A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

Klein, Eric A.; Cooperberg, Matthew R.; Magi‐Galluzzi, Cristina; Simko, Jeffry P.; Falzarano, Sara M.; Maddala, Tara; Chan, June M.; Li, Jianbo; Cowan, Janet E.; Tsiatis, Athanasios C.; Cherbavaz, Diana B.; Pelham, Robert J.; Tenggara-Hunter, Imelda; Baehner, Frederick L.; Knezevic, Dejan; Febbo, Phillip G.; Shak, Steven; Kattan, Michael W.; Lee, Mark; Carroll, Peter R.

doi:10.1016/j.eururo.2014.05.004

Cited by 567 publications

(541 citation statements)

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“…Both the 17‐gene Oncotype DX and the 31‐gene Prolaris improve risk stratification of patients with high risk of PC recurrence at time of diagnosis (Albala et al ., 2016; Cuzick et al ., 2011; Klein et al ., 2014; Knezevic et al ., 2013; Oderda et al ., 2017) and after radical prostatectomy (RP) (Cooperberg et al ., 2013; Cullen et al ., 2015). The 22‐gene Decipher predicts metastasis following RP (Erho et al ., 2013; Karnes et al ., 2013; Klein et al ., 2016).…”

Section: Introductionmentioning

confidence: 99%

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Jiang

Mei

et al. 2018

Molecular Oncology

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We report here numerous novel genes and multiple new signatures which robustly predict prostate cancer (PC) recurrence. We extracted 696 differentially expressed genes relative to a reported PC signature from the TCGA dataset (n = 492) and built a 15‐gene signature (SigMuc1NW) using Elastic‐net with 10‐fold cross‐validation through analyzing their expressions at 1.5 standard deviation/SD below and 2 SD above a population mean. SigMuc1NW predicts biochemical recurrence (BCR) following surgery with 56.4% sensitivity, 72.6% specificity, and 63.24 median months disease free (MMDF) (P = 1.12e‐12). The prediction accuracy is improved with the use of SigMuc1NW's cutpoint (P = 3e‐15) and is further enhanced (sensitivity 67%, specificity 75.7%, MMDF 45.2, P = 0) when all 15 genes were analyzed through their cutpoints instead of their SDs. These genes individually associate with BCR using either SD or cutpoint as the cutoff points. Eight of 15 genes are individual risk factors after adjusting for age at diagnosis, Gleason score, surgical margin, and tumor stage. Eleven of 15 genes are novel to PC. SigMuc1NW discriminates BCR with time‐dependent AUC (tAUC) values of 76.6% at 11.5 months (76.6%–11.5 m), 73.8%‐22.3 m, 78.5%‐32.1 m, and 76.4%–48.4 m. SigMuc1NW is correlated with adverse features of PC, high Gleason scores (odds ratio/OR 1.48, P < 2e‐16), and advanced tumor stages (OR 1.33, P = 4.37e‐13). SigMuc1NW remains an independent risk factor of BCR (HR 2.44, 95% CI 1.53–3.87, P = 1.62e‐4) after adjusting for age at diagnosis, Gleason score, surgical margin, and tumor stage. In an independent PC (MSKCC) cohort (n = 140), these 15 genes were altered in PC vs normal tissue, metastatic PCs vs primary PCs, and recurrent PCs vs nonrecurrent PCs. Importantly, a 10‐gene subsignature SigMuc1NW1 predicts BCR in MSKCC (P = 3.11e‐15) and TCGA (P = 3.13e‐12); SigMuc1NW1 discriminates BCR at 18.4 m with tAUC as 82.5%. Collectively, our analyses support SigMuc1NW as a novel and robust signature in predicting BCR of PC.

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Section: Introductionmentioning

confidence: 99%

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Jiang

Mei

et al. 2018

Molecular Oncology

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“…In an initial validation study, GPS from 395 men with low- to low intermediate-risk disease was incorporated with preoperative models including the Cancer of the Prostate Risk Assessment (CAPRA) score and National Comprehensive Cancer Network (NCCN) risk categories. 67 In both models, a 20-unit increase in GPS was associated with an approximate twofold increased odds of adverse pathology at prostatectomy (model with CAPRA: odds ratio [OR] 2.1; 95% CI, 1.4-3.2; model with NCCN risk classification: OR, 1.9; 95% CI, 1.3-2.8), defined as primary Gleason pattern 4, any Gleason pattern 5, or non organ-confined disease. In a subsequent study of 402 men with low to intermediate-risk disease, 68 a 20-point increase in GPS similarly conveyed a significant increase in risk of biochemical recurrence after treatment (hazard ratio [HR] 2.93; 95% CI, 2.03-4.15; p<0.001) over a median follow-up of 5.2 years; GPS was also an independent predictor of biochemical recurrence (BCR) in multivariable models with baseline clinical factors.…”

Section: Molecular Testing In Active Surveillancementioning

confidence: 99%

Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools

Tosoian¹,

Loeb²,

Epstein³

et al. 2016

American Society of Clinical Oncology Educational Book

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Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5 to 6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with significant morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.

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“…FFPE formalin-fixed paraffin-embedded, RP radical prostatectomy, BCR biochemical recurrence, MFS metastasis free survival, CCP cell cycle progression, CAPRA Cancer of the Prostate Risk Assessment, Bx biopsy, CSS cancer-specific survival, EBRT external beam radiation therapy, GS Gleason score and intermediate-clinical-risk disease-ostensibly candidates for AS-the GPS assay was examined for the prediction of adverse surgical pathology, defined as primary Gleason pattern 4 or higher, and/or non-organ confined disease (≥pT3a or lymph node positive) [39]. In a second recent study examining a cohort of 402 men, the GPS assay was independently associated with risk of BCR and metastatic progression (Table 2) [40].…”

Section: Mfsmentioning

confidence: 99%

“…DCA was performed to compare the net benefit of various decision schema to identify high-grade and/or high-stage disease composed of treatment of all patients, no patients, clinical risk alone (CAPRA score), or the combination of clinical risk and GPS derived from the clinical validation cohort of 395 patients [39]. In each scenario, combined clinical-GPS models generated higher net benefit across all threshold probabilities.…”

Section: Bcr Mfsmentioning

confidence: 99%

Clinical Utility of Biomarkers in Localized Prostate Cancer

2016

Self Cite

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A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emerging tests, with attention on studies addressing clinical utility.

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A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

Cited by 567 publications

References 50 publications

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools

Clinical Utility of Biomarkers in Localized Prostate Cancer

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