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Chowdhury, Saikat

Gupta, Ria

Haridas, Valsala

Kopetz, Scott

Shen, John Paul

Zeineddine, Mohammad

English

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Title of the Poster Presentation Goes HereAuthors of the Poster Presentation Goes HereInstitutional and/or Graduate School of Biomedical Sciences Affiliation Goes Here Background• Activating mutations in the extended RAS (KRAS, NRAS, andBRAF) genes confer resistance to anti-EGFR Ab (e.g.,Cetuximab) therapy of colorectal cancer (CRC) patients1• Left sided RASWT tumors are incorporated in NCCN guidelineas predictor of anti-EGFR Ab therapy2• However, only 40% - 45% RASWT patients have been found torespond to the therapy3• Identification of novel biomarkers is required for betterstratification of the metastatic CRC patients for anti-EGFR AbtherapyMaterials and Methods• Gene expression datasets of two retrospective clinicalcohorts and two pre-clinical cohorts were downloaded fromGene Expressions OmnibusTranscriptional profiling and consensus molecular subtype (CMS) assignment to understand response and resistance to anti-EGFR therapy in colorectal cancerSaikat Chowdhury1,*, Ria Gupta1, Valsala Haridas1, Mohammad A. Zeineddine1, Scott Kopetz1, John Paul Shen11Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA* Presenting author: schowdhury4@mdanderson.orgTranscriptomic datasets used in this studyDatasets Total Samples Sample types Treatment ReferencesCell linesGSE59857 146 CRC Cell lines CetuximabMedico et al., Nat Comm, 2015PDX ModelsGSE76402 216 PDX Models Cetuximab Bertotti et al., Nature, 2015Patient CohortsGSE104645 135 pCRC tissuesFOLFOX/FOLFIRI &CetuximabOkita et al., Oncotarget,2018GSE5851 68 pCRC tissues CetuximabKhambata-Ford et al., J Clin Oncol, 2007Results• Percentages of clinically benefited CMS2 RASWT patients(92% and 68%), PDX models (84%), and sensitive CRC celllines (60%) were highest in both clinical and preclinicalcohorts• Median PFS (7.47 months and 3.06 months) of CMS2RASWT patients in two clinical cohorts were higher than theother CMS subclassesbOkita et al. Khambata-Ford et al.Objective• Identification of transcriptomic determinants for predictingand understanding the primary resistance mechanisms to anti-EGFR antibody therapy of colorectal cancer patients• Workflow:Pre-clinical cohortsClinical cohortsGene expressionsConsensus molecular subtypes (CMS)Protein Activity ScoresCMSClassifier&CMSCallerVIPERClinical benefits & Sensitivities of CMSSurvival analyses of CMSCetuximab treatments vs CMS(RECIST, AUC) (PFS)RASWT & MSS SamplesResistant pathwaysGSEA&ssGSEAIn vitro validation on HT55 and SNUC1 cell linesDrug screeningOkita et al. cohort Khambata-Ford et al. cohortVariables Univariate StudyMultivariate StudyUnivariateStudyMultivariate StudyHR P-value HR P-value HR P-value HR P-valueAge 0.99 ns 0.99 0.63 0.99 0.94 1.00 0.78SexFemale vs Male 1.14 n 0.94 0.79 1.85 0.02* 1.62 0.11RAS gene mutationRASwt vs RASmut 0.34 9.44E-07* 0.318.43E-07* 0.491.00E-02* 0.611.40E-01Tumor sidesLeft vs right 0.68 0.11 0.89 0.66 NA NA NA NACMSCMS1 vs CMS2/3/4 2.19 0.0038* 1.44 0.33 3.47 0.002* 7.10 0.0009*CMS2 vs CMS1/3/4 0.55 0.002* 0.62 0.03 0.44 0.001* 0.44 0.003*CMS3 vs CMS1/2/4 1.2 0.357 1.00 0.99 NA NA NA NACMS4 vs CMS1/2/3 1.22 0.32 1.57 0.05 1.6 0.06 1.59 0.09• Age, sex, and primary tumor sidedness (right vs. left colon)were not significantly associated (p-value > 0.05) withprogression-free survival (PFS) of cetuximab treatment• RAS gene mutation and CMS of CRC patients weresignificantly associated with PFS (p-value < 0.05)• CMS1 and CMS2 patients showed worst and best prognosisto anti-EGFR treatment, respectively• Response to anti-EGFR antibody therapy was higher for left-sided (DCR: ~83% (58/70) vs 62.5% (5/8) for right-sided)tumors• However, after controlling for CMS, DCR for right and leftsided CMS2/RASWT tumors were similar• MTORC1, E2F, and MYC pathway gene-sets were foundsignificantly enriched (FDR < 0.3) in the cetuximab refractoryCMS2 RASWT samples of both clinical and preclinical cohorts• Single sample GSEA revealed that MTORC1, E2F, and MYCpathways were heterogeneously active (NES > 1) in thecetuximab refractory RASWT samplesCMS2 RASWT Non-responder patientsOkita et al. cohort Khambata-Ford et al. cohortCMS2 RASWT CRC cell lines CMS2 RASWT PDX modelsMedico et al. cohort Bertotti et al. cohort• HT55 and SNUC1 cell lines were resistant to cetuximab (IC50> 10µg/ml)• Single agent inhibitors of E2F (AZD7762 and MK-8776),mTOR (Everolimus), and MYC (JQ1) pathways could not inhibitHT55 and SNUC1 cell growth (IC50 > 10µM)Cell viability assays HT55 SNUC1Single-drug assay IC50 AUC IC50 AUCCetuximab (0.01*/0.1$ µg/ml – 100*/50$ µg/ml) > 10 µg/ml 383 > 10 µg/ml 251AZD7762 (0.8 µM – 10 µM) 4.9 µM 159 > 10 µM 180MK-8776 (1.25 µM – 20 µM) > 10 µM 108 > 10 µM 111JQ1 (0.25 µM – 10 µM) > 10 µM 123 > 10 µM 136Everolimus (1 µM – 15 µM) > 10 µM 97.1 > 10 µM 90.7*HT55 cell line assay; $ SNUC1 cell line assayPharmacological parameters of cell viability assays of HT55 and SNUC1 lines  • The addition of AZD7762, MK-8776, Everolimus, and JQ1significantly decreased HT55 cell viability relative to cetuximabalone• However, combinatorial effect of these drugs with cetuximabwas additive, rather than synergisticConclusions• CMS may be used as biomarker for classifying RASWT &MSS CRC patients for anti-EGFR antibody therapy• Both left and right-sided RASWT/MSS/CMS2 tumors maybe benefited from cetuximab therapy• RAS-MAPK independent signaling pathways mayregulate primary resistance to anti-EGFR antibodiesFundingAcknowledgementThis work was supported by the National Cancer Institute (L30 CA171000 and K22 CA234406 toJ.P.S., and The Cancer Center Support Grant P30 CA016672), the Cancer Prevention &Research Institute of Texas (RR180035 to J.P.S., J.P.S. is a CPRIT Scholar in Cancer Research),and the Col. Daniel Connelly Memorial Fund. This study was also supported by the ColorectalCancer Moonshot Program and SPORE program (P50CA221707) of The UT MD AndersonCancer Center.We acknowledge the support of the High-Performance Computing for research facility at TheUniversity of Texas MD Anderson Cancer Center for providing computational resources that havecontributed to the research results reported in this work.Cox proportional hazard analysis of PFS of anti-EGFR treatment in clinical cohorts References1. Therkildsen C, et al., Acta Oncol, 2014;53(7):852-642. National Comprehensive Cancer Network. Colon Cancer (Version 1.2021)3. Vidal J, et al., Ann Oncol, 2019;30(3):439-46

Transcriptional profiling and consensus molecular subtype (CMS) assignment to understand response and resistance to anti-EGFR therapy in colorectal cancer

https://openworks.mdanderson.org/cgi/viewcontent.cgi?article=1057&context=leading-edge

Transcriptional profiling and consensus molecular subtype (CMS) assignment to understand response and resistance to anti-EGFR therapy in colorectal cancer

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