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Pathogenic variants in cancer predisposition genes and risk of non-breast multiple primary cancers in breast cancer patients

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Pathogenic variants in cancer predisposition genes and risk of non-breast multiple primary cancers in breast cancer patients

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Content PATHOGENIC VARIANTS IN CANCER PREDISPOSITION GENES AND RISK OF
NON-BREAST MULTIPLE PRIMARY CANCERS IN BREAST CANCER PATIENTS
by
Zixuan Song
A Thesis Presented to the
FACULTY OF THE USC KECK SCHOOL OF MEDICINE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
APPLIED BIOSTATISTICS AND EPIDEMIOLOGY
May 2024
Copyright [2024] Zixuan Song

ii
TABLE OF CONTENTS
ABSTRACT................................................................................................................................................. iii
Chapter one: Introduction....................................................................................................................1
Chapter two: Materials and methods...............................................................................................4
Study Population ...................................................................................................................................................4
Targeted Sequencing and Bioinformatic Analysis..................................................................................5
Statistical Analysis ................................................................................................................................................5
Chapter three: Result..............................................................................................................................7
Patient Demographic and Clinical Characteristics..................................................................................7
Carrier Frequency of PVs in Cancer Predisposition Genes .................................................................7
Association of PVs in Cancer Predisposition Genes with MPC..........................................................7
Chapter four: Discussion.......................................................................................................................9
Chapter five: Conclusion ....................................................................................................................11
References................................................................................................................................................12
List of Tables ..............................................................................................................................................v

iii
Pathogenic Variants in Cancer Predisposition Genes and Risk of Non-Breast Multiple
Primary Cancers in Breast Cancer Patients
ABSTRACT
Purpose: Past research on the genetic risk of multiple primary cancers (MPCs) in breast cancer
survivors has focused on contralateral breast cancer risk. The goal of this study was to
investigate the contribution of known cancer predisposition genes to the susceptibility of nonbreast MPCs among breast cancer patients.
Methods: We analyzed data from 23,760 breast cancer patients from the CAnceR RIsk
Estimates Related to Susceptibility (CARRIERS) consortium to investigate associations
between pathogenic variants (PVs) in 37 cancer predisposition genes and the risk of non-breast
MPC using logistic regression analyses. We also evaluated potential effect modification by
race/ethnicity, age at breast cancer diagnosis, and estrogen receptor (ER) status.
Results: We found eight genes to be significantly associated with an increased risk of nonbreast MPC, including ATM (OR: 1.77, 95% CI: 1.24-2.52, P=0.002), BLM (OR: 2.32, 95% CI:
1.35-4.00, P=0.002), BRCA1 (OR: 1.70, 95% CI: 1.25-2.31, P=0.001), CHEK2 (OR: 1.41, 95%
CI: 1.02-1.95, P=0.037), MLH1 (OR: 5.43, 95% CI: 1.51-19.5, P=0.01), MSH6 (OR: 2.94, 95%
CI: 1.43-6.02, P=0.003), PPM1D (OR: 1.78, 95% CI: 1.03-3.08, P=0.038), and TP53 (OR: 4.81,
95% CI: 1.69-13.7, P=0.003). The association for ATM was significantly greater among women
with early-onset breast cancer (<=55 years; OR: 3.04, 95% CI: 1.76-5.24, P=1.0×10-4
) than those
with later-onset breast cancer (OR:1.37, 95% CI: 0.85-2.20, P=0.19, PLRT=0.03), while the

iv
association for BRCA1 was greater in later-onset breast cancer cases (OR: 3.30, 95% CI: 2.03-
5.37, P=1.4⋅10-6
) than in early-onset cases (OR:1.54, 95% CI: 0.99-2.39, P=0.05, PLRT=0.02).
Conclusion: Results from our study indicate that PVs in ATM, BLM, BRCA1, CHEK2, MLH1,
MSH6, PPM1D, and TP53 genes are associated with an increased risk of non-breast MPCs
among breast cancer patients. Further investigations are warranted to validate these results in
larger studies. Our findings support a close surveillance of non-breast MPC for women
carrying PVs in these genes.

1
CHAPTER ONE: INTRODUCTION
Cancer is the second leading cause of death in the United States after heart
disease. In the past three decades, the risk of dying from cancer has decreased
substantially as a result of early diagnosis and advances in treatment1
. In 2022, 18.1
million men and women were living with a history of invasive cancer in the U.S., which
represents approximately 5.4% of the US population. Given the growth and aging of the
US population and the improvement in cancer survival, the number of cancer survivors is
predicted to increase by 24.4%, to 22.5 million by 20322
. With the increasing number of
cancer survivors, multiple primary cancers (MPC) have become more common over time,
accounting for 7.8% of all cancer cases in 1975 to 19.7% in 20113
.Depending on the site
of first primary cancer (index cancer), 5% to 26% of cancer survivors develop a second
primary cancer within 25 years after their first cancer diagnosis. Compared with the
general population, cancer survivors have a 1.14-fold risk of developing a new
malignancy, and the risk is higher among cancer survivors aged ≤40 years4
.
Past epidemiologic research in MPC were mostly conducted in specific patient
populations defined by the index cancer, among which breast cancer patients represented one
of the most studied populations. Women who have had breast cancer in the past are known to
have a higher risk of developing a second primary cancer with the most common types being
second primary breast cancer or contralateral breast cancer. Factors identified to be associated
with second primary breast cancer or contralateral breast cancer include younger age at initial

2
diagnosis (<40 years)
5,6–9
, a positive family history of breast cancer in first-degree relatives9 10
,
hormone receptor (HR) negative tumors5,8,11–13 and receipt of radiotherapy treatment5,8,14
.
Breast cancer survivors also have a significantly elevated risk for subsequent cancers of the
thyroid4,15–17, uterine corpus4,17–19, ovary4,17,18, esophagus, stomach, colon, lung, melanoma of
the skin, sarcoma, and acute myeloid leukemia (AML)4
. In addition, older age at initial breast
cancer diagnosis15,17,18,20–22 and receipt of radiotherapy 22–25 have been reported to be
associated with second primary non-breast cancer.
Pathogenic variants (PVs) in cancer predisposition genes also contribute to the
increased risk of developing a second primary cancer in breast cancer patients. PVs in BRCA1
and BRCA2 were found to be associated with a 1.9- to 5.0-fold and 1.4- to 3.0-fold risk of
second primary breast cancer, respectively, and the risks were even higher among carriers
diagnosed before age 4026–29. Increased risk of second primary breast cancer has also been
reported for PVs in CHEK2, PALB2, and TP53 in breast cancer patients28,29,30. In contrast,
little is known regarding the genetic risk of developing a non-breast second primary cancer
among breast cancer patients. A recent analysis in the Multiethnic Cohort Study (MEC) has
linked PVs in BRCA1 with risk of second primary non-breast cancer in 3,223 breast cancer
survivors30. In this analysis, carriers of PVs in ATM, CHEK2, BLM, ERCC3, and ERCC2 also
had a >2-fold risk of developing second primary non-breast cancer than non-carriers, but these
associations were not statistically significant due to small number of carriers, which warrant
further investigations in larger studies30
.

3
A previous analysis in the CAnceR RIsk Estimates Related to Susceptibility
(CARRIERS) Consortium has reported associations of PVs in BRCA1, BRCA2, CHEK2, and
PALB2 with risk of contralateral breast cancer29. Utilizing the available information on MPC
in the CARRIERS Consortium, we conducted this analysis to evaluate the association of PVs
in 37 cancer predisposition genes with risk of MPC and to assess whether the associations were
heterogeneous across racial/ethnic groups or modified by age at breast cancer diagnosis or
estrogen receptor status.

4
CHAPTER TWO: MATERIALS AND METHODS
Study Population
The CARRIERS Consortium includes 17 studies with a total of 39,553 women with
breast cancer and 35,867 study-matched controls, as described previously31. Of the 17
studies, nine studies also collected information on the diagnosis of other primary
malignancies for the majority of the breast cancer patients in the study. These include
four nested case-control studies in prospective cohorts (the Cancer Prevention Study II, the
Cancer Prevention Study 3, the California Teachers’ Study, the Multiethnic Cohort Study),
one clinical-based case-control study (the Mayo Clinic Breast Cancer Study), one populationbased case-control study (the Wisconsin Women’s Health Study), and three case-control
studies enriched with women with early-onset disease or a family history of breast cancer (the
Northern California Breast Cancer Family Registry, the Sister Study, the Two Sister Study)29
31
.
Among breast cancer patients from the nine studies, a total of 23,760 women with
complete information on the diagnosis of other primary malignancies and age at breast cancer
diagnosis were included in the final analysis, of which 2,953 (12.43%) had more than one
primary cancers (multiple primary cancer [MPC]), and 20,807 (87.57%) had only primary
breast cancer (PBC). Given the high prevalence of second primary breast cancer in breast
cancer patients and the previous investigation in contralateral breast cancer in CARRIERS
Consortium30, women with second primary breast cancer were excluded from the final

5
analysis. Both in situ and invasive non-breast cancer were considered as MPC in our analysis.
The study was approved by Institutional Review Board at the Mayo Clinic and all the
participating study sites
Targeted Sequencing and Bioinformatic Analysis
Germline DNA samples were analyzed using a QIAseq multiplex amplicon-based
method from Qiagen, which features dual barcoding and targets all coding regions and
consensus splice sites within 37 cancer predisposition genes. These genes were selected either
due to their presence on commercial hereditary cancer genetic testing panels or because of
their associations with breast, ovarian, endometrial, colorectal, or pancreatic cancer based on
previous reports32. High-quality sequence data (read depth of >20X) were obtained for 99.3%
of the targeted regions. As described previously, among variants with minor allele frequency
(MAF) <0.01 in the overall study population in the CARRIERS Consortium, all loss-of-function
variants (nonsense, frameshift, consensus splice sites) or variants identified as “pathogenic” or
“likely pathogenic” in the ClinVar database were classified as pathogenic variants (PVs)33
.
Statistical Analysis
In this study, we assessed the association between 37 cancer predisposition genes and
the risk of non-breast MPC among women who had ever been diagnosed with breast cancer.
For each gene, women with any PV in each of the cancer predisposition genes were considered
as carriers. Logistic regression analyses were conducted to assess the association of each gene
with the risk of non-breast MPC comparing carriers to noncarriers adjusting for age at
diagnosis of breast cancer, study, race/ethnicity (White, Black, Asian, Hispanic, American

6
Indian/Alaskan Native, Native Hawaiian, Multiracial/other, unknown) and first-degree family
history of breast cancer (positive, negative, unknown). Stratified analyses were also performed
to assess effect modification by age at breast cancer diagnosis (early-onset: <=55, late-onset: >55
years), estrogen receptor (ER) status of breast tumor (negative, positive), and by race/ethnicity
limited to the four largest groups in our study population (White, Black, Asian, and Hispanic).
Likelihood ratio tests (LRT) were used to formally test the interactions comparing models with
and without the interaction terms, limited to genes with at least 5 carriers detected within
each stratum. All statistical tests are two-sided and a p-value less than 0.05 was considered
statistically significant.

7
CHAPTER THREE: RESULT
Patient Demographic and Clinical Characteristics
Of the 23,760 breast cancer patients, the average age at breast cancer diagnosis was
slightly older among women with MPC than those with only PBC (62.1 years versus 59.7 years;
Table 1). Of the 2,953 breast cancer patients with non-breast MPC, 1157 (39.2%) had a
diagnosis of other primary malignancy prior to their breast cancer diagnosis, and the average
latency period between the two primary malignancies was 2.14 years. Compared with women
with only PBC, women with non-breast MPC were more likely to report a positive family
history of breast cancer (31.0% versus 27.0%) or ovarian cancer (4.7% versus 3.5%), or a tumor
that was ER positive (ER+; 56.9% versus 54.0%) or progesterone receptor positive (PR+; 47.7%
versus 45.8%).
Carrier Frequency of PVs in Cancer Predisposition Genes
Of all genes analyzed in this study, PVs were most commonly detected in BRCA2 (354
carriers, 1.49%), followed by CHEK2 (288 carriers, 1.2%), BRCA1 (272 carriers, 1.14%), ATM
(206 carriers, 0.8%) and PALB2 (141 carriers, 0.55%)
Association of PVs in Cancer Predisposition Genes with MPC
In gene-based analyses, statistically significant positive associations with risk of nonbreast MPC were observed for ATM (OR: 1.77, 95% CI: 1.24-2.52, P=0.002), BLM (OR: 2.32,
95% CI: 1.35-4.00, P=0.002), BRCA1 (OR: 1.70, 95% CI: 1.25-2.31, P=0.001), CHEK2 (OR: 1.41,
95% CI: 1.02-1.95, P=0.037), MLH1 (OR: 5.43, 95% CI: 1.51-19.50, P=0.01), MSH6 (OR: 2.94,

8
95% CI: 1.43-6.02, P=0.003), PPM1D (OR: 1.78, 95% CI: 1.03-3.08, P=0.038), and TP53 (OR:
4.81, 95% CI: 1.69-13.7, P=0.003; Table 2).
Among the 22 genes examined for effect modification by age at breast cancer diagnosis,
the association for ATM was significantly greater among women with early-onset breast
cancer (<=55 years; OR: 3.04, 95% CI: 1.76-5.24, P=1.0×10-4
) than among those with later-onset
disease (OR: 1.37, 95% CI: 0.85-2.20, P=0.19, PLRT =0.03). In contrast, the association for
BRCA1 was greater among later-onset breast cancer cases (>55 years; OR: 3.30, 95% CI: 2.03-
5.37, P=1.4x10-6
) than among early-onset cases (<=55 years; OR: 1.54, 95% CI:0.99-2.39,
P=0.05, PLRT =0.02; Table 3). Stronger associations among early-onset breast cancer cases were
also observed for FANCM (PLRT = 0.03), despite no significant association in the overall study
population (Table 3).
No effect modification was observed for the 15 genes assessed in the stratified analysis
by ER status (Table 4). Across the four major racial/ethnic groups in the study population
(White, African American, Asian, and Hispanic/Latino), the association of FANCM with risk
of MPC was significantly different (PLRT=0.037), with the association stronger in African
Americans than in Whites (OR of 2.77 versus 1.05; Table 5). No difference in association was
detected for other genes.

9
CHAPTER FOUR: DISCUSSION
In this large and diverse population of breast cancer patients, we found that PVs in
eight cancer predisposition genes (ATM, BLM, BRCA1, CHEK2, MLH1, MSH6, PPM1D, and
TP53) were strongly associated with increased risk of MPC, with the ORs ranging from 1.41
to 5.43. Our findings also suggest effect modification by age at breast cancer diagnosis for ATM,
BRCA1, and FANCM and heterogeneous effect across racial/ethnic groups for FANCM.
Our results are generally consistent with the few studies assessing the contribution of
PVs in cancer predisposition genes to MPC risk among breast cancer patients. Analyses in the
High-Risk Breast Cancer Program (551 MPC and 449 PBC) and the Familial Breast Cancer
Research Study (340 MPC and 1,464 PBC) have reported a significantly higher frequency of
PVs in MSH6 in women with MPC (breast and non-breast) than those with PBC34. Although
not significant, a higher PV frequency was also observed for ATM, CHEK2, PALB2, and TP53
among women with MPC than those with PBC34. In a recent cohort analysis in the
Multiethnic Cohort Study with 396 non-breast MPC among 3,223 breast cancer patients, PVs
in BRCA1 was significantly associated with a 3.0-fold risk of developing non-breast MPC30
.
Although non-significant, a positive association was also observed for PVs in ATM (hazard
ratio [HR]: 1.91), BLM (HR: 2.74), and CHEK2 (HR: 2.32). Associations for MLH1, MSH6,
PPM1D and TP53 were not reported in this study, as there were <5 carriers for these genes in
the study population. With a much larger sample size in the present study (n = 23,760), our
results provide further evidence supporting a potential role of PVs in eight cancer
predisposition genes. Of note, a majority of these genes have been implicated in previous

10
smaller studies (3,223/6,617) determining the genetic risk of MPC among breast cancer
patients30, 35
.
Our study has strengths and limitations. Our study represents one of the largest
multiethnic studies investigating the genetic risk of MPC in breast cancer survivors. The large
sample size of this study allows us to formally assess the associations of these genes with risk
of MPC, which has not been done in most previous studies with much smaller sample sizes.
The study population is racially/ethnically diverse and derived from many population-based
studies in the CARRIERS Consortium, suggesting that our findings are broadly generalizable.
Despite the large sample size, the number of PVs identified within each racial/ethnic group
was small, which limited the statistical power of the population-specific analyses. It’s known
that subsequent primary cancer survivors can be a result of radiation therapy for the first
primary cancer. However, information on cancer treatment was missing in many participating
studies in the CARRIERS Consortium, which prevented us from fully assessing treatment
effects and their potential interaction with PVs on MPC. This is particularly important for the
interpretation of associations with PPM1D, given that somatic mutations of this gene are
thought to be a driver gene for clonal hematopoiesis and have been found in high frequency
among treatment-induced cancers 36–38
.

11
CHAPTER FIVE: CONCLUSION
Results from this study indicate that germline PVs in ATM, BLM, BRCA1, CHEK2,
MLH1, MSH6, PPM1D, and TP53 contribute to the genetic risk of non-breast MPC in breast
cancer survivors. The suggestive associations observed with non-breast MPC for other genes
(e.g. BRIP1, CDH1, PTEN) warrant further investigations in larger studies. Combined with the
findings from previous analysis for contralateral breast cancer in CARRIERS Consortium29
,
our findings provide further support for a closer surveillance of MPC (breast or non-breast) for
women carrying PVs in these genes.

12
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v
LIST OF TABLES
Table 1 Characteristics of Study Population (N = 23,760)
Characteristics PBC(n=20,807) MPC(n=2,953)
Study, N（%）
CPS3 938 (4.5) 20 (0.7)
CPSII 3495 (16.8) 320 (10.8)
CTS 1748 (8.4) 241 (8.2)
MCBCS 3547 (17.0) 555 (18.8)
MEC 2786 (13.4) 638 (21.6)
NC-BCFR 1734 (8.3) 371 (12.6)
SISTER 1806 (8.7) 301 (10.2)
TWOSISTER 986 (4.7) 103 (3.5)
WWHS 3767 (18.1) 404 (13.7)
Age at BC diagnosis, Mean/SD 59.7 (11.8) 62.1 (11.0)
Age at other cancer diagnosis, Mean/SD -- 60.3 (15.7)
Race/Ethnicity, N（%）
White 16007 (76.9) 2162 (73.2)
Hispanic/Latino 1471 (7.07) 224 (7.6)
Asian 1403 (6.7) 227 (7.7)
African American 1329 (6.4) 245 (8.3)
Native Hawaiian or other Pacific Islander 240 (1.2) 56 (1.9)
Multiracial/Other 162 (0.8) 20 (0.7)
American Indian or Alaskan Native 43 (0.2) 7 (0.2)
Unknown 152 (0.7) 12 (0.4)
Family History of BC, N (%)

vi
Characteristics PBC(n=20,807) MPC(n=2,953)
Study, N（%）
Negative 14783 (70.8) 1972 (66.8)
Positive 5611 (27.0) 916 (31.0)
Unknown 458 (2.2) 65 (2.2)
Family History of OC, N (%)
Negative 19511(93.8) 2745(93.0)
Positive 738(3.5) 139(4.7)
Unknown 558(2.7) 69(2.34)
ER Status of BC
Negative 2352(11.3) 375(12.7)
Positive 11249(54.1) 1681(56.9)
Unknown 7206(34.6) 897(30.4)
PR Status of BC
Negative 3755(18.0) 588(19.9)
Positive 9531(45.8) 1409(47.7)
Unknown 7521(36.1) 956(32.4)
Abbreviations: PBC = primary breast cancer; MPC = multiple primary cancer; BC = breast cancer; OC
= ovarian cancer; ER = estrogen receptor; RP = progesterone receptor; CPS3 = the Cancer Prevention
Study 3; CPSII = the Cancer Prevention Study II; CTS = the California Teachers’ Study; MCBCS = the
Mayo Clinic Breast Cancer Study; MEC = the Multiethnic Cohort Study; NC-BCFR = the Northern
California Breast Cancer Family Registry; SISTER = the Sister Study; TWOSISTER = the Two Sister
Study; WWHS = the Wisconsin Women’s Health Study.

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Table 2 Association of germline PVs in cancer predisposition genes with MPC.
Genea
PBCc
Carrier, N
(%)
MPCc
Carrier, N
(%)
OR (95%CI) b P
APC 7 (0.03%) 0 (0%) – –
ATM 166 (0.78%) 40 (1.35%) 1.77 (1.24-2.52) 0.002
BARD1 33 (0.15%) 1 (0.03%) 0.23 (0.03-1.71) 0.15
BLM 56 (0.26%) 18 (0.61%) 2.32 (1.35-4.00) 0.002
BRCA1 218 (1.02%) 54 (1.82%) 1.70 (1.25-2.31) 0.001
BRCA2 318 (1.49%) 36 (1.21%) 0.88 (0.62-1.25) 0.46
BRIP1 39 (0.18%) 9 (0.30%) 1.93 (0.92-4.05) 0.08
CDH1 8 (0.04%) 3 (0.10%) 2.89 (0.73-11.4) 0.13
CDKN2A 6 (0.03%) 2 (0.07%) 2.49 (0.50-12.5) 0.27
CHEK2 242 (1.14%) 46 (1.55%) 1.41 (1.02-1.95) 0.04
EPCAM 9 (0.04%) 2 (0.07%) 1.68 (0.36-7.87) 0.51
ERCC2 102 (0.48%) 8 (0.27%) 0.59 (0.28-1.21) 0.15
ERCC3 37 (0.17%) 5 (0.17%) 0.91 (0.35-2.34) 0.84
FANCC 50 (0.23%) 5 (0.17%) 0.70 (0.28-1.78) 0.46
FANCM 36 (0.17%) 7 (0.24%) 1.44 (0.63-3.25) 0.39
KRAS 0 (0%) 1 (0.03%) – –
MEN1 2 (0.01%) 0 (0%) – –
MLH1 6 (0.03%) 4 (0.13%) 5.43 (1.51-19.5) 0.01
MRE11A 16 (0.08%) 3 (0.10%) 1.34 (0.38-4.70) 0.64
MSH2 5 (0.02%) 1 (0.03%) 2.58 (0.27-24.7) 0.41
MSH6 26 (0.12%) 11 (0.37%) 2.94 (1.43-6.02) 0.003
MUTYH 37 (0.18%) 7 (0.24%) 1.28 (0.56-2.92) 0.56
NBN 34 (0.16%) 8 (0.27%) 1.57 (0.72-3.43) 0.26

viii
NF1_ 16 (0.08%) 3 (0.10%) 1.34 (0.38-4.67) 0.65
PALB2 117 (0.55%) 24 (0.81%) 1.33 (0.85-2.08) 0.22
PMS2 43 (0.20%) 6 (0.20%) 0.86 (0.36-2.05) 0.74
PPM1D 62 (0.29%) 17 (0.57%) 1.78 (1.03-3.08) 0.04
PRSS1 13 (0.06%) 4 (0.13%) 2.20 (0.68-7.09) 0.19
PTEN 5 (0.02%) 2 (0.07%) 3.60 (0.63-20.6) 0.15
RAD50 35 (0.16%) 7 (0.24%) 1.34 (0.59-3.05) 0.49
RAD51C 28 (0.13%) 4 (0.13%) 1.05 (0.36-3.05) 0.92
RAD51D 24 (0.11%) 2 (0.07%) 0.59 (0.14-2.52) 0.47
RECQL 52 (0.24%) 3 (0.10%) 0.43 (0.13-1.39) 0.16
RINT1 16 (0.08%) 2 (0.07%) 0.74 (0.17-3.29) 0.70
SLX4 29 (0.14%) 4 (0.13%) 0.89 (0.31-2.58) 0.83
TP53 9 (0.04%) 6 (0.20%) 4.81 (1.69-13.7) 0.003
XRCC2 27 (0.13%) 1 (0.03%) 0.26 (0.04-1.96) 0.19
a The association analysis was limited to 34 genes with at least five carriers in all women and at least
one carrier in each comparison group.
b Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated from logistic regression
models adjusting for age at breast cancer diagnosis, study, family history and race/ethnicity. OR of
those genes that have none carriers in either PBC or MPC group were not reported.
c Abbreviations: PBC = primary breast cancer; MPC = multiple primary cancer.

vii
Table 3. Association of PVs in cancer predisposition genes with MPC stratified at age of BC diagnosis.
Gene a
Age at Diagnosis < 55 years (N=7,923) Age at diagnosis >= 55 years (N=15,837)
PBC PLRT
b

Carrier, N
(%)
MPCb

Carrier, N
(%)
OR (95% CI) P
PBC Carrier,
N (%)
MPC Carrier,
N (%)
OR (95% CI) P
ATM 61 (0.85%) 18 (2.43%) 3.04 (1.76-5.24) 1.0×10-4 100 (0.73%) 22 (1.0%) 1.37 (0.85-2.20) 0.19 0.03
BLM 18 (0.25%) 4 (0.54%) 1.85 (0.61-5.55) 0.27 37 (0.27%) 14 (0.63%) 2.46 (1.31-4.61) 0.01 0.72
BRCA1 169 (2.35%) 25 (3.37%) 1.54 (0.99-2.39) 0.05 45 (0.33%) 28 (1.27%) 3.30 (2.03-5.37) 1.43x10-6 0.02
BRCA2 163 (2.27%) 15 (2.02%) 1.02 (0.59-1.76) 0.93 139 (1.02%) 21 (0.95%) 0.98 (0.62-1.57) 0.95 0.99
BRIP1 16 (0.22%) 2 (0.27%) 1.57 (0.35-7.04) 0.55 20 (0.15%) 7 (0.32%) 2.17 (0.90-5.23) 0.08 0.74
CHEK2 102 (1.42%) 17 (2.29%) 1.59 (0.94-2.70) 0.086 136 (1.00%) 29 (1.31%) 1.42 (0.94-2.15) 0.10 0.71
EPCAM 5 (0.07%) 1 (0.13%) 2.25 (0.25-20.4) 0.47 4 (0.03%) 1 (0.05%) 1.29 (0.14-11.6) 0.82 0.78
ERCC2 31 (0.43%) 2 (0.27%) 0.61 (0.14-2.59) 0.5 66 (0.48%) 6 (0.27%) 0.60 (0.26-1.40) 0.23 0.97
ERCC3 13 (0.18%) 1 (0.13%) 0.72 (0.09-5.56) 0.75 22 (0.16%) 4 (0.18%) 1.01 (0.34-3.00) 0.99 0.68
FANCM 13 (0.18%) 5 (0.67%) 3.75 (1.3-10.81) 0.01 23 (0.17%) 2 (0.09%) 0.57 (0.13-2.45) 0.45 0.03
MRE11A 8 (0.11%) 2 (0.27%) 2.58 (0.54-12.4) 0.24 8 (0.06%) 1 (0.05%) 0.71 (0.09-5.79) 0.75 0.31
MSH6 11 (0.15%) 2 (0.27%) 1.69 (0.37-7.79) 0.5 15 (0.11%) 9 (0.41%) 3.34 (1.43-7.80) 0.005 0.40
MUTYH 11 (0.15%) 2 (0.27%) 1.81 (0.39-8.37) 0.45 26 (0.19%) 5 (0.23%) 1.13 (0.43-2.99) 0.81 0.62

viii
NBN 11 (0.15%) 1 (0.13%) 0.77 (0.10-6.02) 0.8 22 (0.16%) 7 (0.32%) 1.89 (0.79-4.50) 0.15 0.40
PALB2 51 (0.71%) 7 (0.94%) 1.22 (0.55-2.71) 0.63 64 (0.47%) 17 (0.77%) 1.49 (0.86-2.58) 0.15 0.68
PMS2 10 (0.14%) 3 (0.40%) 2.91 (0.76-11.1) 0.12 32 (0.24%) 3 (0.14%) 0.48 (0.15-1.58) 0.23 0.05
PPM1D 12 (0.17%) 3 (0.40%) 1.66 (0.44-6.20) 0.45 50 (0.37%) 14 (0.63%) 1.65 (0.90-3.01) 0.11 0.79
PRSS1 4 (0.06%) 1 (0.13%) 3.58 (0.37-34.4) 0.27 8 (0.06%) 3 (0.14%) 1.84 (0.47-7.24) 0.38 0.68
RAD50 18 (0.25%) 1 (0.13%) 0.51 (0.07-3.85) 0.51 17 (0.13%) 6 (0.27%) 2.10 (0.81-5.46) 0.13 0.14
RAD51C 9 (0.13%) 2 (0.27%) 1.95 (0.42-9.13) 0.4 17 (0.13%) 2 (0.09%) 0.74 (0.17-3.30) 0.70 0.37
RAD51D 10 (0.14%) 1 (0.13%) 0.92 (0.11-7.41) 0.94 13 (0.10%) 1 (0.05%) 0.45 (0.06-3.47) 0.44 0.62
RINT1 5 (0.07%) 1 (0.13%) 2.32 (0.27-20.1) 0.45 11 (0.08%) 1 (0.05%) 0.44 (0.06-3.47) 0.43 0.34
a Stratified analyses were conducted for 22 genes with at least 5 carriers within each stratum.
b Abbreviations: PBC = primary breast cancer; MPC = multiple primary cancer.

ix
Table 4. Association of PVs in cancer predisposition genes with MPC stratified by ER status.
Genea
ER-Positive (n=14082) ER-Negative (n=3030)
PLRT PBC b
c

Carrier, N
(%)
MPCc

Carrier, N
(%)
OR (95% CI) P
PBCc

Carrier, N
(%)
MPCc

Carrier, N
(%)
OR (95% CI) P
ATM 99(0.88%) 18(1.07%) 1.28 (0.77-2.15) 0.34 12(0.51%) 2(0.53%) 0.95 (0.2-4.43) 0.94 0.89
BLM 36(0.32%) 11(0.65%) 2.15 (1.07-4.30) 0.03 4(0.17%) 4(1.07%) 6.44 (1.59-26.2) 0.009 0.18
BRCA1 68(0.60%) 19(1.13%) 2.40 (1.42-4.06) 0.001 79(3.36%) 23(6.13%) 2.03 (1.22-3.38) 0.006 0.75
BRCA2 155(1.38%) 19(1.13%) 1.07 (0.66-1.75) 0.78 55(2.34%) 5(1.33%) 0.51 (0.2-1.31) 0.16 0.23
CHEK2 135(1.20%) 25(1.49%) 1.33 (0.86-2.06) 0.20 10(0.43%) 4(1.07%) 3.36 (0.99-11.4) 0.05 0.20
ERCC2 43(0.38%) 2(0.12%) 0.31 (0.07-1.31) 0.11 15(0.64%) 2(0.53%) 0.89 (0.2-3.98) 0.88 0.35
FANCM 16(0.14%) 2(0.12%) 0.81 (0.19-3.56) 0.78 6(0.26%) 2(0.53%) 2.25 (0.44-11.46) 0.33 0.33
MUTYH 21(0.19%) 5(0.30%) 1.65 (0.61-4.49) 0.32 6(0.26%) 1(0.27%) 1.05 (0.12-9.27) 0.97 0.70
PALB2 56(0.50%) 11(0.65%) 1.26 (0.65-2.43) 0.50 27(1.15%) 7(1.87%) 1.69 (0.72-3.99) 0.23 0.60
PPM1D 26(0.23%) 7(0.42%) 1.44 (0.62-3.37) 0.40 7(0.30%) 3(0.80%) 1.85 (0.45-7.59) 0.4 0.76
PRSS1 6(0.05%) 3(0.18%) 3.14 (0.73-13.5) 0.12 3(0.13%) 1(0.27%) 2.27 (0.22-23.5) 0.49 0.86
RAD50 20(0.18%) 5(0.30%) 1.68 (0.61-4.63) 0.31 4(0.17%) 1(0.27%) 2.06 (0.23-18.8) 0.52 0.93

x
RAD51C 11(0.10%) 1(0.06%) 0.53 (0.07-4.23) 0.55 5(0.21%) 2(0.53%) 3.25 (0.6-17.6) 0.17 0.17
RAD51D 10(0.09%) 1(0.06%) 0.79 (0.10-6.35) 0.82 6(0.26%) 1(0.27%) 0.81 (0.09-6.85) 0.84 0.95
RECQL 23(0.20%) 1(0.06%) 0.32 (0.04-2.39) 0.27 7(0.30%) 2(0.53%) 1.56 (0.31-7.83) 0.59 0.24
a Stratified analyses were conducted for 15 genes with at least 5 carriers within each stratum.
b Likelihood ratio test (LRT) was performed in samples with completed data in ER status.
c Abbreviations: PBC = primary breast cancer; MPC = multiple primary cancer.

xi
Table 5. Association of PVs in cancer predisposition genes with MPC stratified by race/ethnicity.
Genea
White
(n=18,169)
African American (n=1,574)
Asian
(n=1,630)
Hispanic
(n=1,695)
PLRT
OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P
ATM 1.93 (1.30-2.86) 0.001 0.82 (0.18-3.78) 0.80 – – 4.78 (1.48-15.4) 0.009 0.07
BLM 1.99 (1.08-3.64) 0.03 5.00 (0.31-80.4) 0.26 – – 5.89 (1.17-29.7) 0.03 0.39
BRCA1 1.64 (1.13-2.40) 0.01 3.35 (1.11-10.1) 0.03 12.0 (1.94-74.3) 0.0075 3.02 (1.22-7.46) 0.017 0.20
BRCA2 1.11 (0.76-1.62) 0.59 – – 1.78 (0.37-8.60) 0.47 1.19 (0.26-5.50) 0.82 0.29
CHEK2 1.38 (0.98-1.94) 0.07 2.40 (0.43-13.4) 0.32 – – 6.68 (0.92-48.3) 0.06 0.60
ERCC2 0.61 (0.28-1.34) 0.22 0.80 (0.10-6.74) 0.84 – – – – 0.93
FANCM 1.05 (0.36-3.01) 0.93 2.77 (0.25-30.3) 0.40 – – – – 0.037
MUTYH 1.09 (0.41-2.86) 0.87 8.40 (0.43-164.6) 0.16 2.02 (0.21-19.9) 0.55 – – 0.61
NF1 1.69 (0.36-7.95) 0.50 4.91 (0.30-79.4) 0.26 – – – – 0.48
PALB2 1.33 (0.74-2.38) 0.35 1.14 (0.32-4.04) 0.84 2.66 (0.50-14.0) 0.25 1.51 (0.43-5.32) 0.52 0.22
PMS2 1.40 (0.40-4.87) 0.60 0.55 (0.13-2.39) 0.42 – – 2.14 (0.22-21.0) 0.51 0.76
PPM1D 1.52 (0.78-2.98) 0.22 0.83 (0.09-7.19) 0.86 – – 3.41 (0.61-18.9) 0.16 0.09
PRSS1 0.76 (0.08-6.81) 0.81 4.20 (0.62-28.6) 0.14 6.28 (0.39-102.0) 0.20 – – 0.43
RAD50 1.77 (0.70-4.47) 0.23 2.44 (0.22-27.4) 0.47 – – – – 0.32
RAD51C 1.09 (0.31-3.78) 0.89 – – 5.51 (0.34-90.3) 0.23 – – 0.45
RAD51D – – 1.36 (0.14-13.50) 0.79 – – 3.16 (0.26-38.1) 0.36 0.26
RINT1 0.47 (0.06-3.83) 0.48 – – 9.32 (0.56-156.4) 0.12 – – 0.51
TP53 5.44 (1.34-22.0) 0.018 – – 5.80 (0.35-95.0) 0.22 8.14 (1.10-60.0) 0.04 0.90
a Stratified analyses were conducted for 18 genes with carriers detected in at least two racial/ethnic groups.
b Likelihood ratio test (LRT) was performed in samples from the four major racial/ethnic groups.

Abstract (if available)

Abstract Past research on the genetic risk of multiple primary cancers (MPCs) in breast cancer survivors has focused on contralateral breast cancer risk. The goal of this study was to investigate the contribution of known cancer predisposition genes to the susceptibility of non-breast MPCs among breast cancer patients. We analyzed data from 23,760 breast cancer patients from the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium to investigate associations between pathogenic variants (PVs) in 37 cancer predisposition genes and the risk of non-breast MPC using logistic regression analyses. We also evaluated potential effect modification by race/ethnicity, age at breast cancer diagnosis, and estrogen receptor (ER) status. We found eight genes to be significantly associated with an increased risk of non-breast MPC, including ATM (OR: 1.77, 95% CI: 1.24-2.52, P=0.002), BLM (OR: 2.32, 95% CI: 1.35-4.00, P=0.002), BRCA1 (OR: 1.70, 95% CI: 1.25-2.31, P=0.001), CHEK2 (OR: 1.41, 95% CI: 1.02-1.95, P=0.037), MLH1 (OR: 5.43, 95% CI: 1.51-19.5, P=0.01), MSH6 (OR: 2.94, 95% CI: 1.43-6.02, P=0.003), PPM1D (OR: 1.78, 95% CI: 1.03-3.08, P=0.038), and TP53 (OR: 4.81, 95% CI: 1.69-13.7, P=0.003). The association for ATM was significantly greater among women with early-onset breast cancer (<=55 years; OR: 3.04, 95% CI: 1.76-5.24, P=1.0×10-4) than those with later-onset breast cancer (OR:1.37, 95% CI: 0.85-2.20, P=0.19, PLRT=0.03), while the association for BRCA1 was greater in later-onset breast cancer cases (OR: 3.30, 95% CI: 2.03-5.37, P=1.4⋅10-6) than in early-onset cases (OR:1.54, 95% CI: 0.99-2.39, P=0.05, PLRT=0.02).

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Asset Metadata

Creator Song, Zixuan (author)

Core Title Pathogenic variants in cancer predisposition genes and risk of non-breast multiple primary cancers in breast cancer patients

School Keck School of Medicine

Degree Master of Science

Degree Program Applied Biostatistics and Epidemiology

Degree Conferral Date 2024-05

Publication Date 05/22/2024

Defense Date 05/21/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag breast cancer,cancer predisposition genes,Epidemiology,multiple primary cancer,OAI-PMH Harvest

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Chen, Fei (committee chair), de Smith, Adam (committee member), Huang, Brian (committee member)

Creator Email sophiesong9846@gmail.com,zixuanso@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113954420

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Legacy Identifier etd-SongZixuan-13004

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