American Association for Cancer Research
Browse

Data from Thermal Proteome Profiling Identifies Oxidative-Dependent Inhibition of the Transcription of Major Oncogenes as a New Therapeutic Mechanism for Select Anticancer Compounds

Posted on 2023-03-31 - 03:23
Abstract

Identification of the molecular mechanism of action (MoA) of bioactive compounds is a crucial step for drug development but remains a challenging task despite recent advances in technology. In this study, we applied multidimensional proteomics, sensitivity correlation analysis, and transcriptomics to identify a common MoA for the anticancer compounds RITA, aminoflavone (AF), and oncrasin-1 (Onc-1). Global thermal proteome profiling revealed that the three compounds target mRNA processing and transcription, thereby attacking a cancer vulnerability, transcriptional addiction. This led to the preferential loss of expression of oncogenes involved in PDGF, EGFR, VEGF, insulin/IGF/MAPKK, FGF, Hedgehog, TGFβ, and PI3K signaling pathways. Increased reactive oxygen species level in cancer cells was a prerequisite for targeting the mRNA transcription machinery, thus conferring cancer selectivity to these compounds. Furthermore, DNA repair factors involved in homologous recombination were among the most prominently repressed proteins. In cancer patient samples, RITA, AF, and Onc-1 sensitized to poly(ADP-ribose) polymerase inhibitors both in vitro and ex vivo. These findings might pave a way for new synthetic lethal combination therapies.

Significance: These findings highlight agents that target transcriptional addiction in cancer cells and suggest combination treatments that target RNA processing and DNA repair pathways simultaneously as effective cancer therapies.

CITE THIS COLLECTION

DataCite
No result found
or
Select your citation style and then place your mouse over the citation text to select it.

SHARE

email

Usage metrics

Cancer Research

AUTHORS (20)

  • Sylvain Peuget
    Jiawei Zhu
    Gema Sanz
    Madhurendra Singh
    Massimiliano Gaetani
    Xinsong Chen
    Yao Shi
    Amir Ata Saei
    Torkild Visnes
    Mikael S. Lindström
    Ali Rihani
    Lidia Moyano-Galceran
    Joseph W. Carlson
    Elisabet Hjerpe
    Ulrika Joneborg
    Kaisa Lehti
    Johan Hartman
    Thomas Helleday
    Roman Zubarev
    Galina Selivanova
need help?