Integrative Pan-Cancer Genomic and Transcriptomic Analyses of Refractory Metastatic Cancer

Yoann Pradat1, Julien Viot2,3, Andrey A Yurchenko4

  • 1Université Paris-Saclay, CentraleSupélec, MICS lab, Gif-Sur-Yvette, France.

Cancer Discovery
|March 2, 2023
PubMed

Insights

Most cancer treatment resistance mechanisms remain unknown. This study analyzed refractory tumors, finding few validated markers but identifying promising investigational ones for future cancer treatment strategies.

Area of Science:

  • Oncology
  • Genomics
  • Translational Research

Background:

  • Metastatic relapse is the primary cause of cancer mortality.
  • Existing knowledge gaps exist regarding cancer treatment resistance mechanisms.
  • The META-PRISM cohort provides a valuable resource for studying refractory metastatic tumors.

Purpose of the Study:

  • To identify known and novel cancer treatment resistance mechanisms.
  • To investigate the utility of molecular markers for survival prediction in advanced cancers.
  • To validate the META-PRISM cohort for resistance mechanism research.

Main Methods:

  • Analysis of a pan-cancer cohort (META-PRISM) of 1,031 refractory metastatic tumors.
  • Whole-exome and transcriptome sequencing of tumor samples.
  • Comparison of genomic profiles between treated and untreated tumors.

Main Results:

  • Refractory tumors, especially prostate, bladder, and pancreatic, showed highly transformed genomes.
  • Standard-of-care resistance biomarkers were found in only 9.6% of tumors, highlighting a clinical validation gap.
  • Investigational and hypothetical resistance mechanisms were enriched in treated patients, suggesting their role in resistance.
  • Molecular markers improved 6-month survival prediction, particularly in advanced breast cancer.

Conclusions:

  • There is a significant lack of validated biomarkers for cancer treatment resistance.
  • Investigational and hypothetical markers show promise for understanding and overcoming treatment resistance.
  • Molecular profiling is crucial for improving survival prediction and guiding clinical trial eligibility in advanced cancers.