A System-wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells

Anna Ressa, Evert Bosdriesz, Joep de Ligt, Sara Mainardi, Gianluca Maddalo, Anirudh Prahallad, Myrthe Jager, Lisanne de la Fonteijne, Martin Fitzpatrick, Stijn Groten, A. F. Maarten Altelaar, Rene Bernards, Edwin Cuppen, Lodewyk Wessels, Albert J. R. Heck

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread up-regulation of receptor tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally compensating for the MAPK pathway inhibition.

Original languageEnglish
Pages (from-to)1892-1908
Number of pages17
JournalMolecular & Cellular Proteomics
Volume17
Issue number 10
DOIs
Publication statusPublished - Oct 2018

Keywords

  • BRAF(V600E)
  • Circuits
  • Colorectal cancer
  • Drug resistance
  • EGFR
  • PTPN11
  • Rintegrative analysis
  • Signaling
  • Systems biology
  • Transcription
  • multi-omics

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