A reliable transcriptomic risk-score applicable to FFPE biopsies improves outcome prediction in localized prostate cancer

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. Researchers at the Fraunhofer Institute for Cell Therapy and Immunology 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 the researchers 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.

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, the researchers 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, they 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.

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. The researchers 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. They 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.

Analysis workflow

A Overview of the included tissue samples we used to develop the ProstaTrend-ffpe signature. Shown are the number of patients included in the study and reasons for exclusion. For 185 patients, we performed a strand-specific transcriptome-wide sequencing from FFPE biopsy tissue. A total of six samples did not meet the quality criteria for RNA-Seq data. In addition, we excluded three samples due to missing clinical follow-up data. The final cohort included 176 patients, for 75 of whom BCR was observed within the follow-up time. FFPE formalin-fixed paraffin-embedded, PCa prostate cancer, DoD death of disease, BCR biochemical recurrence. B For the development of the PCa single-cell atlas, we used scRNA-Seq data of PCa patients from 5 publicly available studies. Spatial transcriptomics data of a human PCa biopsy (GS = 3 + 4) were downloaded from the 10× Genomics database. C The prognostic value of the Transcriptomic Risk Scores (TRS) using ProstaTrend(-ffpe) was evaluated by survival analyses in 9 publicly available cohorts and a meta-analysis with a total of 13 cohorts

Availability – An interactive version of the results of this study can be accessed at https://bioinf.izi.fraunhofer.de/prostatrend/.