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Exploring Predictive Biomarkers and Therapeutic Combinations to Overcome Sotorasib Resistance


KRAS is the most frequently mutated oncogene in cancer. The breakthrough discovery of Sotorasib (AMG510) as the inaugural targeted therapy for KRAS G12C mutation marks a pivotal advancement. However, the emergence of acquired resistance poses a challenge to the efficacy of newly approved KRAS-specific inhibitors. The intricate underpinnings of these resistance mechanisms remain insufficiently elucidated, necessitating comprehensive exploration to unravel their complexities.


To systematically establish in vitro models of sotorasib resistance, shedding light on the intricate dynamics underlying resistance acquisition. In addition, to identify predictive biomarkers of resistance associated with sotorasib resistance and possible therapeutic combinations able to benefit oncology patients.


Mutant NCI-H358 (KRAS G12C) were exposed to incremental doses (2 to 512 nM) of sotorasib by drug-selective pressure model. Then, resistant clones were separated by single-cell sorting and validated later. Proliferation was analyzed in real-time by xCELLigence; protein profile of phospho-MAPKs and phosphor-RTKs were quantified by Arrays; and mRNA expression profile was measure using the PanCancer Pathways panel by NanoString. In silico analysis of the transcriptome data from cell lines (GSE192619) and patient-derived xenograft models (GSE204753) was employed to validate the molecular alterations identified in our resistant sotorasib model. Furthermore, combination therapies with Anti-P38 and anti-AKT were utilized to restore sotorasib sensitivity, and the degree of synergy was quantified using SynergFinder tool.


Resistant clones H358-A1 were selected after 4-6 months of incremental sotorasib exposition (IC50: 4 to 512 nm) and had decreased proliferation cell index (37,8%) and increased doubling time (22h) compared to parental cell lines. Phospho-AKT 1/2 and p38 levels increased in MAPK signaling, and were also higher in H358-A1 resistant cell. Finally, mRNA differential expression showed the most considerably increased of WNT, IL2ORA, and PITX2 and decreased ANGPT1, CD19, and NOS3. Transcriptome data from cell line and patient-derived xenografic models showed similar increased levels of P38, ERK, AKT, and EGFR expression. Combination therapies display synergy score of -2.21 to sotorasib and Adezmapimod (anti-P38) and 0.54 to sotorasib and MK2206 (anti-AKT).


The validated clonal sotorasib resistance model confirmed molecular alterations within the MAPK and tyrosine kinase receptor signaling pathways in resistant cells. The observed differential expression, both in our resistance model and public databases, highlights AKT isoforms and p38 as potential biomarkers of sotorasib resistance. Combination therapies, specifically targeting AKT and p38 inhibitors, hold promise for restoring sotorasib sensibility. Further in vitro and in vivo experiments will be conducted to elucidate the mechanisms underlying this combination strategy.


anti-KRAS, sotorasib resistance, preclinical models,

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Pesquisa básica / translacional


RENATO JOSE DA SILVA OLIVEIRA, RAQUEL ARANTES MEGID, Guilherme Gomes Ribeiro, Izabela Natalia Faria Gomes, Josiane Mourão Dias, Leticia Ferro Leal, Rui Manuel Reis