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Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top‐candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training). Using GLMnet, we trained a novel multimarker model (miMe) comprising nine miRNAs and three methylation markers that predicted postoperative biochemical recurrence (BCR) independently of the established clinicopathological CAPRA‐S nomogram in Cox multivariate regression analysis in Cohort 1 (HR [95% CI]: 1.53 [1.26–1.84], p < 0.001). This result was successfully validated in two independent RP cohorts (Cohort 2, n = 159: HR [95% CI]: 1.35 [1.06–1.73], p = 0.015. TCGA, n = 350: HR [95% CI]: 1.34 [1.01–1.77], p = 0.04). Notably, in CAPRA‐S low‐risk patients, a high miMe score was associated with >6 times higher risk of BCR, suggesting that miMe may help identify PC patients at high risk of progression despite favorable clinicopathological factors postsurgery. Finally, miMe was a significant predictor of cancer‐specific survival (p = 0.019, log‐rank test) in a merged analysis of 357 RP patients. In conclusion, we trained, tested and validated a novel 12‐marker panel (miMe) that showed significant independent prognostic value in three RP cohorts. In the future, combining miMe score with existing clinical nomograms may improve PC risk stratification and thus help guide treatment decisions. What's new? Although localized prostate cancer (PC) can be cured by radical prostatectomy (RP), both over‐ and under‐treatment remain a major clinical problem as currently available routine prognostic tools cannot accurately distinguish aggressive from non‐aggressive PCs at time of diagnosis. Here, the authors report a novel combined miRNA/methylation marker panel (miMe) for PC prognosis that was a significant independent predictor of post‐operative PC outcome in three large RP cohorts. The results suggest that miMe may help guide personalized treatment decisions in the future, e.g. by identifying high‐risk PC patients who might be candidates for intensified therapy. [ABSTRACT FROM AUTHOR]

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome. [Display omitted] • Development of a new classifier for DCIS recurrence or progression • Outcome-associated pathways identified across multiple data types and compartments • Four stroma-specific signatures identified • CNAs characterize DCIS subgroups associated with high-risk invasive cancers Strand et al. have performed a large, comprehensive study to generate a spatially resolved breast precancer atlas. They present a prognostic classifier that predicts both precancer recurrence and invasive progression, which may form the basis for a future clinical test to guide breast precancer treatment. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75–94%) and specificity (84–100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP; 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24–3.10), adjusted p = 0.016; multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also. [ABSTRACT FROM AUTHOR]