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KEAP1 mutations as key crucial prognostic biomarkers for resistance to KRAS-G12C inhibitors

Journal of Translational Medicine volume 23, Article number: 82 (2025) Cite this article

Abstract

Background

KRAS-G12C inhibitors mark a notable advancement in targeted cancer therapies, yet identifying predictive biomarkers for treatment efficacy and resistance remains essential for optimizing clinical outcomes.

Methods

This systematic meta-analysis synthesized studies available through September 2024 across PubMed, Cochrane Library, SpringerLink, and Embase. Using CRISPR/Cas9 technology, this study generated cells with KEAP1 and STK11 knockouts, and utilized lentiviral vectors to overexpress PD-L1. Cellular sensitivity to KRAS-G12C inhibitors—AMG510, MRTX849, and JAB-21822—was evaluated through CCK-8 assays. Comprehensive bioinformatics analyses on stably transfected cell lines were conducted to elucidate pathways mediating resistance.

Results

Analysis of 13 studies involving 1132 patients highlighted the significant efficacy of KRAS-G12C inhibitor monotherapy, particularly among elderly and female patients. Treatment response was notably affected by liver and brain metastases, with KEAP1 mutations identified as a primary negative prognostic factor, closely associated with early resistance to treatment. Validation studies in NCI-H358 cells showed a marked increase in IC50 values for AMG510, MRTX849, and JAB-21822 after KEAP1 knockout (P < 0.0001), with IC50 values rising from 27.78 nm, 116.9 nm, and 118.7 nm in controls, respectively. Comparative analysis of differentially expressed genes in KEAP1 knockout cells versus controls, utilizing GO, KEGG, and Reactome pathway analyses, revealed substantial enrichment in pathways linked to extracellular matrix organization and cell adhesion processes. Although STK11 mutations and heightened PD-L1 expression indicated a trend toward poorer outcomes, these correlations lacked statistical significance.

Conclusion

This research affirms KRAS-G12C inhibitors as promising treatments, especially for certain patient subgroups, and underscores KEAP1 mutations as key biomarkers for resistance. The findings highlight the urgent need for alternative therapeutic approaches in KEAP1-mutant patients and emphasize the role of molecular profiling in tailored treatment strategies.

Introduction

The Rat Sarcoma Virus Oncogene Homologue (RAS) is the most frequently mutated gene across various human cancers. Within the RAS gene family, comprising KRAS, HRAS, and NRAS–the KRAS gene emerges as the most prevalent subtype. KRAS mutations account for approximately 85% of all RAS mutations observed in cancer tissues [1]. Alterations in the KRAS gene are present in around 15–20% of lung cancer cases, 40% of colorectal cancers, and over 50% of pancreatic ductal adenocarcinomas [2]. These mutations lead to aberrant activation of the KRAS protein, thereby playing a central role in uncontrolled cellular proliferation.

The KRAS protein, encoded by the KRAS gene, functions as a guanosine triphosphatase (GTPase) that toggles between inactive and active states. Binding to guanosine diphosphate (GDP) renders KRAS inactive (OFF-state) [3,4,5], whereas guanosine triphosphate (GTP) binding activates it (ON-state), triggering downstream pathways such as the MAPK and PI3K-AKT-mTOR pathway [6]. Historically, KRAS has been a challenging therapeutic target due to its smooth surface and lack of a traditional small-molecule binding site. However, recent studies have identified a potential binding pocket adjacent to the GTP-binding site in the KRAS-G12C mutant. This pocket enables covalent binding to the sulfhydryl group of the mutant cysteine side chain, locking the protein in an inactivated GDP-bound state, thereby blocking the active GTP-bound state and inhibiting downstream signalling, which ultimately impedes tumour growth, invasion, and metastasis [7].

Building on this discovery, the small-molecule inhibitor AMG510 (Sotorasib) was developed to address the unmet need for therapies targeting KRAS-G12C mutations. In a Phase II clinical study (CodeBreaK 100), AMG510 demonstrated notable efficacy, with objective response rates (ORR) and disease control rates (DCR) that led to its accelerated FDA approval for post-line therapy in patients with advanced or metastatic KRAS-G12C-mutant non-small cell lung cancer (NSCLC) [8, 9]. Following this, additional KRAS-G12C inhibitors have emerged, providing new therapeutic options for solid tumours harbouring KRAS-G12C mutations. However, in a recent global, open-label Phase III study (CodeBreaK 200) comparing Sotorasib with docetaxel as a second-line treatment, Sotorasib significantly extended progression-free survival (PFS) relative to docetaxel (HR, 0.66 [95% CI 0.51, 0.86]), yet no substantial difference in overall survival (OS) was observed between the two groups (HR, 1.01 [95% CI 0.77, 1.33]) [10].

These findings suggest that not all patients derive prolonged benefit from KRAS-G12C inhibitors, highlighting an urgent need for further research to help clinicians identify patients likely to benefit most from these therapies. This study undertook a comprehensive analysis of the short- and long-term therapeutic effects of KRAS-G12C inhibitors on solid tumours, aiming to identify biomarkers that could guide the selection of patients more likely to respond favourably to KRAS-G12C inhibitor treatment.

Materials and methods

Search strategy and data extraction

A total of 1591 studies published up to September 30, 2024, were identified and screened across PubMed, Cochrane Library, Springer, and Embase using the search terms “KRAS-G12C inhibitors” and “clinical trial”. After removing duplicates, 1233 records were excluded based on title and abstract review. The remaining 40 full-text articles were assessed according to predefined inclusion criteria. The search methodology, conducted in alignment with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) framework, is illustrated in Figure S1. Thirteen studies met the criteria for qualitative synthesis and were subsequently included in the analysis.

Data extraction from each study was independently carried out by two authors, covering the following key aspects: (1) primary author and publication year, (2) sample size, (3) study design, (4) baseline characteristics and molecular features, (5) treatment regimens, and (6) outcome measures, including ORR, DCR, OS, and PFS which reported. Data of outcomes are obtained either directly from the published literature or by digitizing the survival curves from the included studies using the tool available at https://www.digitizeit.xyz/. Any discrepancies in data extraction were resolved through third-party review or a consensus-based discussion process.

Inclusion and exclusion standards of study

Studies qualified for inclusion if they met the following criteria: (1) prospective clinical trials or retrospective studies investigating KRAS-G12C inhibitors, (2) patient cohorts with KRAS-G12C-mutated solid tumors, and (3) reporting of at least one clinical outcome measure (ORR, DCR, OS, or PFS). Exclusion criteria were: (1) review articles, correspondences, and conference abstracts without full text, (2) studies focused on basic research or animal models, and (3) duplicate publications.

Study qualitative assessment and statistical analysis

The methodological quality of the included studies was assessed using the Methodological Index for Non-randomized Studies (MINORS) [11]. Publication bias was evaluated with STATA SE 12.0 software (StataCorp, College Station, TX, USA) (Table S1).

Analyses of therapeutic efficacy were conducted using RevMan 5.3 software (The Cochrane Collaboration, London, United Kingdom) for molecular feature evaluations and R software version 4.1.3 (https://www.r-project.org/) for all other analyses. A fixed-effects model was performed when I2 < 50%. And we employed Mantel–Haenszel (M–H) method to calculate the pooled effects. Otherwise, a random effects model was adopted and Der Simonian & Laird (D-L) Method was employed. Stratified epidemiological analysis was performed to investigate sources of variability, with statistical significance for inter-cohort comparisons established at a composite P value of less than 0.05.

Cell line and cell culture

The NCI-H358 and H1373 human lung cancer cell lines, both harbouring the KRASG12C mutation, were obtained from American Type Culture Collection (ATCC). Cultures were initiated from cells that had been passaged at least 10 times, and both cell lines were maintained in RPMI-1640 complete medium.

Lentiviral construction and transfection

For the Cas9 expression vector construction, the pLV_hEF1a-NLS-hCas9-NLS-2A-Bla plasmid and target gene knockout vectors, including pLV-hU6-sgRNA-sgRNA_backbone-hef1a-mScarlet for KEAP1 and pLV-U6-sg-gRNA-hEF1a-EGFP-2A-neo for STK11, were cleaved using restriction enzymes. Custom sgRNA sequences were then designed specifically for KEAP1 and STK11. The sgRNA sequence for KEAP1 was as follows: KEAP1-sg: TGACAGCACCGTTCATGACG; for STK11, the sgRNA sequence was STK11-sg1: CCACCGCATCGACTCCACCG. These sgRNAs were subsequently incorporated into the corresponding sgRNA vectors to generate the final sgRNA expression vectors. Cells displaying red (KEAP1-sg) or green (STK11-sg) fluorescence as an indicator of successful transfection were isolated using a FACS Aria SORP cell sorter (BD Biosciences, San Jose, CA, USA). These isolated cells were cultured to generate separate clones and Western Blotting (WB) was performed to ascertain the success of knockout.

The PD-L1 overexpression vector and the control vector were sourced from Obio Technology Corp., Ltd. (Shanghai, China), stored at − 80 °C, and thawed in an ice bath before use. Cells were transduced with lentivirus containing either the PD-L1 cDNA or the control vector in a 37 °C incubator with 5% CO2. Following a 24-h incubation with the lentiviral particles, the culture medium was removed and replaced with fresh medium, allowing the cells to transfect for an additional 48 h. Overexpression of PD-L1 stable cell lines were selected with puromycin.

Western blotting

Cellular extracts were prepared using a modified RIPA buffer supplemented with protease and phosphatase inhibitor cocktails. Protein concentrations in the lysates were quantified with the BCA Protein Assay Kit (Generay Biotechnology Co., Ltd., Shanghai, China). Equal amounts of protein (10 μg) were separated via sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) with the Quick Preparation Kit (Dakewe, Shenzhen, Guangdong, China, #8012011) and transferred onto polyvinylidene difluoride (PVDF) membranes (APPLYGEN, Beijing, China, #P2120‐2).

The membranes were blocked and incubated overnight at 4 °C with primary antibodies specific for KEAP1 (Cell Signalling Technology, #8047), STK11/LKB1 (Cell Signalling Technology, #3047), PD-L1 (Cell Signalling Technology, #13684T), or GAPDH (Abcam, Cambridge, UK, #ab8245). After primary antibody incubation, the membranes were incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies (goat anti-rabbit or mouse IgG) for one hour.

Quantitative real‐time PCR

Total RNA was extracted with the Tissue RNA Purification Kit plus (RN001-50Rxns). Complementary DNA (cDNA) synthesis was performed in a 20-μL reaction volume using the TransScript II All-in-One First-Strand cDNA Synthesis SuperMix kit (TransGen Biotech, Cat#AH341-01, K1622, 752). PCR amplification followed in a 10-μL volume with the QuantiNova SYBR Green PCR kit (Qiagen, Cat#208054). GAPDH served as an internal control for normalization, and relative gene expression levels were analyzed using the 2−ΔΔCT method. Primer sequences for this study are provided in Table S2.

Cell counting kit 8 assay

Cellular specimens were seeded in 96-well microtiter plates at a density of 5,000 cells per well in a complete growth medium. DMSO was used as a control to evaluate cell proliferation for cytotoxicity assessment. KRAS-G12C inhibitors were applied at various concentrations (0, 1, 10, 100, 1,000, 10,000, 50,000, 100,000, and 200,000 nM), and cells were incubated for 48 h. For cell viability assessment, 10 µL of CCK-8 reagent (CCK-8, Dojindo, Catalog No. CK04) was added to each well, followed by a 2-h incubation. Optical density (OD) at 450 nm was measured with a spectrophotometer (SkanIt, Thermo Scientific). The half-maximal inhibitory concentration (IC50) values were calculated using variable slope analysis in GraphPad Prism version 8.0 (La Jolla, CA).

Bioinformatics

Total RNA was extracted from H358 KEAP1-knockout (KEAP1-ko) versus normal controls (KEAP1-nc) cells, STK11-knockout (STK11-ko) versus normal controls (STK11-nc) cells, and H1373 PD-L1-overexpressing (PD-L1-oe) versus vector control (PD-L1-vec) cells following a 24-h treatment with KRAS-G12C inhibitors. RNA sequencing (RNA-seq) was performed by LC-BIO (Hangzhou, China) to identify differentially expressed genes (DEGs). R version 4.1.3 was used to generate heatmap and volcano plots for analyzing the sequencing data. Biological functions and pathways associated with the DEGs were examined through Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) enrichment, and Reactome pathway analyses.

Results

Evaluation of efficacy outcomes

Thirteen studies, comprising 1,132 patients in total, were included in this meta-analysis [9, 12,13,14,15,16,17,18,19,20,21,22,23] (Table 1). For KRAS-G12C inhibitor monotherapy, a pooled analysis of 10 studies involving 895 participants indicated an ORR of 29% (95% CI 26–32%) (Fig. 1A). Additionally, 9 studies with 872 participants reported a pooled DCR of 80% (Fig. 1B). Notably, combining KRAS-G12C inhibitors with Cetuximab yielded a pooled ORR of 52% (95% CI 41–65%) in patients with colorectal cancer (CRC) (Fig. 1C).

Table 1 Information of included studies
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Fig. 1
figure 1

Treatment response to KRAS-G12C inhibitor therapy. A Objective response rates (ORR) of KRAS-G12C inhibitor monotherapy; B ORR of KRAS-G12C inhibitor combined with Cetuximab; C disease control rates (DCR) of KRAS-G12C inhibitor monotherapy. PP: pooled proportion; CI: confidence interval

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Survival outcomes for KRAS-G12C inhibitor monotherapy are also notable, with a 6-month OS proportion of 71% (95% CI 0.68–0.74) (Fig. 2A) and a 12-month OS proportion of 45% (95% CI 0.42–0.48) (Fig. 2B). Across 12 studies with 1,022 patients, the 6-month PFS proportion was 42% (95% CI 0.39–0.45) (Fig. 2C), while the 12-month PFS proportion was 20% (95% CI 0.18–0.23) (Fig. 2D).

Fig. 2
figure 2

Overall survival (OS) and progression-free survival (PFS) of KRAS-G12C inhibitor monotherapy. A 6-month OS; B 12-month OS; C 6-month PFS; D 12-month PFS

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Subgroup analysis of clinical baseline characteristics

KRAS-G12C inhibitor monotherapy showed a higher ORR in patients with NSCLC compared to patients with CRC, while the DCR was similar between both groups, consistent with prior findings (Fig S2A-B). Patients with NSCLC demonstrated a greater benefit in terms of 6-month and 12-month PFS compared to patients with CRC (Fig S2C-D), although they exhibited a lower 12-month OS proportion relative to patients with CRC (Fig S2E).

KRAS-G12C inhibitors appeared to benefit older patients (≥ 65 vs. < 65, P = 0.056) (Fig. 3A), with females showing a trend toward better response than males (P = 0.036) (Fig. 3B). Further analysis explored dosing recommendations for KRAS-G12C inhibitors in patients with NSCLC, revealing no significant difference in ORR between 600 mg twice daily (BID) and 960 mg once daily (QD) dosing groups (P = 0.837) (Fig. 3C).

Fig. 3
figure 3

Effect of clinical characteristics on ORR. A Subgroup analysis of ORR by age; B subgroup analysis of ORR by gender; C subgroup analysis of ORR by dose. QD: once daily; BID: twice daily

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Patients with liver metastases did not demonstrate a superior ORR to those without liver metastases (P = 0.366) (Fig. 4A). Interestingly, KRAS-G12C inhibitors were more effective in enhancing ORR in patients with brain metastases (P = 0.013) (Fig. 4B), although the difference in 12-month OS between groups was not statistically significant (P = 0.291) (Fig. 4C).

Fig. 4
figure 4

Efficacy of metastasis status. A Subgroup analysis of ORR by liver metastasis status; B subgroup analysis of ORR by brain metastasis status; C subgroup analysis of 12-month OS by brain metastasis status

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Crucial gene expression and prognosis of KRAS-G12C inhibitors

The presence of concurrent mutations in patients with KRAS-G12C mutations was identified as a factor influencing prognosis. Consequently, key gene expressions, including KEAP1, STK11, and TP53, were examined, along with the relationship between PD-L1 expression and patient outcomes.

KEAP1: a critical indicator in prognostic biomarker prediction

Patients lacking KEAP1 mutations demonstrated a significantly higher overall response rate compared to those with KEAP1 mutations (P = 0.009), and KEAP1-mutated patients exhibited markedly shorter overall survival (6-month OS P < 0.0001, 12-month OS P = 0.0009) (Fig. 5A–C).

Fig. 5
figure 5

KEAP1 mutation status and prognosis. A Subgroup analysis by KEAP1 mutation status of ORR; B subgroup analysis by KEAP1 mutation status of 6-month OS; C subgroup analysis by KEAP1 mutation status of 12-month OS; D half-maximal inhibitory concentration (IC50) values of H358-KEAP1-normal controls (nc) and H358-KEAP1-knockout (ko) cells in AMG510; E IC50 values of H358-KEAP1-nc and H358-KEAP1-ko cells in MRTX849; F IC50 values of H358-KEAP1-nc and H358-KEAP1-ko cells in JAB-21822. sg: single guide

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These results suggest KEAP1 as a potential predictive marker for poor prognosis in the context of KRAS-G12C inhibitor therapy. To validate KEAP1's role, the gene was successfully knocked out in the NCI-H358 cell line, resulting in a substantial increase in IC50 values for KRAS-G12C inhibitors (AMG510, MRTX849, and JAB-21822), indicating decreased sensitivity post-KEAP1 knockout (P < 0.0001, Fig. 5D–F, Fig S3A). Control group IC50 values were 21.72 nM, 116.9 nM, and 118.7 nM, respectively, while post-knockout IC50 values rose to 141.4 nM, 5,083 nM, and 6,558 nM for the respective inhibitors.

To investigate KEAP1’s role in resistance to KRAS-G12C inhibitors, transcriptomic analysis via RNA sequencing was conducted on NCI-H358 wild-type and KEAP1 knockout cells, revealing 2,490 DEGs, with 638 upregulated and 1,852 downregulated genes (Fig. 6A). GO and KEGG pathway enrichment analyses indicated that DEGs were primarily enriched in extracellular matrix (ECM) components and cell adhesion processes (Fig. 6B, C).

Fig. 6
figure 6

Possible genes and pathway involved in KEAP1 mutation. A Volcano plot for differentially expressed genes (DEGs) in H358 KEAP1-oe vs. KEAP1-vec cell lines; B enrichment analysis of DEGs: Gene ontology (including biological process; cellular component; and molecular function); C KEGG pathway analysis; D reactome pathway analysis

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Reactome analysis further highlighted KEAP1 mutation's impact on cellular interaction processes, with disruptions in key pathways such as NCAM1 interaction, G-alpha signalling events, and ECM organization, identifying these as primary pathways affected by KEAP1 mutation (Fig. 6D).

STK11: offering a mild hint in prognostic estimation

Pooled data indicate that patients with an STK11 mutation experienced reduced benefits and shorter survival compared to those without the mutation in terms of 6-month and 12-month OS, despite only a minimal difference in ORR (STK11 mutation vs. STK11 wild-type: ORR P = 0.57, 6-month OS P = 0.001, 12-month OS P = 0.05) (Fig. 7A–C).

Fig. 7
figure 7

STK11 mutation status and prognosis. A Subgroup analysis by STK11 mutation status of ORR; B subgroup analysis by STK11 mutation status of 6-month OS; C subgroup analysis by STK11 mutation status of 12-month OS; D IC50 values of H358-STK11-nc and H358-STK11-ko cells in AMG510; E IC50 values of H358-STK11-nc and H358-STK11-ko cells in MRTX849; F IC50 values of H358-STK11-nc and H358-STK11-ko cells in JAB-21822

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KRAS (G12C)-mutant NCI-H358 cells displayed sensitivity to KRAS-G12C inhibitors in the absence of KEAP1 or STK11 mutations. Upon silencing STK11 in NCI-H358 cells (Fig S3B), a significant increase in IC50 values for AMG510 (P < 0.0001) was observed, with only minor changes in IC50 values for MRTX849 and JAB-21822 (Fig. 7D–F). These in vitro findings suggest that STK11 knockout renders cells more resistant to KRAS-G12C inhibitors.

TP53: not a central biomarker for prognostic prediction

The presence of a TP53 mutation did not significantly alter ORR or survival outcomes compared to wild-type counterparts (TP53 mutation vs. TP53 wild-type: ORR P = 0.73, 6-month OS P = 0.73, 12-month OS P = 0.67) (Fig S4A-C).

PD-L1 expression levels: a gentle nudge in prognostic forecasting

In the subgroup analysis of PD-L1 expression levels, patients with PD-L1-negative status showed a higher ORR compared to PD-L1-positive patients, although this difference did not reach statistical significance (P = 0.07) (Fig. 8A). To further explore PD-L1’s role, a PD-L1 overexpressing (PD-L1-oe) cell line was developed using the NCI-H1373 lung cancer cell line, which is KRAS-G12C mutant and sensitive to KRAS-G12C inhibitors. qRT-PCR and WB results confirmed elevated PD-L1 expression in the PD-L1-oe cell line (Fig S3C-D). Treatment of the H1373 PD-L1-oe cell line with KRAS-G12C inhibitors showed an increased IC50, indicating a slight reduction in sensitivity to these inhibitors (Fig. 8B–D).

Fig. 8
figure 8

PD-L1 expression and prognosis. A Subgroup analysis of ORR by PD-L1 expression; B IC50 values of H1373-PD-L1-vector (vec) and H1373-PD-L1-overexpression (oe) cells in AMG510; C IC50 values of H1373-PD-L1-vec and H1373-PD-L1-oe cells in MRTX849; D IC50 values of H1373-PD-L1-vec and H1373-PD-L1-oe cells in JAB-21822

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Discussion

This comprehensive study pooled data from 13 studies, revealing significant response and survival benefits associated with KRAS-G12C inhibitor monotherapy. Subgroup analyses, stratified by solid tumour type and clinical and molecular baseline characteristics, identified specific populations most likely to benefit from KRAS-G12C inhibitors. Findings suggest that older patients and females tend to experience a survival advantage, while pre-treatment brain or liver metastases do not significantly impact therapeutic efficacy. KEAP1, STK11, and elevated PD-L1 expression emerged as critical adverse prognostic biomarkers, with KEAP1 mutation standing out as a primary resistance factor mediated through ECM interactions, as demonstrated in vitro.

Patients with NSCLC exhibited a superior response and greater PFS benefit compared to patients with CRC, consistent with previous studies; however, patients with CRC showed greater OS benefits. This divergence between OS and PFS outcomes may be attributed to the higher incidence of grade 3 or higher adverse events reported in the NSCLC cohort [24]. Notably, patients with CRC appeared to benefit more from the combination of KRAS-G12C inhibitors with cetuximab.

Cetuximab, an anti-epidermal growth factor receptor (EGFR) agent, blocks receptor activation by endogenous ligands, thereby inhibiting cell proliferation, promoting apoptosis, and reducing invasion and metastasis capabilities. Combination therapy with cetuximab and chemotherapy has been established as the first-line treatment standard for wild-type RAS/BRAF metastatic CRC [25]. Additionally, KRYSTAL-1 study outcomes suggest this combination therapy may counteract resistance in patients with KRAS mutation-positive CRC [26]. Feedback activation of the RAS pathway via receptor tyrosine kinases (RTKs), such as EGFR, has been identified as a mechanism limiting KRAS inhibitor efficacy and accelerating resistance development. Moreover, KRAS inhibitors may upregulate EGFR expression by downregulating MIG6, intensifying EGFR-mediated resistance [27,28,29]. The KROCUS study, presented at the 2024 ASCO annual meeting, demonstrated promising efficacy and acceptable safety of Fulzerasib in combination with cetuximab as a first-line treatment for KRAS-G12C-mutated advanced NSCLC [30]. Further research in NSCLC is necessary to establish more conclusive evidence.

KRAS-G12C inhibitors exhibited a favourable ORR in senior and female patients. Although chemotherapy combined with immunotherapy is the established first-line treatment for KRAS-mutated advanced NSCLC, elderly patients often experience treatment discontinuation or dose reductions due to adverse event intolerance [31]. Case reports have indicated that KRAS-G12C inhibitors can induce complete response (CR) lasting over six months when used as a first-line treatment [32,33,34], presenting a viable therapeutic alternative with substantial response rates. Sotorasib and Adgrasib, the first two KRAS-G12C inhibitors approved on the market, are recommended at dosages of 960 mg QD and 600 mg BID, respectively [35]. Our study found no significant difference in ORR between these regimens, indicating that both dosing schedules are effective.

Patients with baseline brain metastases commonly encounter intracranial progression during immune checkpoint inhibitor and chemotherapy (CIT) treatment; however, survival outcomes do not appear to be adversely affected by known baseline brain metastases [36]. While clinical trials specifically investigating the intracranial efficacy of KRAS-G12C inhibitors are limited—partially due to the exclusion of patients with active brain metastases—retrospective analyses from the Massachusetts General Hospital (MGH) database and the CodeBreaK 100 study have shown promising intracranial responses to Sotorasib and Adgrasib [37, 38]. However, many patients included in these analyses had received prior brain radiation, complicating the assessment of targeted therapy efficacy in KRAS-G12C-mutant patients. In a prospective evaluation within the KRYSTAL-1 trial, Adagrasib demonstrated an intracranial ORR of 42%, a DCR of up to 90%, and a median OS of 11.4 months [13]. Case studies have also reported that Sotorasib can cross the blood–brain barrier, achieving significant responses in patients with untreated brain metastases [39]. Additional robust evidence is required to comprehensively assess the intracranial efficacy of KRAS-G12C inhibitors.

Despite the advent of KRAS-G12C inhibitors, CIT remains the standard first-line treatment. Biomarkers such as STK11 and KEAP1 have been recognized as predictors of CIT resistance in KRAS-mutant patients [40]. Moreover, patients with co-mutations in STK11, KEAP1, or TP53 have shown improved survival outcomes when treated with a combination of atezolizumab (A) and/or bevacizumab (B) alongside carboplatin/paclitaxel (CP), as opposed to those receiving ACP or BCP alone [41]. However, the influence of these biomarkers on the efficacy of KRAS-G12C inhibitors remains contentious. Our meta-analysis of key clinical trials identified KEAP1 as a critical adverse prognostic biomarker, with KEAP1 co-mutations significantly correlating with reduced ORR, OS, and PFS. Cell-based experiments further confirmed an increased likelihood of early resistance among these patients. KEAP1 functions as a cytoplasmic repressor of the oxidative stress-responsive transcription factor erythroid 2-related factor 2 (NRF2), inhibiting the cystine transporter SLC7A11 and thus modulating resistance to oxidative stress. Mutations in KEAP1 result in SLC7A11 activation and upregulation of the xc- cystine/glutamate antiporter (xCT), which sustains intracellular cysteine levels to counter oxidative stress in NSCLC [42], potentially contributing to KRAS-G12C inhibitor resistance. ECM, a glycosylated extracellular protein involved in cell adhesion, is broadly expressed across tissues, including the placenta, heart, skin, and skeletal muscle [43], and plays essential roles in cell proliferation and angiogenesis [44]. ECM components have been implicated in the activation of NRF2 and mitochondrial shortening, promoting antioxidant metabolic pathways and fostering chemotherapy resistance [45]. Bioinformatics analyses reveal that ECM gene expression correlates with resistance to chemotherapy, immune checkpoint blockers (ICBs), and targeted therapies, and associates with poorer prognosis [46]. Mechanistically, ECM1 drives epithelial-mesenchymal transition, thereby accelerating tumour invasion and metastasis [47, 48].

Consistent with previous findings, no statistically significant difference in response rate was observed between patients with and without STK11 mutations. However, individuals with STK11 mutations demonstrated shorter OS in this study. Additionally, our analysis revealed that STK11 mutation correlates with resistance to various KRAS-G12C inhibitors, with a significant effect noted in the AMG510 group. Although not as influential as KEAP1, STK11 still serves as a negative prognostic biomarker for KRAS-G12C inhibitor treatment.

Prior to KRAS-G12C inhibitor availability, KRAS-G12C/TP53 co-mutated patients showed improved long-term survival with immune checkpoint inhibitor monotherapy compared to those with only KRAS-G12C mutation, likely driven by highly active IFN-γ signalling in a proinflammatory tumour microenvironment [49]. In contrast, TP53 mutations appeared to have minimal impact on survival and response to KRAS-G12C inhibitors, indicating TP53’s limited role as an efficacy biomarker for these therapies.

Patients with KRAS mutations treated with CIT regimens typically exhibit better responses and prolonged survival, particularly when PD-L1 expression levels are high [50]. Conversely, our analysis suggests that patients with low or negative PD-L1 expression may benefit more from KRAS-G12C inhibitors. Although high PD-L1 expression is often associated with an increased IC50 for KRAS-G12C inhibitors, the difference was not statistically significant. Elevated PD-L1 expression may confer some resistance to KRAS-G12C inhibitors, albeit less pronounced than the impact of KEAP1 mutations. These findings support the potential of combining KRAS-G12C inhibitors with immune checkpoint blockers to enhance efficacy and counter resistance.

In the CodeBreaK 100/101 study, 58 patients treated with Sotorasib combined with either Pembrolizumab or Atezolizumab achieved an ORR of 29% (95% CI 18–43%), a DCR of 83% (95% CI 71–91%), and an OS of 15.7 months (95% CI 9.8–17.8 months). Additionally, the combination therapy exhibited a reduced rate of adverse events, such as hepatotoxicity, due to dose reductions of the individual agents [51]. Notably, this regimen demonstrated synergistic effects in the most immunogenic tumour models. Mechanistically, KRAS-G12C inhibition suppresses Myc and enhances interferon signalling, which decreases immunosuppressive cell infiltration, promotes cytotoxic T cell activation and infiltration, and improves antigen presentation [52, 53]. However, preliminary findings indicate that KRAS-G12C inhibitors do not enhance immunotherapy susceptibility in cold tumours [54]. Ongoing clinical trials are examining the efficacy and safety of various combinations of KRAS-G12C inhibitors with ICB, and identifying subgroups likely to benefit from combination therapy remains essential prior to trial initiation.

Prior studies have analyzed adverse events related to KRAS-G12C inhibitors and investigated the impact of common co-mutations on ORR, finding no significant reduction in response among mutation-positive groups [24]. With the expansion of studies and longer follow-up duration, however, KEAP1 mutation has emerged as a definitive adverse biomarker affecting response, as well as both short- and long-term PFS and OS through its influence on cellular interactions. STK11 mutations and high PD-L1 expression similarly indicate shorter survival and earlier resistance to KRAS-G12C inhibitors.

This study has limitations. As KRAS-G12C becomes a more accessible therapeutic target, numerous inhibitors have been developed in recent years, yet comprehensive data on these newer agents remain limited. To strengthen our findings, in vitro experiments were conducted to verify the prognostic significance of key biomarkers in response to three distinct KRAS-G12C inhibitors. In addition, as the limited number of studies included in the overall and subgroup analysis, these clinical and molecular indicators serve as a clinical practice prompt rather than a decisive role. With the development of additional KRAS-G12C inhibitors globally and the execution of more randomized controlled trials (RCTs), more solid evidence is anticipated in the future.

Despite these limitations, our study offered a reference for research into the features of individuals who might benefit from KRAS-G12C inhibitor treatment. Patients with KEAP1 mutation are inclined to have a worse response and experience an early resistance. Drugs acting on ECM or affecting cell adhesion are promising to improve prognosis and we eagerly await the introduction of innovative treatment approaches after probing the intricate mechanisms of drug resistance.

Conclusion

In conclusion, this study investigated the clinical and biological characteristics of patients most likely to benefit from KRAS-G12C inhibitors and identified candidate biomarkers associated with adverse outcomes. Among these, KEAP1 emerged as the key biomarker driving treatment resistance, primarily through mechanisms involving extracellular matrix organization and cell adhesion.

Availability of data and materials

The datasets used and/or analyzed in this study are available from the corresponding authors upon reasonable request.

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Acknowledgements

We are highly grateful to the Jacobio Pharmaceuticals Group for providing JAB-21822.

Funding

This work was supported by the National Natural Science Foundation of China (82072590) and the Translational research project of Medical Oncology Key Foundation of Cancer Hospital Chinese Academy of Medical Sciences (2022-I2M-C&T-B-071).

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  1. Linyan Tian and Chengming Liu have contributed equally to this study.

Authors and Affiliations

  1. Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Linyan Tian, Huiyang Shi, Fang Wei, Wenxin Jiang, Yucheng Dong & Yan Wang

  2. Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Chengming Liu, Enzhi Yin, Nan Sun & Jie He

  3. State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Chengming Liu, Sufei Zheng, Enzhi Yin, Nan Sun & Jie He

  4. Office for Cancer Diagnosis and Treatment Quality Control, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Sufei Zheng

  5. Department of Comprehensive Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Haiyan Xu

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  1. Linyan Tian
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Contributions

Conceptualization, Yan Wang; methodology, Linyan Tian, Chengming Liu; investigation, Linyan Tian, Chengming Liu, Sufei Zheng, Huiyang Shi and Enzhi Yin; writing, Linyan Tian and Chengming Liu; funding acquisition, Yan Wang; resources, Fang Wei, Wenxin Jiang, Yucheng Dong and Haiyan Xu; supervision: Yan Wang, Nan Sun and Jie He; All authors reviewed the manuscript.

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Correspondence to Yan Wang.

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Tian, L., Liu, C., Zheng, S. et al. KEAP1 mutations as key crucial prognostic biomarkers for resistance to KRAS-G12C inhibitors. J Transl Med 23, 82 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12967-025-06089-y

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