Supplementary Table S1 details the efficacy of MRTX0902 in a panel of cancer cell lines.

Supplementary Table S2 shows the antitumor activity of MRTX0902 and adagrasib in a panel of human KRAS G12C-mutant tumor cell line-derived and patient-derived xenograft models.

Supplementary Table S5 details the antitumor activity of MRTX0902 and avutometinib in human KRAS-MAPK pathway mutant tumor cell line-derived xenograft models.

Supplementary Figure S4 shows levels of KRAS-MAPK pathway modulation associated with coadministration of MRTX0902 and adagrasib in the MIA PaCa-2 (KRAS G12C-mutant) model.

Supplementary Figure S6 details the improved antiproliferative activity observed with the MRTX0902/osimertinib combination in EGFR mutant models, PC9 (EGFR ex19del) and NCI-H1975 (EGFR L858R/T790M).

Supplementary Figure S5 shows levels of KRAS-MAPK pathway modulation associated with coadministration of MRTX0902 and adagrasib in the murine CT26 (KRAS G12C-mutant) model.

Supplementary Figure S3 details the antitumor effects and gene set enrichment analysis data associated with coadministration of MRTX0902 and adagrasib in KRAS G12C-mutant human tumor xenograft models.

Supplementary Materials and Methods section includes detailed protocols for the following: Experimental Preparation of MRTX0902 and Avutometinib, SOS1 Biochemical Binding Assay, SOS1 and SOS2 Functional Assays, KRAS-SOS1 Protein-Protiein Interaction (PPI) HTRF Assay, In-Cell Western Assay, 3D Ultra-Low Attachment (ULA) Viability Assay, Immunoblotting and Densitometry Analysis, DUSP6 Quantification from Naive and Tumor-Bearing Mouse Blood, Bioanalysis and Pharmacokinetic Analysis, Synergy Analysis, CRISPR/Cas9 Screening and Data Analysis Methodology, RNAseq Pre-Processing, RNAseq Data Analysis, and Whole Genome Sequencing.

Supplementary Table S3 displays the various genetic co-alterations present in human KRAS G12C-mutant tumor cell line-derived and patient-derived xenograft models evaluated.

Supplementary Figure S7 shows the improved antiproliferative activity observed with the MRTX0902/avutometinib combination in KRAS-MAPK pathway mutant models, LN229 (PTPN11 A72S) and NCI-H1435 (NF1 K615N).

Supplementary Figure S8 details the antitumor effects associated with coadministration of MRTX0902 and adagrasib in the MIA PaCa-2 (KRAS G12C-mutant) model.

Supplementary Figure S2 shows the antitumor activity of MRTX0902 in the LN229 (PTPN11 A72S-mutant) model, with tumor growth inhibition data displayed in Figure S2A and ERK phosphorylation graphed in Figure S2B.

Supplementary Figure S1 details the genetic vulnerabilities and modifiers of response associated with combination treatment of MRTX0902 with adagrasib in the KRAS G12C-mutant MIA PaCa-2 (S1A, S1B, S1D, and S1E) and LU99 (S1C) cell lines in vitro and in vivo.

Supplementary Table S4 shows the antitumor activity of MRTX0902 and osimertinib in human EGFR-mutant tumor cell line-derived xenograft models.

Low-grade serous ovarian cancer (LGSOC) is a rare and distinct cancer in which ∼70% of patients have aberrations in MAPK pathway-associated genes. Following a phase 1 study (FRAME; NCT03875820) of the combination of the RAF/MEK clamp avutometinib with the FAK inhibitor defactinib in LGSOC, a phase 2 study (RAMP-201; NCT04625270) showed a higher response rate for this combination (31% ORR in overall LGSOC population; 44% ORR in patients with mutant KRAS) relative to avutometinib monotherapy (17% ORR in overall LGSOC population; 23% ORR in patients with mutant KRAS). 3D proliferation studies were conducted to assess synergy between avutometinib and defactinib in a patient-derived LGSOC organoid model. This organoid model was used in in-vivo experiments with vehicle, avutometinib, VS-4718 (FAK inhibitor) and the combination for 2 weeks. Tumor samples were collected 2 hours after the last dose and analyzed for p-ERK and p-FAK by IHC, RNA seq and mass spectrometry to understand the contribution of individual drugs and their combinatorial effects. The combination of avutometinib with defactinib in organoids was synergistic (combination index = 0.53). In-vivo, the combination induced tumor regressions in 5/6 animals, whereas avutometinib or VS-4718 alone induced tumor growth inhibition but with no tumor regression. The combination significantly reduced pERK (p=0.0003) and pFAK (p=0.0172) relative to control. Analyzing the gene expression data using multiple MAPK signatures, the combination of avutometinib and VS-4718 caused significantly greater inhibition of the MAPK pathway relative to avutometinib alone. At the individual gene level, avutometinib + VS-4718 induced significant inhibition of the MAPK pathway genes SPRY4, EPHA2, ETV4, ETV5 and CCND1 relative to avutometinib alone, and this inhibition of SPRY4 and EPHA2 was confirmed at the protein level. Further, using multiple MYC signatures, avutometinib alone significantly induced MYC signaling, whereas the combination inhibited MYC signaling. Finally, significant inhibition of PI3K pathway signatures was also observed with the combination of avutometinib + VS-4718, whereas neither avutometinib nor VS-4718 alone showed a significant effect on the PI3K signatures. The combination of avutometinib with defactinib has shown preclinical and clinical activity in LGSOC greater than avutometinib alone, and is being evaluated in a randomized phase 3 trial in patients with LGSOC (RAMP-301; NCT06072781). These preclinical studies show that avutometinib + FAK inhibitor inhibits MAPK pathway signaling more strongly than avutometinib alone. Further, putative mechanisms of resistance to avutometinib, including MYC and PI3K signaling, were overcome by the combination of avutometinib with a FAK inhibitor in LGSOC models. Lisa Pickard, Konstantinos Mitsopolous, Theo Roumeliotis, Silvia Coma, Laura Hover, Alexis De Haven Brandon, Bora Gurel, Jiin Song, Priya S. Hibshman, A Cole Edwards, Jeffrey A. Klomp, Clint A. Stalnecker, Adrienne D. Cox, Jyoti Choudhary, Channing Der, Jonathan A. Pachter, Udai Banerji. Correlative preclinical studies to elucidate mechanisms of synergy of the combination of the RAF/MEK clamp avutometinib and the FAK inhibitor defactinib in low grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6368.

Protein arginine methyltransferase 5 (PRMT5) is a synthetic lethal target in cancers harboring genomic deletions of the MTAP gene, which encodes the enzyme methylthioadenosine phosphorylase. Approximately one in four pancreatic ductal adenocarcinoma (PDAC) cases harbor homozygous deletion of the MTAP gene (MTAP-del), providing a promising novel targeted therapy for PDAC. The methylthioadenosine (MTA)-cooperative PRMT5 inhibitor BMS-986504 (previously known as MRTX1719) leverages the elevated MTA levels present in MTAP-del tumors to selectively block PRMT5 function in cancer but not normal cells and tissues. BMS-986504 demonstrated clinical activity in MTAP-del cancers without the dose-limiting hematological toxicity associated with previous first-generation PRMT5 inhibitors, however the utility of this approach has not been thoroughly investigated in PDAC. Here, we demonstrated that BMS-986504 suppressed PRMT5 function and cell growth in MTAP-del PDAC cells in vitro and in established cell line- and patient-derived xenograft mouse models. Furthermore, CRISPR/Cas9 screens were performed using the MTAP-del, KRAS-mutant MIA PaCa-2 cell line in vitro and in vivo to identify genes that modulated sensitivity to BMS-986504. We identified KRAS as one of the top depleted target genes in both screens (in the top 50 in vitro and the top 20 in vivo). We validated co-targeting KRAS as a combination strategy and found that combined small molecule inhibition of PRMT5 and G12C/D-mutant KRAS (using adagrasib and MRTX1133, respectively) effectively suppressed MTAP-del PDAC growth in vitro and in vivo. We also performed RNA-Seq analysis and determined that PRMT5 inhibition disrupts RNA splicing of genes that are essential for PDAC growth. Further, we determined that, while PRMT5 and KRAS regulate distinct transcriptomes, they converge on common pathways governing cancer cell growth and combined inhibition of PRMT5 and KRAS caused marked downregulation of PDAC-essential genes. These findings provide a rationale for combined inhibition of PRMT5 and KRAS to maximize targeted therapies for MTAP-del and KRAS-mutant biomarker-positive PDAC. Kristina Drizyte-Miller, Lars D. Engstrom, Jeffrey A. Klomp, Clint A. Stalnecker, Laura Waters, Andrew Calinisan, Ryan Robb, Khalilah E. Taylor, Mallory K. Roach, Addison G. Stamey, Seamus Degan, Wen-Hsuan Chang, Xousaen M. Helu, David Nguyen, Laura D. Hover, Elisa Baldelli, Mariaelena Pierobon, Emanuel F. Petricoin, Kirsten L. Bryant, David M. Briere, James G. Christensen, Jill Hallin, Adrienne D. Cox, Peter Olson, Channing J. Der. Combination of MTA-cooperative PRMT5 inhibitor BMS-986504 and KRAS inhibitors for the treatment of MTAP-deleted KRAS-mutant pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3786.

PURPOSE:KRAS inhibitors are revolutionizing the treatment of non-small cell lung cancer (NSCLC), but clinico-genomic determinants of treatment efficacy warrant continued exploration. EXPERIMENTAL DESIGN:Patients with advanced KRASG12C-mutant NSCLC treated with adagrasib [KRYSTAL-1 (NCT03785249)] were included in the analysis. Pretreatment next-generation sequencing data were collected per protocol. HTG EdgeSeq Transcriptome Panel was used for gene expression profiling. Clinical endpoints included objective response, progression-free survival (PFS), and overall survival (OS). KRASG12C-mutant NSCLC cell lines and xenograft models were used for sensitivity analyses and combination drug screens. RESULTS:KEAP1 MUT and STK11MUT were associated with shorter survival to adagrasib [KEAP1: PFS 4.1 vs. 9.9 months, HR 2.7, P < 0.01; OS 5.4 vs. 19.0 months, HR 3.6, P < 0.01; STK11: PFS 4.2 vs. 11.0 months, HR 2.2, P < 0.01; OS 9.8 months vs. not reached (NR), HR 2.6, P < 0.01]. KEAP1WT/STK11WT status identified adagrasib-treated patients with significantly longer PFS (16.9 months) and OS (NR). Preclinical analyses further validate the association between KEAP1 loss of function and adagrasib resistance. Adagrasib and mTOR inhibitor combinations produced higher treatment efficacy in NSCLC models harboring STK11 and KEAP1 co-mutations. NRF2HIGH signaling was associated with shorter survival to adagrasib (PFS: 4.2 vs. 8.4 months, HR 2.0, P = 0.02; OS: 6.5 vs. 19.0 months, HR 2.8, P < 0.01) even in patients with KEAP1WT NSCLC. KEAP1WT/STK11WT/NRF2LOW status identified patients-32%-with longer survival to adagrasib (PFS 12.0 vs. 4.2 months, HR 0.2, P < 0.01; OS NR vs. 8.0 months, HR 0.1, P < 0.01). CONCLUSIONS:KEAP1, STK11, and NRF2 status define patients with KRASG12C-mutant NSCLC with markedly distinct outcomes to adagrasib. These results further support the use of genomic features-mutational and nonmutational-for the treatment selection of patients with KRASG12C-mutant NSCLC.

How the KRAS oncogene drives cancer growth remains poorly understood. Therefore, we established a systemwide portrait of KRAS- and extracellular signal–regulated kinase (ERK)–dependent gene transcription in KRAS-mutant cancer to delineate the molecular mechanisms of growth and of inhibitor resistance. Unexpectedly, our KRAS-dependent gene signature diverges substantially from the frequently cited Hallmark KRAS signaling gene signature, is driven predominantly through the ERK mitogen-activated protein kinase (MAPK) cascade, and accurately reflects KRAS- and ERK-regulated gene transcription in KRAS-mutant cancer patients. Integration with our ERK-regulated phospho- and total proteome highlights ERK deregulation of the anaphase promoting complex/cyclosome (APC/C) and other components of the cell cycle machinery as key processes that drive pancreatic ductal adenocarcinoma (PDAC) growth. Our findings elucidate mechanistically the critical role of ERK in driving KRAS-mutant tumor growth and in resistance to KRAS-ERK MAPK targeted therapies.

8529 Background: KRASG12C inhibitors such as adagrasib and sotorasib have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients develop primary or secondary resistance. A biomarker of response to KRASG12C inhibitor is needed for better patient stratification and to understand the resistance mechanism. Methods: We analyzed transcriptional correlates of adagrasib treatment outcome in 68 patients in the KRYSTAL-1 trial, a phase 1/2 clinical trial of adagrasib monotherapy in the second line and beyond treatment for NSCLC. We also treated KRAS-mutated lung cancer mouse models and organoids with a KRAS inhibitor for the long term and characterized the resistant tumors’ transcriptional profile to identify resistance mechanisms. We also performed serial gene expression analysis of KrasG12D mutated lung organoids undergoing squamous transformation to identify transcription factor involved in the resistance process. Results: In patients with lung adenocarcinoma with KRASG12C and STK11/ LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids, treated with KRAS inhibitors adagrasib and MRTX1133, respectively, reveal that tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. We identify TP63 to be a transcription factor whose expression correlated with squamous transformation. The analysis of lineage plasticity program, adagrasib resistant tumors, and p63 regulon revealed KRT6A to be a common biomarker whose expression correlated with overall survival in the KRYSTAL-1 cohort. Conclusions: KRASG12C mutated lung adenocarcinoma patients with a higher expression of squamous cell carcinoma gene expression signature respond poorly to adagrasib treatment. Expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.