Proteogenomic insights suggest druggable pathways in endometrial carcinoma

Cancer Cell. 2023 Sep 11;41(9):1586-1605.e15. doi: 10.1016/j.ccell.2023.07.007. Epub 2023 Aug 10.


We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Keywords: CPTAC; CTNNB1; PIK3R1; deep learning; endometrial cancer; metformin; proteogenomics; target assays.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Endometrial Neoplasms* / drug therapy
  • Endometrial Neoplasms* / genetics
  • Endometrial Neoplasms* / metabolism
  • Female
  • Humans
  • Metformin* / pharmacology
  • Prospective Studies
  • Proteogenomics*
  • Proto-Oncogene Proteins c-akt / genetics
  • beta Catenin / genetics
  • beta Catenin / metabolism


  • Proto-Oncogene Proteins c-akt
  • beta Catenin
  • Metformin