high risk, particularly for BRCA2. In contrast, Polyphen and
the conservation methods classified few of such variants as high risk.
2.5 Discussion
In this study of young breast cancer patients, we identified numerous variants in
BRCA1/2 by direct sequencing, including 22 BRCA1 and 30 BRCA2 new variants that
have not been reported in the BIC as of April, 2007. We applied various methods to
classify 44 BRCA1 UVs and 95 BRCA2 UVs. To our knowledge, our study is the first
29
Table 2.4 Classification of BRCA1/2 variants (UVs) that were considered clinically not important in BIC database
UV classification methods Number of BRCA1 variants Number of BRCA2 variants
Allele frequency
High risk (LFUV) 1 (1200H) 15 (S326R, S384F, D596H, T598A, S976I, C1290Y, D1420Y, G1529R,
H2116R, T2515I, A2717S, V2728I, S2835P, E2856A, T3013I)
Low risk (HFUV) 2 (I379M, D693N) 6 (N372H, N289H, L929S, N987I, N991D, T1414M)
Polyphen
High risk (Probable) 0 3 (N987I, C1290Y, G1529R, H2116R)
Medium risk (Possible) 1 (I379M) 8 (N289H, N372H, S384F, D596H, S976I, D1420Y, T2515I, E2856A)
Low risk (Benign) 2 (D693N, 1200H) 9 (S326R, T598A, L929S, N991D, T1414M, A2717S, V2728I, S2835P,
T3013I)
Conservation
High risk (High-degree conservation) 1 (I379M) 4 (N289H, D596H, G1529R, E2856A)
Medium risk
(Moderate-degree conservation)
1 (Q1200H) 10 (S326R, T598A, V2728I, S384F, S976I, N987I, C1290Y, D1420Y,
H2116R,T2515I)
Low risk (Low-degree conservation) 1 (D693N) 7 (N372H, L929S, N991D, T1414M, A2717S, S2835P, T3013I)
GMS
High risk (High GMS: >60) 1 (Q1200H) 17 (N289H, S326R, N372H, S384F, D596H, L929S, S976I, N987I, C1290Y,
T1414M, D1420Y, G1529R, T2515I, A2717S, S2835P, E2856A, T3013I)
Low risk (Low GMS: ≤60) 2 (I379M, D693N) 4 (T598A, N991D, H2116R, V2728I)
GMS/conservation
High risk (Deleterious) 0 7 (N289H, D596H, L929S, N987I, 1420Y, G1529R, E2856A)
Medium risk (Unclassified) 2 (I379M, 1200H) 7 (S326R, S384F, S976I, H2116R, T2515I, A2717S, T3013I)
Low risk (Neutral) 1 (D693N) 7 (N372H, T598A, N991D, C1290Y, T1414M, V2728I, S2835P)
30
to attempt to classify a large number of BRCA1/2 UVs identified in population-based
breast cancer patients and to correlate these variants with outcome variables.
We found that classifications of BRCA1/2 UVs using the various classification methods
in general agree with each other (Table 2.1 and Table 2.2). In particular, Polyphen
seemed to be correlated with GMS and sequence conservation, which is expected given
the composite nature of this algorithm. This inter-correlation supports the reliability of
the classification methods.
In general, the BRCA1 UV carriers classified as high risk were at increased risk of
having a family history of breast or ovarian cancer. Family history has been considered
a “powerful tool” in classifying UVs (Easton et al. 2007), and having a first-degree
relative with breast cancer increases breast cancer risk about two fold (2001). The OR
for the high-risk UV group was highest when using Polyphen, suggesting that Polyphen
is better for the purpose of describing high-risk variants when using family history as a
measure of true risk. However, we cannot exclude the possibility that more stringent
cut points to define the high-risk group using other methods (i.e. high-degree
conservation defined as no cross-species variation; or high GMS defined as >100) might
increase the OR estimates of the high-risk group. In this study, we did not have
sufficient numbers of variant carriers to investigate this possibility.
31
Considering that the high-risk BRCA1 UV carriers classified using all classification
methods were at a higher risk of having a family history (either statistically significantly
or non-significantly), we expected to observe similar trends using age of diagnosis or
ER/PR status as the outcome variables. However, this did not occur. The narrow age
range of our study subjects, all of whom were under age 50 at diagnosis, could have
limited the study power. For analyses of ER/PR status, our exclusion of about 30% of
women, because of missing, borderline, or mixed (-/+ or +/-) ER/PR status, may have
limited statistical power. Alternatively, it is possible that only truncating mutations
(resulting in complete loss of BRCA1 functions), but not missense variants (retaining
part of its ability, i.e. to interact with certain proteins), of BRCA1 lead to the high
density of ER/PR negative tumors.
For BRCA2, it is unclear why none of the classification methods identified high-risk UV
carriers when family history was used as the measure of true risk. One explanation
could be the fact that BRCA2 DDCV carriers themselves did not have such a high OR as
seen for BRCA1 DDCV carriers. The BRCA2 DDCV carrier status was also not
associated with age at diagnosis in this study, again possibly because all our subjects
were under 50, and age at diagnosis for BRCA2 DDCV carriers is not as early as for
BRCA1 DDCV carriers (Eerola et al. 2005). In our study, the median ages were 40 and
45 for BRCA1 and BRCA2 carriers, respectively.
32
Homozygous deleterious mutations in BRCA1/2 are lethal (Gowen et al. 1996; Ludwig
et al. 1997; Sharan et al. 1997; Kuschel et al. 2001). In our study, all the low-risk UVs
classified using the allele-frequency method (except those that were common only in
African-Americans) were observed as homozygous and therefore should be benign.
Consistent with this, all our low-risk UVs (HFUVs) that have been classified by BIC
were assessed as clinically non-important. On the contrary, quite a few variants
classified by BIC as non-important are rare variants, and therefore classified as high-
risk UVs (LFUV) in our study. If a variant has arisen very recently, its population
frequency will be low even though the variant is not clinically important (Thompson
and Neel 1997). Therefore, the allele-frequency method may be better for the purpose
of describing low-risk UVs than high-risk UVs.
GMS is a pairwise comparison of the two substituted amino acids, and it has been
argued that a multiple comparison, that is a comparison of the substituted amino acids
taking into account the natural variation of the substituted site across species, would
provide better information (Tavtigian et al. 2006; Tavtigian et al. 2006). One method of
achieving such a multiple comparison is to use the integrated method by Abkevich et al.
(Abkevich et al. 2004). However, in our study, this method was not an improvement
over the individual application of the two methods.
The Polyphen algorithm compares homologous sequences for conservation and
examines the structural and physicochemical aspects of the substitution. We found that
33
the high-risk UV carriers identified using Polyphen had the highest OR of first-degree
family history among those identified using all other methods. We also found that the
number of clinically non-important variants that were classified as high or medium risk
was smallest when using Polyphen. Polyphen has been reported to have the smallest
false positive rate among the various online algorithms including SIFT (Ng and
Henikoff 2006). Polyphen has previously not been applied for BRCA1/2 whereas SIFT
has been adopted for BRCA1 (Fleming et al. 2003; Burk-Herrick et al. 2006). Our
results suggest that Polyphen might be useful to identify high-risk UVs, especially when
the UV has never been reported and/or clinical information is not available.
Efforts to classify UVs are accumulating: several groups have used simple
combinations of sequence conservation and the severity of amino acid substitutions
(Fleming et al. 2003; Abkevich et al. 2004; Burk-Herrick et al. 2006). However,
whether the classification is clinically valid has not been systematically examined
(Abkevich et al. 2004). Others have used extensive multifactorial models, most of them
focusing on a few BRCA1 UVs. These models incorporate several approaches used in
this study as well as clinical characteristics (Goldgar et al. 2004), co-occurrence with
deleterious mutations (Goldgar et al. 2004; Chenevix-Trench et al. 2006), and
histopathological information (Chenevix-Trench et al. 2006). However, while clinical
and co-occurrence information has provided strong evidence to classify UVs (Goldgar
et al. 2004; Easton et al. 2007), such information is not always available, especially for
UVs that have not been reported before. Further, it has been suggested that these
34
“ideal” criteria cannot classify the majority of the UVs (Easton et al. 2007). The
classification methods used in this study may serve as “readily-available” additional
information to classify UVs.
2.6 Conclusions
Our study suggests that the application of different methodologies such as allele
frequency, Polyphen, GMS, and sequence conservation may be useful for evaluating
UVs, especially when little functional or clinical data are available. While we found
high correlations between these classification methods, our study suggests that each
method has different levels of false-positives and false-negatives. Polyphen appeared
more appropriate in identifying high-risk variants whereas allele frequency may be
useful in classifying high-frequency variants as non-important. Although our study
does not directly address the question whether each specific UV is associated with the
risk of breast cancer, our results suggest that these methods could be helpful in
understanding the significance of a UV especially when other clinical or genetic
information is not available. Further, the application of these methods may help to
prioritize UVs for further functional or familial study.
35
Chapter 3. The effect of reproductive factors and oral contraceptives
on breast cancer risk in BRCA1/2 carriers and non-carriers
3.1 Summary
BACKGROUND: Reproductive factors such as multiparity and breastfeeding are
known to reduce breast cancer risk while oral contraceptive (OC) use may slightly
increase breast cancer risk in the general population. However, the effects of these
factors in BRCA1 and BRCA2 mutation carriers are less clear.
METHODS: Case patients were 1,469 female breast cancer patients from Los Angeles
County aged 20-49 years at diagnosis. Control subjects were 444 women without breast
cancer, neighborhood-matched to a subset of cases on race and age. We sequenced
BRCA1/2 genes in the cases, and estimated ORs of breast cancer associated with various
reproductive and hormonal factors in BRCA1/2 mutation carriers and non-carriers using
standard multivariable logistic regression.
RESULTS: Ninety four women had a deleterious mutation in BRCA1 or BRCA2. An
increasing number of full-term pregnancies was associated with a decreased breast
cancer risk regardless of BRCA1/2 mutation status. Longer breastfeeding duration was
protective among BRCA1/2 mutation non-carriers but not among mutation carriers;
however, this apparent effect modification was not statistically significant (p=0.23).
36
Neither OC use overall or the use of low-dose OCs was associated with an increased
risk of breast cancer in any subgroup.
CONCLUSIONS: Our results suggest that parity protects against breast cancer in
BRCA1/2 mutation carriers, while breastfeeding does not. While our data suggest no
association between OC use and breast cancer risk in BRCA1/2 mutation carriers,
further confirmation that currently-available low-dose OCs do not affect breast cancer
risk in carriers is important from a public health perspective given the high prevalence
of OC use in the US.
3.2 Background
3.2.1 BRCA1/2 and breast and ovarian cancer
Women with mutations in BRCA1/2 have a high risk of developing cancers of the breast
and ovaries (Ford et al. 1994; Friedman and Kramer 2005; Levy-Lahad and Friedman
2007). The exact mechanisms for why BRCA1/2 mutation carriers predominantly
develop cancers of these hormonally regulated organs are not clear, but it is possible
that BRCA1/2 may interact with estrogen in breast carcinogenesis. Estrogen is
involved in breast carcinogenesis by promoting cell proliferation and/or by acting as a
genotoxic agent, through its metabolites, generating mutagenic DNA damage (Cavalieri
et al. 2000; Yager and Davidson 2006). BRCA1 and BRCA2 are involved in a number
of cellular functions important in carcinogenesis including DNA damage repair as well
as cell cycle checkpoint (Thompson and Easton 2004). Therefore, it seems plausible
37
that the cancer promoting effects of estrogen would be even stronger in the absence of
functioning BRCA1/2. Further, BRCA1 has been shown to repress estrogen-dependent
and independent transactivation activity of ER-α (Fan et al. 1999; Fan et al. 2001;
Zheng et al. 2001; Fan et al. 2002).
3.2.2 Roles of reproductive and hormonal factors in breast cancer development in
the general population
Reproductive factors such as multiparity, early age at first full-term pregnancy,
breastfeeding, and late age at menarche have been consistently found to protect against
breast cancer (Kelsey et al. 1993; Collaborative Group on Hormonal Factors in Breast
Cancer 2002). Parity and early age at first birth predominantly protect against estrogen
and progesterone receptor positive tumors whereas breastfeeding and late age at
menarche have been found to protect against both receptor positive and negative disease
(Althuis et al. 2004; Ma et al. 2006). Thus, it is possible that these reproductive factors
act through different hormonal mechanisms, some of which may involve estrogen,
progesterone or sex hormone binding globulin (Bernstein et al. 1985; Garcia-Closas et
al. 2002). Oral contraceptive (OC) use has also been associated with a slightly increased
risk of breast cancer (Collaborative Group on Hormonal Factors in Breast Cancer 1996),
although the effect is modest, possibly restricted to current use, and not observed in all
studies.
38
3.2.3 Roles of reproductive and hormonal factors in breast cancer development in
BRCA1/2 mutation carriers
Although the overall effects of these reproductive and hormonal risk factors are well
established, to what extent these risk factors contribute to breast cancer risk in women
with BRCA1 and BRCA2 mutations is less clear. Studies of the role of reproductive
factors on breast cancer in BRCA1/2 mutation carriers have generated somewhat mixed
results. While the protective effect of multiparity seems quite consistent in studies of
BRCA1 mutation carriers, the results from studies of BRCA2 carriers are not clear
(Narod et al. 1995; Jernstrom et al. 1999; Rebbeck et al. 2001; Hartge et al. 2002; King
et al. 2003; Tryggvadottir et al. 2003; Cullinane et al. 2005; Andrieu et al. 2006;
Antoniou et al. 2006). The results on breastfeeding, and age at menarche has been
mixed for BRCA1 mutation carriers while there was no statistically significant
association for BRCA2 in any of the previous studies (Tryggvadottir et al. 2003;
Jernstrom et al. 2004; Kotsopoulos et al. 2005; Andrieu et al. 2006; Chang-Claude et al.
2007). Studies of the role of OCs, particularly the low-dose OC preparations, on breast
cancer risk among BRCA1/2 mutation carriers have also generated mixed results (Ursin
et al. 1997; Narod et al. 2002; Milne et al. 2005; Haile et al. 2006; Brohet et al. 2007).
Most of the previous studies of BRCA1/2 mutation carriers were based on studies of
women from high-risk families, with multiple relatives with breast and/or ovarian
cancer, many whom were recruited from genetic counseling centers. To what extent
such recruitment schemes could have influenced the results of these studies is unknown.
39
In the following we describe results from a population-based study in Los Angeles
where we investigated the effect of oral contraceptives and hormonal lifestyle factors on
breast cancer risk in BRCA1/2 mutation carriers as well as in non-carriers.
3.3 Methods
3.3.1 Subjects
The data collection for the Women’s Learning the Influence of Family and Environment
(LIFE) Study has previously been described (Ma et al. 2006). In brief, female patients
diagnosed with histologically-confirmed first primary invasive breast cancer were
identified through the Los Angeles County Cancer Surveillance Program (CSP), the
NCI SEER population-based cancer registry in Los Angeles County. Eligible cases
were: (1) US-born and English speaking, (2) white (including Hispanic) or African-
American, (3) aged 20-49 years at the time of diagnosis, and (4) residents of Los
Angeles County at the time of diagnosis. A total of 2,882 eligible cases were identified
(2,534 whites and 348 African-Americans) between February, 1998 and May, 2003.
Because the recruitment of African-Americans began after the initiation of the study,
eligible African-American cases were diagnosed from January, 2000 to May, 2003.
Among the 2,882 potentially eligible cases, 1,794 (62%) were interviewed (1,585 white,
209 African-American). Reasons for non-participation were patient refusal (n=428),
not living in Los Angeles County (n=37), not located (n=88), death (n=38), serious
illness or disability (n=18), physician refusal (n=50), or inability to schedule an
interview within 18 months of diagnosis (n=429).
40
Since this study was initially designed as a case-case study to investigate gene-
environment interaction for breast cancer risk, control subjects were recruited for a
subset of case patients diagnosed between July, 2000 and March, 2003. The control
subjects were matched to the case patients on race and age (within 5 years and ages of
20-49). The eligibility criteria for control subjects were the same as those of case
patients except that they had never been diagnosed with invasive or in situ breast cancer.
We identified the case subjects using a neighborhood walk algorithm that had been
previously reported (Marchbanks et al. 2002). We identified 603 eligible control
subjects for the 1,108 case patients (1,018 white, 90 African-American) by the end of
the study. Among them, we interviewed 444 subjects (74%; 409 white, 35 African-
American). Reasons for the non-participation was subject refusal (n=77), not living in
Los Angeles County (n=18), death (n=1), serious illness (2), or inability to schedule the
interview within 18 months from the initial household contact (n=61). On average, we
canvassed 20 houses to find an eligible control subject who agreed to be interviewed.
3.3.2 Data and blood specimen collection
The in-person interview used a structured questionnaire which was modified from that
used in the Women's Contraceptive and Reproductive Experiences (CARE) Study
(Marchbanks et al. 2002) and asked for detailed information on demographic and
environmental factors such as oral contraceptive use, reproductive history,
breastfeeding. We also obtained data on family history and ethnic origin. We obtained
41
information up to the date of diagnosis of the case patient’s invasive breast cancer or the
date of initial household contact of the control subjects. Blood specimens were
successfully collected from 1519 cases (85%) around the time of the interview and
brought to the Norris Cancer Center Genetics Core Laboratory in Styrofoam containers
on frozen ice packs. For the first 50 samples, buffy coat was immediately extracted and
stored, and for the remaining samples we stored whole blood. The study was approved
by the Institutional Review Board of the University of Southern California. All
participants provided written informed consent.
3.3.3 Sequencing of BRCA1 and BRCA2 genes
We sequenced BRCA1/2 genes for 1469 out of 1519 blood specimens. We were unable
to sequence the remaining 50 specimens due to insufficient DNA. The detailed
procedures of BRCA1/2 sequencing were previously reported (Lee et al. 2008). Briefly,
we sequenced all BRCA1 and BRCA2 exons (except BRCA1 exons 1 and 4 and BRCA2
exon 1) as well as all exon-intron boundaries. Exon 1 was not sequenced for either
gene because it is located upstream of the translation start site in both genes. BRCA1
exon 4 was not sequenced because it is not found in the normal BRCA1 mRNA
transcript. DNA extraction, amplification and sequencing were done in the USC
Genomics Core Laboratory using a protocol similar to that previously described
(McKean-Cowdin et al. 2005). Thirty-three randomly selected, blinded samples were
re-sequenced for quality control purposes. The discordance rate was 0.19%: 16
discordant sequencing results out of the total 8646 variant sites sequenced (262 variant
42
sites for each of the 33 samples). We considered women with a truncating mutation in
the BRCA1/2 genes as the mutation carriers. Women with a missense mutation that
have been previously reported to affect the protein function (M1775R, A1708E) were
also considered as the mutation carriers (Chapman and Verma 1996; Vallon-
Christersson et al. 2001; Carvalho et al. 2007).
3.3.4 Variables
We classified women based on their family history of breast or ovarian cancer as
follows: first-degree (mother or full sisters); second-degree (mother’s or father’s full
sisters, or grandmothers); none; unknown. We considered women who had unknown
second-degree family history, but had no first-degree family history, as having no
family history. Current use of combined oral contraceptives (OCs) was defined as use
at the date 6 months prior to the reference date. Women who started their OC use in or
after 1975 were assumed to have used low-dose oral contraceptives only (Narod et al.
2002; Milne et al. 2005; Haile et al. 2006), and therefore we will refer to the use of OCs
during or after 1975 as use of low-dose OCs in this report.
3.3.5 Statistical analyses
When there was indication that the results for the BRCA1 and BRCA2 were dissimilar,
we describe the results from separate analyses. Otherwise, we present the results with
BRCA1/2 combined. We compared demographic and hormone-related factors
depending on the breast cancer status and BRCA1/2 mutation status of the breast cancer
43
patients using analysis of variance tests for continuous variables and Pearson’s chi-
square tests for categorical variables. When the overall p-value was statistically
significant, we performed pairwise comparisons with Bonferroni adjustment. We
performed case-control analyses comparing the BRCA1/2 mutation carrier cases as well
as BRCA1/2 mutation non-carrier cases with all control women to investigate the
association between the breast cancer risk and the various hormonal factors. In our
study, only a subset of cases had matched controls. We have previously shown in this
study that the use of unconditional logistic regression with adjustment for the matching
factors (race, age, and education) generated essentially identical results to that of
unconditional logistic regression stratified by the matching factors, and that of
conditional logistic regression when limited to the matched pairs (Ma et al. 2006). The
standard reproductive risk factors of breast cancer have been shown to be associated
with breast cancer risk in this study (Ma et al. 2006). Therefore we broke the matched
case-control pairs and analyzed all cases and controls using unconditional logistic
regression adjusted for matching factors. Trend tests were based on likelihood ratio
tests. To examine whether mutation status modified the effect of each hormonal factor,
we performed case-case analyses comparing the BRCA1/2 mutation carrier cases with
non-carrier cases on these hormonal factors.
All models were adjusted for age at reference date (<35, 35-<40, 40-<45, 45+),
education ( ≤high school, technical school or some college, college graduate), family
history of breast or ovarian cancer (none, first-degree, second-degree, unknown), race
44
(white, African-American), and on whether the participant considered herself of
Ashkenazi Jewish origin (yes, no), number of full-term pregnancies (never pregnant,
1~2, 3+, non-full-term pregnancy). When examining the effect of breastfeeding or age
at last full-term pregnancy, we also adjusted for age at first full-term pregnancy. All p-
values are two-sided. All analyses were performed using STATA 8.2 (Stata Corp.,
College Station, Texas) and SAS 9.1 (SAS Institute Inc., Cary, NC).
3.4 Results
3.4.1 Comparisons of BRCA1/2 mutation carrier cases, non-carrier cases, and
control subjects
The breast cancer case patients with BRCA1/2 mutations were slightly younger, more
likely to have a first degree family history of breast or ovarian cancer and be of
Ashkenazi Jewish origin compared to case patients without such mutations as well as
control subjects (Table 3.1). Control subjects were more educated, had menarche at a
later age, were more likely to have breastfed, and breastfed for a longer duration than
the non-carrier cases, but there were no statistically significant differences in these
factors between the two case groups or between the control subjects and the carrier
cases. More control subjects reported having ever used OCs than mutation carrier cases.
45
Table 3.1 Characteristics of study subjects according to their disease status and
BRCA1/2 mutation status
¶
Breast cancer patients
Variables Controls BRCA1/2
mutation
carriers
BRCA1/2
mutation non-
carriers
p-value
†
Number of subjects 444 94 1,375
Mean age at reference date ± SD, years 42.6 ± 4.9 41.0 ± 6.4 43.0 ± 5.1 <0.001
*, §
Menopausal status
Pre-menopause 349 (79%) 81 (86%) 1,096 (80%) 0.40
Post-menopause 95 (21%) 13 (14%) 278 (20%)
Race
White 409 (92%) 88 (94%) 1,239 (90%) 0.28
African-American 35 (8%) 6 (6%) 136 (10%)
Ashkenazi Jewish
No 398 (90%) 69 (73%) 1,222 (89%) <0.001
*, §
Yes 46 (10%) 25 (27%) 153 (11%)
Education
High school or lower 60 (14%) 21 (22%) 275 (20%) 0.004
‡
Technical school or some college 150 (34%) 29 (31%) 499 (36%)
College graduate 233 (53%) 44 (47%) 599 (44%)
Family history of breast or ovarian cancer
None 275 (62%) 24 (26%) 757 (55%) <0.001
*, §, ‡
First-degree 50 (11%) 47 (50%) 226 (16%)
Second-degree 108 (24%) 21 (22%) 352 (26%)
Unknown 11 (2%) 2 (2%) 40 (3%)
Mean age at menarche ± SD, years 12.7 ± 1.5 12.7 ± 1.7 12.4 ± 1.5 <0.001
‡
Pregnancy
Never 75 (17%) 24 (26%) 232 (17%) 0.079
Ever full-term pregnancy (>26 weeks) 317 (71%) 56 (60%) 934 (68%)
Ever had a non-full-term pregnancy 51 (11%) 14 (15%) 205 (15%)
Mean number of full-term pregnancies ± SD
||
2.2 ± 1.1 2.1 ± 1.0 2.1 ± 1.0 0.47
Mean age at first full-term pregnancy ± SD
||
27.2 ± 6.2 27.1 ± 6.8 26.4 ± 6.2 0.17
Ever breastfed
||
Never (%) 38 (12%) 7 (13%) 192 (21%) 0.001
‡
Ever (%) 279 (88%) 49 (88%) 737 (79%)
Mean duration of breastfeeding ± SD
**
, weeks 71.6 ± 74.6 70.3 ± 85.7 61.7 ± 69.8 0.005
‡
Ever used OC
Never (%) 48 (11%) 19 (20%) 185 (14%) 0.042
*
Ever (%) 396 (89%) 75 (80%) 1,190 (87%)
Mean duration of OC use ± SD
§§
, years 6.7 ± 6.1 6.9 ± 6.2 7.0 ± 6.5 0.71
¶
Numbers do not add up due to missing values.
†
P-values are based on F-test for continuous variables and Pearson’s chi-square tests for categorical variables,
comparing the control group, BRCA1/2 mutation carriers, and BRCA1/2 mutation non-carriers. Unknown group was
excluded from the statistical test.
||
Among women who had a full-term pregnancy.
**
Among those who ever breastfed.
46
Table 3.1, Continued.
§§
Among those who ever used OC.
*
Control women and BRCA1/2 mutation carrier cases are statistically significantly different using Bonferroni
pairwise comparisons.
§
BRCA1/2 mutation carrier cases and non-carrier cases are statistically significantly different using Bonferroni
pairwise comparisons.
‡
Control women and BRCA1/2 mutaiton non-carrier cases are statistically significantly different using Bonferroni
pairwise comparisons.
Abbreviations: SD, Standard deviation.
47
3.4.2 Full-term pregnancies
An increasing number of full-term pregnancies was associated with a decreased risk of
breast cancer regardless of BRCA1/2 mutation carrier status (Table 3.2), although the
trends did not reach statistical significance. Women who had four or more full-term
pregnancies had about half the breast cancer risk of nulliparous women, both among the
BRCA1/2 mutation carriers and non-carriers. The protective effect of full-term
pregnancies seemed to be mainly limited to women who had their first full-term
pregnancy before age 25 although the numbers became sparse, particularly among the
mutation carriers.
3.4.2 Age at menarche
Later age at menarche was associated with a decreased risk of breast cancer in the
BRCA1/2 mutation non-carriers, but no such protective association was observed in the
carriers (Table 3.2). However, when the analyses were separated according to whether
the mutation was in BRCA1 or BRCA2, there was a protective effect of later age at
menarche among the BRCA1 mutation carriers (p for trend =0.011), and the OR for
menarche at age 14+ (versus age ≤11) was 0.31 (95%CI=0.11-0.87, p for trend=0.011;
data not shown). No such protective effect of later age at menarche was seen for
BRCA2 mutation carriers, but the sample size was small.
48
Table 3.2 Association between hormone-related factors and breast cancer by BRCA1/2 mutation status
*
BRCA1/2 non-carrier cases
vs controls
BRCA1/2 carrier cases
vs controls
BRCA1/2 carrier cases
vs non-carrier cases
No.
Ctrl
No.
Case OR (95%CI)
No.
Case OR (95%CI) OR (95%CI)
All Women
Number of full-term pregnancies
¶
Never pregnant 75 232 1 24 1
1 86 277 1.02 (0.71-1.46) 17 0.77 (0.34-1.75) 0.99 (0.49-1.97)
2 139 391 0.86 (0.62-1.20) 24 0.71 (0.32-1.57) 0.89 (0.47-1.71)
3 57 183 0.91 (0.60-1.37) 8 0.51 (0.18-1.46) 0.62 (0.26-1.50)
4+ 35 83 0.61 (0.37-1.00) 7 0.40 (0.12-1.31) 1.20 (0.45-3.20)
Trend p value
§
0.074 0.092 0.67
Age at first full-term pregnancy and number of
full-term pregnancies
¶
Never pregnant 75 232 1 24 1 1
Age <25 & 1~2 full-term pregnancies 58 223 1.03 (0.68-1.55) 12 0.88 (0.34-2.29) 0.91 (0.41-2.03)
Age <25 & 3 full-term pregnancies 29 107 0.90 (0.54-1.50) 4 0.51 (0.13-1.99) 0.54 (0.17-1.71)
Age <25 & 4+ full-term pregnancies 28 52 0.42 (0.24-0.74) 5 0.31 (0.08-1.15) 1.28 (0.40-4.07)
Age ≥25 & 1~2 full-term pregnancies 167 445 0.88 (0.64-1.22) 29 0.70 (0.33-1.46) 0.94 (0.51-1.74)
Age ≥25 & 3 full-term pregnancies 28 76 0.91 (0.54-1.52) 4 0.53 (0.14-2.08) 0.74 (0.23-2.35)
Age ≥25 & 4+ full-term pregnancies 7 31 1.41 (0.59-3.38) 2 1.14 (0.17-7.86) 1.04 (0.22-4.94)
Age at menarche
<=11 90 323 1 20 1 1
12 109 421 1.08 (0.79-1.49) 31 1.14 (0.54-2.39) 1.17 (0.64-2.16)
13 121 382 0.88 (0.64-1.21) 16 0.55 (0.24-1.26) 0.61 (0.30-1.24)
14+ 121 240 0.56 (0.40-0.77) 27 1.04 (0.50-2.19) 1.90 (1.01-3.59)
Trend p value
§
<0.001 0.71 0.23
49
Table 3.2, Continued.
BRCA1/2 non-carrier cases
vs controls
BRCA1/2 carrier cases
vs controls
BRCA1/2 carrier cases
vs non-carrier cases
No.
Ctrl
No.
Case OR (95%CI)
No.
Case OR (95%CI) OR (95%CI)
Limited to women who had a full-term pregnancy
Breastfeeding duration
**
Never 38 192 1 7 1 1
<1-6 months 104 326 0.66 (0.43-1.02) 22 1.31 (0.45-3.82) 2.06 (0.82-5.22)
7-23 months 111 264 0.52 (0.33-0.81) 16 0.73 (0.23-2.30) 1.79 (0.67-4.82)
24+ months 64 147 0.49 (0.29-0.81) 11 1.29 (0.36-4.61) 2.38 (0.79-7.13)
Trend p value
§
0.002 0.83 0.23
Age at first full-term pregnancy
<25 115 382 1 21 1 1
25-29 71 233 1.10 (0.77-1.59) 14 1.32 (0.54-3.22) 1.23 (0.57-2.65)
30+ 131 319 0.83 (0.58-1.17) 21 0.79 (0.31-2.03) 1.32 (0.60-2.91)
Trend p value
§
0.25 0.66 0.48
Age at last full-term pregnancy
**
15-27 72 263 1 15 1 1
28-31 71 203 0.83 (0.54-1.30) 11 0.72 (0.24-2.11) 0.97 (0.37-2.51)
32-35 94 228 0.88 (0.54-1.43) 13 1.38 (0.41-4.67) 0.99 (0.34-2.90)
36-45 68 214 1.18 (0.68-2.06) 15 2.00 (0.55-7.32) 1.30 (0.41-4.09)
Trend p value
§
0.44 0.22 0.63
*
All analyses were adjusted for family history of breast or ovarian cancer (none, first-degree, second-degree, unknown), age at diagnosis (<35,
35-<40, 40-<45, 45+), education ( ≤High school, technical or some college, college graduate), race (white, African American), Ashkenazi
Jewish (yes, no), and number of full-term pregnancies (never pregnant, 1~2, 3+, non-full-term pregnancy).
¶
Non-full-term pregnancies were categorized into a separate category and dummied out for trend test.
**
Additionally adjusted for age at first full-term pregnancy (<25, 25-29, 30+).
§
Based on likelihood ratio test.
50
3.4.3 Breastfeeding
Among parous women, longer breastfeeding was associated with a decreased breast
cancer risk in the BRCA1/2 mutation non-carriers (p for trend=0.002; Table 3.2). In
contrast, among the BRCA1/2 mutation carriers, there was no such decreasing trend
with increasing duration of breastfeeding, but this apparent effect modification was not
statistically significant (p from case-case analyses = 0.23).
3.4.4 Oral contraceptives
Ever use of OC, duration of OC use, and the time since last use of OCs were not
associated with the breast cancer risk either in BRCA1/2 mutation carriers or non-
carriers in this study (Table 3.3). When we completed a sub-analyses focusing on
women taking low-dose OCs and never users, there was a suggestive protective
association between the use of low-dose OCs and breast cancer risk; however, this
association among the BRCA1/2 mutation carriers did not reach statistical significance
(Table 3.4). When examining the risk among BRCA1 mutation carriers and BRCA2
mutation carriers separately, the OR for low-dose OC use was 0.55 (95%CI=0.22-1.39)
among the BRCA1 mutation carriers, and that of the BRCA2 mutation carriers was 0.94
(95%CI=0.28-3.14; data not shown). Use of high-dose OCs was statistically
nonsignificantly associated with increased breast cancer risk both in the carriers and
non-carriers among younger women (<45 years; Table 3.4). However, among
51
Table 3.3 Association between use of combined oral contraceptives (OC) and breast cancer risk
*
BRCA1/2 non-carrier cases
vs controls
BRCA1/2 carrier cases
vs controls
BRCA1/2 carrier cases
vs non-carrier cases
No.
Ctrl
No.
Case OR (95%CI)
No.
Case OR (95%CI) OR (95%CI)
Ever OC use
Never 48 184 1 19 1 1
Ever 394 1185 0.81 (0.57-1.14) 75 0.68 (0.33-1.38) 0.82 (0.46-1.46)
Duration of OC use
Never used 48 184 1 19 1 1
Used for ≤ 4 years 181 558 0.80 (0.55-1.16) 33 0.65 (0.30-1.42) 0.77 (0.41-1.46)
Used for 5-9 years 115 283 0.66 (0.45-0.98) 25 0.78 (0.34-1.77) 1.00 (0.51-1.98)
Used for ≥10 years 97 331 0.95 (0.64-1.42) 17 0.63 (0.26-1.51) 0.76 (0.36-1.57)
Trend p value
§
0.94 0.49 0.74
Time since last OC use
Never used 48 184 1 19 1 1
Used ≥10 year ago 230 688 0.75 (0.52-1.08) 41 0.66 (0.31-1.42) 0.82 (0.44-1.53)
Used 1~<10 year ago 94 250 0.76 (0.50-1.14) 14 0.49 (0.20-1.23) 0.64 (0.30-1.40)
Currently use or used <1 year ago 68 233 0.99 (0.65-1.52) 20 0.97 (0.40-2.39) 1.03 (0.51-2.11)
Trend p value(among users)
§
0.073 0.42 0.64
OC use by dosage
Never 48 184 1 19 1 1
Low-dose (Use ≥1975) 280 686 0.64 (0.45-0.92) 52 0.61 (0.29-1.29) 0.91 (0.50-1.67)
High-dose (Use before 1975) 112 485 1.22 (0.81-1.82) 23 0.86 (0.36-2.07) 0.67 (0.33-1.40)
* All analyses were adjusted for family history of breast or ovarian cancer (none, first-degree, second-degree, unknown), age at diagnosis (<35,
35-<40, 40-<45, 45+), education ( ≤High school, technical or some college, college graduate), and number of full-term pregnancies (never
pregnant, 1~2, 3+, non-full-term pregnancy), race (white, African American), Ashkenazi Jewish (yes, no).
§
Based on likelihood ratio test.
52
Table 3.4 The role of high-dose and low-dose OC use on breast cancer risk by age
*
BRCA1/2 non-carrier cases
vs controls
BRCA1/2 carrier cases
vs controls
BRCA1/2 carrier cases
vs non-carrier cases
OC use before/after 1975
No.
Ctrl
No.
Case OR (95%CI)
No.
Case OR (95%CI) OR (95%CI)
Age <45
Never 27 98 1 12 1 1
Low-dose (Use ≥1975) 212 538 0.74 (0.46-1.18) 41 0.59 (0.21-1.68) 0.98 (0.45-2.12)
High-dose (Use before 1975) 13 64 1.53 (0.71-3.27) 5 3.39 (0.64-17.8) 1.06 (0.30-3.75)
Age ≥45
Never 21 86 1 7 1 1
Low-dose (Use ≥1975) 68 148 0.53 (0.30-0.95) 11 0.61 (0.18-2.02) 0.97 (0.34-2.76)
High-dose (Use before 1975) 99 421 1.01 (0.58-1.74) 18 0.61 (0.20-1.87) 0.56 (0.21-1.48)
P for interaction between age and low-dose OC
§
0.55 0.64 0.62
P for interaction between age and high-dose OC
§
0.99 0.34 0.66
* All analyses were adjusted for family history of breast or ovarian cancer (none, first-degree, second-degree, unknown), age at diagnosis (<35,
35-<40, 40-<45, 45+), education ( ≤High school, technical or some college, college graduate), and number of full-term pregnancies (never
pregnant, 1~2, 3+, non-full-term pregnancy), race (white, African American), Ashkenazi Jewish (yes, no).
§
Based on likelihood ratio test.
53
BRCA1/2 mutation carriers, only 5 case patients had used high-dose OCs, and the
interaction test between the high-dose OC and age was not statistically significant.
3.5 Discussion
In this population-based study of breast cancer in young women, we found that an
increasing number of full-term pregnancies was associated with a decreased breast
cancer risk regardless of BRCA1/2 status, and that breastfeeding was protective in the
BRCA1/2 mutation non-carriers, but not clearly so in the carriers. OC use overall was
not associated with risk of breast cancer regardless of BRCA1/2 status.
Our observation that an increasing number of full-term pregnancies was protective in
the BRCA1/2 mutation carriers is consistent with the results from most studies of
BRCA1/2 mutation carriers (Narod et al. 1995; Rebbeck et al. 2001; King et al. 2003;
Andrieu et al. 2006; Antoniou et al. 2006), although such protective effects were not
found among BRCA2 mutation carriers in a few studies (Tryggvadottir et al. 2003;
Cullinane et al. 2005). Several mechanisms have been proposed to explain the
protective effect of pregnancy in the general population: decreased levels of estrogen
(Bernstein et al. 1985) and progesterone (Garcia-Closas et al. 2002), increased levels of
sex hormone-binding globulin (Bernstein et al. 1985), and pregnancy-induced
differentiation of breast tissue (Russo et al. 2005). Our observation suggests that these
protective mechanisms of pregnancy may also work in BRCA1/2 mutation carriers.
54
We observed that increased duration of breastfeeding is associated with a decreased
breast cancer risk in the non-carriers, but not among the BRCA1/2 mutation carriers.
This observation is in line with the results from a large collaborative study, showing
that breastfeeding was protective against breast cancer in the general population, but to
a lesser degree among those with a first-degree family history (Collaborative Group on
Hormonal Factors in Breast Cancer 2002). Previous studies of breastfeeding in BRCA2
mutation carriers are generally consistent with our findings (Jernstrom et al. 2004;
Andrieu et al. 2006), although an Icelandic study found a suggestive, but non-
significant protective effect (Tryggvadottir et al. 2003). In this latter study,
breastfeeding was not protective in BRCA2 mutation non-carriers. The reasons for the
difference between this Icelandic study and the other studies are not clear. The two
studies of breastfeeding in BRCA1 mutation carriers yielded contradictory results, with
one study observing a protective effect (Jernstrom et al. 2004) while the other did not
(Andrieu et al. 2006).
Several mechanisms underlying the role of breastfeeding in breast cancer risk have been
proposed, including postponed resumption of ovulatory menstrual cycles, breast tissue
differentiation (Russo and Russo 1994), and decreased estrogen levels (Petrakis et al.
1987). Other proposed mechanisms include excretion of carcinogens from the breast
ductal tissue (Murrell 1991). Whatever the true mechanisms are, our data support most
studies indicating that breastfeeding is not protective against breast cancer in BRCA2
55
mutation carriers, and possibly not in BRCA1 mutation carriers. BRCA1 mutation
carriers have been reported to be more likely to experience poor milk production and
stop breastfeeding (Jernström et al. 1998). It is not clear whether BRCA2 mutation
carriers have similar problems, or whether this modifies the protective effect of
breastfeeding on the breast tissue.
Our observation that late age at menarche is protective in BRCA1 mutation carriers but
not in BRCA2 mutation carriers is consistent with data from one familial study
(Kotsopoulos et al. 2005). In contrast, the International BRCA1/2 Carrier Cohort Study
did not find a statistically protective effect in either BRCA1 or BRCA2 mutation carriers
(Chang-Claude et al. 2007). However, case patients in the latter study were older than
control women (8 year difference in mean age). Further, the duration between
diagnosis and interview was extremely long (average ~10 years) in the latter study
(Andrieu et al. 2006; Chang-Claude et al. 2007), raising concerns of survival bias.
Although a modest increase in breast cancer risk among current OC users has been
reported in a large pooled analysis and a meta-analysis (1996; Kahlenborn et al. 2006),
not all studies have observed this increased risk. In two studies from Los Angeles, there
was no increased risk of breast cancer associated with OC use overall (Ursin et al. 1998;
Marchbanks et al. 2002). Consistent with this, among the non-carrier women in our
current study, we observed no increased risk for overall OC use, and even decreased
risk of breast cancer among users of low-dose OCs.
56
In a previous study of 50 BRCA1/2 mutation carriers, we found a suggestive increased
risk of breast cancer in mutation carriers who had used OCs (Ursin et al. 1997), which
was not found in the current much larger study. The reasons we found a positive
association in the earlier study could have been due to chance, or due to the fact that the
participants in the previous study were very young (diagnosed under 40 years),
diagnosed in the 1980’s, which means they had used high-dose OCs, and relatively
recent users of OCs. Our current results among the young (<45 years) women
suggesting that high-dose OCs may be associated with increased risk of breast cancer
support the possibility (Table 3.4).
The results from our current study of no increased risk by overall OC use in BRCA1/2
mutation carriers are consistent with a recent population-based study of BRCA1/2
mutation carriers (Milne et al. 2005). Further, our observation that use of low-dose OCs
was associated with a seemingly decreased risk of breast cancer in BRCA1/2 mutation
non-carriers and BRCA1 mutation carriers, but not in BRCA2 mutation carriers, are also
consistent with the results from the same population-based study (Milne et al. 2005). In
contrast, a study of BRCA1/2 mutation carrier cases and controls from breast cancer
family registries have reported that the use of low-dose OC was associated with an
increased risk of breast cancer in BRCA2 mutation carriers but not among BRCA1
carriers (Haile et al. 2006). A third study of BRCA1/2 mutation carrier cases and
controls, who had been tested for BRCA1/2 mutations, found a positive association
57
between low-dose OC use and breast cancer risk in BRCA1/2 mutation carriers (Brohet
et al. 2007). However, in the latter studies based on family registries or high risk
women (Haile et al. 2006; Brohet et al. 2007), the mean interval between diagnosis and
interview was very long. OC use has been shown to be associated with localized breast
cancer (Collaborative Group on Hormonal Factors in Breast Cancer 1996). Therefore,
although the authors in the latter studies performed restricted analyses of women
diagnosed within 5 years observing the same association, the concerns for survival bias
cannot be completely ruled out. Further, many of the BRCA1/2 mutation carrier
controls in the Hail et al. study were recruited because their relatives (the probands)
were cancer cases who had a mutation in BRCA1/2 (Haile et al. 2006). Therefore, the
motivation to recall OC use could have been higher for the probands, which may
explain the positive association in the latter studies. Further larger population-based
studies would be useful in order to confirm whether there is truly no association
between low-dose OC use and breast cancer risk in BRCA1/2 mutation carriers.
There are some differences in BRCA1- and BRCA2-related tumors, which includes that
BRCA1-related tumors are more likely to be ER/PR negative than sporadic tumors
whereas BRCA2-related tumors are not (Honrado et al. 2006). However, it is not clear
how this could explain the different roles of low-dose OC use between the BRCA1
mutation carriers and the BRCA2 mutation carriers. Due to the limited sample size of
ER/PR positive BRCA1 carriers, it was not possible to isolate these aspects in this
study.
58
Two recent population-based studies reported that high-dose OCs was associated with
increased breast cancer risk in young BRCA1/2 mutation carriers (Milne et al. 2005) and
non-carriers (Althuis et al. 2003; Milne et al. 2005). The age distribution of these two
studies is even younger than our study. Since we observed a non-significant positive
association between high-dose OCs and breast cancer risk among those younger than 45
years, our findings are not incompatible with these results.
The strengths of our study include our sampling of a large number of population-based
breast cancer patients, sequencing of whole BRCA1/2 genes in cases, and extensive
collection of data on main exposure variables as well as important confounders using a
1-3 hour interview, and use of life-calendars to assist recall. Further, our study is less
likely to be prone to survival bias since our case subjects were interviewed within 18
months from diagnosis.
We compared BRCA1/2 mutation carrier cases and non-carrier cases with the same
population-based controls. Given that the BRCA1 or BRCA2 mutation prevalence in the
general population has been estimated as 0.45% (Malone et al. 2006), few control
subjects are expected to be BRCA1/2 mutation carriers, suggesting that our OR
estimates in non-carriers are reasonable. We used a case-case approach to examine the
potential interaction between BRCA1/2 status and these reproductive factors. Case-case
studies have been shown to be good alternatives to examine gene-environment
59
interactions when the gene variants are rare, but need an assumption of independence
between genotype and environmental exposure (Khoury and Flanders 1996). This
means that, in our study, we assume mutation carriers were not more or less likely to
have given birth or to have used OCs than non-carriers. We believe this assumption
held in our study, especially since we adjusted for family history of breast or ovarian
cancer.
3.6 Conclusions
The protective effect of parity was similar in BRCA1/2 mutation carriers as in non-
carriers, while the effect of breastfeeding was not. Use of the presumably low-dose
OCs was not associated with increased breast cancer risk regardless of BRCA1/2
mutation status. Further confirmation of this latter association will be important from a
public health perspective given the high prevalence of oral contraceptive use in the US.
60
Chapter 4. GRP78 as a novel predictor of responsiveness to
chemotherapy in breast cancer
4.1 Summary
BACKGROUND: The discovery of predictive factors for chemoresistance is critical for
improving adjuvant therapy for cancer patients. The 78 kDa glucose-regulated protein
(GRP78), widely used as an indicator of the unfolded protein response (UPR), is
induced in the tumor microenvironment. In vitro studies suggest that GRP78 confers
chemoresistance to topoisomerase inhibitors such as adriamycin (doxorubicin). Here
we report on a retrospective cohort study of 127 stage II and III breast cancer patients
who were treated with adriamycin-based chemotherapy.
METHODS: Archival tumor specimens were available for analysis and the relationship
of GRP78 expression level to “time to recurrence (TTR),” used as a surrogate marker
for drug resistance, was examined.
RESULTS: Our data shows that 67% of the study subjects expressed high level of
GRP78 in their tumors prior to initiation of chemotherapy, and suggests an association
between GRP78 positivity and shorter TTR (HR=1.78; p=0.16). Interestingly,
subgroup analysis reveals that the hazard ratio (HR) for the GRP78-positive group
increased significantly among patients who did not receive further taxane treatment
61
(HR=3.00; p=0.022) and among mastectomy patients (HR=3.33; p=0.027). The HR
was even stronger among mastectomy patients who did not receive further taxane
treatment, (HR=4.82; p=0.010).
CONCLUSIONS: The use of GRP78 as a predictor for chemoresponsiveness and the
potential interaction of GRP78 and/or the UPR pathways with taxanes warrant larger
studies.
4.2 Background
4.2.1 Current chemotherapy treatment of stage II and III breast cancer patients
Adjuvant therapy of early breast cancer improves survival, however, standard treatment
strategies result in unnecessary treatment and exposure to side effects of large numbers
of women who do not benefit (Bergh 2005). Since current adjuvant strategies are
primarily based on grouped risk assessments mainly using tumor stage, histological
grade and receptor status, there is a critical need for identification of additional, novel
predictive factors for chemo-responsiveness. Adriamycin (doxorubicin), inhibiting
topoisomerase II, is a standard chemotherapeutic agent for adjuvant therapy of early
stage breast cancer. Despite its benefits, approximately 50% of patients with stage II
and III disease will recur within 5 years with drug resistance as a major contributing
factor (Early Breast Cancer Trialists' Collaborative Group 1998).
62
4.2.2 Physiological function of 78 kDa glucose-regulated protein (GRP78)
The 78 kDa glucose-regulated protein (GRP78), also referred to as immunoglobulin
heavy-chain binding protein (BiP), is a central regulator of endoplasmic reticulum
function due to its roles in protein folding and assembly, targeting misfolded protein for
degradation, Ca
2+
-binding in endoplasmic reticulum and controlling the activation of
trans-membrane endoplasmic reticulum stress sensors (Lee 2001). Induction of GRP78
has been widely used as a marker for endoplasmic reticulum stress and the onset of the
unfolded protein response (UPR) (Lee 2001). Due to its anti-apoptotic property, stress
induction of GRP78 represents an important pro-survival component of the
evolutionarily conserved UPR (Yong and Lee 2006).
4.2.3 Roles of GRP78 in chemo-resistance in cancer
Recent evidence shows that the microenvironment of tumors represents physiological
endoplasmic reticulum stress, and the UPR is crucial for survival of tumors cells
subjected to persistent hypoxia (Koumenis 2006). Overexpression of GRP78 has been
reported in many types of cancer cell lines and tumor biopsies including breast cancer
(Fernandez et al. 2000; Li and Lee 2006). The induction of GRP78 in solid tumors can
be attributed to glucose-starvation stress and anoxia in poorly vascularized tumors, as
well as higher glucose utilization rate of cancer cells. In vitro studies show that GRP78
also protects cells from chemotherapeutic agents (Li and Lee 2006). In a panel of
human breast cancer cell lines, the induction of GRP78 was most prominent in the
sublines resistant to topoisomerase II inhibitors (adriamycin and etoposide/VP-16)
63
(Dong et al. 2005). Topoisomerase inhibitors stabilize the topoisomerase-DNA
complexes, resulting in DNA breakage and triggering the apoptotic cascade including
BAX and caspase-7 activation. Recent studies showed that GRP78 confers resistance
against adriamycin- and etoposide-mediated apoptosis in cancer cells, at least in part
through inhibition of BAX and caspase-7 activation (Reddy et al. 2003; Li and Lee
2006; Ranganathan et al. 2006). The strong in vitro link between GRP78
overexpression to the development of resistance to topoisomerase-targeted drugs
suggests that the overexpression of GRP78 within tumors may be predictive of
resistance to adriamycin in breast cancer patients.
4.3 Materials and methods
4.3.1 Study design
Based on the assumption that approximately 65% of patients will be classified as
overexpressing GRP78 (Fernandez et al. 2000), this study was designed to include 300
female patients with stage II or III invasive breast cancer who had received adriamycin-
based adjuvant chemotherapy during 1999 or earlier, to allow for five years of
minimum follow-up. The target of 300 patients, with at least five years of follow-up,
was determined to ensure 80% power to detect a difference in time to recurrence (TTR)
according to GRP78 expression level, if GRP78 positivity conferred a 70% increase in
the recurrence rate as estimated by the hazard ratio (HR). Since adriamycin-based
chemotherapy was not prescribed routinely to patients with stage II or III breast cancer
64
prior to 1989, patients receiving this treatment prior to 1989 were not included to avoid
any bias due to patient selection.
4.3.2 Study subjects
From 1989 to 1999, 432 female patients with stage II or III invasive breast cancer were
treated in the USC/Norris Cancer Hospital, among whom 209 patients were treated with
adriamycin-based adjuvant chemotherapy. Demographic and clinical information were
abstracted from hospital records by Eunjung Lee (E.L.), under the supervision of Dr.
Darcy Spicer (D.S.). Recurrence was defined as the date of documented regional or
systematic recurrence in the patient medical record. Tumor samples collected prior to
initiation of chemotherapy for 127 of the 209 patients were available for
immunohistochemical staining. This study was approved by the USC institutional
review board (IRB). A waiver of informed consent was justified and granted by the
IRB consistent with the waiver criteria of the common rule.
4.3.3 Immunohistochemical staining of GRP78 and evaluation
Five micron sections prepared from formalin-fixed paraffin embedded tissues were
stained for GRP78 using anti-GRP78 H129 antibody (Santa Cruz Biotechnology, Santa
Cruz, CA) as previously described (Shi et al. 1997). The sections were mounted on
slides coated with poly L-lysine, and were deparaffinized in xylene, washed in 100%
ethanol and rehydrated in 95% ethanol. After pre-incubation in 3% hydrogen peroxide
in absolute methanol, antigen retrieval was performed using citrate buffer (pH=6),
65
microwaving for 30 min, and cooling at room temperature for 20 min. Protein blocking
was performed by incubating the slides with normal horse serum for 20 min.
Incubation with 1:100 dilution of the primary antibody, anti-GRP78 H129 antibody
(Santa Cruz Biotech, Santa Cruz, CA) in phosphate-buffered saline was performed for 1
hr. The GRP78 (H129) antibody is a rabbit polyclonal antibody raised against amino
acids 525 to 653 of human GRP78, and by criterion of Western blot analysis, only
recognizes a single protein band GRP78 in human cell lysates. Biotinylated horse anti-
rabbit antibody was used as a secondary antibody at a 1:200 dilution. The slides were
then incubated with avidin-biotin-conjugate (ABC, Vector Laboratories, Inc.,
Burlingame, CA), which was followed by incubation with 0.03% diaminobenzidine.
Counterstaining was performed with hematoxylin.
Plasma cell staining was used as internal positive controls. The negative control was a
sample within each batch in which the primary antibody was omitted.
Immunohistochemically stained slides from each subject were reviewed by a
pathologist, Dr. Peter Nichols (P.N.) who was blinded to all clinical data. Staining was
graded for intensity of staining (1=weak; 2=moderate; 3=strong) and percentage of cells
stained (1=0-<10%; 2=10-<50%; 3=50-100%). The overall index of GRP78 expression
was determined based on the previous two variables: positive when both scores were 2
or above; negative otherwise. To examine the reader-reproducibility of GRP78
immunohistochemistry evaluation, a random sample of 31 slides was chosen, and re-
evaluated by P.N., without knowledge of the previous results. The kappa coefficient
66
was used to evaluate the agreement between two evaluations (Cohen 1960). The kappa
coefficient was 0.73 (95% confidence interval (95% CI): (0.50, 0.98)), indicating
substantial agreement according to the Landis-Koch criterion (Landis and Koch 1977).
4.3.4 Statistical analyses
The following prognostic variables (covariates) were considered: age at diagnosis (<40,
40-49, 50-59, 60+), menopausal status (premenopausal, postmenopausal), histology
(infiltrating ductal carcinoma and infiltrating lobular carcinoma, and others including
medullary carcinoma and papillary carcinoma), T stage (T1, T2, T3/T4, unknown) and
lymph node status (positive, negative), grade (1 or 2, 3, unknown or not-applicable),
lymphovascular invasion (yes, no), extranodal extension (yes, no), estrogen receptor
(ER) and progesterone receptor (PR) (positive, negative), surgery type (mastectomy,
segmental mastectomy), radiation therapy (yes, no), and tamoxifen treatment (yes, no).
Menopausal status at diagnosis had been self-reported in original medical records. If a
woman had bilateral oophorectomy prior to diagnosis, she was classified as
postmenopausal. For women with hysterectomy other than bilateral oophorectomy, we
considered their age at diagnosis to classify their menopausal status (age <50:
premenopausal, age ≥50: postmenopausal). Perimenopausal women were classified as
premenopausal (n=5). We applied the above age cutpoint to classify menopausal status
of women with unknown menopausal status (n=4). Some patients were treated with
tamoxifen for a brief period rather than the recommended 5 year period. We classified
patients who were on tamoxifen less than or equal to 3 months as ‘not treated.’
67
The measure of outcome, time to recurrence (TTR), was calculated from start of
chemotherapy until the date of documented recurrence. For patients who had not
experienced a recurrence at the time of last follow-up (death or last contact at the
hospital or with the treating physician), TTR was censored at the date of last follow-up.
Associations between demographic and clinical characteristics and GRP78 expression
were evaluated using contingency tables and Pearson’s Chi-square test or Fisher’s exact
test. The association between TTR and GRP78 expression or other potential prognostic
factors was evaluated using Kaplan-Meier plot and the Cox Proportional hazards model
(Kalbfleish and Prentice 1980). All p-values reported are two-sided and are based on
the likelihood ratio test associated with the Cox model. Inspection of the hazards
suggested that the assumption of constant proportional hazards was not well satisfied;
analyses were repeated with the logrank test and nearly identical hazard ratio (HR)
estimates and p-values were obtained. For simplicity, all results are reported based on
the Cox model.
Given the size of the study and the number of prognostic variables, instead of
attempting to assess the association between GRP78 and TTR controlling for all these
covariates simultaneously, two strategies were used to assess whether the association
between GRP78 status and TTR was dependent of the standard prognostic variables.
First, the association was re-examined after stratifying by each of the individual
prognostic variables – separately. Second, a propensity score was calculated based on T
68
stage, lymph node status, and grade – variables with the largest (or smallest) hazard
ratios, when examined singly. The association between GRP78 and TTR was re-
evaluated after stratifying by the propensity score divided into quintiles. The propensity
score is a method to adjust simultaneously for 2+ observed covariates (Joffe and
Rosenbaum 1999).
In post hoc examination, the relationship between GRP78 and TTR according to
treatment modalities (types of chemotherapy, surgery, and radiation) was evaluated.
The test of interaction was performed by introducing an interaction term into the Cox
model.
4.4 Results
4.4.1 Patient characteristics
In general, patients with tumor specimens available for GRP78 analysis were not
substantially different in all major prognostic factors, compared to those without
available tumor specimens, with the exception that patients with available specimens
were more likely to have undergone a mastectomy. When the associations between TTR
and each of the patient and tumor characteristics were examined, as expected, T stage of
T3 or T4, lymph node involvement, and high tumor grade, were all associated with
higher hazards of recurring. However, only the association with high tumor grade
reached statistical significance at the 0.05-level (Table 4.1).
69
Table 4.1 Association of patient characteristics with tumor block availability or time to
recurrence
Association with
Tumor Block Availability
Association with
TTR
*
Patient Characteristics
No (%) Yes (%) p-value
†
Hazard
Ratio
p-value
†
Total 82 (100) 127 (100)
Menopausal status
Premenopause 42 (51) 66 (52) 0.92 1
Postmenopause 40 (49) 61 (48) 1.53 0.24
Histology
Infiltrating ductal carcinoma 69 (84) 115 (90) 0.12 1 0.48
Infiltrating lobular carcinoma 7 (8) 10 (8) 1.58
Others
‡
6 (7) 2 (2) -
Stage
T1 ( ≤2 cm) 26 (32) 44 (35) 0.69 1 0.59
T2 (>2 cm, ≤5 cm) 46 (56) 68 (54) 1.10
T3, T4 (>5 cm or inflammatory) 10 (12) 11 (9) 1.78
Tx (cannot be measured) 0 (0) 4 (3) -
Lymph node status
Negative 20 (24) 21 (17) 0.16 1 0.28
Positive 62 (76) 106 (83) 1.82
Lymphovascular invasion
Negative 45 (55) 77 (61) 0.47 1 0.67
Positive 36 (44) 50 (39) 0.85
Unknown 1 (1) 0 (0) -
ER/PR status
§
- / - 23 (28) 27 (21) 0.19 1 0.96
(- / +) or (+ / -) or (+ / +) 54 (66) 97 (76) 1.02
Unknown 5 (6) 3 (2) -
Her-2/neu status
Negative 28 (34) 76 (60) 0.70 1 0.79
Positive 10 (12) 23 (18) 0.86
Unknown 44 (54) 28 (22) -
Grade
**
1+2 29 (42) 52 (45) 0.92 1 0.005
3 30 (43) 52 (45) 3.19
Unknown 10 (14) 11 (10) -
Chemotherapy
Adriamycin-based
║
67 (82) 102 (80) 0.80 1 0.86
Taxanes added
††
15 (18) 25 (20) 1.11
Surgery type and radiation therapy
Segmental, radiated 35 (43) 34 (27) 0.002 1 0.43
Segmental, not radiated 5 (6) 1 (1) -
Mastectomy, radiated 15 (18) 22 (17) 1.55
Mastectomy, not radiated 27 (33) 70 (55) 0.85
*Among patients with tumor blocks (n=127); TTR: time to tumor recurrence.
70
Table 4.1, Continued.
†Based on Chi-square test except for histology, for which p-value is based on Fisher’s exact test.
‡Others include medullary carcinoma and papillary carcinoma, for tumor block available and not-available group.
Tumor-block not-available group also includes muscinous carcinoma and atypical medullary carcinoma.
§Estrogen receptor/progesterone receptor status.
**Limited to infiltrating ductal carcinoma.
║Adriamycin with one or more of cyclophosphamide, 5-fluorouracil or methotrexate.
††Adriamycin-based chemotherapy followed by or combined with taxanes.
71
4.4.2 GRP78 expression in breast cancer patients
As an essential chaperone protein, GRP78 is expressed constitutively at varying basal
levels in most cell types. In the current study, for simplicity, the tumors were classified
into “GRP78-negative” or “GRP78-positive” groups, based on the overall index of
intensity of staining and the percentage of cells stained. Thus, the “negative” group
included tumors that stained weakly and/or with limited stained areas, whereas
“positive” tumors reached or exceeded the staining criterion. The specificity of the
antibody against GRP78 was confirmed by western blot of human cell lysates, as well
as immunohistochemical staining of paraffin sections of established tissue culture cell
lines that expressed differential level of GRP78 (Appendix D). Further, plasma cells
express high levels of GRP78, which facilities immunoglobulin chain assembly (Munro
and Pelham 1986). All subject samples contained plasma cells on their slides, and their
generally uniform high level immunoreactivity with the anti-GRP78 antibody
conveniently served as internal positive controls (Appendix D). Representatives of
GRP78 negative and positive tumors are shown in Figure 4.1. As expected for an
endoplasmic reticulum protein, GRP78 staining was primarily in the
perinuclear/cytoplasmic region. Among the 127 patients, 85 (67%) showed positive
staining of GRP78, which was consistent across all subsets of patients except subsets by
tumor type (histology), where the numbers within categories were very small (Table
4.2).
72
Figure 4.1 Photomicrographs of immunohistochemical staining of GRP78 (400X). A,
Negative staining for GRP78 in neoplastic cells of an infiltrating ductal carcinoma;
plasma cells stain intensely (arrow). B, Intense staining (3+) for GRP78 in neoplastic
cells of an infiltrating ductal carcinoma.
73
Table 4.2 Association between GRP78 expression and patient characteristics
Number of GRP78 Expression
Patient Characteristics
Patients Percent Positive
†
p-value
*
Total 127 67%
Menopausal status
Premenopause 66 64% 0.41
Postmenopause 61 70%
Histology
Infiltrating ductal carcinoma 115 66% 0.045
Infiltrating lobular carcinoma 10 90%
Others
‡
2 0%
Stage
T1 ( ≤2 cm) 44 68% 0.94
T2 (>2 cm, ≤5 cm) 68 68%
T3, T4 (>5 cm or inflammatory) 11 73%
Tx (cannot be measured) 4 (25%)
Lymph node status
Negative 21 57% 0.30
Positive 106 69%
Lymphovascular invasion
Negative 77 66% 0.84
Positive 50 68%
ER/PR status
§
- / - 27 63% 0.62
(- / +) or (+ / -) or (+ / +) 97 68%
Unknown 3 (66%)
Her-2/neu status
Negative 76 66% 0.96
Positive 23 65%
Unknown 28 (71%)
Grade
**
1+2 52 65% 0.84
3 52 67%
Unknown 11 (64%)
Chemotherapy
Adriamycin-based
║
102 67% 0.90
Taxanes added
††
25 68%
Surgery type and radiation therapy
Segmental, radiated 34 62% 0.45
Segmental, not radiated 1 0%
Mastectomy, radiated 22 73%
Mastectomy, not radiated 70 68%
†Percent of subjects with GRP78-positive staining.
*Based on Chi-square test except for histology, for which p-value is based on Fisher’s exact test. Excludes patients
with unknown status.
‡Others include medullary carcinoma and papillary carcinoma.
§Estrogen receptor/progesterone receptor status.
**Limited to infiltrating ductal carcinoma.
║Adriamycin with one or more of cyclophosphamide, 5-fluorouracil or methotrexate.
††Adriamycin-based chemotherapy followed by or combined with taxanes.
74
4.4.3 Association between GRP78 and time to recurrence
Among the 127 study subjects who received adriamycin-based therapy, the GRP78-
positive group showed an increased likelihood of recurring, with a HR of 1.78 (95% CI:
0.77, 4.14) (Figure 4.2A and Table 4.3). Although this trend does not achieve statistical
significance (p=0.16), the observed HR is very close to the value stipulated in the
design (1.70 or 70% increase). Adjustment for each patient and tumor characteristic did
not substantially change the results (Appendix E). In a multivariable analysis, the
magnitude of the association remained the same even after adjusting for T-stage, lymph
node status, and grade using the propensity score.
4.4.4 Post hoc subgroup analyses
Post hoc analyses of GRP78 staining and TTR in subsets of patients by the treatment
modalities reveal two strong and interesting trends (Table 3). First, the HR for the
GRP78-positive group increased significantly among patients treated with adriamycin-
based chemotherapy who did not receive further treatment with taxane (paclitaxel or
docetaxel) (HR=3.00, p=0.022) (also see Figure 4.2B). The interaction (differences in
the two HRs depending on addition of taxanes) was statistically significant (p=0.012).
Further, the adjustment for T-stage, lymph node status, and grade (using propensity
scores) did not change the results. In agreement with taxane treatment exerting an
opposing trend, among patients treated with adriamycin combined with or followed by a
taxane, positive GRP78 appeared to have a lower risk of recurrence with borderline
significance (HR=0.15, p=0.072).
75
Figure 4.2 Probability of remaining recurrence-free according to GRP78 expression in
patients treated with adriamycin-based adjuvant chemotherapy. A, all 127 patients, B,
subset of 102 patients who did not receive taxanes (paclitaxel or docetaxel) as part of
the adriamycin-based regimen, C, subset of 92 patients who underwent mastectomy and
D, subset of 74 patients who underwent mastectomy and did not receive taxanes as part
of the regimen.
B
0.00
0.20
0.40
0.60
0.80
1.00
0 2 4 6 8 10 12 14 16
GRP78 positive
(n=68)
GRP78 negative
(n=34)
No taxane group: p=0.022
Years Since Start of Chemotherapy
Probability of Remaining Recurrence-Free
0.00
0.20
0.40
0.60
0.80
1.00
02 468 10 12 14 16
GRP78 positive
(n=85)
GRP78 negative
(n=42)
All patients: p=0.16
Probability of Remaining Recurrence-Free
Years Since Start of Chemotherapy
A
0.00
0.20
0.40
0.60
0.80
1.00
0 2 4 6 8 1012 1416
GRP78 negative
(n=23)
Mastectomy and no taxane group: p=0.010
GRP78 positive
(n=51)
Years Since Start of Chemotherapy
Probability of Remaining Recurrence-Free
D
0.00
0.20
0.40
0.60
0.80
1.00
0 2 4 6 8 10 12 14 16
GRP78 negative
(n=28)
Mastectomy group: p=0.027
GRP78 positive
(n=64)
Years Since Start of Chemotherapy
Probability of Remaining Recurrence-Free
C
76
Table 4.3 Relative risk of recurrence associated with GRP78 expression
Univariate Analysis Multivariable Analysis
*
Treatment Characteristics GRP78 n Events
†
HR (95% CI)
‡
p value
§
HR (95% CI)
‡
p value
§
Overall analysis
Total subjects Negative 42 7 1 1
Positive 85 24 1.78 (0.77-4.14) 0.16 1.76 (0.74-4.17) 0.18
Subgroup analyses
Chemotherapy
Adriamycin-based
║
Negative 34 4 1 1
Positive 68 23 3.00 (1.04-8.70) 0.022 3.00 (1.02-8.84) 0.026
Taxanes added
**
Negative 8 3 1 1
Positive 17 1 0.15 (0.016-1.46) 0.072 0.24 (0.020-3.00) 0.24
p for interaction
(GRP78 and Chemotherapy) 0.012 0.012
Surgery type
Segmental mastectomy Negative 14 4 1 1
Positive 21 5 0.74 (0.20-2.77) 0.66 0.53 (0.11-2.54) 0.42
Mastectomy Negative 28 3 1 1
Positive 64 19 3.33 (0.98-11.30) 0.027 2.53 (0.73-8.75) 0.11
p for interaction
(GRP78 and Surgery) 0.078 0.28
*Stratified analysis using propensity score (based on T stage, lymph node status, and grade) divided into quintiles.
†Number of recurrences.
‡Hazard ratio (95% confidence interval).
§p-values from likelihood ratio test based on Cox model.
║Adriamycin with one or more of cyclophosphamide, 5-fluorouracil or methotrexate.
**Adriamycin-based chemotherapy followed by or combined with taxanes.
77
Second, when stratified by type of surgery (segmental mastectomy versus mastectomy),
a positive association between GRP78 expression and TTR was observed among
patients who underwent mastectomy (HR=3.33, p=0.027) (also see Figure 4.2C). The
interaction between GRP78 expression and surgery type with regard to TTR was
borderline-significant (p=0.078). However, after adjustment for T-stage, lymph node
status, and grade (using propensity scores), the interaction was not statistically
significant (p=0.28), and the association among patients with mastectomy was reduced
by 25% (HR=2.53, p=0.11). When evaluating the patients who had mastectomy and did
not receive a taxane, the association between positive GRP78 and TTR was stronger
(HR=4.82, 95% CI=1.12-20.87, p=0.010) (Figure 4.2D), and remained statistically
significant after adjustment for T-stage, lymph node status, and grade (HR=3.77, 95%
CI=0.85-16.66, p=0.041). Most patients who had mastectomy did not receive radiation
therapy, whereas all but one patient who had segmental mastectomy received radiation
therapy. Stratification by radiation therapy yielded similar results as with stratification
by type of surgery (data not shown).
4.5 Discussion
GRP78 has been implicated as a major player in cancer progression by its role in
protecting cancer cells from apoptosis, promoting metastasis and allowing dormant
cancer cells to resist adriamycin toxicity (Reddy et al. 2003; Misra et al. 2005;
Ranganathan et al. 2006). The retrospective study reported here supports the in vitro
findings and provides new insight into the relationship between GRP78 induction and
78
chemo-responsiveness. In tumor specimens collected prior to adjuvant therapy, about
65% expressed high level of GRP78. This is in agreement with a previous study which
showed the same percentage of breast tumors that exhibited overexpression of GRP78
mRNA (6). Collectively, these suggest that, although the tumor microenvironment has
been shown to induce the UPR and GRP78 expression, tumors arising from a subset of
patients are unable to induce GRP78 to high level. While the mechanism for the
negative phenotype remains to be determined, our study provides the first evidence that
the difference in GRP78 level in tumors can be exploited to predict response to
adriamycin-based chemotherapy among stage II and III breast cancer patients.
This study further reveals a potentially significant interaction between GRP78 and
taxanes with regard to the resistance to adriamycin-based chemotherapy. In the subset
of patients treated with adriamycin-based chemotherapy without a taxane, the
association between GRP78 positivity and higher risk of recurrence attained statistical
significance, suggesting a strong association between GRP78, or the underlying UPR,
and chemoresistance. In contrast, GRP78 positivity appears to be associated with
higher responsiveness to chemotherapy in patients who received both adriamycin and
taxane treatment. While the observed effect in the taxane group was derived from a
relatively small number of patients, it suggests that taxanes may diminish, or even
reverse, the effect of GRP78 and/or the UPR on adriamycin resistance. Taxanes,
through prevention of polymerization of new microtubules, block endoplasmic
reticulum elongation and movement, which is required for maintenance of its unique
79
subcellular structure (Terasaki and Reese 1994). Further, in breast cancer cells, taxanes
increased nuclear localization of the transcription factor YB-1, which represses
transcription of the GRP78 gene (Li et al. 1997; Fujita et al. 2005). Thus, it is possible
that taxanes can alter or interfere with GRP78 function as well as UPR protective
pathways such as inhibition of translation and degradation of misfolded proteins, by
disrupting the endoplasmic reticulum structure and inhibiting GRP78 transcription.
Further, GRP78 and the UPR may play different roles in different types of cancer and
treatment regimens (Yong and Lee 2006).
We observed a strong association between GRP78 and TTR among mastectomy
patients. However, the heterogeneity in the association by surgery type was reduced
when adjusted for tumor stage, lymph node status, and grade. Therefore, the type of
surgery could have been a proxy of intrinsic tumor characteristics. Alternatively, it
could have been a reflection of radiation therapy: chemoresistant breast cancer cells
were subsequently killed by radiation, masking the role of GRP78 in chemoresistance.
However, the effect of radiation therapy is likely limited to the breast, favoring the
former view. In conclusion, this study suggests that GRP78 may represent a novel
biomarker for prediction of chemo-responsiveness in breast cancer patients. These
results warrant confirmation in larger clinical studies and in other types of cancer.
80
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92
Appendix A. Supplemental methods: sequencing of BRCA1 and BRCA2 genes
DNA extraction, amplification and sequencing was done in the USC Genomics core
laboratory under the supervision of Dr. David Van Den Berg (D.V.D.B.) using a
protocol similar to that previously described (McKean-Cowdin et al. 2005).
DNA extraction and PCR amplification: DNA extraction from 200 μl buffy coat was
performed using a QIAamp 96 Blood kit (Qiagen Inc., Valencia, CA). All BRCA1 and
BRCA2 exons, except BRCA1 exons 1 and 4 and BRCA2 exon 1, and each exon-intron
boundaries were amplified by PCR using exon-specific primers. Exon 1 for BRCA1 and
BRCA2 was not amplified because it is located upstream of translation start site, and
BRCA1 exon 4 was not amplified because it is not found in normal BRCA1 mRNA
trascript. Each PCR reaction contained ~30 ng of genomic DNA, 40 pmoles of forward
and reverse primer, 100 μM dNTPs, 2 U AmpliTaq Gold DNA polymerase (Applied
Biosystems, Foster City, CA), 1× Gold buffer A and MgCl
2
in a total volume of 25 μl.
The PCR mixture was denatured at 94°C for 1 min (except the initial denaturing for 12
min), annealed for 1 min at a temperature varying from 52°C to 58°C depending on the
melting temperature of the exon-specific primer pairs, and extended at 72°C for 1 min
(except the extension for the final cycle for 10min) for 35 cycles. Amplification of
exon 11 was performed in a total volume of 100 μl using a GeneAmp XL PCR kit
(Applied Biosystems Inc.). All PCR reactions were performed in 96-well plates using a
Primus 96 cycler (MWG Biotech, High Point, NC). The amplified PCR products were
93
purified using MultiScreen FB filter plates (Millipore Corporation, Billerica, MA), and
eluted in 70-140 μl double-distilled H
2
O. The presence of the PCR product for each
PCR reaction was measured by agarose-gel electrophoresis using 16 samples from each
plate.
Sequencing reactions: We sequenced the purified PCR products with an ABI PRISM
BigDye Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems Inc.).
The reactions were perfomed using five to 10 ng of the purified PCR products, 10.4
pmoles of forward or reverse primers (for bi-directional sequencing), Ready Reaction
Premix and 1× reaction buffer in a total volume of 12 μl. Cycle sequencing reactions
were performed in a Primus 96 cycler at 96°C for 10 s, annealing at 50°C for 5 s, and
extension at 60°C for 4 min were performed for 25 cycles. Prior to capillary
electrophoresis, unincorporated dye terminators were removed from the extension
product using a DyeEx 96 Plate (Qiagen, Inc.) according to the manufacturer’s
instructions. The purified extension products were denatured at 90°C for 2 min and
placed on ice for 1 min. Sequencing was performed on an ABI PRISM 3700 or 3730xl
DNA Analyzer (Applied Biosystems Inc.).
We processed the data collected from the ABI detection system using the Phred/Phrap
software developed at the University of Washington (Nickerson et al. 1997; Ewing and
Green 1998; Ewing et al. 1998; Gordon et al. 1998). Sequence alignments for each
exon read were viewed in the Consed viewer Software and sequence variations were
94
annotated and recorded (DVDB). Negative controls were checked for the absence of
analyzable sequence. If a sequence was present in the negative control, the position of
where the negative control would have been if a plate flip occurred (NC-flip) was
checked for analyzable sequence. If the NC-flip was negative, the plate was analyzed
as a flip. If the NC-flip was positive, then the sequencing reactions were rerun.
Sequence variation for the forward and reverse read were compared and any discordant
findings were checked to determine which read was correct. Sequence variations were
summarized for each plate using Microsoft Excel and merged into a single file after
completion of each 96-well plate of samples.
Further classification of BRCA1 and BRCA2 Unclassified Variants (UVs) using
the integrated method of sequence conservation and GMS
We adopted a previously-reported classification scheme integrating the sequence
conservation and GMS (Abkevich et al. 2004). Briefly, if the variant was located at a
fully conserved site, it was considered deleterious. In addition, if the variant involved
non-conservative or severe substitution at a conserved site, that is (i) the maximum
GMS between a pair of aligned sequences at the site of variation is not greater than 60
and (ii) GMS for human variant is greater than or equal to three times of the maximum
GMS in the alignment, then it was considered deleterious. If the variant amino acid is
observed in other species, it was considered neutral. In addition, if the variant involves
conservative substitution relative to natural variation across species, that is (i) GMS for
95
human variant is smaller than 61 and (ii) GMS for human variant is smaller than one
third of the maximum GMS in the alignment, it was considered neutral.
96
Appendix B. Sequences used for cross-species comparison of BRCA1 and BRCA2
Species mRNA protein length
BRCA1
§
Homo sapiens U14680 AAA73985 1863aa
Bos taurus (cow) AY077732 AAL76094 1849aa
Pan troglodytes (chimpanzee) AY365046 AAR04849 1863aa
Canis familiaris U50709 AAC48663 1878aa
Monodelphis domestica AY994160 AAX92675 1844aa
Rattus norvegicus AF036760 AAC36493 1817aa
Mus musculus U36475 AAC52323 1812aa
Gorilla gorilla AY589042 AAT44835 1863aa
Pongo pygmaeus (Orangutan) AY589040 AAT44834 1863aa
Macaca mulatta (Rhesus monkey) AY589041 AAT44833 1863aa
BRCA2
†
Homo sapiens U43746 AAB07223 3418aa
Mus musculus U89652 AAB71377 3329aa
Rattus norvegicus U89653 AAB71378 3343aa
Felis catus AB107955 BAC75821 3372aa
Canis familiaris AB043895 BAB91245 3446aa
§
For BRCA1, Felis catus sequence was excluded since the length of the protein sequence was only 948aa.
†
For BRCA2, Pan troglodytes and Bos taurus sequences were excluded since these are predicted sequences.
97
Appendix C. Classification of significance of BRCA1/2 variants identified among early onset breast cancer patients
in Los Angeles and comparison with classification according to BIC (Version updated April 05, 2007).
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
BRCA1
IVS1-115T>C 0.3403;
0.3438;
0.2266
Polymorphism Intronic* NA
Exon 2
185delAG 0.0073;
0.0045; 0
DDCV Frameshift Frameshift Yes
IVS2-32delAT 0; 0; 0.0035 Polymorphism Intronic* NA
Exon 5
Q60R 0; 0.0023; 0 UV LFUV Possible 43 0 Deleterious NA
R71G 0; 0.0068; 0 DDCV Splice
variant,
(Vega et al.
2001)
Probabl
e
125 0 Deleterious Missense Yes
IVS5+1G>A 0; 0.0023; 0 DDCV Splice
variant
Splice Yes
IVS5+21G>A 0.0005; 0; 0 Polymorphism Intronic* UV Unknow
n
IVS5+23T>A 0; 0; 0.0211 Polymorphism Intronic* NA
98
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
IVS5-11T>G 0.0009; 0; 0 UV Intronic,
possibly
creates a
splice
acceptor site
near the end
of intron 5
LFUV Splice Yes
IVS7-34C/T 0.2435;
0.1121;
0.0674
Polymorphism Intronic* Polymorph
ism
No
Exon 8
Y179C 0; 0.0023; 0 UV LFUV Probabl
e
194 0 Deleterious UV Unknow
n
Exon 11
L246V 0.0014; 0; 0 UV LFUV Benign 32 1 Neutral UV Unknow
n
884G/A 0; 0.0023;
0.0035
Polymorphism Synonymou
s
NA
887G/A 0; 0.0023; 0 Polymorphism Synonymou
s
NA
943Ins10 0; 0; 0.0035 DDCV Frameshift Frameshift Yes
T276R 0.0005; 0; 0 UV LFUV Probabl
e
71 0 Deleterious UV Unknow
n
1100A/G 0.0023;
0.0023; 0
Polymorphism Synonymou
s
Polymorph
ism
Unknow
n
S316G 0.0005; 0; 0 UV LFUV Possible 56 0 Deleterious UV Unknow
n
99
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
W321X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
Q356R 0.0682;
0.0251;
0.0106
Polymorphism (Friedman et
al. 1994;
Durocher et
al. 1996;
Dunning et
al. 1997;
Tavtigian et
al. 2006)
Possible 43 2 Unknown Polymorph
ism
Unknow
n
D369del(1225de
l3)
0.0005; 0; 0 UV In frame
deletion
LFUV UV Unknow
n
W372X 0.0009; 0; 0 DDCV Nonsense Nonsense Yes
I379M 0; 0; 0.0141 UV HFUV Possible 10 1 Unknown UV No
S405P 0.0005; 0; 0 UV LFUV Possible 74 2 Unknown NA
1505delG 0; 0.0023; 0 DDCV Frameshift Frameshift Yes
F486L 0; 0.0023; 0 UV LFUV Benign 22 3 Neutral UV Unknow
n
R496C 0; 0.0023; 0 UV LFUV Benign 180 5 Deleterious UV Unknow
n
R496H 0.0005; 0; 0 UV LFUV Benign 29 5 Neutral UV Unknow
n
N550H 0; 0.0023; 0 UV LFUV Benign 68 3 Unknown UV Unknow
n
Q563X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
100
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
E597K 0.0005; 0; 0 UV LFUV Possible 56 1 Neutral UV Unknow
n
A622V 0; 0.0023; 0 UV LFUV Benign 64 4 Unknown UV Unknow
n
2072delGAAA 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
2090A/G 0.0005;
0.0045;
0.0106
Polymorphism Synonymou
s
Polymorph
ism
Unknow
n
K679X 0.0009; 0; 0 DDCV Nonsense Nonsense Yes
D693N 0.0728;
0.0475;
0.0352
UV HFUV Benign 23 6 Neutral Polymorph
ism
No
2201C/T 0.3431;
0.3364;
0.2266
Polymorphism Synonymou
s
Polymorph
ism
No
T703T
(2228A/G)
0; 0.0023;
0.0035
Polymorphism Synonymou
s
UV Unknow
n
N723D 0; 0; 0.0035 UV LFUV Benign 23 2 Unknown UV Unknow
n
E730X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
R756K 0; 0.0023; 0 UV LFUV Benign 26 4 Neutral NA
2430T/C 0.3393;
0.3257;
0.1950
Polymorphism Synonymou
s
Polymorph
ism
No
T790A 0; 0; 0.0035 UV LFUV Benign 58 0 Deleterious UV Unknow
n
2576delC 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
101
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
K820E 0; 0; 0.0282 UV HFUV Benign 56 4 Neutral UV Unknow
n
2594delC 0.0009; 0; 0 DDCV Frameshift Frameshift Yes
R841W 0.0009;
0.0023; 0
UV LFUV Possible 101 7 Unknown UV Unknow
n
S868X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
P871L 0.3555;
0.3802;
0.7210
Polymorphism (Dunning et
al. 1997)
Benign 98 9 Neutral Polymorph
ism
No
N877S 0.0005; 0; 0 UV LFUV Benign 46 4 Neutral NA
2852A/G 0.0023;
0.0023; 0
Polymorphism NA
2953delGTAins
C
0.0005; 0; 0 DDCV Frameshift Frameshift Yes
S955X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
2994delA 0.0005; 0; 0 DDCV Frameshift NA
2999C/T 0.0005; 0; 0 Polymorphism NA
L965F 0.0005; 0; 0 UV LFUV Benign 22 1 Neutral NA
M1008I 0.0023;
0.0023; 0
UV LFUV Benign 10 5 Neutral UV Unknow
n
E1038G 0.3673;
0.3767;
0.2286
Polymorphism (Friedman et
al. 1994;
Durocher et
al. 1996)
Benign 98 1 Unknown Polymorph
ism
No
102
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
S1040N 0.0200;
0.0090;
0.0035
UV HFUV Benign 46 3 Unknown UV Unknow
n
3226delAG 0.0005; 0; 0 DDCV Frameshift NA
S1101N 0.0005; 0; 0 UV LFUV Benign 46 1 Unknown UV Unknow
n
S1140G 0.0005; 0;
0.0211
UV HFUV Benign 56 4 Neutral UV Unknow
n
3481del11 0.0005; 0; 0 DDCV Frameshift NA
K1183R 0.3427;
0.3349;
0.2286
Polymorphism (Friedman et
al. 1994;
Durocher et
al. 1996)
Benign 26 8 Neutral Polymorph
ism
No
S1187N 0; 0.0023; 0 UV LFUV Benign 46 2 Unknown UV Unknow
n
Q1200H 0; 0; 0.0070 UV LFUV Benign 154 2 Unknown UV No
R1203Q 0.0005; 0; 0 UV LFUV Benign 43 5 Neutral UV Unknow
n
3788T/C 0.0005; 0; 0 Polymorphism Synonymou
s
NA
N1236K 0.0009;
0.0023; 0
UV LFUV Possible 94 3 Unknown UV Unknow
n
P1238L 0.0005; 0; 0 UV LFUV Benign 98 1 Neutral UV Unknow
n
3829delT 0; 0.0023; 0 DDCV Frameshift Frameshift Yes
3875del4 0; 0.0023; 0 DDCV Frameshift Frameshift Yes
103
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
N1272S 0; 0.0023; 0 UV LFUV Possible 46 2 Neutral NA
Q1313X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
R1347G 0.0050;
0.0068;
0.0035
UV LFUV Probabl
e
125 2 Unknown UV Unknow
n
M1361L 0.0005; 0; 0 UV LFUV Benign 15 7 Unknown UV Unknow
n
4184del4 0.0005; 0; 0 DDCV Frameshift Frameshift
IVS11+36A>G 0; 0; 0.0035 UV Intronic,
possibly
creates a
splice donor
site near the
start of
intron 11
LFUV NA
Exon 12
4232G/A 0; 0.0023;
0.0035
Polymorphism Synonymou
s
NA
IVS12+9C>T 0; 0.0023; 0 UV Intronic,
possibly
creates a
splice donor
site near the
start of
intron 12
LFUV UV Unknow
n
Exon 13
104
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
4427T/C 0.3419;
0.3303;
0.1979
Polymorphism Synonymou
s
Polymorph
ism
No
R1443X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
Exon 15
W1508X 0; 0.0023; 0 DDCV Nonsense Nonsense Yes
S1512I 0.0050;
0.0023;
0.0035
Polymorphism (Deffenbaug
h et al.
2002;
Phelan et al.
2005)
Possible 142 2 Unknown Polymorph
ism
No
V1534M 0.0005; 0;
0.0035
UV LFUV Possible 21 5 Neutral UV Unknow
n
Exon 16
T1561I 0; 0; 0.0035 UV LFUV Possible 89 1 Unknown UV Unknow
n
Q1604Q
(4931A/G)
0.0009; 0; 0 Polymorphism Synonymou
s
UV Unknow
n
S1613G 0.3339;
0.3273;
0.2286
Polymorphism (Friedman et
al. 1994;
Durocher et
al. 1996)
Benign 56 2 Unknown Polymorph
ism
No
M1628T 0.0009; 0; 0 UV LFUV Benign 81 5 Unknown UV Unknow
n
P1637L 0.0005; 0; 0 UV LFUV Probabl
e
98 1 Unknown UV Unknow
n
105
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
M1652I 0.0095;
0.0045; 0
UV LFUV Probabl
e
10 2 Unknown UV Unknow
n
IVS17+3A>G 0.0005; 0; 0 UV Intronic,
possibly
creates a
splice donor
site near the
start of
intron 17
LFUV UV Unknow
n
Exon 18
A1708E 0.0005;
0.0023; 0
DDCV (Chapman
and Verma
1996;
Vallon-
Christersson
et al. 2001;
Carvalho et
al. 2007)
Probabl
e
107 0 Deleterious Missense Yes
5254delG 0.0005; 0; 0 DDCV Frameshift NA
Exon 19
T1720A 0; 0.0023; 0 UV LFUV Benign 58 3 Unknown UV Unknow
n
5296del4
(5292del4)
0.0005; 0; 0 DDCV Frameshift Frameshift Yes
R1726G 0.0005; 0; 0 UV LFUV Benign 125 3 Neutral UV Unknow
n
106
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
Exon 20
R1751X 0; 0; 0.0035 DDCV Nonsense Nonsense Yes
R1751L 0.0005; 0; 0 UV LFUV Probabl
e
102 0 Deleterious NA
5382InsC 0.0027;
0.0023; 0
DDCV Frameshift Frameshift Yes
Exon 21
M1775R 0; 0; 0.0035 DDCV (Chapman
and Verma
1996;
Williams
and Glover
2003;
Carvalho et
al. 2007)
Probabl
e
91 0 Deleterious Missense Unknow
n
Exon 22
M1783T 0; 0; 0.0035 UV LFUV Probabl
e
81 1 Deleterious UV Unknow
n
C1787S, G1788D
(CG1787>1788S
D )
0; 0.0045; 0 UV LFUV Probabl
e
112 0 Deleterious Missense Unknow
n
W1782R 0; 0; 0.0035 UV LFUV Benign 101 2 Neutral NA
W1782X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
107
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
BRCA2
Exon 2
203G/A 0.2642;
0.1923;
0.1127
Polymorphism Synonymou
s
Polymorph
ism
No
218C>T 0; 0; 0.0141 Polymorphism Synonymou
s
UV Unknow
n
IVS2-7T>A 0.0027;
0.0023; 0
Polymorphism Intronic* UV Unknow
n
Exon 3
Y42C 0.0023;
0.0023; 0
UV LFUV Probabl
e
194 0 Deleterious UV Unknow
n
P59A 0; 0; 0.0035 UV LFUV Probabl
e
27 0 Deleterious UV Unknow
n
426A/G 0.0005; 0; 0 Polymorphism Synonymou
s
NA
T77A 0; 0; 0.0035 UV LFUV Benign 58 0 Deleterious UV Unknow
n
460T/G 0; 0; 0.0176 Polymorphism Synonymou
s
NA
Exon 7
746delG 0; 0; 0.0035 DDCV Frameshift Frameshift Yes
R174H 0.0005; 0; 0 UV LFUV Benign 29 4 Neutral UV Unknow
n
IVS8-25T>C 0.0005; 0; 0 Polymorphism Intronic* NA
108
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
Exon 10
N289H 0.0341;
0.0826;
0.0322
UV HFUV Possible 68 0 Deleterious Polymorph
ism
No
S326R 0.0005;
0.0023; 0
UV LFUV Benign 110 2 Unknown UV No
Q347R 0; 0; 0.0035 UV LFUV Benign 43 2 Neutral UV Unknow
n
H372N
(N372H)
0.2784;
0.2964;
0.1151
UV Mixed
association
studies
(Healey et
al. 2000;
Spurdle et
al. 2002;
Breast
Cancer
Association
2006)
HFUV Possible 68 3 Neutral Polymorph
ism
No
P375S 0.0005; 0; 0 UV LFUV Probabl
e
74 0 Deleterious UV Unknow
n
S384F 0; 0.0023; 0 UV LFUV Possible 155 1 Unknown UV No
W395G 0; 0.0023; 0 UV LFUV Probabl
e
184 2 Unknown UV Unknow
n
1503A/G 0.0027;
0.0023;
0.0070
Polymorphism Synonymou
s
NA
1593A/G 0.0312;
0.0818;
Polymorphism Synonymou
s
Polymorph
ism
No
109
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
0.0319
E462G 0.0005; 0; 0 UV LFUV Possible 98 0 Deleterious UV Unknow
n
I505R 0.0014; 0; 0 UV LFUV Probabl
e
97 0 Deleterious NA
K513R 0; 0.0023; 0 UV LFUV Benign 26 4 Neutral NA
D596H 0.0005; 0; 0 UV LFUV Possible 81 0 Deleterious UV No
2016T/C 0.0009; 0; 0 Polymorphism Synonymou
s
Polymorph
ism
Unknow
n
T598A 0.0009; 0; 0 UV LFUV Benign 58 2 Neutral UV No
G602R 0.0005; 0; 0 UV LFUV Probabl
e
125 0 Deleterious UV Unknow
n
T630I 0.0014; 0; 0 UV LFUV Possible 89 1 Unknown UV Unknow
n
Exon 11
2139T/C 0; 0; 0.0035 UV Second
nucleotide
of exon 11,
possibly
affect
splicing
LFUV NA
2161insA 0.0005; 0; 0 DDCV Frameshift NA
2166C/T 0.0014; 0; 0 Polymorphism Synonymou
s
Polymorph
ism
No
P655R 0.0036; 0; 0 UV LFUV Probabl 103 0 Deleterious UV Unknow
110
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
e n
Q713L 0; 0; 0.0035 UV LFUV Possible 113 2 Unknown UV Unknow
n
Q742X 0; 0.0023; 0 DDCV Nonsense Nonsense Yes
2457T/C 0.0346;
0.0891;
0.0326
Polymorphism Synonymou
s
UV Unknow
n
K745E 0; 0; 0.0035 UV LFUV Benign 56 4 Neutral NA
N900D 0.0005; 0; 0 UV LFUV Benign 23 4 Neutral UV Unknow
n
L929S 0; 0; 0.0106 UV HFUV Benign 145 4 Deleterious UV No
D935K 0.0005; 0; 0 UV LFUV Possible 101 0 Deleterious NA
D935H 0.0005; 0; 0 UV LFUV Possible 81 0 Deleterious UV Unknow
n
K944X 0; 0; 0.0035 DDCV Nonsense Nonsense Yes
3034del4 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
S976I 0; 0; 0.0070 UV LFUV Possible 142 2 Unknown UV No
I982M 0; 0.0023; 0 UV LFUV Benign 10 4 Neutral UV Unknow
n
3185delA 0.0005; 0; 0 DDCV Frameshift NA
Q961Q
(3111G/A)
0.0018; 0; 0 Polymorphism Synonymou
s
UV Unknow
n
N987I 0; 0; 0.0106 UV HFUV Probabl
e
149 2 Deleterious UV No
111
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
N991D 0.0355;
0.0863;
0.0471
UV HFUV Benign 23 4 Neutral UV No
L1019V 0; 0.0023; 0 UV LFUV Benign 32 0 Deleterious UV Unknow
n
T1087I 0.0005; 0; 0 UV LFUV Benign 89 3 Unknown NA
3492insT 0; 0.0023; 0 DDCV Frameshift Frameshift Yes
P1088P
(3492T/C)
0; 0; 0.0282 Polymorphism Synonymou
s
UV Unknow
n
3624A/G 0.3150;
0.2123;
0.2210
Polymorphism Synonymou
s
Polymorph
ism
No
S1172S
(3744G/A)
0.0014; 0; 0 Polymorphism Synonymou
s
UV Unknow
n
F1192C 0; 0.0023; 0 UV LFUV Probabl
e
205 2 Unknown UV Unknow
n
4017T/C 0.1835;
0.1785;
0.2218
Polymorphism Synonymou
s
NA
C1290Y 0; 0; 0.0035 UV LFUV Probabl
e
194 1 Neutral UV No
4075delGT 0.0009; 0; 0 DDCV Frameshift Frameshift Yes
L1356L
(4296G/A)
0.0023;
0.0023; 0
Polymorphism Synonymou
s
UV Unknow
n
1364L 0; 0.0045;
0.0142
UV HFUV Benign 5 2 Neutral UV Unknow
n
Q1396R 0; 0; 0.0070 UV LFUV Benign 43 4 Unknown UV Unknow
n
112
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
T1414M 0; 0; 0.0106 UV HFUV Benign 81 4 Neutral UV No
D1420Y 0.0046; 0; 0 UV LFUV Possible 160 2 Deleterious Polymorph
ism
No
4780delG 0; 0; 0.0035 DDCV Frameshift NA
4791G/A 0; 0.0023;
0.0607
Polymorphism Synonymou
s
Polymorph
ism
No
G1529R 0.0009; 0;
0.0035
UV LFUV Probabl
e
125 0 Deleterious UV No
H1561N 0; 0; 0.0141 UV HFUV Probabl
e
68 1 Unknown UV Unknow
n
T1566A 0.0005; 0; 0 UV LFUV Benign 58 4 Unknown NA
V1610M 0.0005; 0; 0 UV LFUV Benign 21 3 Neutral UV Unknow
n
Y1672H 0; 0.0023; 0 UV LFUV Possible 83 0 Deleterious NA
5302InsA 0; 0.0023; 0 DDCV Frameshift Frameshift Yes
S1733F 0.0009; 0;
0.0035
UV LFUV Possible 155 1 Unknown UV Unknow
n
5427C/T 0.0055;
0.0023;
0.0035
Polymorphism Synonymou
s
Polymorph
ism
No
5580insA 0.0005; 0; 0 DDCV Frameshift NA
5646A/G 0; 0; 0.0319 Polymorphism Synonymou
s
NA
F1870X
(5837TC>AG)
0.0005; 0; 0 DDCV Nonsense Nonsense Yes
113
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
S1871N 0; 0; 0.0035 UV LFUV Benign 46 1 Neutral UV Unknow
n
N1880K 0; 0; 0.0035 UV LFUV Benign 94 4 Unknown UV Unknow
n
S1882X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
D1902K 0; 0; 0.0106 UV HFUV Possible 101 4 Unknown NA
5946delCT 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
T1915M 0.0234;
0.0068;
0.0036
UV HFUV Benign 81 4 Unknown UV Unknow
n
D1923A 0; 0; 0.0035 UV LFUV Benign 126 3 Unknown UV Unknow
n
E1953X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
C1960Y 0; 0; 0.0035 UV LFUV Probabl
e
194 4 Unknown UV Unknow
n
L1965F 0; 0.0023; 0 UV LFUV Benign 22 3 Neutral NA
H1966R 0.0005; 0; 0 UV LFUV Probabl
e
29 4 Neutral UV Unknow
n
G1976V 0; 0; 0.0035 UV LFUV Probabl
e
109 0 Deleterious NA
6174delT 0.0027; 0; 0 DDCV Frameshift Frameshift Yes
I2033M 0.0005; 0; 0 UV LFUV Benign 10 2 Unknown UV Unknow
n
R2034C 0.0041;
0.0023; 0
UV LFUV Possible 180 4 Unknown UV Unknow
n
114
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
H2074N 0; 0.0023;
0.0070
UV LFUV Probabl
e
68 2 Unknown UV Unknow
n
L2106P 0.0005; 0; 0 UV LFUV Benign 98 3 Neutral UV Unknow
n
R2108C 0.0005; 0; 0 UV LFUV Benign 180 4 Unknown UV Unknow
n
R2108H 0.0009; 0;
0.0035
UV LFUV Benign 29 4 Neutral UV Unknow
n
N2113S 0.0005; 0; 0 UV LFUV Benign 46 4 Unknown UV Unknow
n
H2116R 0; 0; 0.0035 UV LFUV Probabl
e
29 2 Unknown UV No
V2138F 0; 0; 0.0141 UV HFUV Benign 50 4 Neutral UV Unknow
n
6741C/G 0.0005;
0.0023;
0.0568
Polymorphism Synonymou
s
Polymorph
ism
Unknow
n
6872del4 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
IVS11-73T>A 0.0005; 0; 0 UV Intronic,
possibly
creates a
splice
acceptor site
near the end
of intron 11
LFUV NA
Exon 12
I2285V 0.0005; 0; 0 UV LFUV Benign 29 0 Deleterious UV Unknow
n
115
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
IVS13+5G>C 0.0005; 0; 0 Polymorphism Intronic* UV Unknow
n
Exon 14
K2339N 0; 0; 0.0282 UV HFUV Benign 94 1 Unknown UV Unknow
n
E2340Q 0; 0; 0.0035 UV LFUV Benign 29 1 Unknown NA
A2351T 0.0005; 0; 0 UV LFUV Benign 58 2 Unknown UV Unknow
n
7297delCT 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
Q2384K 0; 0; 0.0106 UV HFUV Benign 53 4 Neutral UV Unknow
n
7470A/G 0.2201;
0.1697;
0.2043
Polymorphism Synonymou
s
Polymorph
ism
No
D2438H 0.0005; 0; 0 UV LFUV Possible 81 2 Unknown NA
H2440R 0; 0; 0.0352 UV HFUV Probabl
e
29 3 Neutral UV Unknow
n
A2466V 0.0005;
0.0023;
0.0810
UV HFUV Benign 64 2 Unknown UV Unknow
n
Exon 15
I2490T 0.0027;
0.0611;
0.0035
UV HFUV Probabl
e
89 2 Deleterious UV Unknow
n
R2494X 0; 0.0023; 0 DDCV Nonsense Nonsense Yes
116
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
T2515I 0.0009; 0; 0 UV LFUV Possible 89 2 Unknown UV No
IVS16+6C>G 0.0005; 0;
0.0106
UV Intronic,
possibly
creates a
splice donor
site near the
start of
intron 16
HFUV UV Unknow
n
IVS16-14T/C 0.4996;
0.5161;
0.5141
Polymorphism Intronic* Polymorph
ism
No
Exon 17
D2611A 0; 0.0023; 0 UV LFUV Probabl
e
126 0 Deleterious NA
V2620I 0.0005; 0; 0 UV LFUV Benign 29 0 Deleterious NA
8138del5 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
Exon 18
R2678G 0; 0; 0.0035 UV LFUV Probabl
e
125 0 Deleterious UV Unknow
n
A2717S 0.0018; 0; 0 UV LFUV Benign 99 4 Unknown UV No
V2728I 0.0036; 0; 0 UV LFUV Benign 29 2 Neutral Polymorph
ism
No
RLTVG2743del
(8457del15)
0.0005; 0; 0 UV In frame
deletion
LFUV UV Unknow
n
Exon 19
117
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
8651delTTTTCI
nsA
0.0005; 0; 0 DDCV Frameshift NA
V2820V
(8688A/C)
0; 0; 0.0070 Polymorphism Synonymou
s
UV Unknow
n
Exon 20
S2835P 0; 0; 0.0035 UV LFUV Benign 74 4 Neutral UV No
R2842H 0.0005; 0; 0 UV LFUV Possible 29 0 Deleterious UV Unknow
n
8761delAG
(8762delGA)
0.0005; 0; 0 DDCV Frameshift Frameshift Yes
E2856A 0.0032; 0; 0 UV LFUV Possible 107 0 Deleterious UV No
Q2859X 0.0005; 0; 0 DDCV Nonsense Nonsense Yes
8823insT 0; 0.0023; 0 DDCV Frameshift NA
Exon 21
V2908G 0.0005; 0; 0 UV LFUV Possible 109 0 Deleterious UV Unknow
n
IVS21+4A>G 0.0005; 0; 0 Polymorphism Intronic* UV Unknow
n
IVS21-1G>A 0.0005; 0; 0 DDCV Splice
variant
Splice Yes
Exon 22
I2944F 0; 0.0068;
0.0211
UV HFUV Benign 21 0 Deleterious UV Unknow
n
K2950N 0.0009;
0.0023;
UV LFUV Benign 94 0 Deleterious UV Unknow
n
118
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
0.0035
A2951T 0.0032;
0.0361; 0
Polymorphism (Deffenbaug
h et al.
2002)
Benign 58 0 Deleterious Polymorph
ism
No
V2969M 0.0005; 0; 0 UV LFUV Benign 21 0 Deleterious UV Unknow
n
R2973C 0.0005; 0; 0 UV LFUV Probabl
e
180 0 Deleterious UV Unknow
n
9168insA 0.0005; 0; 0 DDCV Frameshift Frameshift Yes
IVS22+26del9 0; 0; 0.0035 Polymorphism Intronic* NA
Exon 23
E3002K 0.0005; 0; 0 UV LFUV Benign 56 0 Deleterious UV Unknow
n
T3013I 0.0014; 0; 0 UV LFUV Benign 89 3 Unknown UV No
A3029T 0.0005; 0; 0 UV LFUV Benign 58 0 Deleterious UV Unknow
n
P3039P
(9345G/A)
0.0009; 0; 0 DDCV Splice
variant,
(Peelen et al.
2000)
Splice Yes
Exon 24
R3052W 0; 0.0023; 0 UV LFUV Probabl
e
101 0 Deleterious UV Unknow
n
V3079I 0; 0; 0.0070 UV LFUV Benign 29 0 Deleterious UV Unknow
n
119
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
Exon 25
Y3092C 0; 0.0023; 0 UV LFUV Probabl
e
194 0 Deleterious UV Unknow
n
Y3098H 0.0005;
0.0023; 0
UV LFUV Benign 83 4 Neutral UV Unknow
n
Exon 26
G3212R 0; 0; 0.0106 UV LFUV Possible 125 0 Deleterious UV Unknow
n
Exon 27
N3221T 0.0005; 0; 0 UV LFUV Benign 65 2 Neutral NA
V3244I 0; 0; 0.0282 UV HFUV Benign 29 4 Neutral UV Unknow
n
K3326X 0.0091;
0.0068; 0
Polymorphism (Mazoyer et
al. 1996)
Polymorph
ism
No
R3370R
(10338G/A)
0.0018;
0.0023; 0
Polymorphism Synonymou
s
UV Unknow
n
T3374I 0; 0; 0.0035 UV LFUV Benign 89 2 Unknown UV Unknow
n
I3412V 0.0028;
0.0622;
0.0958
Polymorphism Located
closer to the
end of the
gene than
the
polymorphic
nonsense
mutation
K3326X,
UNKN
OWN
29 4 Neutral UV Unknow
n
120
MAF in UV classification BIC classification
Variant
NHW
(n=1105);
HW (n=222);
AA (n=142)
Significance Reasons
Allele
frequenc
y
Polyphe
n
Gran-
tham
score
Number
of differ-
ences in
alignmen
t
Grantham/
Alignment
Mutation
effect
Clinical
significa
nce
probably
disposable
Abbreviations: MAF: Minor allele frequency; NHW: non-Hispanic whites, HW: Hispanic whites, AA: African-Americans. DDCV: definitely-disease causing
variant; UV: unclassified variants; LFUV: low-frequency UV ; HFUV: high frequency UV; NA: not applicable (never been reported in BIC).
* Intronic variant, unlikely to influence splicing.
121
Appendix D. Specific detection of GRP78 by H129 antibody
A, Western blot assay. The human neuroblastoma SK-N-SH cells were either grown under normal conditions (-) or treated
with 0.5 µM thapsigargin for 16 hr. Fifty µg of total cell lysate prepared from these cells were subjected to Western blot
analysis, using the anti-GRP78 H129 antibody (1:1000 dilution) as described (Dong et al. 2005). The position of the single
GRP78 protein band highly inducible by thapsigargin stress is indicated ( ◄). B, Chinese hamster ovary (CHO) cells
expressing basal level of GRP78 and its derivative C.1 cells overexpressing GRP78 (Reddy et al. 2003) were embedded in
paraffin after fixation in formalin. The sections prepared from these blocks were stained with the immunohistochemical
technique using the H129 antibody (1:100 dilution). GRP78 level, as depicted by brown staining, was elevated in C.1 cells
as compared to CHO cells (600X). C, Paraffin slides from breast cancer patients were stained with the H129 antibody with
the immunohistochemical technique. Examples of plasma cell staining from two different patients are shown. The plasma
cells showed uniform pattern of strong staining of GRP78 (600X).
122
Appendix E. Multivariable analyses stratified by each of the covariates.
*Adriamycin with one or more of cyclophosphamide, 5-fluorouracil or methotrexate – without taxanes.
†Adriamycin-based chemotherapy followed by or combined with taxanes.
‡Categorization of each covariate is described in the text for the supplemental data in detail.
§Patients with unknown or unavailable grade or Her-2/neu or ER/PR status were included in the analysis as a separate category. ER/PR: estrogen
receptor/progesterone receptor.
Hazard Ratio for Subset of Patients
All
Adriamycin-
based (without
taxanes)
*
Taxanes
Added
†
Segmental
Mastectomy
Mastectomy
Adriamycin-based
(without taxanes),
*
Mastectomy
Number of patients 127 102 25 35 92 74
Univariate analysis 1.78 3.00 0.15 0.74 3.33 4.82
Stratified variables
‡
for
multivariable analysis
Menopausal status 1.73 2.89 0.078 0.73 3.13 4.37
Age at diagnosis 1.55 2.54 0.25 0.57 2.78 3.82
Race 1.63 2.46 0.23 0.69 2.46 3.44
T stage 1.95 2.96 0.25 1.00 2.96 4.46
Lymph node status 1.73 2.85 0.17 0.73 3.08 4.39
Grade
§
1.71 2.85 0.16 0.70 3.23 4.55
Extranodal extension 1.84 3.06 0.11 0.78 3.42 4.98
Lymphovascular invasion 1.74 2.80 0.14 0.76 3.46 4.81
ER/PR status
§
1.91 3.14 0.19 0.75 3.36 4.92
Her-2/neu
§
1.80 3.08 0.17 0.69 3.47 4.99
Surgery type 1.87 3.11 0.16 - - -
Radiation 1.84 3.12 0.14 0.95 3.43 4.83
Chemotherapy
(whether taxanes added)
1.76 - - 0.71 3.31 -
Tamoxifen 1.78 2.97 0.18 0.80 3.28 4.76
Abstract (if available)
Abstract
BRCA1 and BRCA2 (BRCA1/2) genes are well-established breast cancer susceptibility genes. A large number of variants in these genes has been reported, including variants with clearly deleterious effects and variants with unknown significance on breast cancer risk. Classification of such unclassified variants (UVs) is an area of growing interest, but no study has systematically assessed whether the various classification methods are biologically meaningful. Further, given that not all BRCA1/2 deleterious mutation carriers develop breast cancer, environmental modifiers of breast cancer risk in BRCA1/2 mutation carriers need to be identified. In this dissertation, I present results from a population-based case-control study of young breast cancer patients to investigate these issues.
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University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Lee, Eunjung
(author)
Core Title
Genes and hormonal factors involved in the development or recurrence of breast cancer
School
Keck School of Medicine
Degree
Doctor of Philosophy
Degree Program
Epidemiology
Publication Date
04/16/2010
Defense Date
02/26/2008
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
BRCA,breast cancer,GRP78,OAI-PMH Harvest,oral contraceptives,reproductive factors,unclassified variants
Language
English
Advisor
Ursin, Giske (
committee chair
), Haiman, Christopher A. (
committee member
), Hill, Colin (
committee member
), McKean-Cowdin, Roberta (
committee member
), Stram, Daniel O. (
committee member
)
Creator Email
leee@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m1134
Unique identifier
UC1439354
Identifier
etd-Lee-20080416 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-57693 (legacy record id),usctheses-m1134 (legacy record id)
Legacy Identifier
etd-Lee-20080416.pdf
Dmrecord
57693
Document Type
Dissertation
Rights
Lee, Eunjung
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Repository Name
Libraries, University of Southern California
Repository Location
Los Angeles, California
Repository Email
cisadmin@lib.usc.edu
Tags
BRCA
breast cancer
GRP78
oral contraceptives
reproductive factors
unclassified variants