Abstract 370: Resistance to sotorasib does not confer resistance to adagrasib: Why?

Abstract Introduction: KRAS mutations are among the most common gain-of-function alterations, found in approximately 30% of lung adenocarcinomas. These mutations primarily occur at codon 12, leading to amino acid substitutions that impair KRAS's intrinsic GTPase activity, rendering the oncoprotein constitutively active. For decades, KRAS was considered "undruggable" due to the absence of a suitable drug-binding pocket. This paradigm shifted with the development of sotorasib, a covalent inhibitor that irreversibly binds to a cysteine residue, locking KRAS in its inactive GDP-bound state. Despite this breakthrough, the CodeBreaK 100 Phase I/II clinical trial revealed that the objective response rate to sotorasib was only 36%, with a median progression-free survival (PFS) of 7.6 months. These findings underscore that 64% of patients with advanced NSCLC exhibited innate resistance to sotorasib and those who responded eventually developed acquired resistance. Thus, in this study, we aim to explore the mechanisms of sotorasib resistance and evaluate the response of resistant cells to adagrasib using proteomic data. Methods: KRAS G12C NSCLC cell lines were screened for sotorasib sensitivity, and isogenic-resistant lines were developed through incremental exposure. These lines were tested for adagrasib sensitivity. Proteomic changes in parental and resistant cells, untreated or after treatment, were analyzed via mass spectrometry. Results: Incremental sotorasib treatment of sensitive cells generated isogenic resistant lines capable of tolerating sotorasib concentrations up to 20 µM. Exome analysis of resistant cells revealed no acquired driver mutations, which could be correlated with sotorasib resistance. However, these cells exhibited increased expression of ITGB4 and WNT2, leading to activation of PI3K/Akt and Wnt/β-catenin signaling pathways, as confirmed by western blot analysis. Proteomic profiling identified an upregulation of proteins involved in biological processes like cell adhesion and signal transduction, consistent with the activation of ITGB4 and Wnt signaling. Notably, adagrasib treatment significantly suppressed these biological processes and activated metabolic processes. Live-cell imaging and cell cycle analysis further demonstrated that adagrasib induced a more robust cell cycle arrest than sotorasib. Conclusion: This study concludes that sotorasib resistance can arise through the activation of alternative signaling pathways, underscoring the adaptability of biological networks in cancer cells. However, this non-genetic resistance mechanism to sotorasib does not confer cross-resistance to adagrasib, indicating that the fitness acquired by cancer cells to tolerate sotorasib is ineffective against adagrasib. These findings suggest that patients who progress on sotorasib treatment may still benefit from adagrasib, highlighting its therapeutic potential in overcoming resistance. Citation Format: Atish Ranjan Mohanty, Baiyi Quan, Supriyo Bhattacharya, Dana Do, Sravani Ramisetty, Tsui-Fen Chou, John Orban, Prakash Kulkarni, Ravi Salgia. Resistance to sotorasib does not confer resistance to adagrasib: Why [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 370.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-370
Primary Topic
Chronic Myeloid Leukemia Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 370: Resistance to sotorasib does not confer resistance to adagrasib: Why?

Ravi Salgia, Tsui‐Fen Chou, Sravani Ramisetty, Atish Mohanty et al.
Cancer Research
Chronic Myeloid Leukemia Treatments
article

Abstract 370: Resistance to sotorasib does not confer resistance to adagrasib: Why?

Ravi Salgia, Tsui‐Fen Chou, Sravani Ramisetty, Atish Mohanty, John Orban, Baiyi Quan, Prakash Kulkarni, Dana Do, S. Bhattacharya
article en

Abstract

Abstract Introduction: KRAS mutations are among the most common gain-of-function alterations, found in approximately 30% of lung adenocarcinomas. These mutations primarily occur at codon 12, leading to amino acid substitutions that impair KRAS's intrinsic GTPase activity, rendering the oncoprotein constitutively active. For decades, KRAS was considered "undruggable" due to the absence of a suitable drug-binding pocket. This paradigm shifted with the development of sotorasib, a covalent inhibitor that irreversibly binds to a cysteine residue, locking KRAS in its inactive GDP-bound state. Despite this breakthrough, the CodeBreaK 100 Phase I/II clinical trial revealed that the objective response rate to sotorasib was only 36%, with a median progression-free survival (PFS) of 7.6 months. These findings underscore that 64% of patients with advanced NSCLC exhibited innate resistance to sotorasib and those who responded eventually developed acquired resistance. Thus, in this study, we aim to explore the mechanisms of sotorasib resistance and evaluate the response of resistant cells to adagrasib using proteomic data. Methods: KRAS G12C NSCLC cell lines were screened for sotorasib sensitivity, and isogenic-resistant lines were developed through incremental exposure. These lines were tested for adagrasib sensitivity. Proteomic changes in parental and resistant cells, untreated or after treatment, were analyzed via mass spectrometry. Results: Incremental sotorasib treatment of sensitive cells generated isogenic resistant lines capable of tolerating sotorasib concentrations up to 20 µM. Exome analysis of resistant cells revealed no acquired driver mutations, which could be correlated with sotorasib resistance. However, these cells exhibited increased expression of ITGB4 and WNT2, leading to activation of PI3K/Akt and Wnt/β-catenin signaling pathways, as confirmed by western blot analysis. Proteomic profiling identified an upregulation of proteins involved in biological processes like cell adhesion and signal transduction, consistent with the activation of ITGB4 and Wnt signaling. Notably, adagrasib treatment significantly suppressed these biological processes and activated metabolic processes. Live-cell imaging and cell cycle analysis further demonstrated that adagrasib induced a more robust cell cycle arrest than sotorasib. Conclusion: This study concludes that sotorasib resistance can arise through the activation of alternative signaling pathways, underscoring the adaptability of biological networks in cancer cells. However, this non-genetic resistance mechanism to sotorasib does not confer cross-resistance to adagrasib, indicating that the fitness acquired by cancer cells to tolerate sotorasib is ineffective against adagrasib. These findings suggest that patients who progress on sotorasib treatment may still benefit from adagrasib, highlighting its therapeutic potential in overcoming resistance. Citation Format: Atish Ranjan Mohanty, Baiyi Quan, Supriyo Bhattacharya, Dana Do, Sravani Ramisetty, Tsui-Fen Chou, John Orban, Prakash Kulkarni, Ravi Salgia. Resistance to sotorasib does not confer resistance to adagrasib: Why [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 370.

Cancer ResearchVol. 85(8_Supplement_1)
California Institute of Technology (US), University of Maryland, Baltimore (US), City Of Hope National Medical Center (US), California Library Association (US)
Openalex Percentile: Top 89%
Chronic Myeloid Leukemia Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.