A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.

BACKGROUND: Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics. METHODS: All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments. RESULTS: Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies. CONCLUSIONS: We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

New markers in prostate cancer: genomics / Nuevos marcadores en cáncer de próstata: Genómica

Prostate cancer (PCa) is a very heterogeneous disease with unknown outcome at the time of first diagnosis. Multiple clinicopathological parameters and modern imaging approaches are currently used to detect PCa and to assess the necessity of early or delayed treatment according to the predicted aggressiveness of the tumor. Despite regular adjustments of predictive systems based on histopathological factors such as the Gleason grading system or based on prostate MRI such as the Prostate Imaging Reporting and Data System (PIRADS) these tools for risk stratification of PCa patients still harbor significant limitations with regard to the accuracy of PCa outcome prediction. Therefore, great hopes have been placed on the use of biomolecular markers which might be more closely associated with the underlying biological characteristics of this tumor entity and able to predict the course of the disease better than clinical parameters. Such biomarkers are expected to serve as valuable tools not only to improve PCa diagnostics but also to enhance pre- and posttreatment risk stratification which could finally facilitate therapeutic decisions. In this review, current literature on genomic biomarkers used for PCa detection and early prediction of the tumor aggressiveness is examined. First, germline mutations and single nucleotide polymorphisms which might influence PCa onset are discussed in relation to the usefulness of targeted PCa screening approaches. Moreover, different urine- and tissue-based diagnostic tests assessing PCa-associated alterations on genetic, epigenetic and transcriptional level are reviewed. Most of these genomic biomarker assays were validated in large patient cohorts and their potential clinical usability could be proven. They provide useful diagnostic information to facilitate decisions with regard to screen men at risk to develop PCa or to repeat diagnostics in men with negative biopsy results, but persistent suspicion of cancer. Several assays can assist the early identification of patients with high-risk PCa, who potentially would need treatment, and may facilitate the selection of patients suitable for active surveillance. More evidence of the clinical usability of such genomic PCa detection assays has to be provided by further prospective studies to support the transferability of these new diagnostic approaches to daily clinical practice

El cáncer de próstata (CaP) es una enfermedad muy heterogénea con una evolución desconocida en el momento del primer diagnóstico. Actualmente se utilizan múltiples parámetros clínico-patológicos y abordajes radiológicos modernos para detectar el CaP y evaluar la necesidad de tratamiento temprano o diferido de acuerdo con la agresividad predecible del tumor. A pesar de los ajustes regulares de los sistemas predictivos basados en factores histopatológicos, como la escala de Gleason, o en la RMN prostática, como el PI-RADS (Prostate Imaging Reporting and Data System), estas herramientas de estratificación de riesgos del CaP todavía tienen importantes limitaciones con respecto a la precisión de predicción de la evolución del CaP. Por lo tanto, se han depositado grandes esperanzas en el uso de marcadores biomoleculares, los cuales podrían estar más íntimamente relacionados con las características biológicas subyacentes de esta entidad tumoral y serían capaces de predecir el curso de la enfermedad mejor que los parámetros clínicos. Se espera que dichos biomarcadores sirvan como valiosas herramientas no sólo para mejorar el diagnóstico de CaP sino también mejorar la estratificación de riesgos pre- y post-tratamiento lo que podría facilitar las decisiones terapéuticas. En esta revisión, examinamos la literatura actual sobre biomarcadores genómicos utilizados para la detección del CaP y la predicción temprana de la agresividad tumoral. Primero, se discuten las mutaciones de líneasgerminales y polimorfismos de un único nucleótido que podrían influenciar el inicio del CaP en relación con la utilidad de abordajes de cribado de CaP dirigidos. Además, se revisan diferentes pruebas diagnósticas en orina y tejidos que evalúan las alteraciones al nivel genético, epigenético y transcripcional asociadas con CaP. La mayoría de estas pruebas de biomarcadores genéticos fueron validadas en grandes cohortes de pacientes y su potencial usabilidad clínica puede probarse. Suministran información diagnóstica útil para facilitar las decisiones en relación con el cribado de varones en riesgo de desarrollar CaP o repetir pruebas diagnósticas en varones con biopsia negativa y sospecha persistente de cáncer. Varios tests pueden asistir en la identificación temprana de pacientes con CaP de alto riesgo, que potencialmente necesitarían tratamiento, y pueden facilitar la selección de pacientes adecuados para vigilancia activa. Para apoyar la transferibilidad de estos nuevos abordajes diagnósticos a la práctica es necesaria más evidencia sobre la utilidad clínica de dichas pruebas de detección genómica de CaP mediante nuevos estudios prospectivos