PITX1 Is a Regulator of TERT Expression in Prostate Cancer with Prognostic Power

  • Alexandra M Poos
  • Cornelia Schroeder
  • Neeraja Jaishankar
  • Daniela Röll
  • Marcus Oswald
  • Jan Meiners
  • Delia M Braun
  • Caroline Knotz
  • Lukas Frank
  • Manuel Gunkel
  • Roman Spilger
  • Thomas Wollmann
  • Adam Polonski
  • Georgia Makrypidi-Fraune
  • Christoph Fraune
  • Markus Graefen
  • Inn Chung
  • Alexander Stenzel
  • Holger Erfle
  • Karl Rohr
  • Aria Baniahmad
  • Guido Sauter
  • Karsten Rippe
  • Ronald Simon (Shared last author)
  • Rainer Koenig (Shared last author)

Related Research units

Abstract

The current risk stratification in prostate cancer (PCa) is frequently insufficient to adequately predict disease development and outcome. One hallmark of cancer is telomere maintenance. For telomere maintenance, PCa cells exclusively employ telomerase, making it essential for this cancer entity. However, TERT, the catalytic protein component of the reverse transcriptase telomerase, itself does not suit as a prognostic marker for prostate cancer as it is rather low expressed. We investigated if, instead of TERT, transcription factors regulating TERT may suit as prognostic markers. To identify transcription factors regulating TERT, we developed and applied a new gene regulatory modeling strategy to a comprehensive transcriptome dataset of 445 primary PCa. Six transcription factors were predicted as TERT regulators, and most prominently, the developmental morphogenic factor PITX1. PITX1 expression positively correlated with telomere staining intensity in PCa tumor samples. Functional assays and chromatin immune-precipitation showed that PITX1 activates TERT expression in PCa cells. Clinically, we observed that PITX1 is an excellent prognostic marker, as concluded from an analysis of more than 15,000 PCa samples. PITX1 expression in tumor samples associated with (i) increased Ki67 expression indicating increased tumor growth, (ii) a worse prognosis, and (iii) correlated with telomere length.

Bibliographical data

Original languageEnglish
Article number1267
ISSN2072-6694
DOIs
Publication statusPublished - 01.03.2022
PubMed 35267575