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author:("Feng, aiding")
1.  Toward Rigorous Data Harmonization in Cancer Epidemiology Research: One Approach 
American Journal of Epidemiology  2015;182(12):1033-1038.
Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a “correct” way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.
doi:10.1093/aje/kwv133
PMCID: PMC4675662  PMID: 26589709
cancer epidemiology; data harmonization; data pooling
2.  Epigenomic profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue 
The Prostate  2015;75(16):1941-1950.
Background
Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites.
Methods
The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed.
Results
In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value <0.001), the majority of which were hypermethylated (n = 1,946; 95%). DNA methylation profiles accurately distinguished between PCa and benign tissue samples. Twenty-seven top-ranked hypermethylated CpGs had a mean methylation difference of at least 40% between tissue types, which included 25 CpGs in 17 genes. Furthermore, for ten genes over 50% of promoter region CpGs were hypermethylated in PCa versus benign tissue. The top-ranked differentially methylated genes included three genes that were associated with both promoter hypermethylation and reduced gene expression: SCGB3A1, HIF3A, and AOX1. Analysis of The Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings.
Conclusions
This study of PCa versus adjacent benign tissue showed many differentially methylated CpGs and regions in and outside gene promoter regions, which may potentially be used for the development of future epigenetic-based diagnostic tests or as therapeutic targets.
doi:10.1002/pros.23093
PMCID: PMC4928710  PMID: 26383847
Prostate cancer; DNA methylation; mRNA expression; tumor; benign
3.  Diacetylspermine Is a Novel Prediagnostic Serum Biomarker for Non–Small-Cell Lung Cancer and Has Additive Performance With Pro-Surfactant Protein B 
Journal of Clinical Oncology  2015;33(33):3880-3886.
Purpose
We have investigated the potential of metabolomics to discover blood-based biomarkers relevant to lung cancer screening and early detection. An untargeted metabolomics approach was applied to identify biomarker candidates using prediagnostic sera from the Beta-Carotene and Retinol Efficacy Trial (CARET) study.
Patients and Methods
A liquid chromatography/mass spectrometry hydrophilic interaction method designed to profile a wide range of metabolites was applied to prediagnostic serum samples from CARET participants (current or former heavy smokers), consisting of 100 patients who subsequently developed non–small-cell lung cancer (NSCLC) and 199 matched controls. A separate aliquot was used to quantify levels of pro-surfactant protein B (pro-SFTPB), a previously established protein biomarker for NSCLC. On the basis of the results from the discovery set, blinded validation of a metabolite, identified as N1,N12-diacetylspermine (DAS), and pro-SFTPB was performed using an independent set of CARET prediagnostic sera from 108 patients with NSCLC and 216 matched controls.
Results
Serum DAS was elevated by 1.9-fold, demonstrating significant specificity and sensitivity in the discovery set for samples collected up to 6 months before diagnosis of NSCLC. In addition, DAS significantly complemented performance of pro-SFTPB in both the discovery and validations sets, with a combined area under the curve in the validation set of 0.808 (P < .001 v pro-SFTPB).
Conclusion
DAS is a novel serum metabolite with significant performance in prediagnostic NSCLC and has additive performance with pro-SFTPB.
doi:10.1200/JCO.2015.61.7779
PMCID: PMC4652011  PMID: 26282655
4.  MUC1 Expression by Immunohistochemistry Is Associated with Adverse Pathologic Features in Prostate Cancer: A Multi-Institutional Study 
PLoS ONE  2016;11(11):e0165236.
Background
The uncertainties inherent in clinical measures of prostate cancer (CaP) aggressiveness endorse the investigation of clinically validated tissue biomarkers. MUC1 expression has been previously reported to independently predict aggressive localized prostate cancer. We used a large cohort to validate whether MUC1 protein levels measured by immunohistochemistry (IHC) predict aggressive cancer, recurrence and survival outcomes after radical prostatectomy independent of clinical and pathological parameters.
Material and Methods
MUC1 IHC was performed on a multi-institutional tissue microarray (TMA) resource including 1,326 men with a median follow-up of 5 years. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazard models and the Log-rank test.
Results
The presence of MUC1 expression was significantly associated with extracapsular extension and higher Gleason score, but not with seminal vesicle invasion, age, positive surgical margins or pre-operative serum PSA levels. In univariable analyses, positive MUC1 staining was significantly associated with a worse recurrence free survival (RFS) (HR: 1.24, CI 1.03–1.49, P = 0.02), although not with disease specific survival (DSS, P>0.5). On multivariable analyses, the presence of positive surgical margins, extracapsular extension, seminal vesicle invasion, as well as higher pre-operative PSA and increasing Gleason score were independently associated with RFS, while MUC1 expression was not. Positive MUC1 expression was not independently associated with disease specific survival (DSS), but was weakly associated with overall survival (OS).
Conclusion
In our large, rigorously designed validation cohort, MUC1 protein expression was associated with adverse pathological features, although it was not an independent predictor of outcome after radical prostatectomy.
doi:10.1371/journal.pone.0165236
PMCID: PMC5112958  PMID: 27846218
5.  Analytic Validation of a Clinical-Grade PTEN Immunohistochemistry Assay in Prostate Cancer by Comparison to PTEN FISH 
PTEN loss is a promising prognostic and predictive biomarker in prostate cancer. Because it occurs most commonly via PTEN gene deletion, we developed a clinical-grade, automated and inexpensive immunohistochemical assay to detect PTEN loss. We studied the sensitivity and specificity of PTEN immunohistochemistry relative to 4-color fluorescence in situ hybridization (FISH) for detection of PTEN gene deletion in a multi-institutional cohort of 731 primary prostate tumors. Intact PTEN immunostaining was 91% specific for absence of PTEN gene deletion, (549/602 tumors with 2 copies of the PTEN gene by FISH showed intact expression of PTEN by immunohistochemistry) and 97% sensitive for presence of homozygous PTEN gene deletion (absent PTEN protein expression by immunohistochemistry in 65/67 tumors with homozygous deletion). PTEN immunohistochemistry was 65% sensitive for presence of hemizygous PTEN gene deletion, with protein loss in 40/62 hemizygous tumors. We reviewed the 53 cases where immunohistochemistry showed PTEN protein loss and FISH showed 2 intact copies of the PTEN gene. On re-review, there was ambiguous immunohistochemistry loss in 6% (3/53) and failure to analyze the same tumor area by both methods in 34% (18/53). Of the remaining discordant cases, 41% (13/32) revealed hemizygous (n=8) or homozygous (n=5) PTEN gene deletion that was focal in most cases (11/13). The remaining 19 cases had 2 copies of the PTEN gene by FISH, representing truly discordant cases. Our automated PTEN immunohistochemistry assay is a sensitive method for detection of homozygous PTEN gene deletions. Immunohistochemistry screening is particularly useful to identify cases with heterogeneous PTEN gene deletion in a subset of tumor glands. Mutations, small insertions or deletions and/or epigenetic or microRNA-mediated mechanisms may lead to PTEN protein loss in tumors with normal or hemizygous PTEN gene copy number.
doi:10.1038/modpathol.2016.88
PMCID: PMC4967011  PMID: 27174589
Prostatic carcinoma PTEN; fluorescence in situ hybridization; immunohistochemistry; radical prostatectomy; biomarker
6.  MAPRE1 as a plasma biomarker for early-stage colorectal cancer and adenomas 
Blood-based biomarkers for early detection of colorectal cancer (CRC) could complement current approaches to CRC screening. We previously identified the APC-binding protein MAPRE1 as a potential CRC biomarker. Here we undertook a case-control validation study to determine the performance of MAPRE1 in detecting early CRC and colon adenoma and to assess the potential relevance of additional biomarker candidates. We analyzed plasma samples from 60 patients with adenomas, 30 with early CRC, 30 with advanced CRC, and 60 healthy controls. MAPRE1 and a set of 21 proteins with potential biomarker utility were assayed using high-density antibody arrays, and CEA was assayed using ELISA. The biologic significance of the candidate biomarkers was also assessed in CRC mouse models. Plasma MAPRE1 levels were significantly elevated in both patients with adenomas and patients with CRC compared with controls (P < 0.0001). MAPRE1 and CEA together yielded an area under the curve of 0.793 and a sensitivity of 0.400 at 95% specificity for differentiating early CRC from controls. Three other biomarkers (AK1, CLIC1, and SOD1) were significantly increased in both adenoma and early CRC patient plasma samples and in plasma from CRC mouse models at preclinical stages compared with controls. The combination of MAPRE1, CEA, and AK1 yielded sensitivities of 0.483 and 0.533 at 90% specificity and sensitivities of 0.350 and 0.467 at 95% specificity for differentiating adenoma and early CRC, respectively, from healthy controls. These findings suggest that MAPRE1 can contribute to the detection of early-stage CRC and adenomas together with other biomarkers.
doi:10.1158/1940-6207.CAPR-15-0077
PMCID: PMC4633385  PMID: 26342024
colorectal cancer; early detection; MAPRE1; blood-based biomarker; proteomics
7.  Early Phase Studies of Biomarkers: What Target Sensitivity and Specificity Values Might Confer Clinical Utility? 
Clinical chemistry  2016;62(5):737-742.
BACKGROUND
Many cancer biomarker research studies seek to develop markers that can accurately detect or predict future onset of disease. To design and evaluate these studies one must specify the levels of accuracy sought. However, justified target levels are rarely available.
METHODS
We describe a way to calculate target levels of sensitivity and specificity for a biomarker intended to be applied in a defined clinical context. The calculation requires knowledge of the prevalence or incidence of cases in the clinical population and the ratio of benefit associated with the clinical consequences of a positive biomarker test in cases to cost associated with a positive biomarker test in controls. Guidance is offered on soliciting the cost-benefit ratio. The calculations are based on the longstanding decision theoretic concept of providing a net benefit on average in the population and they rely on some assumptions about uniformity of costs and benefits to those tested.
RESULTS
Calculations are illustrated with three applications: predicting colon cancer recurrence in stage 1 patients; predicting interval breast cancers after mammographic screening; and screening for ovarian cancer.
CONCLUSIONS
It is feasible to specify target levels of biomarker performance that enable evaluation of the potential clinical impact of biomarkers in early phase studies. Nevertheless biomarkers meeting the criteria should still be tested rigorously in studies where the actual impact on patient outcomes of using the biomarker to make clinical decisions is measured.
doi:10.1373/clinchem.2015.252163
PMCID: PMC5003106  PMID: 27001493
Accuracy; True Positive Rate; Study Design; Biomarker Performance; Cost
8.  Two-stage biomarker panel study and estimation allowing early termination for futility 
Biostatistics (Oxford, England)  2015;16(4):799-812.
Technological advances have yielded a wealth of biomarkers that have the potential to detect chronic diseases such as cancer. However, most biomarkers considered for further validation turn out not to have strong enough performance to be used in clinical practice. Group sequential designs that allow early termination for futility may be cost-effective for biomarker studies based on biobanks of stored specimens. Previous studies proposed a group sequential design for the validation of a single biomarker. In this article, we adapt a 2-stage design to the setting where a panel of candidate biomarkers are under investigation. Conditional estimators of the clinical performance are proposed under an updated risk model that uses all accrued data, and can be computed through resampling procedures. Under a special case where a multivariate binormal distribution applies for biomarkers following a suitable transformation, these estimators have analytical forms, alleviating the computational burden while retaining statistical efficiency. Performance of the proposed 2-stage design and estimators are compared with a traditional fixed-sample design and an existing 2-stage design that allows early termination but does not update the risk model with accrued information. Our proposed design and estimators show an ability to reduce sample size when the biomarker panel is not promising, while controlling rejection rate and gaining efficiency when the panel is promising. We apply the proposed methods to a biomarker panel development for the detection of high-grade prostate cancer in a study conducted within the National Cancer Institute's Early Detection Research Network.
doi:10.1093/biostatistics/kxv017
PMCID: PMC4570581  PMID: 25964662
Biomarker panel evaluation; Conditional estimate; Groupsequential methods; Two-stage design
9.  The Net Reclassification Index (NRI): a Misleading Measure of Prediction Improvement Even with Independent Test Data Sets 
Statistics in biosciences  2014;7(2):282-295.
The Net Reclassification Index (NRI) is a very popular measure for evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors. However, the statistical properties of this novel measure have not been explored in depth. We demonstrate the alarming result that the NRI statistic calculated on a large test dataset using risk models derived from a training set is likely to be positive even when the new marker has no predictive information. A related theoretical example is provided in which an incorrect risk function that includes an uninformative marker is proven to erroneously yield a positive NRI. Some insight into this phenomenon is provided. Since large values for the NRI statistic may simply be due to use of poorly fitting risk models, we suggest caution in using the NRI as the basis for marker evaluation. Other measures of prediction performance improvement, such as measures derived from the ROC curve, the net benefit function and the Brier score, cannot be large due to poorly fitting risk functions.
doi:10.1007/s12561-014-9118-0
PMCID: PMC4615606  PMID: 26504496
risk prediction; receiver operating characteristic; diagnostic test; biomarkers; classification
10.  Epigenetic signature of Gleason score and prostate cancer recurrence after radical prostatectomy 
Clinical Epigenetics  2016;8:97.
Background
Identifying the subset of patients with clinically localized prostate cancer (PCa) at the highest risk of recurrence remains challenging, and better prognostic markers are needed. Gleason score is the best predictor of PCa aggressiveness and prognosis. In the present study, we generated an epigenetic signature based on high versus low Gleason score tumors and evaluated its ability to predict recurrence after radical prostatectomy.
Methods
Genome-wide DNA methylation data from The Cancer Genome Atlas (TCGA; no. of patients = 333) and the elastic net method were used to generate an epigenetic signature by contrasting patients with high (8–10) versus low (≤6) Gleason score tumors. The signature was then tested in a cohort of 523 patients with clinically localized disease who had radical prostatectomy. Samples taken from the primary tumor were used for DNA methylation and mRNA expression profiling. Patients were followed for PCa recurrence on average for 8 years after diagnosis.
Results
The epigenetic signature includes 52 differentially methylated CpG sites. In the testing cohort, the signature was associated with poorer recurrence-free survival (hazard ratio per 25 % increase = 1.78; 95 % confidence interval 1.48, 2.16). The signature significantly improved the area under the curve (AUC) for PCa recurrence compared to clinical-pathological parameters alone, particularly among patients diagnosed with Gleason score 7 tumors (0.64 vs. 0.76, P = 1.34E−4). Results were comparable for patients with Gleason 3 + 4 and those with 4 + 3 tumors. Gene Set Enrichment Analysis showed that higher levels of the signature were associated with increased expression of genes related to cell cycle proliferation and decreased expression of androgen-responsive genes.
Conclusions
This report shows evidence that DNA methylation patterns measured in prostate tumor cells are predictive of PCa aggressiveness. The epigenetic signature may have clinical utility to improve prognostication particularly in patients with intermediate Gleason score 7 tumors.
Electronic supplementary material
The online version of this article (doi:10.1186/s13148-016-0260-z) contains supplementary material, which is available to authorized users.
doi:10.1186/s13148-016-0260-z
PMCID: PMC5024414  PMID: 27651837
Clinically localized prostate cancer; Tumor tissue; DNA methylation; Gene expression; Risk prediction for prognosis; Genome-wide profiling; Elastic net regularization
11.  Unbiased estimation of biomarker panel performance when combining training and testing data in a group sequential design 
Biometrics  2016;72(3):888-896.
Summary
Motivated by an ongoing study to develop a screening test able to identify patients with undiagnosed Sjögren’s Syndrome in a symptomatic population, we propose methodology to combine multiple biomarkers and evaluate their performance in a two-stage group sequential design that proceeds as follows: biomarker data is collected from first stage samples; the biomarker panel is built and evaluated; if the panel meets pre-specified performance criteria the study continues to the second stage and the remaining samples are assayed. The design allows us to conserve valuable specimens in the case of inadequate biomarker panel performance. We propose a nonparametric conditional resampling algorithm that uses all the study data to provide unbiased estimates of the biomarker combination rule and the sensitivity of the panel corresponding to specificity of 1-t on the receiver operating characteristic curve (ROC). The Copas & Corbett (2002) correction, for bias resulting from using the same data to derive the combination rule and estimate the ROC, was also evaluated and an improved version was incorporated. An extensive simulation study was conducted to evaluate finite sample performance and propose guidelines for designing studies of this type. The methods were implemented in the National Cancer Institutes Early Detection Network Urinary PCA3 Evaluation Trial.
doi:10.1111/biom.12480
PMCID: PMC4974170  PMID: 26845527
Biomarker panel; Conditional estimation; Logistic regression; Shrinkage correction; Two-stage design
12.  Associations of Body Mass Index, Smoking, and Alcohol Consumption With Prostate Cancer Mortality in the Asia Cohort Consortium 
American Journal of Epidemiology  2015;182(5):381-389.
Many potentially modifiable risk factors for prostate cancer are also associated with prostate cancer screening, which may induce a bias in epidemiologic studies. We investigated the associations of body mass index (weight (kg)/height (m)2), smoking, and alcohol consumption with risk of fatal prostate cancer in Asian countries where prostate cancer screening is not widely utilized. Analysis included 18 prospective cohort studies conducted during 1963–2006 across 6 countries in southern and eastern Asia that are part of the Asia Cohort Consortium. Body mass index, smoking, and alcohol intake were determined by questionnaire at baseline, and cause of death was ascertained through death certificates. Analysis included 522,736 men aged 54 years, on average, at baseline. During 4.8 million person-years of follow-up, there were 634 prostate cancer deaths (367 prostate cancer deaths across the 11 cohorts with alcohol data). In Cox proportional hazards analyses of all cohorts in the Asia Cohort Consortium, prostate cancer mortality was not significantly associated with obesity (body mass index >25: hazard ratio (HR) = 1.08, 95% confidence interval (CI): 0.85, 1.36), ever smoking (HR = 1.00, 95% CI: 0.84, 1.21), or heavy alcohol intake (HR = 1.00, 95% CI: 0.74, 1.35). Differences in prostate cancer screening and detection probably contribute to differences in the association of obesity, smoking, or alcohol intake with prostate cancer risk and mortality between Asian and Western populations and thus require further investigation.
doi:10.1093/aje/kwv089
PMCID: PMC4643758  PMID: 26243736
alcohol drinking; Asia; mortality; obesity; prostate cancer; prostate-specific antigen; smoking
13.  Expression of Cell Cycle-regulated Genes and Prostate Cancer Prognosis in a Population-based Cohort 
The Prostate  2015;75(13):1354-1362.
BACKGROUND
Prostate cancer (PCa) is clinically and biologically heterogeneous, making it difficult to predict at detection whether it will take an indolent or aggressive disease course. Cell cycle-regulated genes may be more highly expressed in actively dividing cells, with transcript levels reflecting tumor growth rate. Here we evaluated expression of cell cycle genes in relation to PCa outcomes in a population-based cohort.
METHODS
Gene expression data were generated from tumor tissues obtained at radical prostatectomy for 383 population-based patients (12.3-years average follow-up). The overall mean and individual transcript levels of 30 selected cell cycle genes was compared between patients with no evidence of recurrence (73%) and those who recurred (27%) or died (7%) from PCa.
RESULTS
The multivariate adjusted hazard ratio (HR) for a change from the 25th to 75th percentile of mean gene expression level (range 8.02–10.05) was 1.25 (95% CI 0.96–1.63; P = 0.10) for PCa recurrence risk, and did not vary substantially by Gleason score, TMPRSS2-ERG fusion status, or family history of PCa. For lethal PCa, the HR for a change (25th to 75th percentile) in mean gene expression level was 2.04 (95% CI 1.26–3.31; P = 0.004), adjusted for clinicopathological variables. The ROC curve for mean gene expression level alone (AUC = 0.740) did not perform as well as clinicopathological variables alone (AUC = 0.803) for predicting lethal PCa, and the addition of gene expression to clinicopathological variables did not substantially improve prediction (AUC = 0.827; P = 0.18). Higher TK1 expression was strongly associated with both recurrent (P = 6.7×10−5) and lethal (P = 6.4×10−6) PCa.
CONCLUSIONS
Mean expression level for 30 selected cell cycle-regulated genes was unrelated to recurrence risk, but was associated with a two-fold increase in risk of lethal PCa. However, gene expression had less discriminatory accuracy than clinical variables alone for predicting lethal events. Transcript levels for several genes in the panel were significantly overexpressed in lethal vs. non-recurrent PCa.
doi:10.1002/pros.23016
PMCID: PMC4992473  PMID: 25990700
cell cycle-regulated genes; gene expression; patient outcomes; population-based cohort; prostate cancer
14.  Outcomes of active surveillance for the management of clinically localized prostate cancer in the prospective, multi-institutional Canary PASS cohort 
The Journal of urology  2015;195(2):313-320.
Purpose
Active surveillance represents a strategy to address the overtreatment of prostate cancer, yet uncertainty regarding individual patient outcomes remains a concern. We evaluated outcomes in a prospective multi-center study of active surveillance.
Methods
We studied 905 men in the prospective Canary Prostate cancer Active Surveillance Study (PASS) enrolled between 2008 to 2013. We collected clinical data at study entry and at pre-specified intervals and determined associations with adverse reclassification defined as increased Gleason grade or greater cancer volume on follow-up biopsy. We also evaluated the relationships of clinical parameters with pathology findings in participants who underwent surgery after a period of active surveillance.
Results
During a median follow-up of 28 months, 24% of participants experienced adverse reclassification, of whom 53% underwent treatment while 31% continued active surveillance. Overall, 19% of participants received treatment, 68% with adverse reclassification while 32% opted for treatment without disease reclassification. In multivariate Cox proportional hazards modeling, percent of biopsy cores with cancer, BMI, and PSA density were associated with adverse reclassification (P = 0.01, 0.04, 0.04). Of 103 participants subsequently treated by radical prostatectomy, 34% had adverse pathology, defined as primary pattern 4–5 or non-organ confined disease, including two with positive lymph nodes, with no significant relationship between risk category at diagnosis and findings at surgery (P = 0.76).
Conclusion
Most men remain on active surveillance at five years without adverse reclassification or adverse pathology at surgery. However, clinical factors had only modest association with disease reclassification, supporting the need for approaches that improve prediction of this outcome.
doi:10.1016/j.juro.2015.08.087
PMCID: PMC4970462  PMID: 26327354
prostatic neoplasms; prospective studies; active surveillance
15.  A multicenter study shows PTEN deletion is strongly associated with seminal vesicle involvement and extracapsular extension in localized prostate cancer 
The Prostate  2015;75(11):1206-1215.
BACKGROUND
Loss of the phosphatase and tensin homolog (PTEN) tumor suppressor gene is a promising marker of aggressive prostate cancer. Active surveillance and watchful waiting are increasingly recommended to patients with small tumors felt to be low risk, highlighting the difficulties of Gleason scoring in this setting. There is an urgent need for predictive biomarkers that can be rapidly deployed to aid in clinical decision-making. Our objectives were to assess the incidence and ability of PTEN alterations to predict aggressive disease in a multicenter study.
METHODS
We used recently developed probes optimized for sensitivity and specificity in a four-color FISH deletion assay to study the Canary Retrospective multicenter Prostate Cancer Tissue Microarray (TMA). This TMA was constructed specifically for biomarker validation from radical prostatectomy specimens, and is accompanied by detailed clinical information with long-term follow-up.
RESULTS
In 612 prostate cancers the overall rate of PTEN deletion was 112 (18.3%). Hemizygous PTEN losses were present in 55/612 (9.0%) of cancers, whereas homozygous PTEN deletion was observed in 57/612 (9.3%) of tumors. Significant associations were found between PTEN status and pathologic stage (P<0.0001), seminal vesicle invasion (p=0.0008), extracapsular extension (p<0.0001), and Gleason score (p=0.0002). In logistic regression analysis of clinical and pathological variables, PTEN deletion was significantly associated with extracapsular extension, seminal vesicle involvement, and higher Gleason score. In the 406 patients in which clinical information was available, PTEN homozygous (p=0.009) deletion was associated with worse post-operative recurrence-free survival (number of events = 189), pre-operative prostate specific antigen (PSA) (p<0.001) and pathologic stage (p=0.03).
CONCLUSION
PTEN status assessed by FISH is an independent predictor for recurrence free survival in multivariate models, as were seminal vesicle invasion, extracapsular extension Gleason score and preoperative PSA. Furthermore, these data demonstrate that the assay can be readily introduced at first diagnosis in a cost effective manner analogous to the use of FISH for analysis of HER2/neu status in breast cancer. Combined with published research beginning 17 years ago, both the data and tools now exist to implement a PTEN assay in the clinic.
doi:10.1002/pros.23003
PMCID: PMC4475421  PMID: 25939393
active surveillance; Gleason score; biomarker; PI3K/PTEN/Akt pathway; Fluorescence in Situ Hybridization; Tissue Array Analysis
16.  Evaluation of a novel saliva‐based epidermal growth factor receptor mutation detection for lung cancer: A pilot study 
Thoracic Cancer  2016;7(4):428-436.
Background
This article describes a pilot study evaluating a novel liquid biopsy system for non‐small cell lung cancer (NSCLC) patients. The electric field‐induced release and measurement (EFIRM) method utilizes an electrochemical biosensor for detecting oncogenic mutations in biofluids.
Methods
Saliva and plasma of 17 patients were collected from three cancer centers prior to and after surgical resection. The EFIRM method was then applied to the collected samples to assay for exon 19 deletion and p.L858 mutations. EFIRM results were compared with cobas results of exon 19 deletion and p.L858 mutation detection in cancer tissues.
Results
The EFIRM method was found to detect exon 19 deletion with an area under the curve (AUC) of 1.0 in both saliva and plasma samples in lung cancer patients. For L858R mutation detection, the AUC of saliva was 1.0, while the AUC of plasma was 0.98. Strong correlations were also found between presurgery and post‐surgery samples for both saliva (0.86 for exon 19 and 0.98 for L858R) and plasma (0.73 for exon 19 and 0.94 for L858R).
Conclusion
Our study demonstrates the feasibility of utilizing EFIRM to rapidly, non‐invasively, and conveniently detect epidermal growth factor receptor mutations in the saliva of patients with NSCLC, with results corresponding perfectly with the results of cobas tissue genotyping.
doi:10.1111/1759-7714.12350
PMCID: PMC4930962  PMID: 27385985
EGFR mutation; liquid biopsy; lung cancer; saliva diagnostics
17.  Improving the Quality of Biomarker Discovery Research: the Right Samples and Enough of Them 
Background
Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs.
Methods
The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE).
Results
We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions.
Conclusions
Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified.
Impact
The scientific rigor of discovery research should be improved.
doi:10.1158/1055-9965.EPI-14-1227
PMCID: PMC4452419  PMID: 25837819
case-control; specimen repository; statistical power; sample size
18.  Confirmation of Genetic Variants Associated with Lethal Prostate Cancer in a Cohort of Men from Hereditary Prostate Cancer Families 
Germline genetic variants have been suggested as prognostic biomarkers for identifying patients at high risk for lethal prostate cancer (PCa). Validation studies have confirmed the association of several single nucleotide polymorphisms (SNPs) with fatal PCa, but whether these variants affect PCa-specific mortality (PCSM) in patients with an inherited predisposition to PCa, based on familial history, is unknown. For this study, a cohort of 957 PCa patients from 270 hereditary prostate cancer (HPC) families of European ancestry was genotyped for a panel of 22 PCSM-associated SNPs. Death certificates were reviewed to confirm cause of death. Mixed-effect Cox proportional hazards models were used to assess survival according to genotypes, accounting for relatedness and clinicopathological factors. Within this cohort, 98 PCa deaths were confirmed over an average follow-up period of 12.7 years after diagnosis. Variant allele carriers for three SNPs had significantly altered risk for PCSM (rs635261 at RNASEL, HR, 0.35, 95% CI, 0.18–0.66; P = 0.002; rs915927 in XRCC1, HR, 1.91, 95% CI, 1.21–3.02; P = 0.009; and rs2494750 at AKT1, HR, 0.45, 95% CI, 0.23–0.90; P = 0.016). These results confirm the association of genetic variation in three genes with PCa lethality in a cohort of men with an inherited susceptibility to the disease and provide validation evidence that germline SNPs provide prognostic information for PCa patients. Development of a panel of germline biomarkers with clinical utility for distinguishing patients at detection who have an increased risk for fatal PCa is warranted.
doi:10.1002/ijc.29241
PMCID: PMC4331209  PMID: 25273821
Hereditary prostate cancer; mortality; SNPs; XRCC1; AKT1
19.  Projecting Benefits and Harms of Novel Cancer Screening Biomarkers: A Study of PCA3 and Prostate Cancer 
Background
New biomarkers for early detection of cancer must pass through several phases of development. Early phases provide information on diagnostic properties but not on population benefits and harms. Prostate cancer antigen 3 (PCA3) is a promising prostate cancer biomarker still in early development. We use simulation modeling to project the impact of adding PCA3 to prostate-specific antigen (PSA) screening on prostate cancer detection and mortality in the United States.
Methods
We used data from a recent study of PCA3 in men referred for prostate biopsy to extend an existing simulation model of PSA growth, disease progression and survival. We specified several PSA-PCA3 strategies designed to improve specificity and reduce overdiagnosis. Using these strategies to screen a cohort of men biennially between ages 50 and 74, we projected true and false positive tests, overdiagnoses, and lives saved relative to a PSA-based strategy with a cutoff of 4.0 ng/ml for biopsy referral.
Results
We identified several PSA-PCA3 strategies that substantially reduced false positive tests and overdiagnoses while preserving the majority of lives saved. PCA3>35 for biopsy referral in men with PSA between 4.0 and 10.0 ng/ml retained 85% of lives saved while approximately halving false positives and reducing overdiagnoses by 25%.
Conclusions
Adding PCA3 to PSA screening can significantly reduce adverse screening outcomes. Strategies can be identified that preserve most of the lives saved relative to PSA-based screening.
Impact
Simulation modeling provides advance projections of population outcomes of new screening biomarkers and may help guide early detection research.
doi:10.1158/1055-9965.EPI-14-1224
PMCID: PMC4383671  PMID: 25613117
Biomarker development; computer simulation; mass screening; prostate cancer antigen 3; prostatic neoplasms
20.  Replication of a Genetic Variant for Prostate Cancer-Specific Mortality 
Background
Few genetic variants have been confirmed as being associated with prostate cancer-specific mortality (PCSM). A recent study identified 22 candidate single-nucleotide polymorphisms (SNPs) associated with PCSM in a Seattle-based patient cohort. Five of these associations were replicated in an independent Swedish cohort.
Methods
We genotyped these 22 SNPs in Physicians’ Health Study (PHS) participants diagnosed with prostate cancer (PCa). Utilizing the same model found to be most significant in the Seattle cohort, we examined the association of these SNPs with lethal disease with Cox proportional hazards models.
Results
One SNP, rs5993891 in the ARVCF gene on chromosome 22q11, which had also replicated in the Swedish cohort, was also significantly associated with PCSM in the PHS cohort (hazard ratio (HR)=0.32; P=0.01). When we tested this SNP in an additional cohort (Health Professionals Follow-up Study, HPFS), the association was null (HR=0.95, P=0.90); however, a meta-analysis across all studies showed a statistically significant association with a HR of 0.52 (0.29–0.93, P=0.03).
Conclusions
The association of rs5993891 with PCSM was further replicated in PHS and remains significant in a meta-analysis, though there was no association in HPFS. This SNP may contribute to a genetic panel of SNPs to determine at diagnosis whether a patient is more likely to exhibit an indolent or aggressive form of PCa. This study also emphasizes the importance of multiple rounds of replication.
doi:10.1038/pcan.2015.18
PMCID: PMC4537383  PMID: 25939514
21.  A multicenter study shows PTEN deletion is strongly associated with seminal vesicle involvement and extracapsular extension in localized prostate cancer 
The Prostate  2015;75(11):1206-1215.
BACKGROUND
Loss of the phosphatase and tensin homolog (PTEN) tumor suppressor gene is a promising marker of aggressive prostate cancer. Active surveillance and watchful waiting are increasingly recommended to patients with small tumors felt to be low risk, highlighting the difficulties of Gleason scoring in this setting. There is an urgent need for predictive biomarkers that can be rapidly deployed to aid in clinical decision-making. Our objectives were to assess the incidence and ability of PTEN alterations to predict aggressive disease in a multicenter study.
METHODS
We used recently developed probes optimized for sensitivity and specificity in a four-color FISH deletion assay to study the Canary Retrospective multicenter Prostate Cancer Tissue Microarray (TMA). This TMA was constructed specifically for biomarker validation from radical prostatectomy specimens, and is accompanied by detailed clinical information with long-term follow-up.
RESULTS
In 612 prostate cancers, the overall rate of PTEN deletion was 112 (18.3%). Hemizygous PTEN losses were present in 55/612 (9.0%) of cancers, whereas homozygous PTEN deletion was observed in 57/612 (9.3%) of tumors. Significant associations were found between PTEN status and pathologic stage (P < 0.0001), seminal vesicle invasion (P = 0.0008), extracapsular extension (P < 0.0001), and Gleason score (P = 0.0002). In logistic regression analysis of clinical and pathological variables, PTEN deletion was significantly associated with extracapsular extension, seminal vesicle involvement, and higher Gleason score. In the 406 patients in which clinical information was available, PTEN homozygous (P = 0.009) deletion was associated with worse post-operative recurrence-free survival (number of events = 189), pre-operative prostate specific antigen (PSA) (P < 0.001), and pathologic stage (P = 0.03).
CONCLUSION
PTEN status assessed by FISH is an independent predictor for recurrence-free survival in multivariate models, as were seminal vesicle invasion, extracapsular extension, and Gleason score, and preoperative PSA. Furthermore, these data demonstrate that the assay can be readily introduced at first diagnosis in a cost effective manner analogous to the use of FISH for analysis of HER2/neu status in breast cancer. Combined with published research beginning 17 years ago, both the data and tools now exist to implement a PTEN assay in the clinic. Prostate 75: 1206–1215, 2015. © 2015 The Authors. The Prostate, published by Wiley Periodicals, Inc.
doi:10.1002/pros.23003
PMCID: PMC4475421  PMID: 25939393
active surveillance; Gleason score; biomarker; PI3K/PTEN/Akt pathway; fluorescence in situ hybridization; tissue array analysis
22.  Can Urinary PCA3 Supplement PSA in the Early Detection of Prostate Cancer? 
Journal of Clinical Oncology  2014;32(36):4066-4072.
Purpose
Given the limited sensitivity and specificity of prostate-specific antigen (PSA), its widespread use as a screening tool has raised concerns for the overdiagnosis of low-risk and the underdiagnosis of high-grade prostate cancer. To improve early-detection biopsy decisions, the National Cancer Institute conducted a prospective validation trial to assess the diagnostic performance of the prostate cancer antigen 3 (PCA3) urinary assay for the detection of prostate cancer among men screened with PSA.
Patients and Methods
In all, 859 men (mean age, 62 years) from 11 centers scheduled for a diagnostic prostate biopsy between December 2009 and June 2011 were enrolled. The primary outcomes were to assess whether PCA3 could improve the positive predictive value (PPV) for an initial biopsy (at a score > 60) and the negative predictive value (NPV) for a repeat biopsy (at a score < 20).
Results
For the detection of any cancer, PPV was 80% (95% CI, 72% to 86%) in the initial biopsy group, and NPV was 88% (95% CI, 81% to 93%) in the repeat biopsy group. The addition of PCA3 to individual risk estimation models (which included age, race/ethnicity, prior biopsy, PSA, and digital rectal examination) improved the stratification of cancer and of high-grade cancer.
Conclusion
These data independently support the role of PCA3 in reducing the burden of prostate biopsies among men undergoing a repeat prostate biopsy. For biopsy-naive patients, a high PCA3 score (> 60) significantly increases the probability that an initial prostate biopsy will identify cancer.
doi:10.1200/JCO.2013.52.8505
PMCID: PMC4265117  PMID: 25385735
23.  Proteomic profiling of the autoimmune response to breast cancer antigens uncovers a suppressive effect of hormone therapy 
Purpose
Proteomics technologies are well suited for harnessing the immune response to tumor antigens for diagnostic applications as in the case of breast cancer. We previously reported a substantial impact of hormone therapy (HT) on the proteome. Here we investigated the effect of HT on the immune response toward breast tumor antigens.
Experimental design
Plasmas collected 0-10 months prior to diagnosis of ER+ breast cancer from 190 post-menopausal women and 190 controls that participated in the Women's Health Initiative (WHI) Observational Study were analyzed for the effect of HT on IgG reactivity against arrayed proteins from MCF-7 or SKBR3 breast cancer cell line lysates following extensive fractionation.
Results
HT user cases exhibited significantly reduced autoantibody reactivity against arrayed proteins compared to cases who were not current users. An associated reduced level of IL-6 and other immune-related cytokines was observed among HT users relative to non-users.
Conclusion and clinical relevance
Our findings suggest occurrence of a global altered immune response to breast cancer derived proteins associated with HT. Thus a full understanding of factors that modulate the immune response is necessary to translate autoantibody panels into clinical applications.
doi:10.1002/prca.201200058
PMCID: PMC4681300  PMID: 23401414
24.  Epigenomic profiling of prostate cancer identifies differentially methylated genes in TMPRSS2:ERG fusion-positive versus fusion-negative tumors 
Clinical Epigenetics  2015;7:128.
Background
About half of all prostate cancers harbor the TMPRSS2:ERG (T2E) gene fusion. While T2E-positive and T2E-negative tumors represent specific molecular subtypes of prostate cancer (PCa), previous studies have not yet comprehensively investigated how these tumor subtypes differ at the epigenetic level. We therefore investigated epigenome-wide DNA methylation profiles of PCa stratified by T2E status.
Results
The study included 496 patients with clinically localized PCa who had a radical prostatectomy as primary treatment for PCa. Fluorescence in situ hybridization (FISH) “break-apart” assays were used to determine tumor T2E-fusion status, which showed that 266 patients (53.6 %) had T2E-positive PCa. The study showed global DNA methylation differences between tumor subtypes. A large number of differentially methylated CpG sites were identified (false-discovery rate [FDR] Q-value <0.00001; n = 27,876) and DNA methylation profiles accurately distinguished between tumor T2E subgroups. A number of top-ranked differentially methylated CpGs in genes (FDR Q-values ≤1.53E−29) were identified: C3orf14, CACNA1D, GREM1, KLK10, NT5C, PDE4D, RAB40C, SEPT9, and TRIB2, several of which had a corresponding alteration in mRNA expression. These genes may have various roles in the pathogenesis of PCa, and the calcium-channel gene CACNA1D is a known ERG-target. Analysis of The Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings.
Conclusions
This study identified substantial differences in DNA methylation profiles of T2E-positive and T2E-negative tumors, thereby providing further evidence that different underlying oncogenic pathways characterize these molecular subtypes.
Electronic supplementary material
The online version of this article (doi:10.1186/s13148-015-0161-6) contains supplementary material, which is available to authorized users.
doi:10.1186/s13148-015-0161-6
PMCID: PMC4676897  PMID: 26692910
DNA methylation; CpG site; Epigenetics; Epigenomic profiling; Prostate cancer; Gene fusion; TMPRSS2; ERG; Tumor tissue; Unsupervised clustering; mRNA expression; C3orf14; CACNA1D; GREM1; KLK10; NT5C; PDE4D; RAB40C; SEPT9; TRIB2; TCGA
25.  Evaluation of ERG and SPINK1 by Immunohistochemical Staining and Clinicopathological Outcomes in a Multi-Institutional Radical Prostatectomy Cohort of 1067 Patients 
PLoS ONE  2015;10(7):e0132343.
Distinguishing between patients with early stage, screen detected prostate cancer who must be treated from those that can be safely watched has become a major issue in prostate cancer care. Identification of molecular subtypes of prostate cancer has opened the opportunity for testing whether biomarkers that characterize these subtypes can be used as biomarkers of prognosis. Two established molecular subtypes are identified by high expression of the ERG oncoprotein, due to structural DNA alterations that encode for fusion transcripts in approximately ½ of prostate cancers, and over-expression of SPINK1, which is purportedly found only in ERG-negative tumors. We used a multi-institutional prostate cancer tissue microarray constructed from radical prostatectomy samples with associated detailed clinical data and with rigorous selection of recurrent and non-recurrent cases to test the prognostic value of immunohistochemistry staining results for the ERG and SPINK1 proteins. In univariate analysis, ERG positive cases (419/1067; 39%) were associated with lower patient age, pre-operative serum PSA levels, lower Gleason scores (≤3+4=7) and improved recurrence free survival (RFS). On multivariate analysis, ERG status was not correlated with RFS, disease specific survival (DSS) or overall survival (OS). High-level SPINK1 protein expression (33/1067 cases; 3%) was associated with improved RFS on univariate and multivariate Cox regression analysis. Over-expression of either protein was not associated with clinical outcome. While expression of ERG and SPINK1 proteins was inversely correlated, it was not mutually exclusive since 3 (0.28%) cases showed high expression of both. While ERG and SPINK1 appear to identify discrete molecular subtypes of prostate cancer, only high expression of SPINK1 was associated with improved clinical outcome. However, by themselves, neither ERG nor SPINK1 appear to be useful biomarkers for prognostication of early stage prostate cancer.
doi:10.1371/journal.pone.0132343
PMCID: PMC4501723  PMID: 26172920

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