Abstract 4317: Targeting KRAS in appendiceal cancer: promising results with MRTX1133 and RMC-6236 in organoids and PDX models
Abstract Oncogenic KRAS mutations are frequent in mucinous appendiceal adenocarcinoma (AA) (63.4%), with G12D accounting for just over half (50.9%) and G12V representing 23.0%. There remains a significant unmet need for effective targeted therapies of AA. The advent of novel RAS inhibitors, such as KRASG12D inhibitor MRTX1133 and Pan-RAS inhibitor RMC-6236, offer a promising opportunity to address this therapeutic gap by directly targeting this oncogene. Here, we investigate the therapeutic impacts of these two new inhibitors in preclinical models of AA tumors. One AA organoid model with KRASG12D and one with KRASG12V mutation were each treated with MRTX1133 and RMC-6236. Additionally, the orthotopic AA PDX model TM00351 (Jackson Laboratory) harboring KRASG12D was treated intraperitoneally (IP) with MRTX1133 (15 mg/kg) (N=5) or vehicle (N=5), administered BID for 4 weeks. MRTX1133 was highly effective for KRASG12D but not KRASG12V organoids (IC50 4.1 nM vs 1.8 uM, sum-of-squares F test p < 0.0001). In contrast, both KRASG12D and KRASG12V organoids were sensitive to RMC-6236 (IC50 4.4 nM vs 0.5 nM, respectively). Both inhibitors significantly increased Caspase-3/7, consistent with induction of apoptosis (p-value < 0.01). IP treatment with MRTX1133 led to a marked decrease in tumor volumes (measured by MRI) at 4 weeks after treatment in orthotopic KRASG12D PDX models (MRTX1133: 1.15 fold change from baseline vs Control: 2.39, p = 0.04). Furthermore, MRTX1133-treated mice showed better PFS than mice in the control group (median: 5 weeks vs unreached, p-value = 0.005). Pathologic evaluation showed that MRTX1133 treatment significantly reduced cellularity in tumor tissues, with only a few cells showing positive for Ki-67. pAKT expressions did not change. pERK expressions were reduced considerably in KRASG12D mutant tumor cells but did not change in KRASWT stromal cells, indicating MRTX1133 mediated RAS-MEK-ERK pathway inhibition is specific to tumor cells only. Gene Set Enrichment analysis revealed significant downregulations of hallmark gene set ‘E2F targets (NES = -1.9, p-adj = 0.06)’ and the newly developed ‘RAS/ERK upregulated (NES = -2.3, p-adj = 0.06)’ gene set after MRTX1133 treatment. Also, downregulations of RAS-MEK-ERK pathway proteins, such as pMEK (logFC = -3.3, p-adj = 2.9 X 10-5) in RPPA, confirmed robust inhibition of this pathway by MRTX1133. This is the first report demonstrating the therapeutic efficacies of G12D and pan-KRAS inhibitors in preclinical models of AA. This data is consistent with the oncogenic effect of KRAS, which is mediated by RAS-MEK-ERK pathway, not by PI3K/AKT pathway. Single-agent MRTX1133 was highly potent and specific to KRASG12D AA tumors, whereas pan-RAS inhibitor RMC-6236 inhibited both KRASG12D and KRASG12V organoids at nanomolar concentrations. MRTX1133 demonstrated robust suppression of the RAS-MEK-ERK pathway and prolonged survival in vivo models of AA. Citation Format: Saikat Chowdhury, Ichiaki Ito, Vinay K. Pattalachinti, Abdelrahman MG Yousef, Mahmoud MG Yousef, Mohammad Mahdi Fanaeian, John Paul Shen. Targeting KRAS in appendiceal cancer: promising results with MRTX1133 and RMC-6236 in organoids and PDX models [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 4317.
Authors
- John Paul Shen (ORCID: https://orcid.org/0000-0003-4588-2775)
- Saikat Chowdhury (ORCID: https://orcid.org/0000-0002-0783-3959)
- Ichiaki Ito (ORCID: https://orcid.org/0000-0002-3425-0070)
- Mohammad Mahdi Fanaeian (ORCID: https://orcid.org/0000-0002-4867-8334)
- Abdelrahman Yousef (ORCID: https://orcid.org/0000-0001-7761-8149)
- Vinay K. Pattalachinti (ORCID: https://orcid.org/0009-0007-7293-0548)
- Mahmoud M.G. Yousef
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- The University of Texas at San Antonio Health Science Center (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-4317
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00