Signalomics for molecular tumor boards and precision oncology of breast and gynecological cancers

  • Tatiana V. Denisenko
  • , Anna E. Ivanova
  • , Alexey Koval
  • , Denis N. Silachev
  • , Lee Jia
  • , Gennadiy T. Sukhikh
  • , Vladimir L. Katanaev*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Precision oncology led to the establishment and widespread application of molecular tumor boards (MTBs)—multidisciplinary units combining molecular and clinical assessment of individual cancer cases for swift selection of personalized treatments. Whole-exome or gene panel sequencing, combined with transcriptomic, immunohistochemical, and other molecular analyses, often permits dissection of molecular drivers of a tumor and identification of its potential targetable vulnerabilities, instructing clinical oncologists on sometimes unconventional treatment options. However, cancer drivers are often unleashed mutation-independently, especially in breast and gynecological cancers, and deleterious mutations are not always pathogenic. To complement the MTB arsenal, we chart here the molecular toolset we call Signalomics that permits fast and robust assessment of a panel of oncogenic signaling pathways in fresh tumor samples. Using transcriptional reporters introduced in primary tumor cells, this approach identifies the pathways overactivated in a given tumor and validates their sensitivity to targeted therapies, providing actionable insights for personalized treatment strategies. Integration of Signalomics into MTB workflows bridges the gap between molecular profiling and functional pathway analysis, refining clinical treatment decisions and advancing precision oncology.

Original languageEnglish
Pages (from-to)952-959
Number of pages8
JournalMolecular Systems Biology
Volume21
Issue number8
Early online dateJun 2025
DOIs
Publication statusPublished - 4 Aug 2025

Keywords

  • Breast and Gynecological Cancers
  • Molecular Tumor Board
  • Oncogenic Signaling Pathways
  • Precision Oncology
  • Signalomics

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