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Identifying the signaling pathways involved will nominate drug combinations to promote chemoresponse, but cell population-level studies are inherently fraught, and single-cell transcriptomics are limited to indirect ontology-based inferences. To understand EMT heterogeneity at a signaling protein level, we combined iterative indirect immunofluorescence imaging of pancreas cancer cells and tumors and mutual information (MI) modeling. Focusing first on MAP kinase pathways, MI predicted that cell-to-cell variation in ERK activity surprisingly dominated control of EMT heterogeneity in response to diverse growth factors and chemotherapeutics, but that JNK compensated when MEK was inhibited. Population-level models could not capture these experimentally validated MI predictions. The dominant role of ERK was predicted by MI even when analyzing seven potential EMT-regulating signaling nodes. More generally, this work provides an approach for studying highly multivariate signaling\/phenotype relationships based on protein measurements in any setting.<\/jats:p>","DOI":"10.1101\/2025.02.08.637251","type":"posted-content","created":{"date-parts":[[2025,2,9]],"date-time":"2025-02-09T22:35:17Z","timestamp":1739140517000},"source":"Crossref","is-referenced-by-count":1,"title":["ERK plays a conserved dominant role in pancreas cancer cell EMT heterogeneity driven by diverse growth factors and chemotherapies"],"prefix":"10.64898","author":[{"given":"Michelle C.","family":"Barbeau","sequence":"first","affiliation":[{"name":"Department of Pathology, University of Virginia, Charlottesville, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brooke A.","family":"Brown","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, University of Virginia, Charlottesville, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sara 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