Tissue proteome signatures associated with five grades of prostate cancer and benign prostatic hyperplasia

Rebeca Kawahara, Saulo Recuero, Fabio C. S. Nogueira, Gilberto B. Domont, Katia R. M. Leite, Miguel Srougi, Morten Thaysen-Andersen*, Giuseppe Palmisano

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The histology-based Gleason score (GS) of prostate cancer (PCa) tissue biopsy is the most accurate predictor of disease aggressiveness and an important measure to guide treatment strategies and patient management. The variability associated with PCa tumor sampling and the subjective determination of the GS are challenges that limit accurate diagnostication and prognostication. Thus, novel molecular signatures are needed to distinguish between indolent and aggressive forms of PCa for better patient management and outcomes. Herein, label-free LC-MS/MS proteomics is used to profile the proteome of 50 PCa tissues spanning five grade groups (= 10 per group) relative to tissues from individuals with benign prostatic hyperplasia (BPH). Over 2000 proteins are identified albeit at different levels between and within the patient groups, revealing biological processes associated with specific grades. A panel of 11 prostate-derived proteins including IGKV3D-20, RNASET2, TACC2, ANXA7, LMOD1, PRCP, GYG1, NDUFV1, H1FX, APOBEC3C, and CTSZ display the potential to stratify patients from low and high PCa grade groups. Parallel reaction monitoring of the same sample cohort validate the differential expression of LMOD1, GYG1, IGKV3D-20, and RNASET2. The four proteins associated with low and high PCa grades reported here warrant further exploration as candidate biomarkers for PCa aggressiveness.

Original languageEnglish
Article number1900174
Pages (from-to)1-12
Number of pages12
JournalProteomics
Volume19
Issue number21-22
DOIs
Publication statusPublished - Nov 2019

Keywords

  • biomarkers
  • gleason score
  • mass spectrometry
  • prostate cancer
  • proteome
  • proteomics

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