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DTSTART:19700308T020000
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DTSTAMP:20210402T160552Z
LOCATION:Track 3
DTSTART;TZID=America/New_York:20201113T123000
DTEND;TZID=America/New_York:20201113T124500
UID:submissions.supercomputing.org_SC20_sess222_ws_cafcw108@linklings.com
SUMMARY:Causal Deconvolution of a Mechanistic Model of EGFR and ERK Signal
 ing Explains Adaptive and Genetic Resistance in Melanoma
DESCRIPTION:Workshop\n\nCausal Deconvolution of a Mechanistic Model of EGF
 R and ERK Signaling Explains Adaptive and Genetic Resistance in Melanoma\n
 \nFroehlich\n\nAllosteric interactions are at the core of many signal tran
 sduction processes and provide robustness and enable context dependency fo
 r the underlying molecular mechanisms. This is prominently captured by par
 adoxical activation, a clinically observed phenomenon where RAF inhibitors
  inhibit tumor growth in BRAF mutant cancers, but promote tumor growth in 
 BRAF wild-type cancers. Energy based formalisms to describe such allosteri
 c effects in kinetic models have been developed, but approaches to enable 
 intelligibility of and address the computational complexity associated wit
 h such large, multi-scale models are currently missing.\n\nHere we demonst
 rate the use of a programmatic, thermodynamic, energy-balanced rule-based 
 formalism in PySB to describe allosteric interactions. We tackle the numer
 ical challenges of large kinetic models by using and extending state of th
 e art high performance computing simulation and calibration tools.  To add
 ress the conceptual challenge of rendering large kinetic models intelligib
 le, we introduce a novel approach to causally separate intertwined signali
 ng channels.\n\nWe apply these methods to an ordinary differential equatio
 n model of adaptive resistance in melanoma (EGFR and ERK pathways, >1k sta
 te variables, >10k reactions), accounting for paradoxical activation. We t
 rained the model on absolute proteomic and phospho-proteomic as well as ti
 me-resolved immunofluorescence data, both in dose-response to small molecu
 le inhibitors. We deconvolve oncogenic and physiological causal paths to d
 erive simple explanations for complex dose-response relationships, explain
  how synergy and antagonism can arise without direct drug interaction and 
 establish a link between adaptive and genetic resistance in melanoma.\n\nR
 egistration Category: Workshop Reg Pass
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