Recommendations for the Equitable and Widespread Implementation of Liquid Biopsy for Cancer Care.

Liquid biopsies-tests that detect circulating tumor cellular components in the bloodstream-have the potential to transform cancer by reducing health inequities in screening, diagnostics, and monitoring. Today, liquid biopsies are being used to guide treatment choices for patients and monitor for cancer recurrence, and promising work in multi-cancer early detection is ongoing. However, without awareness of the barriers to adoption of this new technology and a willingness to build mitigation efforts into the implementation of widespread liquid biopsy testing, the communities that could most benefit may be the last to access and use them. In this work, we review the challenges likely to affect the accessibility of liquid biopsies in both the general population and underserved populations, and recommend specific actions to facilitate equitable access for all patients.

Predictive Biomarkers of Overall Survival in Patients with Metastatic Renal Cell Carcinoma Treated with IFNα ± Bevacizumab: Results from CALGB 90206 (Alliance).

PURPOSE: CALGB 90206 was a phase III trial of 732 patients with metastatic renal cell carcinoma (mRCC) comparing bevacizumab plus IFNα (BEV + IFN) with IFNα alone (IFN). No difference in overall survival (OS) was observed. Baseline samples were analyzed to identify predictive biomarkers for survival benefit. PATIENTS AND METHODS: A total of 32 biomarkers were assessed in 498 consenting patients randomly assigned into training (n = 279) and testing (n = 219) sets. The proportional hazards model was used to test for treatment arm and biomarker interactions of OS. The estimated coefficients from the training set were used to compute a risk score for each patient and to classify patients by risk in the testing set. The resulting model was assessed for predictive accuracy using the time-dependent area under the ROC curve (tAUROC). RESULTS: A statistically significant three-way interaction between IL6, hepatocyte growth factor (HGF), and bevacizumab treatment was observed in the training set and confirmed in the testing set (P < 0.0001). The model based on IL6, HGF, and bevacizumab treatment was predictive of OS (P < 0.001), with the high- and low-risk groups having a median OS of 10.2 [95% confidence interval (CI), 8.0-13.8] and 34.3 (95% CI, 28.5-40.5) months, respectively. The average tAUROC for the final model of OS based on 100 randomly split testing sets was 0.78 (first, third quartiles = 0.77, 0.79). CONCLUSIONS: IL6 and HGF are potential predictive biomarkers of OS benefit from BEV + IFN in patients with mRCC. The model based on key biological and clinical factors demonstrated predictive efficacy for OS. These markers warrant further validation in future anti-VEGF and immunotherapy in mRCC trials. See related commentaries by Mishkin and Kohn, p. 2722 and George and Bertagnolli, p. 2725.

Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

As of January of 2021, the highly transmissible B.1.1.7 variant of SARS-CoV-2, which was first identified in the United Kingdom (U.K.), has gained a strong foothold across the world. Because of the sudden and rapid rise of B.1.1.7, we investigated the prevalence and growth dynamics of this variant in the United States (U.S.), tracking it back to its early emergence and onward local transmission. We found that the RT-qPCR testing anomaly of S gene target failure (SGTF), first observed in the U.K., was a reliable proxy for B.1.1.7 detection. We sequenced 212 B.1.1.7 SARS-CoV-2 genomes collected from testing facilities in the U.S. from December 2020 to January 2021. We found that while the fraction of B.1.1.7 among SGTF samples varied by state, detection of the variant increased at a logistic rate similar to those observed elsewhere, with a doubling rate of a little over a week and an increased transmission rate of 35-45%. By performing time-aware Bayesian phylodynamic analyses, we revealed several independent introductions of B.1.1.7 into the U.S. as early as late November 2020, with onward community transmission enabling the variant to spread to at least 30 states as of January 2021. Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Balancing Confounding and Generalizability Using Observational, Real-world Data: 17-gene Genomic Prostate Score Assay Effect on Active Surveillance.

Randomized, controlled trials can provide high-quality, unbiased evidence for therapeutic interventions but are not always a practical or viable study design for certain healthcare decisions, such as those involving prognostic or predictive testing. Studies using large, real-world databases may be more appropriate and more generalizable to the intended target population of physicians and patients to answer these questions but carry potential for hidden bias. We illustrate several emerging methods of analyzing observational studies using propensity score matching (PSM) and coarsened exact matching (CEM). These advanced statistical methods are intended to reveal a "hidden experiment" within an observational database, and so refute or confirm a potential causal effect of assignment to an intervention and study outcome. We applied these methods to the Optum™ Research Database (ORD; Eden Prairie, MN) of electronic health records and administrative claims data to assess the effect of the 17-gene Genomic Prostate Score® (GPS™; Genomic Health, Redwood City, CA) assay on use of active surveillance (AS). In a traditional multivariable logistic regression, the GPS assay increased the use of AS by 29% (95% CI, 24%-33%). Upon applying the matching methods, the effect of the GPS assay on AS use varied between 27% and 80% and the matched data were significant among all algorithms. All matching algorithms performed well in identifying matched data that improved the imbalance in baseline covariates. By using different matching methods to assess causal inference in an observational database, we provide further confidence that the effect of the GPS assay on AS use is statistically significant and unlikely to be a result of confounding due to differences in baseline characteristics of the patients or the settings in which they were seen.

The 17-Gene Genomic Prostate Score Assay Predicts Outcome After Radical Prostatectomy Independent of PTEN Status.

OBJECTIVE: To compare the ability of loss of phosphatase and tensin homolog (PTEN) and Genomic prostate score assay (GPS) in predicting the biochemical-recurrence (BCR) and clinical-recurrence (CR) after radical prostatectomy (RP) for clinically localized prostate cancer (PCa). METHODS: Three hundred seventy seven patients with and without CR were retrospectively selected by stratified cohort sampling design from RP database. PTEN status (by immunohistochemistry [IHC] and fluorescence in situ hybridization [FISH]) and GPS results were determined for RP specimens. BCR was defined as Prostate Specific Antigen (PSA) ≥ 0.2 ng/mL or initiation of salvage therapy for a rising PSA. CR was defined as local recurrence and/or distant metastases. RESULTS: Baseline mean age, PSA, and GPS score for the cohort were 61.1 years, 8 ng/dL, and 32.8. PTEN loss was noted in 38% patients by FISH and 25% by IHC. The concordance between FISH and IHC for PTEN loss was 66% (Kappa coefficient 0.278; P < .001). On univariable analysis, loss of PTEN by FISH or IHC was associated with BCR and CR (P < .05). However, after adjusting for GPS results, PTEN loss was not a significant predictor for CR or BCR (P > .1). The GPS result remained strongly associated with CR and BCR after adjusting for PTEN status (P < .001). PTEN status and GPS results only weakly correlated. GPS was widely distributed regardless of PTEN status indicating the biological heterogeneity of PCa even in PTEN-deficient cases. CONCLUSION: GPS is a significant predictor of aggressive PCa, independent of PTEN status. After adjustment for GPS results, PTEN was not independently associated with recurrence for PCa.

Validation of the 16-Gene Recurrence Score in Patients with Locoregional, High-Risk Renal Cell Carcinoma from a Phase III Trial of Adjuvant Sunitinib.

Purpose: Adjuvant sunitinib prolonged disease-free survival (DFS; HR, 0.76) in patients with locoregional high-risk renal cell carcinoma (RCC) in the S-TRAC trial (ClinicalTrials.gov NCT00375674). The 16-gene Recurrence Score (RS) assay was previously developed and validated to estimate risk for disease recurrence in patients with RCC after nephrectomy. This analysis further validated the prognostic value of RS assay in patients from S-TRAC and explored the association of RS results with prediction of sunitinib benefit.Patients and Methods: The analysis was prospectively designed with prespecified genes, algorithm, endpoints, and analytical methods. Primary RCC was available from 212 patients with informed consent; primary analysis focused on patients with T3 RCC. Gene expression was quantitated by RT-PCR. Time to recurrence (TTR), DFS, and renal cancer-specific survival (RCSS) were analyzed using Cox proportional hazards regression.Results: Baseline characteristics were similar between patients with and those without RS results, and between the sunitinib and placebo arms among patients with RS results. RS results predicted TTR, DFS, and RCSS in both arms, with the strongest results observed in the placebo arm. When high versus low RS groups were compared, HR for recurrence was 9.18 [95% confidence interval (CI), 2.15-39.24; P < 0.001) in the placebo arm; interaction of RS results with treatment was not significant.Conclusions: The strong prognostic performance of the 16-gene RS assay was confirmed in S-TRAC, and the RS assay is now supported by level IB evidence. RS results may help identify patients at high risk for recurrence who may derive higher absolute benefit from adjuvant therapy. Clin Cancer Res; 24(18); 4407-15. ©2018 AACR.

A 17-Gene Genomic Prostate Score Assay Provides Independent Information on Adverse Pathology in the Setting of Combined Multiparametric Magnetic Resonance Imaging Fusion Targeted and Systematic Prostate Biopsy.

PURPOSE: Multiparametric magnetic resonance imaging and biopsy based molecular tests such as the 17-gene Oncotype DX® Genomic Prostate Score™ assay are increasingly performed to improve risk stratification in men with clinically localized prostate cancer. The prostate score assay was previously shown to be a significant independent predictor of adverse pathology findings at radical prostatectomy in men diagnosed by systematic biopsies only. Therefore, we investigated the ability of the prostate score assay to predict adverse pathology findings in the setting of magnetic resonance imaging guided prostate biopsy. MATERIALS AND METHODS: We identified men diagnosed with NCCN® (National Comprehensive Cancer Network®) very low, low or intermediate risk prostate cancer who underwent simultaneous multiparametric magnetic resonance imaging fusion targeted and systematic prostate biopsy with subsequent radical prostatectomy within 6 months. Prostate score assay testing was performed on biopsy tissue with the highest Gleason score. The primary outcome of the study was adverse pathology findings, defined as Gleason score 4 + 3 or greater disease and/or pT3+ at radical prostatectomy. Independent predictors of adverse pathology findings were determined in a multivariable model to adjust for clinical parameters. RESULTS: A total of 134 men were eligible for primary analysis. On univariable analysis the UCLA score, magnetic resonance imaging, prostate score assay results and biopsy Gleason score were significant predictors of adverse pathology findings. After multivariable adjustment prostate score assay values remained a significant predictor of adverse pathology results (prostate score assay per 20 U OR 3.28, 95% CI 1.74-6.62, p <0.001). A wide and overlapping distribution of prostate score assay results was seen across PI-RADS® (Prostate Imaging Reporting and Data System) version 2 scores. CONCLUSIONS: The prostate score assay result is an independent predictor of adverse pathology findings in patients who were diagnosed with very low, low or intermediate risk prostate cancer in the setting of multiparametric magnetic resonance imaging fusion prostate biopsy. This assay can be useful as an independent technology or an adjunct technology to multiparametric magnetic resonance imaging to individualize risk stratification of low and intermediate risk prostate cancer.

Improving risk stratification among veterans diagnosed with prostate cancer: impact of the 17-gene prostate score assay.

BACKGROUND: Active surveillance (AS) has been widely implemented within Veterans Affairs' medical centers (VAMCs) as a standard of care for low-risk prostate cancer (PCa). Patient characteristics such as age, race, and Agent Orange (AO) exposure may influence advisability of AS in veterans. The 17-gene assay may improve risk stratification and management selection. OBJECTIVES: To compare management strategies for PCa at 6 VAMCs before and after introduction of the Oncotype DX Genomic Prostate Score (GPS) assay. STUDY DESIGN: We reviewed records of patients diagnosed with PCa between 2013 and 2014 to identify management patterns in an untested cohort. From 2015 to 2016, these patients received GPS testing in a prospective study. Charts from 6 months post biopsy were reviewed for both cohorts to compare management received in the untested and tested cohorts. SUBJECTS: Men who just received their diagnosis and have National Comprehensive Cancer Network (NCCN) very low-, low-, and select cases of intermediate-risk PCa. RESULTS: Patient characteristics were generally similar in the untested and tested cohorts. AS utilization was 12% higher in the tested cohort compared with the untested cohort. In men younger than 60 years, utilization of AS in tested men was 33% higher than in untested men. AS in tested men was higher across all NCCN risk groups and races, particular in low-risk men (72% vs 90% for untested vs tested, respectively). Tested veterans exposed to AO received less AS than untested veterans. Tested nonexposed veterans received 19% more AS than untested veterans. Median GPS results did not significantly differ as a factor of race or AO exposure. CONCLUSIONS: Men who receive GPS testing are more likely to utilize AS within the year post diagnosis, regardless of age, race, and NCCN risk group. Median GPS was similar across racial groups and AO exposure groups, suggesting similar biology across these groups. The GPS assay may be a useful tool to refine risk assessment of PCa and increase rates of AS among clinically and biologically low-risk patients, which is in line with guideline-based care.

A Biopsy-based 17-gene Genomic Prostate Score as a Predictor of Metastases and Prostate Cancer Death in Surgically Treated Men with Clinically Localized Disease.

BACKGROUND: A 17-gene biopsy-based reverse transcription polymerase chain reaction assay, which provides a Genomic Prostate Score (GPS-scale 0-100), has been validated as an independent predictor of adverse pathology and biochemical recurrence after radical prostatectomy (RP) in men with low- and intermediate-risk prostate cancer (PCa). OBJECTIVE: To evaluate GPS as a predictor of PCa metastasis and PCa-specific death (PCD) in a large cohort of men with localized PCa and long-term follow-up. DESIGN, SETTING, AND PARTICIPANTS: A retrospective study using a stratified cohort sampling design was performed in a cohort of men treated with RP within Kaiser Permanente Northern California. RNA from archival diagnostic biopsies was assayed to generate GPS results. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We assessed the association between GPS and time to metastasis and PCD in prespecified uni- and multivariable statistical analyses, based on Cox proportional hazard models accounting for sampling weights. RESULTS AND LIMITATIONS: The final study population consisted of 279 men with low-, intermediate-, and high-risk PCa between 1995 and 2010 (median follow-up 9.8 yr), and included 64 PCD and 79 metastases. Valid GPS results were obtained for 259 (93%). In univariable analysis, GPS was strongly associated with time to PCD, hazard ratio (HR)/20 GPS units=3.23 (95% confidence interval [CI] 1.84-5.65; p<0.001), and time to metastasis, HR/20 units=2.75 (95% CI 1.63-4.63; p<0.001). The association between GPS and both end points remained significant after adjusting for National Comprehensive Cancer Network, American Urological Association, and Cancer of the Prostate Risk Assessment (CAPRA) risks (p<0.001). No patient with low- or intermediate-risk disease and a GPS of<20 developed metastases or PCD (n=31). In receiver operating characteristic analysis of PCD at 10 yr, GPS improved the c-statistic from 0.78 (CAPRA alone) to 0.84 (GPS+CAPRA; p<0.001). A limitation of the study was that patients were treated during an era when definitive treatment was standard of care with little adoption of active surveillance. CONCLUSIONS: GPS is a strong independent predictor of long-term outcomes in clinically localized PCa in men treated with RP and may improve risk stratification for men with newly diagnosed disease. PATIENT SUMMARY: Many prostate cancers are slow growing and unlikely to spread or threaten a man's life, while others are more aggressive and require treatment. Increasingly, doctors are using new molecular tests, such as the17-gene Genomic Prostate Score (GPS), which can be performed at the time of initial diagnosis to help determine how aggressive a given patient's cancer may be. In this study, performed in a large community-based healthcare network, GPS was shown to be a strong predictor as to whether a man's prostate cancer will spread and threaten his life after surgery, providing information that may help patients and their doctors decide on the best course of management of their disease.

Association between a 17-gene genomic prostate score and multi-parametric prostate MRI in men with low and intermediate risk prostate cancer (PCa).

BACKGROUND: We aimed to directly compare results from multi-parametric prostate MRI (mpMRI) and a biopsy-based 17-gene RT-PCR assay providing a Genomic Prostate Score (GPS) among individuals who were candidates for active surveillance with low and intermediate risk prostate cancer (PCa). PATIENTS AND METHODS: We evaluated the association between GPS results (scale 0-100) and endorectal mpMRI findings in men with clinically localized PCa. MR studies were reviewed to a five-tier scale of increasing suspicion of malignancy. Mean apparent diffusion coefficient (ADC) was calculated from a single dominant lesion. Mean rank of the GPS (0-100) among MRI strata was compared with the Kruskal-Wallis test and Dunn's multiple comparison test. Spearman's correlation was performed to examine the association between mean ADC and scaled GPS. RESULTS: Of 186 patients who received GPS testing, 100 were identified who received mpMRI. Mean GPS results differed between mpMRI categories (p = 0.001); however a broad range was observed in all mpMRI categories. Among men with biopsy Gleason pattern 3+3, mean GPS results were not significantly different among MRI groups (p = 0.179), but GPS differences were seen among MRI categories for patients with pattern 3+4 (p = 0.010). Mean ADC was weakly associated with GPS (σ = -0.151). Stromal response (p = 0.015) and cellular organization (p = 0.045) gene group scores differed significantly by MRI findings, but no differences were seen among androgen signaling or proliferation genes. CONCLUSIONS: Although a statistically significant association was observed between GPS results and MRI scores, a wide range of GPS values were observed across imaging categories suggesting that mpMRI and genomic profiling may offer non- overlapping clinical insights.

Identifying Health Information Technology Needs of Oncologists to Facilitate the Adoption of Genomic Medicine: Recommendations From the 2016 American Society of Clinical Oncology Omics and Precision Oncology Workshop.

At the ASCO Data Standards and Interoperability Summit held in May 2016, it was unanimously decided that four areas of current oncology clinical practice have serious, unmet health information technology needs. The following areas of need were identified: 1) omics and precision oncology, 2) advancing interoperability, 3) patient engagement, and 4) value-based oncology. To begin to address these issues, ASCO convened two complementary workshops: the Omics and Precision Oncology Workshop in October 2016 and the Advancing Interoperability Workshop in December 2016. A common goal was to address the complexity, enormity, and rapidly changing nature of genomic information, which existing electronic health records are ill equipped to manage. The subject matter experts invited to the Omics and Precision Oncology Workgroup were tasked with the responsibility of determining a specific, limited need that could be addressed by a software application (app) in the short-term future, using currently available genomic knowledge bases. Hence, the scope of this workshop was to determine the basic functionality of one app that could serve as a test case for app development. The goal of the second workshop, described separately, was to identify the specifications for such an app. This approach was chosen both to facilitate the development of a useful app and to help ASCO and oncologists better understand the mechanics, difficulties, and gaps in genomic clinical decision support tool development. In this article, we discuss the key challenges and recommendations identified by the workshop participants. Our hope is to narrow the gap between the practicing oncologist and ongoing national efforts to provide precision oncology and value-based care to cancer patients.

Use of a 17-Gene Prognostic Assay in Contemporary Urologic Practice: Results of an Interim Analysis in an Observational Cohort.

OBJECTIVE: To study the impact of genomic testing in shared decision making for men with clinically low-risk prostate cancer (PCa). MATERIALS AND METHODS: Patients with clinically low-risk PCa were enrolled in a prospective, multi-institutional study of a validated 17-gene tissue-based reverse transcription polymerase chain reaction assay (Genomic Prostate Score [GPS]). In this paper we report on outcomes in the first 297 patients enrolled in the study with valid 17-gene assay results and decision-change data. The primary end points were shared decision on initial management and persistence on active surveillance (AS) at 1 year post diagnosis. AS utilization and persistence were compared with similar end points in a group of patients who did not have genomic testing (baseline cohort). Secondary end points included perceived utility of the assay and patient decisional conflict before and after testing. RESULTS: One-year results were available on 258 patients. Shift between initial recommendation and shared decision occurred in 23% of patients. Utilization of AS was higher in the GPS-tested cohort than in the untested baseline cohort (62% vs 40%). The proportion of men who selected and persisted on AS at 1 year was 55% and 34% in the GPS and baseline cohorts, respectively. Physicians reported that GPS was useful in 90% of cases. Mean decisional conflict scores declined in patients after GPS testing. CONCLUSION: Patients who received GPS testing were more likely to select and persist on AS for initial management compared with a matched baseline group. These data indicate that GPS help guide shared decisions in clinically low-risk PCa.

Active Surveillance Use Among a Low-risk Prostate Cancer Population in a Large US Payer System: 17-Gene Genomic Prostate Score Versus Other Risk Stratification Methods.

Many men with low-risk prostate cancer (PCa) receive definitive treatment despite recommendations that have been informed by two large, randomized trials encouraging active surveillance (AS). We conducted a retrospective cohort study using the Optum™ Research Database (Eden Prairie, MN) of electronic health records and administrative claims data to assess AS use for patients tested with a 17-gene Genomic Prostate Score™ (GPS; Genomic Health, Redwood City, CA) assay and/or prostate magnetic resonance imaging (MRI). De-identified records were extracted on health plan members enrolled from June 2013 to June 2016 who had ≥1 record of PCa (n 5 291,876). Inclusion criteria included age ≥18 years, new diagnosis, American Urological Association low-risk PCa (stage T1-T2a, prostate-specific antigen ≤10 ng/mL, Gleason score 5 6), and clinical activity for at least 12 months before and after diagnosis. Data included baseline characteristics, use of GPS testing and/or MRI, and definitive procedures. GPS or MRI testing was performed in 17% of men (GPS, n 5 375, 4%; MRI, n 5 1174, 13%). AS use varied from a low of 43% for men who only underwent MRI to 89% for GPStested men who did not undergo MRI (P <.001). At 6-month follow-up, AS use was 31.0% higher (95% CI, 27.6%-34.5%; P <.001) for men receiving the GPS test only versus men who did not undergo GPS testing or MRI; the difference was 30.5% at 12-month follow-up. In a large US payer system, the GPS assay was associated with significantly higher AS use at 6 and 12 months compared with men who had MRI only, or no GPS or MRI testing.

Health Economic Impact and Prospective Clinical Utility of Oncotype DX® Genomic Prostate Score.

Prostate cancer (CaP) will be diagnosed in approximately 181,000 American men in 2016. Despite the high number of deaths from CaP in the United States, the disease has a protracted natural history and many men diagnosed with CaP will not die of the disease regardless of treatment. Unfortunately, identification of men with truly indolent/ nonaggressive CaP is challenging; limitations of conventional diagnostic modalities diminish the ability of physicians to accurately stage every case of CaP based on biopsy results alone. The resulting uncertainty in prognosis may prompt men with low-risk CaP to proceed to morbid and expensive treatments for an unclear survival benefit. Incorporation of the Genomic Prostate Score (GPS) as part of the decision algorithm for patients with National Comprehensive Cancer Network very low-risk and low-risk cancer led to a substantial increase in uptake of active surveillance and substantial cost savings. GPS provides physicians and patients with an additional tool in assessing personalized risk and helps guide individual decision making.

Pharmacogenetic Discovery in CALGB (Alliance) 90401 and Mechanistic Validation of a VAC14 Polymorphism that Increases Risk of Docetaxel-Induced Neuropathy.

PURPOSE: Discovery of SNPs that predict a patient's risk of docetaxel-induced neuropathy would enable treatment individualization to maximize efficacy and avoid unnecessary toxicity. The objectives of this analysis were to discover SNPs associated with docetaxel-induced neuropathy and mechanistically validate these associations in preclinical models of drug-induced neuropathy. EXPERIMENTAL DESIGN: A genome-wide association study was conducted in metastatic castrate-resistant prostate cancer patients treated with docetaxel, prednisone and randomized to bevacizumab or placebo on CALGB 90401. SNPs were genotyped on the Illumina HumanHap610-Quad platform followed by rigorous quality control. The inference was conducted on the cumulative dose at occurrence of grade 3+ sensory neuropathy using a cause-specific hazard model that accounted for early treatment discontinuation. Genes with SNPs significantly associated with neuropathy were knocked down in cellular and mouse models of drug-induced neuropathy. RESULTS: A total of 498,081 SNPs were analyzed in 623 Caucasian patients, 50 (8%) of whom experienced grade 3+ neuropathy. The 1,000 SNPs most associated with neuropathy clustered in relevant pathways including neuropathic pain and axonal guidance. An SNP in VAC14 (rs875858) surpassed genome-wide significance (P = 2.12 × 10-8, adjusted P = 5.88 × 10-7). siRNA knockdown of VAC14 in stem cell-derived peripheral neuronal cells increased docetaxel sensitivity as measured by decreased neurite processes (P = 0.0015) and branches (P < 0.0001). Prior to docetaxel treatment, VAC14 heterozygous mice had greater nociceptive sensitivity than wild-type litter mate controls (P = 0.001). CONCLUSIONS: VAC14 should be prioritized for further validation of its potential role as a predictor of docetaxel-induced neuropathy and biomarker for treatment individualization. Clin Cancer Res; 22(19); 4890-900. ©2016 AACR.

Gene expression in normal-appearing tissue adjacent to prostate cancers are predictive of clinical outcome: evidence for a biologically meaningful field effect.

PURPOSE: We evaluated gene expression in histologically normal-appearing tissue (NT) adjacent to prostate tumor in radical prostatectomy specimens, assessing for biological significance based on prediction of clinical recurrence (cR - metastatic disease or local recurrence). RESULTS: A total of 410 evaluable patients had paired tumor and NT. Forty-six genes, representing diverse biological pathways (androgen signaling, stromal response, stress response, cellular organization, proliferation, cell adhesion, and chromatin remodeling) were associated with cR in NT (FDR < 20%), of which 39 concordantly predicted cR in tumor (FDR < 20%). Overall GPS and its stromal response and androgen-signaling gene group components also significantly predicted time to cR in NT (RM-corrected HR/20 units = 1.25; 95% CI: 1.01-1.56; P = 0.024). EXPERIMENTAL DESIGN: Expression of 732 genes was measured by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) separately in tumor and adjacent NT specimens from 127 patients with and 374 without cR following radical prostatectomy for T1/T2 prostate cancer. A 17-gene expression signature (Genomic Prostate Score [GPS]), previously validated to predict aggressive prostate cancer when measured in tumor tissue, was also assessed using pre-specified genes and algorithms. Analysis used Cox proportional hazards models, Storey's false discovery rate (FDR) control, and regression to the mean (RM) correction. CONCLUSIONS: Gene expression profiles, including GPS, from NT adjacent to tumor can predict prostate cancer outcome. These findings suggest that there is a biologically significant field effect in primary prostate cancer that is a marker for aggressive disease.

Patient-specific Meta-analysis of 2 Clinical Validation Studies to Predict Pathologic Outcomes in Prostate Cancer Using the 17-Gene Genomic Prostate Score.

OBJECTIVE: To perform patient-specific meta-analysis (MA) of two independent clinical validation studies of a 17-gene biopsy-based genomic assay as a predictor of favorable pathology at radical prostatectomy. MATERIALS AND METHODS: Patient-specific MA was performed on data from 2 studies (732 patients) using the Genomic Prostate Score (GPS; scale 0-100) together with Cancer of the Prostate Risk Assessment (CAPRA) score or National Comprehensive Cancer Network (NCCN) risk group as predictors of the likelihood of favorable pathology (LFP). Risk profile curves associating GPS with LFP by CAPRA score and NCCN risk group were generated. Decision curves and receiver operating characteristic curves were calculated using patient-specific MA risk estimates. RESULTS: Patient-specific MA-generated risk profiles ensure more precise estimates of LFP with narrower confidence intervals than either study alone. GPS added significant predictive value to each clinical classifier. A model utilizing GPS and CAPRA provided the most risk discrimination. In decision-curve analysis, greater net benefit was shown when combining GPS with each clinical classifier compared with the classifier alone. The area under the receiver operating characteristic curve improved from 0.68 to 0.73 by adding GPS to CAPRA, and 0.64 to 0.70 by adding GPS to NCCN risk group. The proportion of patients with LFP >80% increased from 11% using NCCN risk group alone to 23% using GPS with NCCN. Using GPS with CAPRA identified the highest proportion-31%-of patients with LFP >80%. CONCLUSION: Patient-specific MA provides more precise risk estimates that reflect the complete body of evidence. GPS adds predictive value to 3 widely used clinical classifiers, and identifies a larger proportion of low-risk patients than identified by clinical risk group alone.

A Biopsy-based 17-gene Genomic Prostate Score Predicts Recurrence After Radical Prostatectomy and Adverse Surgical Pathology in a Racially Diverse Population of Men with Clinically Low- and Intermediate-risk Prostate Cancer.

BACKGROUND: Biomarkers that are validated in independent cohorts are needed to improve risk assessment for prostate cancer (PCa). OBJECTIVE: A racially diverse cohort of men (20% African American [AA]) was used to evaluate the association of the clinically validated 17-gene Genomic Prostate Score (GPS) with recurrence after radical prostatectomy and adverse pathology (AP) at surgery. DESIGN, SETTING, AND PARTICIPANTS: Biopsies from 431 men treated for National Comprehensive Cancer Network (NCCN) very low-, low-, or intermediate-risk PCa between 1990 and 2011 at two US military medical centers were tested to validate the association between GPS and biochemical recurrence (BCR) and to confirm the association with AP. Metastatic recurrence (MR) was also evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Cox proportional hazards models were used for BCR and MR, and logistic regression was used for AP. Central pathology review was performed by one uropathologist. AP was defined as primary Gleason pattern 4 or any pattern 5 and/or pT3 disease. RESULTS AND LIMITATIONS: GPS results (scale: 0-100) were obtained in 402 cases (93%); 62 men (15%) experienced BCR, 5 developed metastases, and 163 had AP. Median follow-up was 5.2 yr. GPS predicted time to BCR in univariable analysis (hazard ratio per 20 GPS units [HR/20 units]: 2.9; p<0.001) and after adjusting for NCCN risk group (HR/20 units: 2.7; p<0.001). GPS also predicted time to metastases (HR/20 units: 3.8; p=0.032), although the event rate was low (n=5). GPS was strongly associated with AP (odds ratio per 20 GPS units: 3.3; p<0.001), adjusted for NCCN risk group. In AA and Caucasian men, the median GPS was 30.3 for both, the distributions of GPS results were similar, and GPS was similarly predictive of outcome. CONCLUSIONS: The association of GPS with near- and long-term clinical end points establishes the assay as a strong independent measure of PCa aggressiveness. Tumor aggressiveness, as measured by GPS, and outcomes were similar in AA and Caucasian men in this equal-access health care system. PATIENT SUMMARY: Predicting outcomes in men with newly diagnosed prostate cancer is challenging. This study demonstrates that a new molecular test, the Genomic Prostate Score, which can be performed on a patient's original prostate needle biopsy, can predict the aggressiveness of the cancer and help men make decisions regarding the need for immediate treatment of their cancer.