Pancancer modelling predicts the context-specific impact of somatic mutations on transcriptional programs

Hatice U Osmanbeyoglu1, Eneda Toska2, Carmen Chan2

  • 1Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box No. 460, New York, New York 10065, USA.

Nature Communications
|February 1, 2017
PubMed

Insights

Piecemeal cancer therapies targeting specific gene mutations may not work across all cancer types. This study reveals how the same mutation affects gene activity differently in various cancers, impacting targeted treatment strategies.

Area of Science:

  • Genomics
  • Cancer Biology
  • Computational Biology

Background:

  • Pancancer studies identify frequently altered genes, suggesting broad applicability of pathway-targeted therapies.
  • However, the impact of 'actionable mutations' varies context-specifically across different tumor types and genetic backgrounds.

Purpose of the Study:

  • To computationally integrate proteomic and mRNA sequencing data across 12 TCGA datasets.
  • To interpret the context-specific impact of somatic alterations on functional signatures, including protein and transcription factor activities.

Main Methods:

  • Applied a computational strategy to integrate parallel (phospho)proteomic and mRNA sequencing data.
  • Analyzed 12 The Cancer Genome Atlas (TCGA) tumor datasets.
  • Interpreted somatic alteration impacts using functional signatures like (phospho)protein and transcription factor (TF) activities.

Main Results:

  • Predicted distinct dysregulated transcriptional regulators downstream of somatic alterations in different cancers.
  • Validated context-specific differential TF activity associated with mutant PIK3CA in isogenic cancer cell line models.

Conclusions:

  • Somatic alterations have context-specific impacts on gene regulatory programs and signaling networks.
  • Findings have implications for the pancancer use of targeted drugs and combination therapy design.

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