Biomedical subjects

Ziding Feng

Publications and source records attributed to Ziding Feng.

At least 55 records · Page 3Linked to original sources

PubMed2003

Extended lifespan of Barrett's esophagus epithelium transduced with the human telomerase catalytic subunit: a useful in vitro model.

As there has been no previous information on the consequences of telomerase expression in genetically altered, mortal cells derived from pre-malignant tissue, we sought to determine the effect of hTERT (human catalytic subunit of telomerase reverse transcriptase) transduction of pre-malignant cell strains from Barrett's esophagus that do not contain telomerase activity and possess a finite lifespan. Primary cultures of Barrett's esophageal epithelium transduced with a retrovirus containing hTERT were characterized by growth factor requirements, cytogenetics and flow cytometry. Expression of telomerase lengthened telomeres and greatly extended the lifespan of hTERT transduced (hTERT+) Barrett's esophagus cells. Growth factor dependency of the hTERT+ cultures remained largely similar to the parental cultures, although there was a modest increase in the ability to grow in agar. Chromosomal instability, measured by both karyotypic and FISH (fluorescence in situ hybridization) analyses, was reduced but not abrogated by hTERT transduction, suggesting that telomerase expression can enhance genomic stability. However, the persistence of residual instability gave rise to new clonal and non-clonal genetic variants, and in one hTERT+ culture a new DNA aneuploid population was observed, the only time such a ploidy shift has been seen in Barrett's cell strains in vitro. These in vitro observations are analogous to the clinical progression to aneuploidy that often precedes cancer in Barrett's esophagus, and suggest that reactivation of telomerase may be permissive for continued genetic evolution to cancer. Long-lived Barrett's esophagus epithelial cultures should provide a useful in vitro model for studies of neoplastic evolution and chemopreventive therapies.

Barrett Esophagus↗

PubMed2003

General quality of life 2 years following treatment for prostate cancer: what influences outcomes? Results from the prostate cancer outcomes study.

PURPOSE: The goal of this study was to determine the relationship between primary treatment, urinary dysfunction, sexual dysfunction, and general health-related quality of life (HRQOL) in prostate cancer. METHODS: A sample of men with newly diagnosed prostate cancer between 1994 and 1995 was randomly selected from six population-based Surveillance, Epidemiology, and End Results registries. A baseline survey was completed by 2,306 men within 6 to 12 months of diagnosis, and these men also completed a follow-up HRQOL survey 2 years after diagnosis. Logistic regression models were used to determine whether primary treatment, urinary dysfunction, and sexual dysfunction were independently associated with general HRQOL outcomes approximately 2 years after diagnosis as measured by the Medical Outcomes Study 36-item Short Form Health Survey. The magnitude of this effect was estimated using least square means models. RESULTS: After adjustment for potential confounders, primary treatment was not associated with 2-year general HRQOL outcomes in men with prostate cancer. Urinary function and bother were independently associated with worse general HRQOL in all domains. Sexual function and bother were also independently associated with worse general HRQOL, although the relationship was not as strong as in the urinary domains. CONCLUSION: Primary treatment is not associated with 2-year general HRQOL outcomes in prostate cancer. Although both sexual and urinary function and bother are associated with quality of life, men who are more bothered by their urination or impotence are more likely to report worse quality of life. This implies that future research should be directed toward finding ways to improve treatment-related outcomes or help patients better cope with their posttreatment urinary or sexual dysfunction.

Aged↗

PubMed2003

Smoke exposure, histologic type and geography-related differences in the methylation profiles of non-small cell lung cancer.

Aberrant methylation of several known or putative tumor suppressor genes occurs frequently during the pathogenesis of lung cancers. There are major smoke exposure, histology, geography and gender-related changes in non-small cell lung cancer (NSCLC). We investigated smoking-related, histologic, geographic and gender differences in the methylation profiles of resected NSCLCs. We examined 514 cases of NSCLC and 84 corresponding nonmalignant lung tissues from 4 countries (USA, Australia, Japan and Taiwan) for the methylation status of 7 genes known to be frequently methylated in lung cancers [p16, RASSF1A (RAS association domain family 1), APC, RARbeta, CDH13, MGMT and GSTP1]. Multivariate analyses were used for data analysis. Adenocarcinoma was the major histologic type in women and never smokers; analyses that involved smoke exposure and gender were limited to this histology. Our major findings are a) methylation status of any single gene was largely independent of methylation status of other genes; b) the rates of methylation of p16 and APC and the mean Methylation Index (MI), a reflection of the overall methylation status, were significantly higher in ever smokers than in never smokers; c) the mean MI of tumors arising in former smokers was significantly lower than the mean of current smokers; d) the methylation rates of APC, CDH13 and RARbeta were significantly higher in adenocarcinomas than in squamous cell carcinomas; e) methylation rates of MGMT and GSTP1 were significantly higher in the USA and Australian cases than in those from Japan and Taiwan; and (f) no significant gender-related differences in methylation patterns were noted. Our findings demonstrate important smoke exposure, histologic type and geography-related differences in the methylation profiles of NSCLC tumors.

Adenomatous Polyposis Coli Protein↗

PubMed2003

Development of common data elements: the experience of and recommendations from the early detection research network.

There have been an increasing number of large research consortia in recent years funded by the National Cancer Institute (NCI) to facilitate multi-disciplinary, multi-institutional cancer research. Some of these consortia have central data collection plans similar to a multi-center clinical trial whereas others plan to store data locally and pool or share the data at a later date. Regardless of the goal of the consortium, there is a need to standardize the way certain data are collected and stored, transferred, or reported across the institutions involved. This communication is a report of the process and current status of the development of common data elements (CDEs) by the Early Detection Research Network (EDRN). The development of the CDEs involved several stages with each stage requiring input from multi-disciplinary experts in oncology, epidemiology, biostatistics, pathology, informatics, and study coordination. An effort was made to be consistent with other consortia developing similar CDEs and to follow data standards when available. Initial focus was on identifying the minimum data that would be necessary to collect on all EDRN study participants and EDRN specimens. There are currently CDEs in the development or pilot phase for eight different organ sites and 13 different types of specimen procurements and plans to develop CDEs for 12 or more additional types of specimens.

Data Collection↗

PubMed2003

A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection.

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of 'signature' protein profiles specific to each pathologic state (e.g. normal vs. cancer) or differential profiles between experimental conditions (e.g. treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data-analytic strategy for discovering protein biomarkers based on such high-dimensional mass spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data-analytic strategy takes properties of the SELDI mass spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After this pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Algorithms↗

PubMed2003

Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality data.

We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations. The method is illustrated with a prostate cancer study, where the sample size is 248, and the number of variables is 48,538 (generated using the ProteinChip technology). Using a discrete wavelet transform, the 48,538 data points are represented by 1271 wavelet coefficients. Information criteria identified 11 of the 1271 wavelet coefficients with the highest discriminatory power. The linear classifier with the 11 wavelet coefficients detected prostate cancer in a separate test set with a sensitivity of 97% and specificity of 100%.

Data Compression↗

PubMed2003

An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers.

Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein "signals" from background "noise" in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.

Journal Article↗

PubMed2003

Low-fat diet: effect on anthropometrics, blood pressure, glucose, and insulin in older women.

OBJECTIVE: The Women's Health Trial: Feasibility Study in Minority Populations (WHT: FSMP) documented that a low-fat diet was associated with a reduced fat intake in older women of diverse ethnic backgrounds. The purpose of the current study was to examine the effect of the low-fat diet on anthropometric and biochemical variables. DESIGN: Randomized clinical trial in 2,208 postmenopausal women, 50 to 79 years of age. RESULTS: The decrease in fat intake correlated directly with a decrease in body weight (r=.22, P<.001). After 6 months, the intervention group had an average weight loss of 1.8 kg. Body mass index decreased 0.7 kg/m2. Waist circumference decreased 1.8 cm. All of these changes were statistically significant, compared to changes in the control group (P<.01). Changes in systolic (-3.1 mm Hg) and diastolic (-1.1 mm Hg) blood pressures (BP) occurred in the intervention group. The decrease in systolic BP reached statistical significance (P=.02), relative to the control group. Decreases in plasma glucose were small (-0.2 mmol/L) in the intervention group, although there was a trend for difference from the control group (P=.11). Decreases in serum insulin levels were small (-0.5 microIU/mL) in the intervention group, although there was, again, a trend for difference from the control group. CONCLUSIONS: In older White, Black, and Hispanic women, a long-term low-fat dietary intervention was accompanied by modest, but statistically significant, decreases in body weight and anthropometric indices, without any particular attempt being made to reduce calories. Changes in glucose and insulin were small. The long-term biological significance of the glucose and insulin changes is unknown.

Aged↗

PubMed2003

Association of HPC2/ELAC2 polymorphisms with risk of prostate cancer in a population-based study.

Genetic polymorphism in HPC2/ELAC2 was recently associated with risk of sporadic prostate cancer. To determine the contribution of two HPC2/ELAC2 missense variants (Ser217Leu and Ala541Thr) to the risk of developing prostate cancer, we conducted a population-based case-control study of middle-aged men (40-64 years). Cases (n=591) were ascertained from the Seattle-Puget Sound Surveillance, Epidemiology, and End Results Cancer Registry and Controls (n=538) from the same general population were identified through random-digit dialing. Subjects were residents of King County, Washington, and were frequency matched on age. Cases (32%) had a slightly higher frequency of the Leu217 variant compared with controls (29%), but there were no differences in the frequency of the Thr541 allele (4%). When considering joint genotypes, white men homozygous for the Leu217 variant on an Ala541/Ala541 background had an increased risk of prostate cancer [odds ratio (OR)=1.84; 95% confidence interval (CI), 1.11-3.06]. Different risk profiles were also observed when cases were stratified by disease aggressiveness. Men with at least one Leu217 allele had an elevated risk (OR=1.34; 95% CI, 1.02-1.76) of less aggressive prostate cancer (localized stage and Gleason score < or = 7), with a stronger association among men with two Leu217 alleles (OR=1.73; 95% CI, 1.08-2.77). The Ala541Thr polymorphism was not associated with risk, and neither variant was associated with more aggressive prostate cancer phenotypes. We estimate that the Ser217Leu genotype may account for approximately 14% of less aggressive prostate cancer cases and 9% of all sporadic cases in the general United States population of white men <age 65 years.

Adenocarcinoma↗

PubMed2002

Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men.

The prostate-specific antigen test has been a major factor in increasing awareness and better patient management of prostate cancer (PCA), but its lack of specificity limits its use in diagnosis and makes for poor early detection of PCA. The objective of our studies is to identify better biomarkers for early detection of PCA using protein profiling technologies that can simultaneously resolve and analyze multiple proteins. Evaluating multiple proteins will be essential to establishing signature proteomic patterns that distinguish cancer from noncancer as well as identify all genetic subtypes of the cancer and their biological activity. In this study, we used a protein biochip surface enhanced laser desorption/ionization mass spectrometry approach coupled with an artificial intelligence learning algorithm to differentiate PCA from noncancer cohorts. Surface enhanced laser desorption/ionization mass spectrometry protein profiles of serum from 167 PCA patients, 77 patients with benign prostate hyperplasia, and 82 age-matched unaffected healthy men were used to train and develop a decision tree classification algorithm that used a nine-protein mass pattern that correctly classified 96% of the samples. A blinded test set, separated from the training set by a stratified random sampling before the analysis, was used to determine the sensitivity and specificity of the classification system. A sensitivity of 83%, a specificity of 97%, and a positive predictive value of 96% for the study population and 91% for the general population were obtained when comparing the PCA versus noncancer (benign prostate hyperplasia/healthy men) groups. This high-throughput proteomic classification system will provide a highly accurate and innovative approach for the early detection/diagnosis of PCA.

Aged↗

PubMed2002

Presence of simian virus 40 DNA sequences in human lymphomas.

Simian virus 40 (SV40)--a potent oncogenic virus--has been associated previously with some types of human tumours, but not with lymphomas. We examined human tumours for the presence of specific SV40 DNA sequences by PCR and Southern blotting. Viral sequences were present in 29 (43%) of 68 non-Hodgkin lymphomas, and in three (9%) of 31 of Hodgkin's lymphomas. Viral sequences were detected at low frequencies (about 5%) in 235 epithelial tumours of adult and paediatric origin, and were absent in 40 control tissues. Our data suggest that SV40 might be a cofactor in the pathogenesis of non-Hodgkin lymphomas.

Adult↗

PubMed2002

An intervention study on screening for breast cancer among single African-American women aged 65 and older.

BACKGROUND: Older African-American women with single marital status are least likely to use screening procedures. This study aimed to evaluate a breast screening intervention program conducted in this population. METHODS: Ten public housing complexes were randomly assigned to either the intervention or the control group. African-American women aged 65 and over were recruited into the study if they were widowed, divorced, separated, or never married and did not have a history of breast cancer (n = 325). The intervention program was delivered by lay health educators at the participant's apartment and was designed to increase knowledge about breast screening, reduce psychological problems, and increase support from significant others. Breast-screening-related cognition and behavior were measured at baseline and at 1 and 2 years postintervention. RESULTS: Comparisons of the preintervention and postintervention measurements showed that while the proportion of women who had a clinical breast examination or mammogram in the preceding year was decreased at 1 year postintervention in the control group, it was increased in the intervention group. However, the differences did not reach a significant level. No consistent patterns could be found in changes of breast self-examination and variables in knowledge, attitudes, and beliefs. When analyses were restricted to women whose significant others had provided information or help on breast screening, results were better, but the differences between the intervention and control groups still did not reach statistical significance. CONCLUSIONS: These results did not suggest significant effects of an intervention program that used lay health educators to promote breast cancer screening in older single African-American women.

Black or African American↗

PubMed2002

Some design issues in a community intervention trial.

We present statistical considerations for the design of a 20-community randomized trial. The community intervention aims at multiple cancer prevention health behaviors including reducing dietary fat, increasing fruit and vegetable intake, smoking cessation, and increasing colorectal cancer screening. To better measure the overall impact of the intervention, individual endpoints as well as a global test of multiple endpoints are used. The statistical power analysis takes into account the heterogeneity between communities, the correlation between health behaviors over time, and the correlation between multiple endpoints. The study is being conducted in a relatively confined geographic area. Several measures have been taken to account for potential contamination. These include collecting information in baseline and follow-up surveys on intervention dose and conducting surveys in three similar communities in another part of the state.

Adolescent↗

PubMed2002

Cancer prevention behaviors and socioeconomic status among Hispanics and non-Hispanic whites in a rural population in the United States.

OBJECTIVES: Socioeconomic status is explored as a predictor of differences between Hispanics and non-Hispanic Whites in cancer prevention behavior. METHODS: In a cross-sectional study, in-person interviews (n = 1795) were conducted in a population-based random sample of adults in 20 communities with a high proportion of Hispanics. RESULTS: Hispanics were significantly less likely than non-Hispanic Whites to ever have had cervical (p < 0.001), breast (p = 0.007), or colorectal cancer (FOBT p = 0.008; sigmoidoscopy/colonoscopy p < 0.002) screening. After adjusting for socioeconomic status (education and having health insurance), only differences in cervical cancer remained significant (p = 0.024). After adjusting for socioeconomic status, Hispanics had a significantly higher intake of fruits and vegetables per day (4.84 servings) than non-Hispanic Whites (3.84 servings) (p < 0.001); and fat behavior score was marginally significant after adjustment for socioeconomic status (p = 0.053). Significantly fewer Hispanics were current smokers than non-Hispanic Whites (p < 0.001). CONCLUSIONS: There is only limited support for the hypothesis that socioeconomic status is a major determinant of some cancer-related behaviors; specifically, socioeconomic status is related to mammography and colorectal screening, but not cervical cancer, dietary behavior, or smoking.

Adolescent↗

PubMed2002

Effect of c-mpl ligands after total body irradiation (TBI) with and without allogeneic hematopoietic stem cell transplantation: low-dose TBI does not prevent sensitization.

This study investigates the potential role of the recombinant c-mpl ligands (recombinant human thrombopoietin [rhTPO] and pegylated recombinant human megakaryocyte growth and development factor [PEG-rhMGDF]) on the recovery of platelet counts after TBI with and without allogeneic hematopoietic stem cell transplantation (HSCT) in an established canine model. Initially, 3 cohorts, each with 2 nonirradiated dogs, received increasing doses of rhTPO (5 microg/kg per day; 10 microg/kg per day; 20 microg/kg per day) for 7 days to determine the optimal dose. The dose of 10 microg/kg per day of rhTPO was selected for subsequent studies. Ten dogs then received either rhTPO or placebo for 28 days after 200 cGy TBI without HSCT. The rhTPO group had fewer days with platelet counts <20,000/microL (9.8 days versus 17.8 days, P < .05) and significantly increased granulocyte counts (n = 5) compared to the controls (n = 5). RhTPO-specific antibodies developed in 2 dogs, which caused a significant but transient decrease of the platelet counts. Retreatment of these sensitized dogs with rhTPO resulted in profound transient decreases in platelet counts. In the next study, 20 dogs received either PEG-rhMGDF or placebo for 21 days after 920 cGy TBI and allogeneic HSCT. The median time to platelet recovery (>20,000/microL) for the PEG-rhMGDF group (n = 10) was 14.0 days compared to 15.5 days for the control group (n = 10; log rank, P = .35). There were no significant differences in the total time to platelet counts <20,000/microL or in the time to recover neutrophil counts >500/microL. The effects of rhTPO on recovery of platelet and granulocyte counts after sublethal TBI were modest, and no effects of PEG-rhMGDF were observed on hematopoietic recovery after high-dose TBI and allogeneic HSCT. The significant effect that rhTPO-specific antibodies had on the platelet counts may limit the clinical role of recombinant c-mpl ligands unless sensitization can be prevented.

Animals↗

PubMed2002

A polymorphism in the CYP17 gene and risk of prostate cancer.

Steroid hormones are important in the etiology and progression of prostate cancer, and expression of genes involved in hormone production may alter susceptibility. One such gene is CYP17, which encodes the cytochrome P450c17a enzyme responsible for the biosynthesis of testosterone. A T to C transition (A2 allele) in the 5' promoter region of the gene is hypothesized to increase the rate of gene transcription, increase androgen production, and thereby increase risk of prostate cancer. To test this hypothesis, germ-line DNA samples from a large population-based study of incident prostate cancer cases (n = 590) and controls (n = 538) of similar age without the disease were genotyped. The frequency of the A2 allele was similar in cases and controls. Compared with men with the A1/A1 genotype, the adjusted odds ratio was 0.81 for the A1/A2 and 0.87 for the A2/A2 genotype. Risk estimates did not vary substantially by age or race. However, stratification by family history of prostate cancer revealed that among white men with an affected first-degree relative, homozygotes for the A2 allele had a significant elevation in risk (odds ratio = 19.2; 95% confidence interval, 2.2-157.4) compared with men who were homozygous for the A1 allele (interaction P = 0.0005). These results suggest that the CYP17 A2/A2 genotype predicts susceptibility to prostate cancer in white men with a family history of the disease. It is also possible that CYP17 interacts with other genes that influence risk of familial prostate cancer.

Adult↗

PubMed2002

Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients.

BACKGROUND: The low specificity of the prostate-specific antigen (PSA) test makes it a poor biomarker for early detection of prostate cancer (PCA). Because single biomarkers most likely will not be found that are expressed by all genetic forms of PCA, we evaluated and developed a proteomic approach for the simultaneous detection and analysis of multiple proteins for the differentiation of PCA from noncancer patients. METHODS: Serum samples from 386 men [197 with PCA, 92 with benign prostatic hyperplasia (BPH), and 96 healthy individuals], randomly divided into training (n = 326) and test (n = 60) sets, were analyzed by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. The 124 peaks detected by computer analyses were analyzed in the training set by a boosting tree algorithm to develop a classifier for separating PCA from the noncancer groups. The classifier was then challenged with the test set (30 PCA samples, 15 BPH samples, 15 samples from healthy men) to determine the validity and accuracy of the classification system. RESULTS: Two classifiers were developed. The AdaBoost classifier completely separated the PCA from the noncancer samples, achieving 100% sensitivity and specificity. The second classifier, the Boosted Decision Stump Feature Selection classifier, was easier to interpret and used only 21 (compared with 74) peaks and a combination of 21 (vs 500) base classifiers to achieve a sensitivity and specificity of 97% for the test set. CONCLUSIONS: The high sensitivity and specificity achieved in this study provides support of the potential for SELDI, coupled with a bioinformatics learning algorithm, to improve the early detection/diagnosis of PCA.

Algorithms↗

PubMedDate not supplied

The early detection research network surface-enhanced laser desorption and ionization prostate cancer detection study: A study in biomarker validation in genitourinary oncology.

Prostate-specific antigen (PSA) screening has led to a dramatic increase in prostate cancer detection with a concurrent stage migration. Although the test has revolutionized prostate cancer detection by identifying disease that is potentially curable in the majority of men, only 25% of men receiving test results of PSA > 4 ng/ml will have prostate cancer and many men receiving a normal PSA will have disease, including high-grade disease. There is a need for improved biomarkers for detecting prostate cancer. One such method of cancer detection is surface-enhanced laser desorption and ionization (SELDI). The Early Detection Research Network (EDRN) validation study for SELDI for prostate cancer is described. In a three-stage study, the portability and reproducibility of the technique will be determined; the predictive algorithm will be refined in a multi-institutional case-control population; followed by ultimate validation in the context of a prospective trial with complete disease ascertainment. The unique aspect of the EDRN SELDI validation study is the novel use of two groups of cancer cases: those cases with higher-risk disease (Gleason > or = 7) and those cases with lower-risk disease (Gleason < or = 6). This study will allow the first evaluation of a predictive algorithm that includes prognosis in disease screening. The EDRN SELDI prostate cancer biomarker validation study is a rigorous evaluation of a new detection method for prostate cancer. The methodologies used for this evaluation will prove useful for guiding future biomarker studies in this challenging disease.

Biomarkers, Tumor↗