Proteogenomics Reveals Perturbed Signaling Networks in Malignant Melanoma Cells Resistant to BRAF Inhibition

Marisa Schmitt1, Tobias Sinnberg2, Katrin Bratl1

  • 1Quantitative Proteomics, University of Tuebingen, Tuebingen, Germany.

Insights

Proteogenomics reveals how genetic variants drive cancer drug resistance and alter cell signaling. AURKA inhibition effectively targets BRAFi-resistant melanoma, while RUNX1 variants impact protein interactions.

Area of Science:

  • Proteogenomics
  • Cancer Medicine
  • Molecular Biology

Background:

  • Nucleotide variants in protein-coding regions significantly impact cancer etiology.
  • Proteogenomics allows analysis of nonsynonymous variants at proteome and phosphoproteome levels.
  • Understanding drug resistance mechanisms is crucial for effective cancer therapy.

Purpose of the Study:

  • To develop and apply a proteogenomics workflow to study BRAFi resistance in malignant melanoma (A375 cells).
  • To identify oncogenic variants and signaling pathway alterations in drug-resistant cells.
  • To investigate variant-driven posttranslational modification (PTM) changes and their impact on cell signaling.

Main Methods:

  • Proteogenomics workflow development and application to A375 melanoma cell line.
  • Mass spectrometry (MS) for proteome and phosphoproteome analysis.
  • Multiomic integrated signaling network reconstruction and drug target prediction.

Main Results:

  • Identified gain-of-function AURKA (F31I) variant contributing to BRAFi resistance.
  • Detected MAPK pathway reactivation in BRAFi-resistant A375 cells.
  • Demonstrated AURKA inhibition efficacy against BRAFi-resistant cells.
  • Confirmed variant-driven PTM changes in 12 proteins, including RUNX1 S276L variant affecting its interactome.

Conclusions:

  • Proteogenomics is a powerful approach for dissecting complex cancer mechanisms.
  • AURKA inhibition represents a potential therapeutic strategy for BRAFi-resistant melanoma.
  • Amino acid variants can significantly alter protein function and signaling networks, independent of drug resistance.

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