{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:58:51Z","timestamp":1785405531148,"version":"3.56.0"},"posted":{"date-parts":[[2026,7,10]]},"group-title":"Cancer Biology","reference-count":25,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"award":["U54 OD036472"],"award-info":[{"award-number":["U54 OD036472"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["OT2 OD032742"],"award-info":[{"award-number":["OT2 OD032742"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,7,10]]},"abstract":"<jats:title>Summary<\/jats:title>\n                <jats:p>\n                  Pancreatic ductal adenocarcinoma (PDAC) is driven by oncogenic KRAS in roughly 90% of cases, and KRAS-pathway inhibition has finally become clinically active. Durable benefit, however, will require identifying the adaptive and baseline vulnerabilities that shape response to KRAS inhibition. Two resistance mechanisms have been proposed separately in the literature \u2014 receptor-tyrosine-kinase bypass of KRAS, and dependence on the adhesion kinase FAK \u2014 but whether they are one target class or two, and which should partner a KRAS inhibitor, is unresolved. We integrate public perturbation, dependency, and survival data to nominate them as\n                  <jats:italic>mechanistically separable<\/jats:italic>\n                  candidate combination partners.\n                <\/jats:p>\n                <jats:p>\n                  Two findings define the separation. First, KRAS loss increases ERBB2\/3 receptor expression. This appeared in both an inducible genetic KRAS-extinction model and, independently, in five PDAC lines treated with pharmacological KRAS-G12C\/D inhibitors, while MAPK output collapsed as expected. The signal was clearest for ERBB2 and in the genetic model; in the small pharmacological cohort the effect was modest and its confidence intervals crossed zero, so we treat ERBB2\/3 up-regulation as a candidate adaptive response \u2014 ERBB2-dominant and ERBB3-compatible \u2014 not a proven resistance mechanism. Second, focal adhesion kinase (FAK\/PTK2) is the top-ranked standing druggable dependency within the KRAS\/Src\/RTK\/adhesion network we examined (essential in 58% of pancreatic lines), yet it is\n                  <jats:italic>not<\/jats:italic>\n                  induced by KRAS shutdown. FAK dependency is present at baseline and, in DepMap, is statistically independent of a line\u2019s KRAS dependency (Spearman \u03c1 = +0.05, n.s.) \u2014 a genuinely standing vulnerability rather than a KRAS-rebound effect. The candidate adaptive response and the standing dependency are not positively co-regulated across the perturbed lines (pooled Spearman \u03c1 = \u22120.43, but n = 8 and n.s., so this cannot by itself establish independence); we therefore treat them as separable on mechanistic grounds \u2014 each nominated by different data and engaged by a different drug \u2014 rather than as statistically demonstrated independent programs.\n                <\/jats:p>\n                <jats:p>\n                  A Src-centered signaling-landscape analysis associates patient prognosis with the coordinated invasion-and-RTK program these nodes organize, rather than with any single transcript; this program remains prognostic after adjustment for a conventional EMT\/stromal signature, which does not (Src-neighborhood per\u2013standard-deviation OS hazard ratio 1.9, p \u2248 3 \u00d7 10\u207b\u2075; EMT signature null on adjustment). Together these results motivate a concrete, testable hypothesis: that FAK inhibition (a standing dependency) and ERBB inhibition (a candidate induced adaptive response) are\n                  <jats:italic>separable<\/jats:italic>\n                  candidate partners for a KRAS inhibitor, best evaluated as distinct arms of a biomarker-stratified platform. They also clarify why single-agent Src inhibition \u2014 a non-oncogene dependency tested as monotherapy, without a KRAS backbone, in advanced rather than micro-metastatic disease \u2014 was not positioned to surface either mechanism. No protein-level, phospho-signaling, or combination-response validation is performed here; all findings are computational nominations that require experimental validation before any clinical inference.\n                <\/jats:p>\n                <jats:sec>\n                  <jats:title>Highlights<\/jats:title>\n                  <jats:list list-type=\"bullet\">\n                    <jats:list-item>\n                      <jats:p>KRAS inhibition is associated with an induced ERBB2\/3 up-regulation \u2014 ERBB2-dominant, ERBB3-compatible \u2014 directionally reproduced across genetic KRAS extinction and pharmacological KRAS-G12C\/D inhibition; the pharmacological effect is modest and underpowered<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Genome-wide dependency nominates FAK \u2014 essential in 58% of pancreatic lines \u2014 as the top-ranked standing candidate co-target within the KRAS network; FAK dependency is present at baseline, statistically independent of KRAS dependency, and not co-regulated with the induced ERBB response<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>\n                        Patient prognosis associates with a Src-organized invasion-and-RTK program, not with\n                        <jats:italic>SRC<\/jats:italic>\n                        ,\n                        <jats:italic>KRAS<\/jats:italic>\n                        , or any single-gene transcript, and this program stays prognostic after adjustment for a conventional EMT\/stromal signature\n                      <\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>The two mechanisms are separable on mechanistic grounds \u2014 nominated by different data and not positively co-regulated (though the direct correlation is underpowered, n = 8, n.s.) \u2014 motivating a multi-arm platform that could test FAK and ERBB partner arms as distinct hypotheses rather than one bundled combination<\/jats:p>\n                    <\/jats:list-item>\n                  <\/jats:list>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>In brief<\/jats:title>\n                  <jats:p>Blocking KRAS in pancreatic cancer is now clinically feasible, but resistance is the obstacle. Using only public data, Chen and colleagues nominate two mechanistically separable candidate combination partners for KRAS inhibitors: a candidate ERBB2-dominant adaptive (putative escape) response that is induced when KRAS is blocked, and FAK, the top-ranked standing dependency in the KRAS network \u2014 present at baseline and independent of a tumor\u2019s KRAS dependency. Because the two are nominated by different data and are not positively co-regulated, they argue for a multi-arm KRAS-combination trial that tests each as a separate hypothesis \u2014 and they explain why the earlier single-agent Src trials, run without a KRAS backbone and in the wrong disease setting, were not positioned to detect either. The findings are computational nominations that require experimental validation.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.07.09.737590","type":"posted-content","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T17:15:34Z","timestamp":1783703734000},"source":"Crossref","is-referenced-by-count":0,"title":["Induced ERBB response and standing FAK dependency nominate separable KRAS-combination hypotheses in pancreatic cancer"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2151-9381","authenticated-orcid":false,"given":"Jake Y.","family":"Chen","sequence":"first","affiliation":[{"name":"Systems Pharmacology AI Research Center, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ehsan","family":"Saghapour","sequence":"additional","affiliation":[{"name":"Systems Pharmacology AI Research Center, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikhil","family":"Kurmachalam","sequence":"additional","affiliation":[{"name":"Systems Pharmacology AI Research Center, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geetanjali","family":"Oishe","sequence":"additional","affiliation":[{"name":"Systems Pharmacology AI Research Center, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhandos","family":"Sembay","sequence":"additional","affiliation":[{"name":"Systems Pharmacology AI Research Center, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026071407000528000_2026.07.09.737590v1.1","article-title":"Global cancer statistics 2024: GLOBOCAN estimates of incidence and mortality worldwide for 34 cancers in 186 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