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Capture and analysis of circulating tumor cells in patients with hepatocellular carcinoma: analysis of a pilot study

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Content CTC: CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS
WITH HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY

Capture and Analysis of Circulating Tumor Cells in Patients with
Hepatocellular Carcinoma – Analysis of a Pilot Study
Cheng Dong
University of Southern California

Author Note
Cheng Dong, Department of Preventive Medicine, Keck School of Medicine

CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY
Table of Contents
Abstract 1
Introduction 2
Hepatocellular Carcinoma (HCC) 2
Circulating Tumor Cells (CTC) 5
Hypothesis 9
Method 10
Study design 10
Statistical analysis
Summary of testing
14
16
Result 18
Patient characteristics 18
CTC classification and association with patient cohorts 21
CTC change 22
Association between baseline CTC and baseline characteristics 23
Conclusion 26
Discussion 28
References 29

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Abstract
Hepatocellular carcinoma (HCC), which we can also call malignant hepatoma, is a primary liver
cancer and a major cause of cancer morbidity and mortality all over the world. According to
Zhang Y, Li J, Cao L, Xu W, and Yin Z (2012), circulating tumor cells (CTCs) reflect the
information of HCC metastasis or recurrence. This makes CTC as a useful biomarker of HCC.
The popular standard method based on immunomagnetic binding of epithelial cell adhesion
molecules (EpCAMs) cannot be used to collect CTC of HCC because HCC cells rarely express
EpCAM. However, Dr. Amir Goldkorn solved this problem by developing a parylene–C slot
microfilter platform. So a total of 170 HCC patients are planned to be recruited to analyze CTC
in HCC. For now, only 93 patients are enrolled to this program and the study is still in process.
The hypothesis in this study to be tested are (1) Patients with advanced disease stage will have
more CTCs. (2) The numbers of CTC are decreased after treatment.

Keywords: HCC, CTC

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Introduction
Hepatocellular Carcinoma (HCC)
Description
Hepatocellular carcinoma (HCC) is the fifth most known worldwide tumor with a great
challenge in terms of its complex etiology and its management. As the third most common cause
of cancer deaths all over the world (about 600,000 patients die annually), HCC also contributes
to 85% - 90% of primary liver cancer (Chiappini, 2012). Although HCC is not as usual as other
cancers in United States, there are still 24,120 new cases and 18,910 deaths in USA in 2010.
Alcoholism, Hepatitis B, Hepatitis C (25% of causes globally), Aflatoxin, Cirrhosis of the
liver, Hemochromatosis, Wilson’s disease, Type 2 Diabetes consist of main risk factors for HCC.
The major risk factors are different among different countries. For example, Cirrhosis becomes
the main causative agent of HCC in United States, while Hepatitis B is the main reason in China
because of low vaccination rates. The increasing prevalence of hepatitis C, which leads to a raise
in incidence rate of HCC, attracts a lot attention in diagnosis and prognosis of HCC.
The possibility of a man to develop HCC is eight times more than a woman due to the
stimulatory effects of androgen and the protective effects of estrogen. The incidence rate of HCC
also varies in different age stages (Shiou-hwei & Pei-jer, 2010). Incidence of HCC increases
along with age. People who are between 50 to 70 years old are under high risk of developing
HCC in western countries.

Disease stage
BCLC stage. In order to get the best treatment option and establish a prognosis estimate,
selecting an appropriate staging system is the first priority. The Barcelona-Clinic Liver Cancer
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(BCLC) staging system could assist us in estimating the prognosis and the evaluation of
treatment’s result by choosing a principle therapy.
Single tumor or 3 nodules less than 5 cm, normal bilirubin and no portal hypertension are
signs of early stage (Stage 0 or A) in HCC. Radical approach (resection and ablation, liver
transplantation; or percutaneous treatments) is the optimal treatment for patients at this stage. If
patients have 3 nodules less than 3 cm or have single tumors less than 5 cm, liver transplantation
should be considered. Chemoembolization is the best choice for patients with multinodular non-
invasive tumors who are at Stage B. Vascular invasion or metastases and performance status test
(PST) = 1 – 2, are evidences of Stage C. Patients with advanced HCC at this stage will benefit
from randomized controlled trials (RCT). Finally, at Stage D (the end-stage HCC, PST>2),
patients will receive symptomatic treatment (Josep M, Josep & Jordi, 2004).
Milan criteria. Patients with HCC are qualified for liver transplantation if they meet the
following conditions:
1. No lesion larger than 5 cm
2. ≤ 3 lesions with diameter ≤ 3 cm
3. No extrahepatic involvement
4. No major vessel involvement.
However, the “UCSF” criteria, proposed by University of California San Francisco, suggests
that the Milan criteria might be stringent. The “UCSF” states that liver transplantation should be
used when patients have a solitary tumor smaller than 6.5 cm, or 3 of fewer nodules, with the
largest lesion <= 4.5 cm or total tumor diameter <=8.5 cm without vascular invasion. Patel et al.
(2012) found that no difference in survival was identified between patients transplanted by
UCSF criteria or Milan criteria.
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Extra Hepatic Metastasis and Portal Vein Invasion. Evaluating the clinical features of
extrahepatic metastases or portal vein invasion is very important to determine the most
appropriate treatment method. In a clinical trial, 14.0 – 36.7% of patients with HCC have been
reported to have extrahepatic metastasis. Lung, lymph nodes, bone and adrenal gland are main
metastatic sites. 12.5 – 39.7% of patients with HCC show portal venous invasion, even though
the progress of diagnosis of HCC at an early stage has been improved. A study of HCC with
extrahepatic metastases showed that patients with extrahepatic were more likely to have vessel
invasion (Natsuizaka M el at. 2005).
Child Pugh Status. A major way to determine the prognosis, assess the effect of treatment
and necessary of liver transplantation is Child–Pugh score (Child–Turcotte–Pugh score), which
employs five clinical measures of liver disease. Chronic liver disease is classified into Child–
Pugh class A to C. One-year survival in classes A (5 - 6 points), class B (7 - 9 points), class C
(10 – 15 points) is 100%, 81%, 45%, respectively.

Treatment
Nonsurgical therapy is a more effective way for patients who are at advanced stage to avoid
disease processing. The most popular method is transcatheter arterial chemoembolization
(TACE). Even though some studies state there is no benefit from TACE, other reports suggesting
that survival rate increased by 15% per year in a group of 112 patients brought hope to HCC
patients. Other methods, like TheraSphere, systemic or regional chemotherapy, combination of
gemcitabine and oxaliplatin (GEMOX) are also used clinically.
Even though surgical resection of HCC can extend life and reduce tumor burden, up to 75%
of patients still develop intrahepatic recurrence within 5 years. In contrast, orthotopic liver
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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transplantation is a better method to eliminate the possibility of local recurrence at the resection
margin and clear up the cirrhotic liver (http://www.medscape.com/viewarticle/452731_7).

Prevention
People are encouraged to have hepatitis B and C vaccination program. Drinkers and smokers
should obey some daily limits. Participation in screening programs is encouraged to patients with
a family history or liver disease.

Circulating Tumor Cells (CTCs)
Clinical Significance
Circulating tumor cells (CTC) is the reflection of the vigorous nature of tumor because they
are cells circulating in the bloodstream from a primary tumor. People didn’t realize the clinical
significance of CTCs when it was first found by Thomas Ashworth, who concluded that CTCs
came from an existing cancer structure. Now, more and more studies have suggested that CTCs
are very important to predict clinical outcome of patients with different kinds of solid cancers.
The reason of clinical characteristics of HCC invading into vessels, generating metastases in the
portal vein and other organs is still unknown. So detecting and enumerating these cells have been
an effective way to understand metastasis in depth. In addition, progression-free survival and
overall survival can be predicted by CTC (Figure 1). So the biological information from CTC
will serve as a booster on selection of optimal treatment options and prognosis.

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Figure1: Kaplan Meier Analysis of overall survival before starting a new line of therapy for
patients with metastatic breast, colorectal and prostate cancer. (Significance of Circulating
Tumor Cells detected by the CellSearch System in Patients with Metastatic Breast Colorectal and
Prostate Cancer)

Figure 1 from “Significance of Circulating Tumor Cells detected by the CellSearch System
in Patients with Metastatic Breast Colorectal and Prostate Cancer” showed that patients were
classified into 2 groups, favorable and unfavorable CTC. Different cutoff values were chosen to
distinguish favorable and unfavorable CTC according to different cancer. It is obvious that the
median OS (Overall Survival) for Metastatic breast cancer (MBC), Metastatic colorectal cancer
(MCRC), and Metastatic prostate cancer (MPC) with less CTCs is longer than that with more
CTCs M (Miller, Doyle & Terstappen, 2010).

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Isolation and enumeration of CTCs
High sensibility and specific methods of CTC detection should be used due to the extremely
small number of CTCs in the bloodstream. The standard method to collect CTC based on
immunomagnetic binding of cell surface epithelial cell adhesion molecules (EpCAM) expressed
on cancer cells is not applicable to HCC cells because of rare expression of EpCAM. But this
will not be a problem by using a parylene – C slot microfilter platform, which can isolate and
characterize live circulating tumor cells (CTC) from bloodstream rapidly and efficiently.
CTC capture on a parylene-C slot microfilter platform needs a filter fabrication, constant
pressure fluid delivery system (Figure 2) and cell lines. The method includes, (1) Calculation of
capture efficiency, cell viability, and enrichment. (2) Patient specimen collection and processing.
(3) Scanning electron microscopy. (4) Telomeric repeat amplification protocol assay. The new
method solves the problem that most existing cell capture techniques are not applicable to some
tumor types that rarely express cell surface antigen. Another advantage of this new technique is
that it can capture live CTCs in a fast and efficient way and will not preclude the removal of cells
for further study (Xu, Lu, Tai & Amir Goldkorn, 2010).
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Figure 2: Microfilter fabrication and constant-pressure fluid delivery system. A,microfilter
fabrication process. B,bright-field micrograph of slot microfilter. C,constant-pressure fluid
delivery system and filter assembly.(A Cancer Detection Platform Which Measures Telomerase
Activity from Live Circulating Tumor Cells Captured on a Microfilter)

Tumor-specific markers of HCC to detect CTC
1. Alpha-fetoprotein (AFP)
Alpha-fetoprotein (AFP), found in human fetus, is a major plasma protein produced by the
yolk sac and the liver. AFP levels are above the normal when at birth and then decline gradually.
An increase of serum AFP levels occurs when people have those diseases: Omphalocele,
Hepatocellular carcinoma/hepatoma, Neural tube defects, Nonseminomatous germ cell tumors,
Yolk sac tumor, Ataxia telangiectasia. As a major biomarker, AFP with a level above 500 ng/ml
can be the evidence of hepatocellular carcinoma, germ cell tumors, and metastatic cancers of the
liver.
AFP is correlated with tumor size and volume. According to a study from Thailand, HCC
patients with AFP > 400 ng/ml are more likely to have greater size, portal vein thrombosis. A
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decrease of AFP levels will occur when tumor is removed by surgical method. A progressively
rise in AFP levels is usually followed by disease recurrence (Bialecki & Di Bisceglie, 2005).
2. Transforming Growth Factor Beta-1 (TGF-β1)
Transformation growth factor beta 1 (TGF-β1), which is one of transforming growth factor
beta superfamily of cytokines, shows many important cellular effects, such as the control of cell
growth, cell differentiation and proliferation. The high sensitivity and specificity of TGF-β1
level, due to the higher levels of circulating TGF-β1 and TGF-β1 mRNA in the HCC patients,
make it become an optimal biomarker for diagnosis and prognosis of HBV-induced HCC.
3. Insulin-Like Growth Factor (IGF)-II
Insulin-Like Growth Factor 2, one of protein hormones with similar structure to insulin, can
stimulate growth hormone during gestation. According to some studies, even though IGF-II is
specific of the HCC, the fact that there are only 34% positive frequency of circulating IGF-II
mRNA in HCC shows it is not really sensitive. IGF-II can help detect CTC when combined with
other circulating biomarkers.

Hypothesis
There are two hypothesis generated according to previous studies on clinical significance of
CTCs detected in patients with other cancers. (1) The number of CTCs is the reflection of extent
of HCC. Patients in advanced stage HCC are more likely to have more CTCs than patients in
intermediate or early stage. (2) After treatment, the number of CTCs is decreased.

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Methods
Study Design
Patient recruitment and eligible criteria
Patients were recruited from 3 institutions: University of Southern California (USC) Norris
Comprehensive Cancer Center, LAC+USC Medical Center and University Hospital. Based on
the Barcelona Clinic Liver Cancer (BCLC) staging system, those patients were categorized into 3
groups, cohort 1, cohort 2, and cohort 3. A total of 170 patients should be enrolled: Sixty patients
in cohort 1, thirty patients in cohort 2, and eighty patients in cohort 3. According to the accrual
rate, full accrual will be completed over 21 months from the start date (9/27/2011). So far, a total
of 93 patients had been recruited to this study: thirty-four patients in cohort 1, thirty patients in
cohort 2, and twenty-nine patients in cohort 3.
Patients enrolled into cohort 1, were those who are at advanced stage based on existence of
macrovasular invasion and/or extrahepatic metastases. During first 4 weeks of enrollment,
patients were required to receive first line systemic therapy, which included sorafenib as single
agent, sorafenib combined with IGFR antibody as section of a clinical trial, other therapy with
antiangiogenic activity. CTC should be collected at those time points: prior to start of treatment
(baseline), on day 1 of cycle 2, then on day 1 of every odd numbered cycle (3, 5, 7…) and at
progression. During the study, basic demographics, stage of disease, best radiologic response,
time of progression were collected and restaging imaging studies as per standard of care were
required.
Patients at intermediate stage for cohort 2 were supposed to have liver directed therapy
within 4 weeks of enrollment. No prior liver directed therapy or systemic therapy was necessary.
The time points of CTC collection were: prior to start of treatment (baseline), 1 to 2 hours post
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TACE, one week post treatment, 8 weeks post-treatment, and at progression. Restaging imaging
studies as per standard of care were still required.
Eligible patients with early stage HCC were qualified for cohort 3 and were listed for liver
transplant, as well as those who were receiving or planning to receive ablative bridge therapy.
The collection time points were: at enrollment (baseline), then every 6 months (~2-3 draws total)
and when unlisted for liver transplant. It was necessary to have restaging imaging studies done
and follow up patients who underwent liver transplant.

Clinical data collection
A case report forms (CRFs) was performed to optimize prospective clinical data capture for
the study. Those clinical data were being collected in USC Norris Comprehensive Cancer Center
electronic database.

Successful capture and enumeration of CTC from patient blood samples
The successful process of collecting blood samples for CTC analysis was benefited from an
amendment to protocol OS-11-5, which was possible to develop cohort-specific eligibility
checklist, to develop a specimen collection form, to collect series sample and to establish a work
flow process to draw and deliver samples to the laboratory in an effect way. At collection time
points, the tube with 7.5 ml peripheral blood drawn by standard venipuncture was delivered to
laboratory at room temperature. Depleting red blood cells and isolating the “buffy coat” layer
containing CTC and white blood cells should be done. The Nuance multispectral imaging
platform was used to enumerate captured CTC.

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Successful molecular characterization of CTCs
Additional blood samples on a subset of 22 patients from Cohort 3 were collected to perform
mRNA isolation cDNA synthesis and qRT-PCR analysis of HCC-associated gene transcript
levels. IGF-II and MET were shown to have special significance in this process. Dong et al.
(2005) showed that IGF-II levels were significantly higher in HCC than those in chronic hepatitis
or liver cirrhosis. Rimassa et al at the 2012 American Society of Clinical Oncology annual
meeting suggested that MET plays an important role in. predicting HCC. So both IGF-II and
MET are potential biomarkers in HCC.

CTC classification
M. Craig Miller’s study (2010) found the flowing:
For MBC and MPC a threshold of 5 CTC/7.5 mL and for MCRC a threshold of 3 CTC/7.5
mL were used to stratify patients into those with Favorable outcomes (CTC<3 or <5) and
those with Unfavorable outcomes (CTC≥3 or ≥5). Median OS for MBC, MCRC, and MPC
patients with Favorable CTC was 21.9 (95%CI: 20.1-28.6), 18.5 (95%CI: 15.2-21.2), and
21.7 (95%CI: 21.3-NR) months, respectively. In contrast median OS for MBC, MCRC, and
MPC patients with Unfavorable CTC was 10.9 (95%CI: 7.0-15.2), 9.4 (95%CI: 7.5-11.6),
and 11.5 (95%CI: 9.3-13.7) months, respectively.
This study showed that the result was different among different CTC groups. So classifying
CTC into groups is useful to understand the characteristics of CTC, and then helps understand
dissemination, drug resistance and treatment outcome.
Thus, analysis of Baseline CTC stratified into 7 groups, 3 groups and 2 groups were done
during the study. The 7 groups' cutoff values of CTC were: 0 CTC/7.5 ml, 1 CTC/7.5 ml, 2-5
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CTC/7.5 ml, 6-10 CTC/7.5 ml, 11-50 CTC/7.5 ml, 51-100 CTC/7.5 ml and >100 CTC/7.5 ml,
respectively. For CTC stratified into 3 groups, 0-5 CTC/7.5 ml, 6-50 CTC/7.5 ml, >50 CTC/7.5
ml were selected as the cutoff values. A threshold of 5 CTC/7.5 ml was used to categorize HCC
patients into 2 groups.

Factors associated with HCC
To evaluate the association of CTC and disease stage, BCLC stage, Milan criteria, UCSF
criteria, portal vein invasion and extra hepatic metastasis were important factors that should be
analyzed because the classification of patient cohorts was based on these criteria. In addition to
these significant factors, the flowing factors also play important roles in HCC.
Age. In our study, age was defined from the date of birth to the on-study date and was
recorded as whole years of age. Some studies suggested, “Incidence of HCC increased with age,
peaking between 30 and 50 years of age. In western countries, HCC usually occurs between the
ages of 50 and 70. In areas where hepatitis B virus is prevalent, HCC usually occurs between the
ages of 20 and 40.” (https://www.clinicalkey.com/topics/surgery/hepatocellular-carcinoma.html).
To test if there is evidence of significant difference among CTC groups with respect to different
age groups, the study population was classified by age into 3 groups: 43-55 years old, 56-70
years old, >70 years old.
Gender. Men are four times more likely to develop HCC than women in the United States.
So gender affect should be considered into analysis of CTC.
Etiology of cirrhosis. Patients with cirrhosis are more likely to develop HCC. Hepatitis C is
the major reason for HCC in the United States. So two groups (viral, Non-viral) were classified
to help detect the association between CTC and etiology of cirrhosis.
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Diagnosis of HCC. The diagnosis of Hepatocellular Carcinoma was based on:
(1) The presence of one or more liver lesions, measuring ≥2cm, with characteristic arterial
enhancement and venous washout in the setting of liver cirrhosis and/or Hepatitis or C infection;
(2) The presence of liver lesion(s) with AFP≥400;
(3) Tissue confirmation in the absence of A and/or B.

Statistical analysis
Univariate statistics:
Univariate statistical analysis was used to test the hypotheses that if there was a change in
CTC after treatment. Measurement of CTC data was the first step in the process that guided the
final analysis. The descriptive statistics include: range (difference between minimum and
maximum values), average (mean), median, mode (most frequently occurring value), variance
(one measure of dispersion of a data set), and standard deviation (square root of the variance).
The normality test of univariate statistics was performed in order to select an appropriate test:
parametric statistics or nonparametric statistics. According to online source, parametric statistics
are based on the assumption that the data in the study are drawn form a population with a normal
(bell-shaped) distribution and/or normal sampling distribution. Nonparametric methods are used
when the data distribution is unknown
(http://www.cengage.com/marketing/book_content/1439080674_zikmund/book/ch21.pdf).

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Table 1 Test Normality
Graphical Methods Numerical Methods
Descriptive Stem-and-leaf plot, (skeletal) box plot,
dot plot, histogram
Skewness
Kurtosis
Theory-driven P-P plot
Q-Q plot
Shapiro-Wilk, Shapiro-Francia
test, Kolmogorov-Smirnov test
(Lillefors test),
From Hun Myoung Park. “Univariate Analysis and Normality Test Using SAS, Stata, and SPSS”
(http://rt.uits.iu.edu/visualization/analytics/docs/normality-docs/normality.pdf)

According to the normality test, Wilcoxon signed rank test was selected to test the null
hypothesis.
Wilcoxon signed rank test:
The signed rank statistic is computed as

Where is the rank of after discarding values of , and is the number
of values not equal to . Average ranks are used for tied values
(http://support.sas.com/documentation/cdl/en/procstat/63104/HTML/default/viewer.htm#procstat
_univariate_sect029.htm).

Exact test:
Due to small counts of the cells, fisher’s exact test was used to determine if there were
nonrandom associations between two categorical variables (CTC and other factors).
Hypergeometric distribution to compute probabilities of possible tables based on the observed
row and column totals was performed to do the statistics.
Fisher’s exact p-values are computed by summing probabilities p over defined sets of tables,
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Mantel-Haenszel Chi-Square Test:
The Mantel-Haenszel chi-square statistics was used to test if there was a linear association
between two categorical variables with ordinal scale. In study, this was applied to test linear
association between categorical CTC and other ordinal factors.
The Mantel-Haenszel chi-square statistic is calculated as:

where is the Pearson correlation between the row variable and the column variable.

Summary of Testing:
Scientific Hypothesis 1:
The number of CTCs is the reflection of extent of HCC. Patients in advanced stage HCC are
more likely to have larger numbers of CTCs than patients in intermediate or early stage.
From that we develop the following scientific hypothesis:
H0: P1 = P2 = P3
Let Pi is the proportion of patients in cohort i where CTC number is at level of ≤ 5
circulating tumor cell per 7.5 mL of blood.
Ha: P1 ≠ P2 ≠ P3;
To test the statistical significance, we will use Fisher’s exact test.

Scientific Hypothesis 2:
After treatment, the numbers of CTCs are decreased.
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From that, we developed the statistical hypothesis:
H0: m0 = 0
Let m0 is the difference of population median in CTC between before treatment group and
after treatment group.
Ha: m0 ≠ 0;
To test the statistical significance, we use the Wilcoxon signed rank test.

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Result
Patient characteristics
A total of 93 patients were eligible to be enrolled in this study. 34 (35%) HCC patients were
enrolled into Cohort 1. Thirty (33%) HCC patients were stratified into Cohort 2. Twenty-nine
(32%) patients were defined as Cohort 3. Most of patients (55%) were from USC Norris
Comprehensive Cancer Center. The range of age was from 33 years old to 90 years old (median,
60). Population were stratified into 3 groups by age: 43-55 years old, 56-70 years old, >71 years
old. A Half of patients (54%) were between 57 to 70 years old. There were 76 (82%) men
enrolled, which was almost 5 times than women. This may indicate that males have higher
incidence rate of HCC than females. The median values of Baseline AFP for cohort 1, cohort 2,
and cohort 3 were 303.0 (3 - 56952), 39 (2 - 6948), and 8.0 (2 - 4461), respectively. That
suggested that disease stage was associated with the numbers of Baseline AFP. In cohort 1, there
were 24 (73%) patients at BCLC stage C and 9 (27%) patients at BCLC stage B. In cohort 2,
there were 13 (48%) patients at BCLC stage A and 14 (52%) patients at BCLC stage B. In cohort
3, there were 23 (96%) patients at BCLC stage A and 1 (4%) patient at BCLC stage B. These
data make sense based on BCLC staging criteria. Because most HCC patients who were at
advanced stage were supposed to be classified into BCLC stage C, who were at intermediate
stage were supposed to be at BCLC stage B or stage A, who were at earlier stage were supposed
to be stratified into BCLC stage A. All the patients in cohort 1 didn't meet Milan Criteria and
UCSF Criteria. Eleven (33%) patients in cohort 1 had portal vein invasion and 17 (52%) patients
in the same cohort had extra hepatic metastasis. No patient was found to have portal vein
invasion and hepatic metastasis in cohort 2 and cohort 3. These data suggest that patients with
advanced stage HCC were more likely to appear metastases. Almost 66% of patients were
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classified into Child-Pugh class A (5 - 6 points). Twenty-five (29%) of patients were qualified
for Child-Pugh class B (7 – 9 points). Only 5 (6%) patients were classified into Child-Pugh class
C (10 – 15 points). Sixty-four percent of risk factors were Hepatitis B or Hepatitis C. Other non-
viral reasons were alcohol, NASH. Fifty-six percent of diagnosis of Hepatocellular Carcinoma
relied on: the presence of one or more liver lesions, measuring ≥2cm, with characteristic arterial
enhancement and venous washout in the setting of liver cirrhosis and/or Hepatitis or C infection.
Fifty-seven (71%) patients didn’t have prior treatments. The treatment that most (63%) patients
had accepted was Intra-Arterial Chemotherapy (IAC). (Table 2)

Table 2 Demographics and Baseline Clinical Characteristics
Cohort 1 Cohort 2 Cohort 3 Total
Total Patients 34 (100%) 30 (100%) 29 (100%) 93 (100%)
Institutions
University Hospital 1 (3%) 1 (3%) 26 (90%) 28 (30%)
LACGEN 7 (21%) 7 (24%) 0 (0%) 14 (15%)
Norris CCC 26 (76%) 22 (73%) 3 (10%) 51 (55%)
Age at On Study
Median (range) 63.0 (43–90) 57.5 (33–77) 61.0 (49–72) 60 (33-90)
43-55 7 (20%) 11 (37%) 9 (31%) 27 (29%)
56-70 19 (56%) 13 (43%) 18 (62%) 50 (54%)
71-90 8 (24%) 6 (20%) 2 (7%) 16 (17%)
Gender
Female 6 (18%) 4 (13%) 7 (24%) 17 (18%)
Male 28 (82%) 26 (87%) 22 (76%) 76 (82%)
Baseline AFP
Median (range) 303.0 (3–56952) 39.0 (2–6948) 8.0 (2-4461) 43.5 (2-56952)
<400 19 (56%) 25 (83%) 27 (93%) 71 (76%)
>=400 15 (44%) 5 (17%) 2 (7%) 22 (24%)
Missing 0 0 0 0
Disease Stage at Baseline
BCLC Stage
A 0 (0%) 13 (48%) 23 (96%) 36 (42%)
B 9 (27%) 14 (52%) 1 (4%) 24 (29%)
C 24 (73%) 0 0 (0%) 24 (29%)
Missing 1 3 5 9
Within Milan Criteria
Yes 0 (0%) 13 (48%) 23 (96%) 36 (43%)
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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No 33 (100%) 14 (52%) 1 (4%) 48 (57%)
Missing 1 3 5 9
Within UCSF Criteria
Yes 0 (0%) 19 (70%) 24 (100%) 43 (51%)
No 33 (100%) 8 (30%) 0 (0%) 41 (49%)
Missing 1 3 5 9
Portal Vein Invasion
Yes 11 (33%) 0 (0%) 0 (0%) 11 (13%)
No 22 (67%) 27 (100%) 24 (100%) 73 (87%)
Missing 1 3 5 9
Extra hepatic Metastasis
Yes 17 (52%) 0 (0%) 0 (0%) 17 (20%)
No 16 (48%) 27 (100%) 24 (100%) 67 (80%)
Missing 1 3 5 9
Child Pugh Status
A 22 (65%) 17 (63%) 18 (69%) 57 (66%)
B 11 (32%) 9 (33%) 5 (19%) 25 (29%)
C 1 (3%) 1 (4%) 3 (12%) 5 (6%)
Missing 0 3 3 6
Etiology of Cirrhosis
Viral (Hepatitis B, Hepatitis C) 21 (62%) 17 (60%) 20 (69%) 58 (64%)
Non-viral (Alcohol, NASH, Other) 13 (38%) 11 (40%) 9 (31%) 33 (36%)
Missing 0 2 0 2
Diagnose based on
Lesions>=2cm, Hepatitis B or C 13 (38%) 18 (67%) 17 (71%) 48 (56%)
Absence of Hepatitis A and/or B 4 (12%) 4 (15%) 1 (4%) 9 (11%)
Hepatitis B and/or C, AFP>=400 6 (18%) 1 (3%) 1 (4%) 8 (9%)
Lesions>=2cm, any type hepatitis 11 (32%) 4 (15%) 5 (21%) 20 (24%)
Missing 0 3 5 8
Prior Treatment
Yes 8 (24%) 1 (4%) 18 (78%) 27 (29%)
Intra-Arterial Chemotherapy (IAC) 4 (50%) 0 13 (72%) 17 (63%)
Surgical Resection 2 (25%) 0 0 2 (7%)
Surgical Resection and IAC 2 (25%) 1 (100%) 0 3 (12%)
RFA 0 0 2 (11%) 2 (7%)
TACE 0 0 2 (11%) 2 (7%)
RFA and IAC 0 0 1 (6%) 1 (4%)
No 26 (76%) 26 (96%) 5 (22%) 57 (71%)
Missing 0 3 6 9

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CTC Classification and association with 3 patient Cohorts
When Baseline CTCs were classified into 7 groups, more details could be specified. From
table 3, missing CTC data were found from 14 patients. The numbers of patients with advanced
stage at level of 0, 1, 2 - 5, 6 – 10 and 11 – 50 circulating tumor cell per 7.5 mL of blood were 11
(35%), 8 (26%), 9 (29%), 1 (3%), and 2 (7%), respectively. No patient was detected at level
of >50 circulating tumor cell per 7.5 mL of blood. In cohort 2, the numbers of patients at level of
0, 1, 2 - 5, 6 - 10, 11 - 50, 51 - 100 and >100 circulating tumor cell per 7.5 mL of blood were 7
(30%), 0, 6 (26%), 5 (22%), 2 (9%), 1 (4%), 2 (9%), 1 (4%), and 2 (9%), respectively. In cohort
3, the number of patients at level of 0, 1, 2 - 5, 6 - 10, 11 - 50, 51 - 100 and >100 circulating
tumor cell per 7.5 mL of blood were 1 (4%), 2 (8%), 9 (38%), 5 (20%), 3 (13%), 1 (4%), and 3
(13%), respectively. (Table 3)
From table 4, we can see that only 3 (10%) patients in cohort 1 were at level of > 5
circulating tumor cell per 7.5 mL of blood. Most of patients (90%) in cohort 1 were at level of ≤
5 circulating tumor cell per 7.5 mL of blood. More patients (54% of patients) at early stage
(cohort 3) were at level of > 5 circulating tumor cell per 7.5 mL of blood. The fisher exact test
showed that there is statistically significant difference in patient proportions at level of ≤ 5
circulating tumor cell per 7.5 mL of blood among 3 patient cohorts with P value < 0.001. There
were more patients at level of ≤ 5 circulating tumor cell per 7.5 mL of blood in cohort 1 than
patients in cohort 2 and cohort 3. So CTC groups were associated with patient cohort groups and
our statistical hypothesis that patients have the same distribution of CTC at level of ≤ 5
circulating tumor cell per 7.5 mL of blood among 3 patient cohorts was rejected. (Table 4)
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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22

In conclusion, according to these 2 tables of different groups of CTC, people in cohort 3
were more likely to have larger numbers of CTC than that of patients in cohort 2 and cohort 1,
which is the opposite as we thought.

Table 3 Baseline CTC
CTC Cohort 1 Cohort 2 Cohort 3 Total
0 11 (35%) 7 (30%) 1 (4%) 19 (24%)
1 8 (26%) 0 2 (8%) 10 (13%)
2-5 9 (29%) 6 (26%) 9 (38%) 24 (31%)
6-10 1 (3%) 5 (22%) 5 (20%) 11 (14%)
11-50 2 (7%) 2 (9%) 3 (13%) 7 (9%)
51-100 0 1 (4%) 1 (4%) 2 (3%)
>100 0 2 (9%) 3 (13%) 5 (6%)
Missing 3 7 5 15

Table 4 Baseline CTC
CTC Cohort 1 Cohort 2 Cohort 3 Total
≤ 5 28 (90%) 13 (57%) 11 (46%) 52 (67%)
>5 3 (10%) 10 (43%) 13 (54%) 26 (33%)
Missing 3 7 5 15
P-value
1
<0.001
P-value
2
<0.001
1. based on Fisher’s Exact Test
2. based on Mantel-Haenszel Chi-Square Test

CTC Change
Wilcoxon Signed Rank Test was used to test if there is a difference in the median numbers
of CTC after treatment. According to the result, there was no statistically significant change in
median of CTC numbers between before treatment and after treatment group because the P-value
= 0.26. The large missing data of post treatment should be paid more attention. (Table 5)
But from table 6, a total of 26 (54%) patients had decreased CTC numbers from baseline.
Eight (17%) patients’ CTC numbers were not been changed compared with baseline. The
numbers of CTCs in 14 (29%) patients were increased from baseline. This occurred obviously at
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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level of ≤ 5 circulating tumor cell per 7.5 mL of blood. Almost 64% of patients at this level had
CTC numbers decreased. So even though the change in median of CTC numbers was not
statistically significant, most patients had fewer numbers of CTC. (Table 6)

Table 5 CTC change test
CTC Median Standard deviation Interquartile range Min Max Missing
Prior-treatment 3.25 179 6 0 1152 15
Post-treatment 5 179 11 0 1152 44
P-value
1
0.26
1. based on Wilxcon Signed Rank Test

Table 6 CTC change
CTC Decreased from baseline No changed from baseline Increased from baseline
≤ 5 19 (64%) 7 (23%) 4 (13%)
5-50 7 (50%) 0 7 (50%)
>50 0 1 (25%) 3 (75%)
Total 26 (54%) 8 (17%) 14 (29%)

Association between baseline CTC and baseline characteristics
Table 7 showed associations of Baseline CTC (≤ 5 CTC per 7.5 mL, >5 CTC per 7.5 mL)
with Baseline disease characteristics. Fisher’s Exact Chi-Square Test was performed to detect the
associations. According to P-value, there was no association between CTC groups and age,
gender, Baseline AFP, Child Pugh Status, Etiology of Cirrhosis and the criteria that diagnose
was based on are not statistically significant (P-value < 0.05). But the difference of patient
proportions at specific disease stage was statistically significant across different CTC level
groups because all the P-value < 0.05. So baseline CTC groups were associated with baseline
disease stage. The difference of patient proportions at BCLC stage A, B, C was statistically
significant among different CTC groups. Patient at BCLC stage B were more likely to be at level
of ≤ 5 circulating tumor cell per 7.5 mL of blood, same as patients at BCLC stage C. The
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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proportions of patients at level of ≤ 5 circulating tumor cell per 7.5 mL of blood is larger than
that of patients at level of >5 circulating tumor cell per 7.5 mL of blood among those who did
not meet Milan criteria or UCSF criteria. And the CTC numbers of patients who did not have
Extra Hepatic Metastases were more likely to have CTC at level of ≤ 5 circulating tumor cell per
7.5 mL of blood. (Table 7)
When Baseline CTCs were stratified into 3 groups, Mantel-Haenszel Chi-Square Test could
be used to test linear trend. From table 8, the linear trend was found between disease stage
(BCLC stage, Milan Criteria, UCSF Criteria, and Extra Hepatic Metastases) and CTC groups (P
value < 0.05). (Table 8)
Table 7 Association of Baseline CTC with Baseline Disease Characteristics (n=93)
Baseline CTC P-value
1

≤ 5 (n=52) >5 (n=26)
Age 0.21
43-55 11 (21%) 8 (31%)
56-70 29 (56%) 16 (62%)
71-90 12 (23%) 2 (7%)
Gender 0.21
Female 7 (15%) 7 (27%)
Male 45 (85%) 19 (73%)
Baseline AFP 0.18
<400 36 (69%) 22 (85%)
≥400 16 (31%) 4 (15%)
Child Pugh Status 0.36
Class A 32 (62%) 17 (65%)
Class B 18 (34%) 6 (23%)
Class C 2 (4%) 3 (12%)
Etiology of Cirrhosis 0.34
Viral 34 (65%) 14 (54%)
Non-viral 18 (35%) 12 (46%)
BCLC Stage 0.003
A 18 (35%) 17(65%)
B 12 (23%) 7(27%)
C 22 (42%) 2(8%)
Milan Criteria 0.007
No 34 (65%) 9 (35%)
Yes 18 (35%) 17 (65%)
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1.

based on Fisher exact test

Table 8 Association of Baseline CTC with Baseline Disease Characteristics (n=93)
Baseline CTC P-value
1
P-value
2

0-5 (52) 6-50 (19) >50 (7)
Age 0.56 0.12
43-57 11 (21%) 6 (32%) 2 (29%)
57-69 29 (56%) 11 (58%) 5 (71%)
69-90 12 (23%) 2 (10%) 0
Gender 0.11 0.07
Female 7 (13%) 4 (21%) 3 (43%)
Male 45 (87%) 15 (79%) 4 (57%)
Baseline AFP 0.18
<400 36 (69%) 16 (84%) 6 (86%) 0.43 0.17
≥400 16 (31%) 3 (16%) 1 (14%)
Child Pugh Status 0.38 0.91
Class A 32 (62%) 12 (63%) 5 (71%)
Class B 18 (34%) 4 (21%) 2 (29%)
Class C 2 (4%) 3 (16%) 0
Etiology of Cirrhosis 0.62 0.41
Viral 34 (65%) 10 (53%) 4 (57%)
Non-viral 18 (35%) 9 (47%) 3 (43%)
BCLC Stage 0.018 0.002
A 18 (35%) 12 (63%) 5 (71%)
B 12 (23%) 5 (26%) 2 (29%)
C 22 (42%) 2 (11%) 0
Milan Criteria 0.037 0.012
No 34 (65%) 7 (37%) 2 (29%)
Yes 18 (35%) 12 (63%) 5 (71%)
UCSF Criteria 0.003
No 32 (62%) 7 (27%)
Yes 20 (38%) 19 (73%)
Portal Vein Invasion 0.09
No 42 (81%) 25 (96%)
Yes 10 (19%) 1 (4%)
Extra Hepatic Metastases 0.042
No 37 (71%) 24 (92%)
Yes 15 (29%) 2 (8%)
Diagnose based on 0.83
Lesions>=2cm, B or C 29 (56%) 16 (61%)
Absence of A and/or B 4 (7%) 3 (12%)
B and/or C, AFP>=400 5 (10%) 2 (8%)
Lesions>=2cm, any type hepatitis 14 (27%) 5 (19%)
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UCSF Criteria 0.011 0.003
No 32 (62%) 6 (32%) 1 (14%)
Yes 20 (38%) 13 (68%) 6 (86%)
Portal Vein Invasion 0.28 0.07
No 42 (81%) 18 (95%) 7 (100%)
Yes 10 (19%) 1 (5%) 0
Extra Hepatic Metastases 0.12 0.03
No 37 (71%) 17 (89%) 7 (100%)
Yes 15 (29%) 2 (11%) 0
Diagnose based on 0.55 0.89
Lesions>=2cm, B or C 29 (56%) 13 (67%) 3 (43%)
Absence of A and/or B 4 (7%) 2 (11%) 1 (14%)
B and/or C, AFP>=400 5 (10%) 2 (11%) 0
Lesions>=2cm, any type hepatitis 14 (27%) 2 (11%) 3 (43%)
1. based on Fisher exact test
2. based on Mantel-Haenszel Chi-Square test

Conclusion
So far, a total of 93 patients were eligible to be enrolled in this study and 15 patients had
missing Baseline CTC data. So the CTC analysis was done from only 78 patients. According to
Fisher’s Exact Test, the null hypothesis that there is no statistically significant difference in
patient proportions at level of ≤ 5 circulating tumor cell per 7.5 mL of blood among 3 cohorts
was rejected. The distribution of patients at level of ≤ 5 circulating tumor cell per 7.5 mL of
blood was statistically significant different across 3 patient cohorts. Patients in cohort 1
(advanced stage) were more likely to have fewer CTCs than patients in cohort 2 (intermediate
stage) and cohort 3 (early stage). This is opposite as we originally thought.
According to Wilcoxon signed rank test, the change in median of the CTC numbers was not
statitically significant. But from table 6, most patients had decreased numbers of CTC .
But all these conclusions are controversial because of small numbers of patients and large
missing data. The study has not been completed yet and patients’ recruitment is still in process.
CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY
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Follow-up study and analysis should be developed because of the clinical significance of CTC in
HCC.

CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
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Discussion
This study is supposed to recruit 60 patients with advanced stage HCC into cohort 1, 30
patients with intermediate stage HCC into cohort 2 and 80 patients with early stage HCC into
cohort 3. A total of 170 patients should be enrolled in this study. Ongoing accrual to 3 patient
cohorts per the original project timeline is still in process. According to the result, it is very
interesting that patients with advanced stage are more likely to have fewer circulating tumor cells,
which exactly opposite as our scientific hypothesis. But for now, it is still too soon to get final
conclusion due to small numbers of patients (93 patients). Wilcoxon signed rank test told us that
there is no statistically significant change in CTC numbers after treatment. But almost 54% of
patients had decreased CTC showed from table 6 is the evidence that most patients had
decreased CTC numbers. The small numbers of CTC in patients’ blood and the large missing
data may be the reason that there is no statistically significant change in the numbers of CTC.
Anyway, all the results cannot be confirmed because of uncompleted accrual. After completion
of the whole study, the full dataset may tell the truth.

CAPTURE AND ANALYSIS OF CIRCULATING TUMOR CELLS IN PATIENTS WITH
HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY
29

References

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Carcinoma. International Journal of Hepatology, doi: 10.1155/2012/684802

2. Wu, Li-Jun; Pan, Yi-Da; Pei, Xiao-Yu; Chen, Hong; Nguyen, Samantha; et al (2012).
Capturing circulating tumor cells of hepatocellular carcinoma. Cancer Letters, 326.1, 17-22.

3. Yeh SH, Chen PJ (2010). Gender disparity of hepatocellular carcinoma: the roles of sex
hormones. Oncology, suppl. S1, 78, 172-9.

4. McEvoy SH, McCarthy CJ, Lavelle LP, Moran DE, Cantwell CP, Skehan SJ, Gibney RG,
Malone DE (2013). Hepatocellular carcinoma: illustrated guide to systematic radiologic
diagnosis and staging according to guidelines of the American Association for the Study of Liver
Diseases. Radiographics, 33(6), 1653-68.

5. Llovet, Josep M; Fuster, Josep; Bruix, Jordi (2004). The Barcelona approach: diagnosis,
staging, and treatment of hepatocellular carcinoma. Liver Transplantation, 10(2 Suppl 1), S115-
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Sagol, Funda Obuz, Mesut Akarsu and Ibrahim Astarcioglu (2011). Comparison of Milan and
UCSF criteria for liver transplantation to treat hepatocellular carcinoma. World J Gastroenterol,
17(37), 4206–4212.

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HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY
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6. Mitsuteru Natsuizaka, Takumi Omura, Toru Akaike, Yasuaki Kuwata, Katsu Yamazaki,
Takahiro Sato, . . . Masahiro Asaka (2005). Clinical features of hepatocellular carcinoma with
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7. Minagawa, Masami (2006). Treatment of hepatocellular carcinoma accompanied by portal
vein tumor thrombus. World journal of gastroenterology. WJG (1007-9327), 12(47), 561-7.

8. Tong Xu, Bo Lu, Yu-Chong Tai, and Amir Goldkorn (2010). A Cancer Detection Platform
Which Measures Telomerase Activity from Live Circulating Tumor Cells Captured on a
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HEPATOCELLULAR CARCINOMA – ANALYSIS OF A PILOT STUDY
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12. Dong ZZ, Yao DF, Yao DB, Wu XH, Wu W, Qiu LW, Jiang DR, Zhu JH, Meng XY (2005).
Expression and alteration of insulin-like growth factor II-messenger RNA in hepatoma tissues
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4655-60.

Abstract (if available)

Abstract Hepatocellular carcinoma (HCC), which we can also call malignant hepatoma, is a primary liver cancer and a major cause of cancer morbidity and mortality all over the world. According to Zhang Y, Li J, Cao L, Xu W, and Yin Z (2012), circulating tumor cells (CTCs) reflect the information of HCC metastasis or recurrence. This makes CTC as a useful biomarker of HCC. The popular standard method based on immunomagnetic binding of epithelial cell adhesion molecules (EpCAMs) cannot be used to collect CTC of HCC because HCC cells rarely express EpCAM. However, Dr. Amir Goldkorn solved this problem by developing a parylene–C slot microfilter platform. So a total of 170 HCC patients are planned to be recruited to analyze CTC in HCC. For now, only 93 patients are enrolled to this program and the study is still in process. The hypothesis in this study to be tested are (1) Patients with advanced disease stage will have more CTCs. (2) The numbers of CTC are decreased after treatment.

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Asset Metadata

Creator Dong, Cheng (author)

Core Title Capture and analysis of circulating tumor cells in patients with hepatocellular carcinoma: analysis of a pilot study

School Keck School of Medicine

Degree Master of Science

Degree Program Biostatistics

Publication Date 07/17/2014

Defense Date 07/17/2014

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

Tag CTC,HCC,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Gauderman, William James (committee chair), Groshen, Susan L. (committee member), Stram, Daniel O. (committee member)

Creator Email chengdon@usc.edu,veran.dc@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-444458

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