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Toward Pathway-and Pancancer-Guided Interpretation of an Individual’s Cancer Genome

Talkat Computational Cancer Biology 2016 · 2016-02-01..02-05
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slides:none on file

Reference maps from a pan-cancer atlas (11,000 samples, 33 tumor types) place individual tumors by molecular phenotype, flag ~20–25% of cases that cross tissue boundaries, and guide treatment hypotheses; a pediatric sarcoma mapped to neuroblastoma-like tumors with ALK activity and responds to crizotinib plus a JAK–STAT inhibitor. Methods include a paradigm shift score to call functional driver effects from pathway discordance, network reconstruction with tie-dye patient networks to link mutations → TFs → kinases, and proteomic validation of inferred linkers; networks yield candidate combination targets tested in cell lines.

AI-written summary · about

  1. 0:00Start
  2. 6:34INTEGRATED SUBTYPING OF BLCA DISTINGUISHES PATIENT OUTCOMES
  3. 13:07Mutational patterns correlate with lineage.
  4. 15:30Distinguishing drivers from passengers (needle in a needle stack)
  5. 15:59Predicting Driver Genes
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