Abstract
KRAS mutations represent the most common driver genetic alterations in multiple malignant tumors, particularly exerting well-defined oncogenic driver roles in non-small cell lung cancer, colorectal cancer, and pancreatic ductal adenocarcinoma. The recent success of KRAS G12C mutation-specific allosteric inhibitors marks a therapeutic milestone in KRAS-targeted oncology. However, the rapid emergence of drug resistance in clinical applications has significantly limited the durable efficacy of these agents. The resistance mechanisms exhibit profound complexity, encompassing multidimensional pathways such as secondary/co-occurring mutations, compensatory reprogramming of signaling pathways, cellular lineage plasticity, and immune evasion within the tumor microenvironment. Studies have demonstrated that the identification of resistance-associated biomarkers is not only of critical clinical value for predicting treatment response and early warning of resistance but also provides a key entry point for dissecting resistance mechanisms. This review systematically summarizes the latest research advances in KRAS-mutant inhibitor resistance biomarkers, with a focus on the analysis of resistance molecular mechanisms, discovery of predictive biomarkers, current limitations and challenges, and exploration of biomarker-based combination therapy strategies. By integrating basic research and clinical data, we highlight the breakthroughs required to realize the application value of resistance biomarkers and prospects future research directions and priorities, aiming to provide a biomarker-related theoretical framework for precision therapy of KRAS-mutant tumors and accelerate the clinical translation of resistance-overcoming strategies.
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1 Introduction
The rat sarcoma (RAS) viral oncogene homologue gene family, comprising three major isoforms (HRAS, KRAS, and NRAS), plays a central role in human oncogenesis as critical molecular drivers. These genes demonstrate pan-cancer mutational prevalence, with approximately 20% of solid tumors harboring somatic RAS mutations that frequently associate with adverse clinical outcomes [1,2,3]. Among the isoforms, KRAS (Kirsten rat sarcoma viral oncogene homolog) emerges as the predominant oncogenic variant, exhibiting distinct tissue-specific distribution patterns. Its mutation burden reaches > 90% in pancreatic ductal adenocarcinoma (PDAC), followed by substantial prevalence in colorectal (CRC, 30–50%) and non-small cell lung cancers (NSCLC, 20–30%). This geographic specificity underscores the unique pathogenic significance of KRAS across different tumor types [4,5,6]. At the molecular level, constitutively active KRAS mutants sustain oncogenic signaling through perpetual stimulation of downstream effector pathways. The MAPK/ERK cascade and PI3K-AKT-mTOR axis are particularly crucial mediators, orchestrating malignant proliferation and metabolic reprogramming that fuel tumor progression [7].
The pivotal role of KRAS mutants and their downstream effectors in oncogenesis has spurred extensive development of targeted inhibitors [8]. However, due to its structural complexity, lack of canonical druggable pockets, and picomolar affinity for GDP/GTP nucleotides, KRAS has long been regarded as an “undruggable” target, resulting in extremely limited therapeutic approaches targeting its mutations [9,10,11]. In past therapeutic attempts against KRAS oncogenic mutations, researchers have primarily explored strategies including interfering with its membrane localization, reducing the expression of activated KRAS proteins, disrupting the formation of KRAS effector complexes to block downstream proliferative signal transduction, and stabilizing inactive conformations of KRAS [12]. Remarkably, breakthroughs in cryo-electron microscopy and structure-based drug design have enabled precise targeting of mutation-specific conformations [13, 14]. A landmark advance came with the development of KRAS conformation-specific inhibitors (e.g., sotorasib/adagrasib)—by selectively binding to the GDP-bound state of mutant KRAS, these inhibitors have successfully achieved covalent modification of this target, demonstrating superior therapeutic potential in clinical applications for NSCLC [4, 15,16,17,18]. Notably, in data from multiple clinical studies involving patients with mutant NSCLC, including those with comparative treatments against docetaxel, sotorasib and adagrasib have demonstrated favorable confirmed objective response rates (ORR), disease control rates (DCR), and progression-free survival (PFS), along with more favorable safety profiles [19,20,21].
While the successful development of KRAS covalent inhibitors has challenged the historical perception of KRAS as an “undruggable” target, the clinical benefits of monotherapy remain substantially constrained by suboptimal objective response rates and a median progression-free survival of approximately 6 months, underscoring the critical challenge of therapeutic resistance [22, 23]. Mechanistic studies reveal that the resistance process exhibits dynamic and multi-dimensional characteristics: KRAS mutations, compensatory activation of bypass signaling, cellular phenotypic plasticity, and spatiotemporal heterogeneity in immune microenvironment remodeling. Together, these mechanisms form an evolutionary resistance network [24, 25]. Thus, elucidating the molecular underpinnings of KRAS-mutant inhibitors resistance is imperative for developing next-generation inhibitors, rationalizing combinatorial therapeutic strategies, and ultimately improving patient survival outcomes [26].
In the era of precision oncology, biomarkers are not merely critical tools but the cornerstone for unraveling therapeutic responses and resistance mechanisms to KRAS-mutant inhibitors [27]—their identification and validation are indispensable for translating mechanistic insights into clinical benefit. Innovative clinical trial designs must transcend conventional paradigms focused solely on monotherapy efficacy, instead centering on combinatorial strategies that integrate KRAS-mutant inhibitors with targeted therapies, chemotherapy, or immunotherapy—all driven by high-confidence resistance biomarkers. These biomarkers, spanning genomic, transcriptomic, and phenotypic landscapes, are pivotal: they enable early prediction of primary or acquired resistance, guide precise selection of synergistic drug combinations, and dynamically monitor treatment responses to refine personalized regimens [28,29,30]. Currently, studies on resistance mechanisms to KRAS-mutant inhibitors have revealed intricate molecular networks, yet it is the characterization of associated biomarkers that transforms this complexity into actionable knowledge [31]. Beyond deepening our understanding of tumor adaptive evolution, biomarkers serve as the bridge between bench discoveries and bedside applications—without them, even the most promising combinatorial strategies risk failure due to patient heterogeneity [32,33,34]. This review focuses on the multidimensional resistance mechanisms of KRAS-mutant inhibitors, systematically synthesizes research progress on resistance-associated biomarkers, explores key scientific questions in this field, and outlines its translational application potential in clinical precision medicine. These efforts aim to provide a solid theoretical foundation and clinical decision-making reference for optimizing treatment regimens in KRAS-mutant tumors.
2 Clinical applications and current landscape of drug resistance in KRAS mutation inhibitors
2.1 Function and mutational characteristics of KRAS
KRAS, a proto-oncogene with high mutation frequency in human malignancies, encodes a small molecular guanine nucleotide-binding protein possessing intrinsic GTPase activity [35, 36]. Under normal physiological conditions, transmembrane receptors such as epidermal growth factor receptor (EGFR), fibroblast growth factor receptor (FGFR), and human epidermal growth factor receptor 2 (HER2) activate KRAS through signaling cascades upon extracellular stimulation. Upon activation, KRAS adopts a GTP-bound active conformation that triggers critical signaling pathways including RAF-MEK-ERK and PI3K-AKT-mTOR axes, thereby precisely regulating tumor cell growth, proliferation, differentiation, and survival [9, 37, 38]. Following signal transduction, KRAS hydrolyzes GTP to GDP through its inherent GTPase activity, transitioning to an inactive conformation to terminate signaling via negative feedback regulation. This dynamic activation-inactivation cycle enables KRAS to function as a molecular switch that precisely controls signal cascade reactions [39, 40]. When KRAS undergoes mutation, its molecular switch function becomes dysregulated: mutant KRAS loses self-inactivation capacity by impairing GTP hydrolysis efficiency and nucleotide exchange kinetics, persistently maintaining a GTP-bound activated state. This leads to aberrant activation of downstream pro-growth signaling pathways, which paradoxically provide continuous proliferative signals to tumor cells while suppressing apoptosis, thereby driving tumorigenesis and progression [7, 41]. Studies confirm that KRAS hotspot mutations (e.g., G12C, G12D, G12V, G13D) universally compromise GTPase activity, locking KRAS in the active state. Notably, the KRAS G12C mutation (glycine at position 12 is mutated to cysteine) stands out as one of the most prevalent KRAS hotspot mutations, particularly prominent in NSCLC, accounting for approximately 45% of all NSCLC-associated KRAS mutations [6, 39, 42, 43]. This mutation serves as a critical driver of tumor development and progression.
2.2 Representative KRAS mutation inhibitors
2.2.1 Covalent inhibitors
Covalent inhibitors directed against the KRAS G12C variant - the predominant mutation subtype across KRAS-driven malignancies — have undergone extensive therapeutic development. These targeted agents achieve mutant-selective inactivation through irreversible covalent bonding with cysteine 12 (Cys12) in the switch II pocket, a critical regulatory domain of KRAS G12C mutants. This strategic engagement stabilizes the oncoprotein in its inactive GDP-bound conformation, effectively blocking downstream signaling transduction. Representative FDA-approved drugs, including sotorasib (AMG510) and adagrasib (MRTX849), selectively stabilize KRAS G12C in its inactive GDP-bound state, thereby blocking downstream signaling activation and suppressing tumor growth [44, 45]. Clinical trial data demonstrate that both sotorasib and adagrasib exhibit superior antitumor activity and acceptable safety profiles in patients with advanced solid tumors harboring KRAS G12C mutations, particularly in NSCLC [21, 46, 47]. However, these inhibitors are exclusively effective against G12C-mutant cancers and show no efficacy in malignancies driven by other KRAS mutations [48]. Additionally, their therapeutic outcomes vary significantly across tumor types: while demonstrating favorable efficacy in NSCLC, both agents exhibit limited responses and high rates of acquired resistance in CRC [49, 50]. This discrepancy may stem from CRC-specific resistance mechanisms, such as reactivation of the EGFR pathway, compensatory activation of the PI3K/AKT axis, and aberrant KRAS protein localization [51].
2.2.2 Allosteric inhibitors
The successful development of covalent KRAS G12C inhibitors has validated the therapeutic potential of the switch II domain in the RAS family as a druggable target [52]. However, although covalent inhibitors have revolutionized the treatment of G12C-mutant cancers, their utility is restricted to this single mutation subtype due to their reliance on forming covalent bonds with the unique cysteine residue at position 12 — highlighting the need for broader-acting agents. Unlike mutation-specific inhibitors that directly target this site, allosteric inhibitors bind to allosteric regulatory sites (non-catalytic regions) of KRAS, inducing conformational changes to indirectly suppress its functional activity. They avoid covalent modifications of specific mutant residues but instead stabilize inactive conformations of KRAS and block effector protein engagement, enabling broad-spectrum inhibition across diverse KRAS mutant subtypes and effectively overcoming the mutation — type limitations of traditional covalent inhibitors [53, 54]. Allosteric targeting of conserved structural domains (switch I/II) is critical to achieving this goal: because these regions exhibit structural conservation across KRAS mutants and RAS isoforms, inhibitors binding here could bypass the mutation-specific restrictions of covalent agents. Compound BI2852, developed through structure-based drug design, targets the switch-I/II domain of KRAS, disrupting interactions with all effector molecules and thereby achieving concomitant suppression of downstream signaling pathways [55, 56]. The pan-RAS monoclonal antibody JAM20 demonstrates nanomolar affinity binding to the conserved switch I/II domain, while exhibiting broad-spectrum inhibitory activity against KRAS, NRAS, and HRAS isoforms. This cross-isoform targeting capability leads to significant suppression of RAS-driven oncogenic signaling and tumor progression [57]. Compared to covalent inhibitors, allosteric agents offer key advantages: they cover most KRAS mutations via conserved domains (not mutation-specific residues), eliminate reliance on rare residue modifications, and may reduce resistance from target residue secondary mutations—a challenge for covalent inhibitors. These findings demonstrate that targeting the switch I/II domain not only applies to RAS in distinct activation states but also establishes a new paradigm for developing pan-RAS inhibitors capable of covering all RAS family isoforms [58,59,60].
2.3 Clinical drug resistance phenomenon and its impacts of KRAS-mutant inhibitors
Although inhibitors targeting KRAS-mutant proteins have achieved groundbreaking progress in clinical applications, their therapeutic efficacy remains significantly constrained by acquired resistance. Clinical data reveal that KRAS G12C inhibitor monotherapy yields a median progression-free survival of approximately 6 months in NSCLC patients, while this metric drops to around 3 months in CRC patients-a disparity reflecting the complexity of distinct tumor microenvironments and resistance mechanisms [49, 61]. Notably, in PDAC, where KRAS mutations (predominantly G12D) are nearly ubiquitous (> 90%), responses to KRAS-targeted therapies are even more limited [62]. Regarding the temporal window of resistance development, disease progression typically emerges during early to mid-treatment phases, with some patients showing signs of progression within weeks of initiating KRAS-targeted therapy. In preclinical patient-derived xenograft, genetically engineered mouse and cell line models have shed light on the rapid onset of resistance: for instance, In cells and tumor xenograft models harboring KRAS G12V mutations, KRAS G12V mutations can induce PD-L1 expression via the transforming growth factor-β/epithelial-mesenchymal transition (TGF-β/EMT) signaling pathway and promote immune evasion in KRAS-mutant non-small cell lung cancer [63,64,65]. Clinically, worsening tumor-related symptoms such as aggravated pain and declining performance status often accompany resistance, necessitating timely adjustment of therapeutic strategies through radiographic assessment and molecular profiling [49, 50]. To address these challenges, next-generation highly selective KRAS-mutant inhibitors and diverse combination regimens are under active clinical investigation [52]. Moving forward, breakthroughs in elucidating resistance mechanisms, coupled with the establishment of early biomarker screening and dynamic monitoring systems, will be pivotal in improving patient prognosis and extending survival.
3 Biomarkers of therapeutic resistance to KRAS-mutant inhibitors
3.1 Biomarkers based on resistance mechanisms of KRAS-mutant inhibitors
The emergence of resistance to KRAS-mutant inhibitors manifests profound interpatient and intratumoral heterogeneity, driven by multidimensional adaptive mechanisms spanning including KRAS secondary mutations, compensatory bypass signaling activation, tumor microenvironment crosstalk, and epigenetic reprogramming. Within this complex landscape, the precise identification of predictive biomarkers has emerged as a cornerstone for optimizing therapeutic strategies: these biomarkers not only provide molecular insights into resistance mechanisms but also form the foundation for developing personalized combination therapies. In the following sections, we systematically summarize current key biomarkers based on molecular pathways of KRAS-mutant inhibitors resistance and evaluate their clinical translational potential, aiming to provide novel perspectives for resistance surveillance and precision intervention.
3.1.1 Biomarkers for secondary mutations and KRAS-mutant amplification
In primary resistance mechanisms, secondary mutations of KRAS play a pivotal role in driving resistance to KRAS-mutant inhibitors. These mutations impair drug efficacy by disrupting the inhibitor-binding pocket or enhancing nucleotide exchange activity, thereby compromising therapeutic effects [66]. Mutations occurring in the switch II pocket or allosteric binding sites of KRAS (e.g., G12C to G12D/V/R/W substitutions) abolish covalent binding to cysteine residues, while mutations such as K16T, Y96C/D, and R68S reduce drug affinity through structural alterations of the binding pocket, collectively conferring varying degrees of resistance to KRAS G12C inhibitors [28, 67, 68]. Furthermore, KRAS-mutant copy number amplification has emerged as a key driver of drug resistance, typically driven by chromosomal instability, defective DNA replication checkpoints, or errors in mitotic segregation. These processes lead to the emergence of extra copies of the KRAS locus, thereby increasing transcription and overexpression of KRAS mutant protein. Specifically, amplification-induced overexpression of KRAS mutants could drive sustained activation of downstream oncogenic signaling pathways: including the MAPK pathway and the PI3K/AKT/mTOR axis by increasing the pool of active KRAS-GTP. This hyperactivation promotes critical hallmarks of cancer, such as uncontrolled proliferation, evasion of apoptosis, and enhanced cell survival [6, 32, 64]. Notably, KRAS-mutant amplification has been shown to exacerbate resistance to anti-EGFR therapies, particularly in CRC, where its presence significantly diminishes response rates [44]. Clinically, the emergence of KRAS mutations in circulating tumor DNA (ctDNA) correlates strongly with poor prognosis. Dynamic monitoring of KRAS mutation allele frequency during treatment provides real-time tumor burden assessment, enabling timely therapeutic adjustments [69, 70]. To address these challenges, the detection of resistance-associated biomarkers-including secondary KRAS mutations (e.g., G12D/R/V/W, G13D, Q61H, R68M/S, H95D/Q/R, Y96C/D/S) and high-level KRAS-mutant allelic amplification in tumor tissues or liquid biopsies-serves as critical negative predictors for resistance surveillance [64, 71, 72].
3.1.2 Biomarkers of bypass signaling pathway activation
Beyond the KRAS-centric genetic alterations discussed above, bypass signaling activation also constitutes a central adaptive resistance mechanism to KRAS-mutant inhibitors, wherein tumors dynamically rewire oncogenic dependencies through compensatory activation of parallel signaling axes to sustain critical survival signaling (Fig. 1).
On one hand, this involves compensatory activation of upstream receptor tyrosine kinases (RTKs): tumor cells achieve direct activation of the PI3K/AKT/mTOR or RAS/RAF/MEK/ERK pathways through genetic amplification of receptors such as EGFR, HER2, MET, AXL and FGFR, or activating mutations (e.g., HER2 V777L), and ligand overexpression (e.g., EGF, HGF) [64, 73,74,75]. For example, approximately 30% of resistant patients treated with KRAS G12C inhibitors develop EGFR extracellular domain amplification, leading to reduced cetuximab binding but sustained kinase activity [76, 77]. Notably, the activation-inactivation dynamics of KRAS are enzymatically regulated by diverse factors, and targeting these regulators provides an indirect strategy to modulate KRAS activity. Among these, Son of sevenless (SOS) and SH2-containing protein tyrosine phosphatase 2 (SHP2)—acting as critical signaling hubs downstream of RTKs — cooperatively drive persistent KRAS-GTP activation and downstream signaling propagation, playing a pivotal role in feedback-driven adaptive resistance to KRAS-mutant inhibitors. Following KRAS-mutant inhibitors treatment, tumors frequently reactivate RAS proliferative signaling through SHP2/SOS upregulation and RTK feedback activation, thereby driving therapeutic resistance [22]. It has been reported that SHP2 promotes resistance to adagrasib in KRAS G12C-driven lung cancer cells by regulating the β-catenin/c-MYC axis [78].
On the other hand, it involves activating alterations in downstream signaling nodes: mutations in other RAS family members such as NRAS (Q61K), HRAS (G13R), or functional variants in pathway components like BRAF (V600E) and MEK1/2 (K57T/N) directly reinitiate RAS-MAPK signaling [63, 64]. Additionally, loss-of-function mutations in PTEN or PIK3CA activating mutations specifically enhance PI3K/AKT pathway activity by phosphorylating AKT, which inhibits apoptosis and promotes glycolytic metabolic reprogramming to facilitate tumor cell survival [79,80,81]. RAS GTPase-activating proteins (RAS-GAPs) are key negative regulators of the RAS signaling pathway. It inactivates RAS by catalyzing the hydrolysis of GTP to GDP, thereby terminating downstream signal transduction. In contrast, inactivating mutations or epigenetic silencing of RAS-GAPs lead to sustained activation of RAS and promoted tumorigenesis. Consequently, NF1 mutation status commonly serves as a biomarker for predicting responses to KRAS-mutant inhibitors in clinical practice [64, 82]. Furthermore, these molecular alterations that drive bypass signaling activation represent a key class of resistance biomarkers in tumors treated with KRAS-mutant inhibitors. To address the intricate resistance networks orchestrated by signaling plasticity, multidimensional omics profiling that integrates genomic, transcriptomic, and proteomic platforms enables longitudinal mapping of adaptive signaling trajectories and early detection of resistance evolution.
Taking KRAS G12C as an example, this schematic delineates critical biomarkers underlying genetic resistance mechanisms (KRAS-centric variants, upstream bypass activation, alterations in key regulators of intermediate signaling, and reactivation of downstream pathways) to KRAS G12C inhibitors
3.1.3 Co-mutation biomarkers
Co-mutations in key genes such as KEAP1, STK11, CDKN2A, TP53, and SMAD4 are significantly associated with intrinsic resistance to KRAS mutant inhibitors. These genetic alterations synergistically drive resistance development through multidimensional mechanisms, including activation of bypass signaling and remodeling of the immune microenvironment [66, 83, 84]. Among these, KEAP1 and STK11 mutations hold significant clinical relevance in NSCLC: Studies have confirmed that the concurrent presence of KEAP1 and KRAS mutations leads to significantly reduced response rates to immune checkpoint inhibitors, suggesting their role as potential biomarkers for predicting resistance to immunotherapy combination strategies [85, 86]. Additionally, KEAP1 mutations activate the NRF2 antioxidant stress pathway, which synergizes with STK11 mutations to accelerate early-onset resistance to KRAS G12C inhibitors [87, 88]. In a prospective study of advanced KRAS-mutant NSCLC, KRAS/SMAD4 co-mutations have been validated as independent poor prognostic factors [89]. CDKN2A deletions enhance adaptive resistance to KRAS-mutant inhibitors by deregulating cell cycle control in tumor cells [90, 91]. Furthermore, the tumor suppressor gene TP53 (encoding p53 protein) is frequently mutated across multiple cancer types and is closely associated with therapeutic resistance. Loss-of-function mutations in TP53 drive resistance to KRAS-mutant inhibitors through multidimensional mechanisms, including genomic instability, apoptosis resistance, compensatory pathway activation, and immune evasion. Clinically, integrating TP53 mutation status with KRAS variant profiling enhances the predictive accuracy of KRAS-mutant inhibitor response [72, 92]. In a prospective analysis of sequencing data from CRC patients, the mutation rates of TP53 and KRAS were 81.91% and 43.62%, respectively. Tumor mutational burden driven by such co-mutations may hold potential as a key biomarker for predicting treatment outcomes in CRC patients [93]. Taken together, combined detection of these co-mutated genes via next-generation sequencing not only facilitates precise assessment of patient responsiveness to KRAS-mutant inhibitors and immunotherapy but also provides clinicians with more comprehensive prognostic information for individualized care.
3.1.4 Tumor microenvironment-associated biomarkers
The remodeling of the tumor immune microenvironment also plays a critical role in the resistance mechanisms of KRAS-mutant inhibitors. Studies have shown that KRAS inhibition therapy may drive tumor cell immune evasion by altering antigen expression on the surface of tumor cells and suppressing the activity of tumor-infiltrating lymphocytes [87, 94]. Additionally, changes in the expression of immune checkpoint molecules are part of the resistance mechanisms: KRAS-mutant inhibitors use could lead to upregulation of molecules such as programmed death-ligand 1(PD-L1), which further suppresses T-cell immune activity and enables tumors to effectively escape immune surveillance. As a key biomarker in immunotherapy, PD-L1 expression levels have been widely studied across multiple cancer types [81, 95]. Notably, in KRAS-mutant NSCLC patients, PD-L1 upregulation or T-cell exhaustion markers (e.g., TIM-3, LAG-3) are associated with resistance to combinations of immunotherapy and KRAS-mutant inhibitors [21, 96, 97]. Among them, the M2-type polarization marker—CD206+ in tumor-associated macrophages is highly expressed (promoting the formation of an immunosuppressive microenvironment) [98]. As it is associated with PD-L1 upregulation and T-cell exhaustion, it is also considered an immunosuppression-related biomarker [99]. More importantly, localizing these immune checkpoint molecules is a critical step in dissecting the characteristics of the tumor immune microenvironment and guiding immunotherapeutic strategies. By integrating techniques including immunohistochemistry, immunofluorescence, flow cytometry, and digital spatial profiling, their expression locations, cellular origins, and functional associations are clarified from the level of tissue spatial distribution to single-cell phenotypes, enabling the construction of a comprehensive expression profile to support precise target selection in immunotherapy. For these checkpoint molecules, therapeutic targeting is typically achieved by disrupting their inhibitory signaling. For instance: For PD-L1, monoclonal antibodies (e.g., atezolizumab, durvalumab) block its interaction with PD-1 on T cells, reversing T-cell suppression. For T-cell exhaustion markers such as TIM-3 and LAG-3, the development of targeted antibodies (e.g., cobolimab for TIM-3, relatlimab for LAG-3) restores effector T-cell function by interfering with their binding to ligands [100,101,102].
Furthermore, the hepatocyte growth factor (HGF)/mesenchymal-epithelial transition factor (MET) axis emerges as a pivotal adaptive resistance mechanism to KRAS-mutant inhibitors, driven by dynamic microenvironmental crosstalk. Specifically, central to this bypass signaling is ligand-dependent activation of the MET receptor tyrosine kinase: binding of HGF induces MET homodimerization and transphosphorylation at tyrosine residues, which recruits adaptor proteins to activate parallel pro-survival cascades such as PI3K/AKT/mTOR and RAS/RAF/MEK/ERK, thereby bypassing the inhibitory effects of targeted drugs [103, 104]. Activation of the HGF/MET axis is frequently observed in resistance to various targeted therapies (e.g., combination therapies with EGFR or KRAS G12C inhibitors), with relevant biomarkers including MET gene amplification, exon 14 skipping mutations, and HGF/MET protein overexpression [105,106,107].
In summary, the reconfiguration of the tumor immune microenvironment establishes a tripartite resistance network through interconnected mechanisms of immune evasion, checkpoint receptor activation, and compensatory signaling bypasses. Multidimensional characterization of associated biomarkers—including PD-L1/TIM-3/LAG-3 expression landscapes, CD206+ tumor-associated macrophage infiltration gradients, and molecular aberrations in the HGF/MET axis — may enable systematic identification of therapeutic vulnerabilities. Such analyses could facilitate the design of precision-driven combination strategies, integrating immune checkpoint blockade, macrophage polarization reprogramming, and pathway-specific kinase inhibition to disrupt this adaptive resistance network.
3.1.5 Biomarkers associated with cell fate transition and phenotypic remodeling
Cellular lineage plasticity refers to the ability of tumor cells to dynamically transition between different phenotypic states; this transition is independent of genetic mutations, enabling them to evade targeted therapies. In KRAS-mutant cancers, such plasticity is increasingly recognized as a key non-genetic mechanism of drug resistance. Preclinical studies have shown that KRAS mutant inhibitors can trigger transcriptional reprogramming in tumor cells, activating lineage-specific transcription factors, which in turn drive lineage transitions [38, 108]. Among these resistance patterns, adenocarcinoma-to-squamous transition (AST) represents the most prominent paradigm, characterized by significant upregulation of squamous epithelial marker transcription factors such as ΔNp63, SOX2, and KRT5/14 [83, 109]. These core regulatory factors not only drive tumor cell lineage reprogramming but also confer resistance to KRAS-mutant inhibitors through activation of downstream pro-survival signaling pathways [83]. EMT also plays a pivotal role in KRAS-mutant inhibitor resistance. Studies demonstrate that KRAS G12C inhibitors could induce EMT via PI3K pathway activation, thereby endowing tumor cells with enhanced proliferative and invasive capabilities - a fundamental mechanism underlying both intrinsic and acquired resistance [110, 111]. This process shows significant correlation between upregulated expression of EMT core markers (e-cadherin, vimentin) and drug-resistant phenotypes [112, 113]. Therapeutic targeting of key EMT regulators or associated signaling pathways may thus emerge as novel strategies to overcome the resistance of KRAS-mutant inhibitors [114]. Furthermore, adenocarcinoma-to-neuroendocrine (NE) transdifferentiation is observed in KRAS-mutant NSCLC patients treated with KRAS inhibitors. This transition is driven by the upregulation of neuroendocrine lineage transcription factors such as ASCL1, NEUROD1, and INSM1, which suppress epithelial programs and activate a neuroendocrine gene signature (e.g., chromogranin A, synaptophysin), resulting in reduced drug sensitivity by decoupling KRAS signaling from downstream proliferative pathways [64, 115]. Collectively, cellular plasticity mediated by AST, EMT, or NE transdifferentiation constitutes a key mechanism of drug resistance in KRAS-mutant cancers. Biomarkers associated with these transitions hold promise for guiding patient stratification, while combinatorial strategies that co-target both KRAS and plasticity drivers may enhance therapeutic outcomes.
3.1.6 Metabolic reprogramming biomarkers
Metabolic remodeling induced by KRAS-mutant inhibition emerges as a pivotal adaptive mechanism driving drug-resistant tumor cell survival. Emerging research highlights that pharmacological inhibition of KRAS triggers profound reprogramming of metabolic phenotypes, whereby cancer cells adapt to therapeutic stress by rewiring core energy metabolic pathways, including upregulated glycolytic flux and enhanced fatty acid metabolism, to sustain bioenergetic homeostasis under drug pressure [116, 117]. This metabolic reprogramming is intrinsically linked to cellular proteostasis, achieved primarily through the differential regulation of key metabolic enzymes. Significantly, the subcellular relocalization of proteins (e-cadherin and scribble) activates YAP signaling, thereby promoting cell survival and proliferation [61, 118]. As a core adaptive mechanism by which cells respond to therapeutic stress, molecular features associated with metabolic reprogramming possess dual clinical value: the abnormally high expression of key metabolic enzymes (e.g., HK2, GLS1) and concentration changes in signature metabolites (e.g., lactate, glutamine) not only serve as biomarkers for predicting drug resistance, but the metabolic pathways they mediate (e.g., glycolysis, glutaminolysis) also emerge as potential therapeutic targets [119,120,121].
Based on the above descriptions and introductions, we systematically summarize the principal resistance biomarkers associated with KRAS-mutant inhibitors, covering their molecular mechanisms and detection methodologies (Table 1). Core technologies include: Next-generation sequencing (NGS) for comprehensive profiling of mutations, indels, copy number variations, and fusion genes; Fluorescence in situ hybridization (FISH) to validate gene amplifications/deletions; Immunohistochemistry (IHC) assessing protein activation; Droplet digital PCR (ddPCR) enabling ultrasensitive detection of low-frequency resistance mutations; and multiplex immunofluorescence (mIF) for spatial immunophenotyping of the tumor microenvironment. Critically, ctDNA-based dynamic monitoring (NGS/ddPCR) permits real-time tracking of resistance evolution (such as KRAS secondary mutations and RTK amplifications). In summary, the optimal detection method should be selected for different clinical application scenarios (Table 2).
3.2 Biomarkers based on bioinformatics and high-throughput technology research
Beyond the previously discussed biomarkers linked to KRAS-mutant inhibitors resistance mechanisms, recent breakthroughs in clinical bioinformatics analysis, multi-omics sequencing (encompassing genomics, transcriptomics, and proteomics), and functional experimental validation have uncovered several promising individual biomarkers capable of predicting resistance to KRAS-mutant inhibitors [122].
A systematic meta-analysis and validation study revealed that KEAP1 mutations serve as a key negative prognostic factor in specific patient subgroups, establishing KEAP1 as a critical biomarker for predicting resistance to KRAS G12C inhibitors [123]. In KRAS-mutant lung cancer, elevated FGL1 expression negatively correlates with CD8+ T-cell infiltration, positioning FGL1 as a potential diagnostic biomarker. Targeting the YAP-FGL1 axis has been shown to enhance the efficacy of anti-PD-1 immunotherapy [124]. Additionally, tissue factor (TF) is highly expressed in KRAS-mutant NSCLC, with the TF/mTORC2 axis identified as a novel mechanism driving immunosuppression and KRAS G12C resistance [125]. Transcriptomic and epigenomic analyses further demonstrated that KRT6A expression levels effectively predict treatment response to KRAS-mutant inhibitors in lung adenocarcinoma patients, offering a predictive biomarker for KRAS-targeted therapy [83]. In pancreatic ductal adenocarcinoma with KRAS G12C mutations, upregulated RPS3 expression correlates with poor patient prognosis. Mechanistically, RPS3 promotes sotorasib resistance by inhibiting apoptosis through interactions with MDM2/MDM4, highlighting its potential as a resistance biomarker [27]. Moreover, the inflammatory chemokines CXCL1 and CXCL5 play significant roles in various cancers. Elevated serum levels of CXCL1/CXCL5 are associated with drug resistance in KRAS-mutant tumors, suggesting their utility in monitoring treatment response and predicting resistance. As accessible blood-based biomarkers, CXCL1 and CXCL5 hold promise for future clinical applications in personalized therapy [51].
Multi-omics profiling has emerged as pivotal methodologies in cancer resistance research, substantially enhancing our mechanistic understanding while simultaneously uncovering novel biomarker candidates for therapeutic development. Lin et al. [126] conducted comprehensive analysis of publicly available sequencing data from AMG510-resistant cases, identifying critical resistance-associated molecules including SLC2A1, TLE1, and FAM83A. These molecules demonstrate significant modulation of multiple signaling pathways and tumor microenvironment components, establishing their potential as biomarkers for KRAS-mutant inhibitor resistance. A sequencing analysis revealed that aldehyde dehydrogenase 1 family member A1 (ALDH1A1) - a key enzyme in retinoic acid biosynthesis and redox homeostasis - exhibits marked upregulation in response to KRAS-mutant inhibition and mediates cross-cancer resistance [127]. Clinical genomic investigations of KRAS G12C-mutant PDAC patients treated with adagrasib or sotorasib identified characteristic acquired resistance alterations, including secondary PIK3CA and KRAS mutations, genomic amplifications of KRAS G12C, MYC, MET, EGFR, and CDK6 [128]. Proteomic and phosphoproteomic profiling of KRAS G12C cell lines and lung tumor tissues revealed markers associated with high-level epithelial subtype ERBB2/3 signaling and mesenchymal subtype FGFR1/AXL signaling [129]. Collectively, by comparing gene expression profiles between drug-resistant and sensitive cells, researchers were able to identify a series of upregulated or downregulated genes that may provide a biological marker basis for drug resistance. A genomic sequencing analysis aggregating individual patient data from 143 patients observed a highly diverse genomic landscape, such as acquired amplifications or copy number gains of the KRAS, activating mutations in the KRAS kinase domain, switch-II pocket mutations that affect the binding site of first-generation KRAS G12C inhibitors, mutations in NRAS/HRAS subtypes [130]. These multi-omics approaches collectively provide a robust biological marker framework for understanding and targeting KRAS-mutant inhibitors resistance.
4 Clinical application and translation of biomarkers
Advances in elucidating KRAS-mutant inhibitor resistance mechanisms and their associated biomarkers have positioned the clinical validation and translational implementation of these biomarkers as a pivotal breakthrough strategy to overcome precision oncology bottlenecks. Current studies are focusing on developing detection strategies with high sensitivity and specificity, aiming to achieve precise prediction and intervention of resistance through multidimensional data integration. Notably, the value of biomarkers extends across the entire treatment cycle of KRAS-mutant inhibitors, thereby forming a closed-loop management system of “prediction-monitoring-intervention”.
4.1 Stratified practice of clinical application scenarios
For baseline assessment before treatment, multidimensional biomarker analysis can identify potential responsive populations and optimize initial treatment strategies. Clinical evidence shows that NSCLC patients with STK11/LKB1 co-mutations exhibit a significantly limited objective response rate to monotherapy with KRAS G12C inhibitors, whereas combination therapy with KRAS-mutant inhibitors and PD-1 blockade (e.g., adagrasib and nivolumab) significantly enhances efficacy-this establishes the clinical value of STK11 mutation status as a stratification biomarker for immune combination therapy [131]. Additionally, patients with high PD-L1 expression or enriched CD8+ T cell infiltration in the tumor microenvironment are more likely to benefit from the synergistic effects of KRAS-mutant inhibitors and immune checkpoint inhibitors [132, 133]. Detecting the activation status of the HGF/MET axis can also guide the combination of KRAS-mutant inhibitors with MET-targeted agents [134].
During dynamic monitoring of treatment, liquid biopsy can real-time capture resistance-related molecular events. In the KRYSTAL-1 trial, ctDNA analysis revealed that among colorectal cancer patients with KRAS G12C mutations, those developing NRAS/EGFR mutations demonstrated an improved objective response rate when treated with the combination of adagrasib and cetuximab [63, 135]. Additionally, a sudden increase in plasma levels of EGFR ligands (such as amphiregulin and epiregulin) often signals EGFR bypass activation-mediated resistance [136, 137]. Studies in colorectal cancer have shown that timely initiation of salvage regimens combining KRAS-mutant inhibitors with EGFR-TKIs (afatinib) confers more significant clinical benefits [138].
Molecular profiling informed by resistance biomarkers enables rational optimization of intervention strategies through mechanism-adaptive regimen selection. For instance, in cases of “genome-driven resistance” (e.g., secondary KRAS G12C to KRAS G12V mutations), next-generation pan-KRAS-mutant inhibitors (MRTX1257) or targeting synthetic lethal pathways (e.g., CDK4/6 inhibitor abemaciclib) may be explored [139,140,141]. In contrast, for “microenvironment-regulated resistance” (TGF-β pathway activation), combining KRAS-mutant inhibitors with TGF-β receptor antagonists (galunisertib) could restore tumor sensitivity to KRAS-mutant inhibitors. Notably, in neoadjuvant therapy for rectal cancer, galunisertib combined with chemoradiotherapy achieved a 32% complete response rate (NCT02688712), highlighting the potential of TGF-β blockade in overcoming microenvironment-mediated resistance [142].
4.2 Biomarker-guided strategies in combination therapy
In clinical practice to overcome tumor resistance, the precise detection of biomarkers provides a critical breakthrough for developing personalized therapeutic strategies. Taking KRAS G12C-mutated tumors as an example, combination targeted therapy has emerged as a core strategy to address both primary and acquired resistance to KRAS-mutant inhibitors, based on in-depth understanding of the underlying resistance mechanisms. Studies indicate that compensatory activation of the EGFR signaling pathway is a key mechanism of resistance to KRAS G12C inhibitors, and the combination of KRAS G12C inhibitors with EGFR-targeted agents (e.g., cetuximab) has demonstrated synergistic efficacy in clinical trials [49, 143]. Notably, in patients with KRAS G12C-mutated colorectal cancer, combination regimens significantly improved the objective response rate compared to monotherapy (46% in a KRYSTAL-1 study-NCT03785249). Longitudinal biopsy analyses of lung cancer patients progressing on sotorasib treatment revealed that HER2 amplification mediates resistance via activation of the MAPK signaling pathway. Preclinical studies confirmed that combining KRAS G12C inhibitors with SHP2 inhibitors (e.g., RMC-4630) effectively blocks HER2-driven resistance signals, demonstrating marked synergistic antitumor activity in both in vitro and in vivo models [124, 144]. Additionally, in resistance cases associated with NRAS/BRAF mutations, these genetic alterations lead to bypass signaling escape by activating the MEK-ERK axis. Co-administration of MEK inhibitors (e.g., trametinib, cobimetinib) suppresses downstream signaling and successfully reverses resistance phenotypes in preclinical models [145].
Dynamic combination strategies stratified by resistance mechanisms (e.g., KRASi + EGFRi, KRASi + SHP2i, KRASi + MEKi) have advanced into multiple clinical trials (e.g., NCT04449874, NCT05074810, NCT04185883, NCT04585035), offering a novel translational paradigm to overcome the limitations of KRAS-targeted therapies. While combination strategies demonstrate enhanced synergistic efficacy, they concurrently introduce heightened complexity and the potential for overlapping or novel toxicities. Clinical evidence illustrates this challenge: In trials combining SHP2 inhibitors with KRAS G12C inhibitors, frequent treatment-related adverse events (TRAEs) include peripheral edema, neutropenia, and thrombocytopenia (NCT04699188). The toxicity burden appears even more significant with KRAS G12C inhibitor-immunotherapy combinations; notably, concurrent administration of sotorasib with pembrolizumab or atezolizumab resulted in grade 3–4 TRAEs in 72% of patients [146]. Additionally, synergistic use of MEK inhibitors with KRAS G12C inhibitors is frequently associated with diarrhea, rash, and nausea (NCT04185883). Collectively, these safety challenges and complexities underscore the critical need for refined biomarker-guided risk-benefit assessments to optimize therapeutic utility. Consequently, ongoing trials aim not only to evaluate efficacy but also to define manageable toxicity profiles through careful dose escalation and schedule optimization [33].
5 Challenges and difficulties
Despite transformative breakthroughs in KRAS-targeted therapies offering promising hope for patients with KRAS-mutated tumors, primary and acquired resistance remain central bottlenecks limiting their clinical benefits. While multiple candidate resistance biomarkers with clinical translational potential have been identified, the systematic application of these biomarkers still faces critical challenges, including spatiotemporal heterogeneity and stability of resistance mechanisms, limitations in biomarker detection technologies, and gaps in clinical validation frameworks [81].
5.1 Heterogeneity of KRAS-related resistance biomarkers
Tumor heterogeneity manifests as multidimensional differences in genomic, transcriptomic, and phenotypic features among cells within the same tumor mass, serving as a hallmark driving tumor evolution and therapeutic resistance [147]. This dynamic heterogeneity not only influences tumor biological behavior but also complicates the detection and clinical application of biomarkers. For KRAS mutations, their biological effects and resistance biomarker profiles exhibit significant cancer type-specific variations across solid tumors [148]. The impact of KRAS mutations and their associated resistance mechanisms differ markedly among tumor types such as NSCLC, CRC, and PDAC. In NSCLC, studies reveal that KRAS G12C mutations frequently co-occur with STK11/LKB1 inactivation mutations. These co-mutations activate the KEAP1/NRF2 oxidative stress pathway and induce phenotypic plasticity, leading to a increase in primary resistance rates to KRAS-mutant inhibitors [88]. In CRC, KRAS mutations are not only markers of poor prognosis but also critical drivers of resistance to anti-EGFR therapies (e.g., cetuximab). When KRAS mutations co-occur with BRAF or PIK3CA mutations, synergistic resistance effects emerge through dual activation of the MAPK and PI3K-AKT-mTOR pathways [69, 87, 149]. In PDAC, KRAS mutations remodel the tumor metabolic microenvironment and induce stem cell-like properties, resulting in broad resistance to chemotherapy (e.g., gemcitabine) and targeted therapies. Single-cell sequencing has uncovered that KRAS-mutant subclones secrete TGF-β to activate surrounding stellate cells, forming physical/biochemical barriers that exacerbate drug resistance [150]. Taken together, KRAS mutational status plays a pivotal role in tailoring therapeutic strategies across cancer types. To enhance treatment efficacy, it is imperative to deeply understand the cancer type-specific resistance biomarkers associated with KRAS mutations when designing personalized regimens. Integrating multi-omics profiling and dynamic monitoring of resistance mechanisms will be key to overcoming heterogeneity-driven therapeutic challenges.
5.2 Limitations of biomarker detection technologies
The detection of KRAS resistance biomarkers faces multiple technical limitations, including the spatiotemporal heterogeneity of tissue biopsies (which fail to comprehensively capture dynamically evolving resistant subclones), insufficient sensitivity of liquid biopsies, high costs and technical complexity of single-cell and spatial omics technologies, and the lack of standardized clinical validation frameworks [151, 152]. Furthermore, certain resistance mechanisms involve protein expression or phosphorylation state alterations (e.g., HER2/MET protein overexpression), which cannot be fully assessed by DNA sequencing alone [153]. These challenges result in delayed resolution of resistance detection compared to clinical needs. Thus, future advancements require multimodal dynamic monitoring, development of cost-effective high-throughput technologies, and cross-platform standardization to drive the clinical translation of precision detection strategies.
5.3 Shortcomings in clinical validation systems and biomarker stratification
Even when potential biomarkers are identified, their clinical utility is constrained by the high heterogeneity of patients’ molecular contexts, tumor microenvironments, and treatment histories, as well as the limited sample sizes of study cohorts. For example, molecular events associated with resistance to KRAS G12C inhibitors, such as NF1 deletions or PTEN mutations, exhibit significant variability in predictive power across cancer types [64, 154]. While these biomarkers serve as negative predictors of therapeutic response in NSCLC, their relevance in CRC is attenuated due to divergent pathway compensation mechanisms. Specially, the overall prevalence of such biomarkers is generally low, resulting in insufficient statistical power. Furthermore, longitudinal monitoring of resistance biomarkers often requires repeated invasive procedures or frequent liquid biopsies, leading to poor patient compliance in real-world clinical settings [155]. Most current studies are based on retrospective analyses or small sample cohorts, lacking prospective multicenter data validation, thus leading to inadequate evidence levels for biomarker grading systems [156].
6 Future research directions and innovations
To realize the clinical utility of KRAS-mutant inhibitor resistance biomarkers, future research must prioritize addressing current challenges including inadequate resolution of heterogeneity, lagging detection technologies, and lack of clinical validation. This may be achieved through interdisciplinary technological integration and mechanistic innovation to advance the clinical translation of precision resistance management. Moving forward, future research directions should primarily focus on the following core areas:
6.1 Strategies for the discovery of novel biomarkers
In targeted therapy for KRAS-mutated solid tumors, the discovery and validation of novel biomarkers represent a core for overcoming drug resistance. By longitudinally sampling patient-derived specimens and integrating genomics, epigenomics, proteomics, and metabolomics data, comprehensive landscapes of resistance evolution can be constructed to further dissect the multidimensional drivers of resistance mechanisms [157,158,159]. Single-cell multi-omics technologies enable deep characterization of transcriptional regulatory network heterogeneity in resistant subclones, while spatial transcriptomics precisely maps interaction hubs between resistant cells and stromal-immune components within the tumor microenvironment [160]. Additionally, with the advancement of novel AI technologies, AI-driven predictive models (such as deep neural networks and random forest algorithms) efficiently mine latent resistance-associated molecular signatures from multi-omics datasets [158]. These efforts, combined with functional organoid platforms and CRISPR screening technologies, will facilitate rapid identification of druggable targets [140, 161].
6.2 Clinical translational application
The future clinical translation of KRAS-mutant inhibitors resistance biomarkers will center on advancing dynamic monitoring technologies and integrating multidimensional intervention strategies. By developing ultra-sensitive liquid biopsy platforms that integrate third-generation sequencing, ddPCR, and exosomal proteomics, these platforms enable real-time tracking of low-abundance resistant clones and non-genetic resistance signals [162,163,164]. Concurrently, establishing a multimodal surveillance system integrating tissue biopsy-based spatial heterogeneity mapping, high-frequency liquid biopsy-driven dynamic tracking, and radiomic feature extraction will facilitate early detection of resistant subclones [165,166,167,168]. At the intervention level, developing more novel combination therapy strategies based on resistance mechanisms effectively overcome resistance-for example, the combination of KRAS-mutant inhibitors with anti-EGFR antibodies or immune checkpoint inhibitors has demonstrated significant efficacy in clinical trials. Moreover, AI-driven multi-omics integration models and adaptive stratified treatment strategies will propel resistance management beyond “single-molecule static detection” toward “spatiotemporal dynamic network profiling,” ultimately constructing a multi-tiered (molecular-cellular-tissue) panoramic monitoring system [169]. Notably, standardized detection workflows and interdisciplinary collaboration will accelerate the clinical adoption of novel biomarkers. Preclinical validation platforms, including patient-derived tumor models and organoids, provide ideal systems for mechanistic verification, thereby expediting biomarker translation into clinical trials [81, 140, 170].
7 Conclusion
In recent years, the clinical application of KRAS-mutant inhibitors has achieved remarkable progress, demonstrating promising efficacy in treating certain advanced malignancies. However, the emergence of drug resistance has become a critical factor limiting further therapeutic improvement. Research on KRAS-mutant inhibitors resistance mechanisms and related biomarkers provides a pivotal breakthrough for overcoming targeted therapy bottlenecks. Through the integration of multi-omics technologies and functional screening, researchers have systematically revealed multidimensional resistance mechanisms: tumor cells evade drug pressure via endogenous genetic mutations, co-mutations, signaling pathway reprogramming, and microenvironmental or phenotypic remodeling. The application of bioinformatics and high-throughput technologies has significantly advanced the discovery and validation of KRAS-mutant inhibitors resistance biomarkers. Notably, the combination of liquid biopsy and single-cell sequencing technologies offers a powerful tool for real-time monitoring of resistance evolution. These innovations not only enhance biomarker identification efficiency but also support the development of precision treatment strategies.
Nevertheless, challenges persist, particularly due to tumor heterogeneity and microenvironment complexity, which limit the predictive value of single biomarkers. Future research should prioritize three areas: (1) developing highly sensitive dynamic monitoring technologies to capture spatiotemporal heterogeneity; (2) deciphering interactions between resistant cell subpopulations and the microenvironment; and (3) promoting biomarker-guided precision combination therapies. In summary, KRAS-mutant inhibitors resistance research has evolved from a gene-centric perspective to a systems biology era. Overcoming current limitations and achieving precise, durable clinical translation will require interdisciplinary collaboration and technological innovation. Further efforts should focus on clinical validation and dynamic monitoring of biomarkers to ensure their utility in personalized treatment. Ultimately, integrating multidisciplinary expertise and fostering collaborative innovation will be essential to address KRAS-mutant inhibitors resistance, thereby improving patient survival and quality of life.
Data availability
No datasets were generated or analysed during the current study.
References
Yang H, Zhou X, Fu D, et al. Targeting RAS mutants in malignancies: successes, failures, and reasons for hope. Cancer Commun (London England). 2023;43(1):42–74.
Chen S, Li F, Xu D, et al. The function of RAS mutation in cancer and advances in its drug research. Curr Pharm Design. 2019;25(10):1105–14.
Prior IA, Hood FE, Hartley JL. The frequency of Ras mutations in cancer. Cancer Res. 2020;80(14):2969–74.
Chen Y, Liu QP, Xie H, et al. From bench to bedside: current development and emerging trend of KRAS-targeted therapy. Acta Pharmacol Sin. 2024;45(4):686–703.
Stickler S, Rath B, Hamilton G. Targeting KRAS in pancreatic cancer. Oncol Res. 2024;32(5):799–805.
Timar J, Kashofer K. Molecular epidemiology and diagnostics of KRAS mutations in human cancer. Cancer Metastasis Rev. 2020;39(4):1029–38.
Hunter JC, Manandhar A, Carrasco MA, et al. Biochemical and structural analysis of common Cancer-Associated KRAS mutations. Mol Cancer Res. 2015;13(9):1325–35.
Wadood A, Ajmal A, Rehman AU. Strategies for targeting KRAS: A challenging drug target. Curr Pharm Design. 2022;28(23):1897–901.
Huang L, Guo Z, Wang F, et al. KRAS mutation: from undruggable to druggable in cancer. Signal Transduct Target Therapy. 2021;6(1):386.
Wu HZ, Xiao JQ, Xiao SS, et al. KRAS: A promising therapeutic target for cancer treatment. Curr Top Med Chem. 2019;19(23):2081–97.
Singhal A, Li BT, O’Reilly EM. Targeting KRAS in cancer. Nat Med. 2024;30(4):969–83.
Orgován Z, Keserű GM. Small molecule inhibitors of RAS proteins with oncogenic mutations. Cancer Metastasis Rev. 2020;39(4):1107–26.
Janes MR, Zhang J, Li LS, et al. Targeting KRAS mutant cancers with a covalent G12C-Specific inhibitor. Cell. 2018;172(3):578–e58917.
Cheng H, Li P, Chen P, et al. Structure-based design and synthesis of potent and selective KRAS G12D inhibitors. ACS Med Chem Lett. 2023;14(10):1351–7.
Mausey N, Halford Z. Targeted therapies for previously undruggable KRAS-Mutated Non-Small cell lung cancer: A review of Sotorasib and adagrasib. Annals Pharmacotherapy. 2024;58(6):622–35.
Punekar SR, Velcheti V, Neel BG, et al. The current state of the Art and future trends in RAS-targeted cancer therapies. Nat Rev Clin Oncol. 2022;19(10):637–55.
Lanman BA, Allen JR, Allen JG, et al. Discovery of a covalent inhibitor of KRAS(G12C) (AMG 510) for the treatment of solid tumors. J Med Chem. 2020;63(1):52–65.
El Zaitouni S, Laraqui A, Boustany Y, et al. Potency and safety of KRAS G12C inhibitors in solid tumors: A systematic review. Clin Med Insights Oncol. 2025;19:11795549251331759.
de Langen AJ, Johnson ML, Mazieres J, et al. Sotorasib versus docetaxel for previously treated non-small-cell lung cancer with KRAS(G12C) mutation: a randomised, open-label, phase 3 trial. Lancet. 2023;401(10378):733–46.
Wu X, Song W, Cheng C, et al. Small molecular inhibitors for KRAS-mutant cancers. Front Immunol. 2023;14:1223433.
Skoulidis F, Li BT, Dy GK, et al. Sotorasib for lung cancers with KRAS p.G12C mutation. N Engl J Med. 2021;384(25):2371–81.
Zhu C, Guan X, Zhang X, et al. Targeting KRAS mutant cancers: from druggable therapy to drug resistance. Mol Cancer. 2022;21(1):159.
Jiao D, Yang S. Overcoming Resistance to Drugs Targeting KRAS(G12C) Mutation. Innovation (Cambridge (Mass.)) 2020;1(2).
Ye W, Lu X, Qiao Y, et al. Activity and resistance to KRAS(G12C) inhibitors in non-small cell lung cancer and colorectal cancer. Biochim et Biophys Acta Rev Cancer. 2024;1879(3):189108.
Ryan MB, de la Fece F, Phat S, et al. Vertical pathway Inhibition overcomes adaptive feedback resistance to KRAS(G12C) Inhibition. Clin Cancer Res. 2020;26(7):1633–43.
Dunnett-Kane V, Nicola P, Blackhall F et al. Mechanisms of resistance to KRAS(G12C) inhibitors. Cancers. 2021;13(1).
Ramalingam PS, Priyadharshini A, Emerson IA, et al. Potential biomarkers uncovered by bioinformatics analysis in Sotorasib resistant-pancreatic ductal adenocarcinoma. Front Med. 2023;10:1107128.
Koga T, Suda K, Fujino T, et al. KRAS secondary mutations that confer acquired resistance to KRAS G12C inhibitors, Sotorasib and adagrasib, and overcoming strategies: insights from in vitro experiments. J Thorac Oncol. 2021;16(8):1321–32.
Colombo M, Ndembe G, Broggini M. Targeting and resistance: anticipating the expectable. J Thorac Oncol. 2021;16(8):1239–41.
Liu Z, Lenz HJ, Yu J et al. Differential Response and Resistance to KRAS-Targeted Therapy. Mol Carcinogenesis. 2025.
Zhuang H, Fan J, Li M, et al. Mechanistic insights into the clinical Y96D mutation with acquired resistance to AMG510 in the KRAS(G12C). Front Oncol. 2022;12:915512.
Zhang J, Zhang J, Liu Q, et al. Resistance looms for KRAS G12C inhibitors and rational tackling strategies. Pharmacol Ther. 2022;229:108050.
Miyashita H, Kato S, Hong DS. KRAS G12C inhibitor combination therapies: current evidence and challenge. Front Oncol. 2024;14:1380584.
Li HY, Qi WL, Wang YX, et al. Covalent inhibitor targets KRas(G12C): A new paradigm for drugging the undruggable and challenges ahead. Genes Dis. 2023;10(2):403–14.
Cox AD, Fesik SW, Kimmelman AC, et al. Drugging the undruggable RAS: mission possible? Nat Rev Drug Discov. 2014;13(11):828–51.
Fan G, Lou L, Song Z, et al. Targeting mutated GTPase KRAS in tumor therapies. Eur J Med Chem. 2021;226:113816.
Mo J, Moye SL, McKay RM, et al. Neurofibromin and suppression of tumorigenesis: beyond the GAP. Oncogene. 2022;41(9):1235–51.
Waters AM, Der CJ. The critical driver and therapeutic target for pancreatic cancer. Cold Spring Harb Perspect Med. 2018;8:9.
Parikh K, Banna G, Liu SV, et al. Drugging KRAS: current perspectives and state-of-art review. J Hematol Oncol. 2022;15(1):152.
Zhu G, Pei L, Xia H, et al. Role of oncogenic KRAS in the prognosis, diagnosis and treatment of colorectal cancer. Mol Cancer. 2021;20(1):143.
Simanshu DK, Nissley DV, McCormick F. RAS proteins and their regulators in human disease. Cell. 2017;170(1):17–33.
Mondal K, Posa MK, Shenoy RP, et al. KRAS mutation subtypes and their association with other driver mutations in oncogenic pathways. Cells. 2024;13:14.
Rose-Nussbaumer J. Statistical significance vs clinical significance-That is the question. JAMA Ophthalmol. 2021;139(11):1235.
Tenekeci AK, Unal AA, Ceylan F, et al. An updated overview of K-RAS G12C inhibitors in advanced stage non-small cell lung cancer. Future Oncol (London England). 2024;20(37):3019–38.
Rennella E, Henry C, Dickson CJ, et al. Dynamic conformational equilibria in the active States of KRAS and NRAS. RSC Chem Biol. 2025;6(1):106–18.
Hong DS, Fakih MG, Strickler JH, et al. KRAS(G12C) Inhibition with Sotorasib in advanced solid tumors. N Engl J Med. 2020;383(13):1207–17.
Reck M, Carbone DP, Garassino M, et al. Targeting KRAS in non-small-cell lung cancer: recent progress and new approaches. Annals Oncology: Official J Eur Soc Med Oncol. 2021;32(9):1101–10.
Haider K, Sharma A, Yar MS, et al. Novel approaches for the development of direct KRAS inhibitors: structural insights and drug design. Expert Opin Drug Discov. 2022;17(3):247–57.
Miyashita H, Hong DS. Combining EGFR and KRAS G12C inhibitors for KRAS G12C mutated advanced colorectal cancer. J Cancer Immunol. 2024;6(2):62–9.
Kwon YJ, Kim DY, Kim UI, et al. Basroparib overcomes acquired resistance to MEK inhibitors by inhibiting Wnt-mediated cancer stemness in KRAS-mutated colorectal cancer. Biochem Pharmacol. 2025;235:116842.
Park YL, Kim HP, Ock CY, et al. EMT-mediated regulation of CXCL1/5 for resistance to anti-EGFR therapy in colorectal cancer. Oncogene. 2022;41(14):2026–38.
Torres-Jiménez J, Espinar JB, de Cabo HB, et al. Targeting KRAS(G12C) in Non-Small-Cell lung cancer: current standards and developments. Drugs. 2024;84(5):527–48.
Chen H, Smaill JB, Liu T, et al. Small-Molecule inhibitors directly targeting KRAS as anticancer therapeutics. J Med Chem. 2020;63(23):14404–24.
Gorfe AA, Cho KJ. Approaches to inhibiting oncogenic K-Ras. Small GTPases. 2021;12(2):96–105.
Tran TH, Alexander P, Dharmaiah S, et al. The small molecule BI-2852 induces a nonfunctional dimer of KRAS. Proc Natl Acad Sci USA. 2020;117(7):3363–4.
Kessler D, Gmachl M, Mantoulidis A, et al. Drugging an undruggable pocket on KRAS. Proc Natl Acad Sci USA. 2019;116(32):15823–9.
Wallon L, Khan I, Teng KW et al. Inhibition of RAS-driven signaling and tumorigenesis with a pan-RAS monobody targeting the switch I/II pocket. Proc Natl Acad Sci USA. 2022;119(43): e2204481119.
Kessler D, Bergner A, Böttcher J, et al. Drugging all RAS isoforms with one pocket. Future Med Chem. 2020;12(21):1911–23.
Kim D, Herdeis L, Rudolph D, et al. Pan-KRAS inhibitor disables oncogenic signalling and tumour growth. Nature. 2023;619(7968):160–6.
McCarthy MJ, Pagba CV, Prakash P, et al. Discovery of High-Affinity noncovalent allosteric KRAS inhibitors that disrupt effector binding. ACS Omega. 2019;4(2):2921–30.
Yang W, Zhang M, Zhang TX, et al. YAP/TAZ mediates resistance to KRAS inhibitors through inhibiting proapoptosis and activating the SLC7A5/mTOR axis. JCI Insight. 2024;9:24.
de Jesus VHF, Mathias-Machado MC, de Farias JPF, et al. Targeting KRAS in pancreatic ductal adenocarcinoma: the long road to cure. Cancers. 2023;15:20.
Zhao Y, Murciano-Goroff YR, Xue JY, et al. Diverse alterations associated with resistance to KRAS(G12C) Inhibition. Nature. 2021;599(7886):679–83.
Awad MM, Liu S, Rybkin II, et al. Acquired resistance to KRAS(G12C) Inhibition in cancer. N Engl J Med. 2021;384(25):2382–93.
Pan LN, Ma YF, Li Z, et al. KRAS G12V mutation upregulates PD-L1 expression via TGF-β/EMT signaling pathway in human non-small-cell lung cancer. Cell Biol Int. 2021;45(4):795–803.
Di Federico A, Ricciotti I, Favorito V, et al. Resistance to KRAS G12C Inhibition in Non-small cell lung cancer. Curr Oncol Rep. 2023;25(9):1017–29.
Tanaka N, Lin JJ, Li C, et al. Clinical acquired resistance to KRAS(G12C) Inhibition through a novel KRAS Switch-II pocket mutation and polyclonal alterations converging on RAS-MAPK reactivation. Cancer Discov. 2021;11(8):1913–22.
Tu G, Liu Q, Qiu Y, et al. In Silico study of the acquired resistance caused by the secondary mutations of KRAS G12C protein using long time molecular dynamics simulation and Markov state model analysis. Int J Mol Sci. 2022;23:22.
Cong B, Stamou E, Pennel K et al. WNT Signalling Promotes NF-κB Activation and Drug Resistance in KRAS-Mutant Colorectal Cancer. bioRxiv: the preprint server for biology. 2023.
Evrard C, Ingrand P, Rochelle T, et al. Circulating tumor DNA in unresectable pancreatic cancer is a strong predictor of first-line treatment efficacy: the KRASCIPANC prospective study. Dig Liver Disease: Official J Italian Soc Gastroenterol Italian Association Study Liver. 2023;55(11):1562–72.
Ernst SM, von der Thüsen JH, Dubbink HJ, et al. Letter regarding clinical utility of Circulating tumor DNA in patients with advanced KRASG12C-Mutated NSCLC treated with Sotorasib. J Thorac Oncol. 2024;19(8):e29–30.
Lim TKH, Skoulidis F, Kerr KM, et al. KRAS G12C in advanced NSCLC: prevalence, co-mutations, and testing. Lung Cancer (Amsterdam Netherlands). 2023;184:107293.
Ryan MB, Coker O, Sorokin A, et al. KRAS(G12C)-independent feedback activation of wild-type RAS constrains KRAS(G12C) inhibitor efficacy. Cell Rep. 2022;39(12):110993.
Liu J, Kang R, Tang D. The KRAS-G12C inhibitor: activity and resistance. Cancer Gene Ther. 2022;29(7):875–8.
Mishra R, Patel H, Alanazi S, et al. HER3 signaling and targeted therapy in cancer. Oncol Rev. 2018;12(1):355.
Yaeger R, Mezzadra R, Sinopoli J, et al. Molecular characterization of acquired resistance to KRASG12C-EGFR Inhibition in colorectal cancer. Cancer Discov. 2023;13(1):41–55.
Amodio V, Yaeger R, Arcella P, et al. EGFR Blockade reverts resistance to KRAS(G12C) Inhibition in colorectal cancer. Cancer Discov. 2020;10(8):1129–39.
Li W, Wu Y, Dai L, et al. SHP2 contributes to resistance of KRAS p.G12C-Driven lung cancer cells to MRTX849 by regulating β-catenin/c-MYC axis. Ann Clin Lab Sci. 2023;53(4):630–40.
Ma J, Lyu H, Huang J, et al. Targeting of erbB3 receptor to overcome resistance in cancer treatment. Mol Cancer. 2014;13:105.
Chan CH, Chiou LW, Lee TY, et al. PAK and PI3K pathway activation confers resistance to KRAS(G12C) inhibitor Sotorasib. Br J Cancer. 2023;128(1):148–59.
Ashouri K, Wong A, Mittal P, et al. Exploring predictive and prognostic biomarkers in colorectal cancer: A comprehensive review. Cancers. 2024;16:16.
Nussinov R, Tsai CJ, Jang H. Anticancer drug resistance: an update and perspective. Drug Resist Updates: Reviews Commentaries Antimicrob Anticancer Chemother. 2021;59:100796.
Tong X, Patel AS, Kim E, et al. Adeno-to-squamous transition drives resistance to KRAS Inhibition in LKB1 mutant lung cancer. Cancer Cell. 2024;42(3):413–e4287.
Cai D, Hu C, Li L, et al. The prevalence and prognostic value of KRAS co-mutation subtypes in Chinese advanced non-small cell lung cancer patients. Cancer Med. 2020;9(1):84–93.
Di Federico A, De Giglio A, Parisi C, et al. STK11/LKB1 and KEAP1 mutations in non-small cell lung cancer: prognostic rather than predictive? Eur J Cancer. 2021;157:108–13.
de Cordeiro VC, Corassa M, Saldanha E, et al. STK11 and KEAP1 mutations in non-small cell lung cancer patients: descriptive analysis and prognostic value among Hispanics (STRIKE registry-CLICaP). Lung Cancer. 2022;170:114–21.
Bteich F, Mohammadi M, Li T, et al. Targeting KRAS in colorectal cancer: A bench to bedside review. Int J Mol Sci. 2023;24:15.
Manolakos P, Ward LD. A critical review of the prognostic and predictive implications of KRAS and STK11 mutations and Co-Mutations in metastatic Non-Small lung cancer. J Personalized Med. 2023;13:6.
Sun Y, Li Z, Jian H, et al. Impact of KRAS mutation subtypes and Co-Occurring mutations on response and outcome in advanced NSCLC patients following First-Line treatment. J Clin Med. 2022;11:14.
Oshima M, Okano K, Muraki S, et al. Immunohistochemically detected expression of 3 major genes (CDKN2A/p16, TP53, and SMAD4/DPC4) strongly predicts survival in patients with resectable pancreatic cancer. Ann Surg. 2013;258(2):336–46.
Borazanci E, Dang CV, Robey RW, et al. Pancreatic cancer: A riddle wrapped in a mystery inside an enigma. Clin Cancer Res. 2017;23(7):1629–37.
Shoucair S, Habib JR, Pu N, et al. Comprehensive analysis of somatic mutations in driver genes of resected pancreatic ductal adenocarcinoma reveals KRAS G12D and mutant TP53 combination as an independent predictor of clinical outcome. Ann Surg Oncol. 2022;29(4):2720–31.
Wan X, Zhang X, Xu M, et al. Unveiling the role of KRAS in Chinese colorectal cancer patients: a positive influence on tumor mutational burden. Transl Cancer Res. 2024;13(9):4752–62.
Yang M, Mu Y, Yu X, et al. Survival strategies: how tumor hypoxia microenvironment orchestrates angiogenesis. Biomed Pharmacother. 2024;176:116783.
Doroshow DB, Bhalla S, Beasley MB, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2021;18(6):345–62.
Uruga H, Mino-Kenudson M. Predictive biomarkers for response to immune checkpoint inhibitors in lung cancer: PD-L1 and beyond. Virchows Arch. 2021;478(1):31–44.
Imyanitov EN, Iyevleva AG, Levchenko EV. Molecular testing and targeted therapy for non-small cell lung cancer: current status and perspectives. Crit Rev Oncol Hematol. 2021;157:103194.
Katopodi T, Petanidis S, Domvri K, et al. Kras-driven intratumoral heterogeneity triggers infiltration of M2 polarized macrophages via the circHIPK3/PTK2 immunosuppressive circuit. Sci Rep. 2021;11(1):15455.
Kamimaki C, Kobayashi N, Hirata M, et al. T-cell response to Phytohemagglutinin in the interferon-γ release assay as a potential biomarker for the response to immune checkpoint inhibitors in patients with non-small cell lung cancer. Thorac Cancer. 2021;12(11):1726–34.
de Gomes AL, Cerdá S, de Miguel M. New checkpoint inhibitors on the road: targeting TIM-3 in solid tumors. Curr Oncol Rep. 2022;24(5):651–8.
Lee D, Cho M, Kim E, et al. PD-L1: from cancer immunotherapy to therapeutic implications in multiple disorders. Mol Ther. 2024;32(12):4235–55.
Arafat Hossain M. A comprehensive review of immune checkpoint inhibitors for cancer treatment. Int Immunopharmacol. 2024;143(Pt 2):113365.
Suzuki S, Yonesaka K, Teramura T, et al. KRAS inhibitor resistance in MET-Amplified KRAS (G12C) Non-Small cell lung cancer induced by RAS- and Non-RAS-Mediated cell signaling mechanisms. Clin Cancer Research: Official J Am Association Cancer Res. 2021;27(20):5697–707.
Huang X, Li E, Shen H, et al. Targeting the HGF/MET axis in cancer therapy: challenges in resistance and opportunities for improvement. Front Cell Dev Biology. 2020;8:152.
Lee GD, Lee SE, Oh DY, et al. Exon 14 skipping mutations in lung adenocarcinoma: clinicopathologic implications and prognostic values. J Thorac Oncol. 2017;12(8):1233–46.
Dias Carvalho P, Martins F, Mendonça S, et al. Mutant KRAS modulates colorectal cancer cells invasive response to fibroblast-secreted factors through the HGF/C-MET axis. Int J Cancer. 2022;151(10):1810–23.
Kim JY, Welsh EA, Fang B, et al. Phosphoproteomics reveals MAPK inhibitors enhance MET- and EGFR-Driven AKT signaling in KRAS-Mutant lung cancer. Mol Cancer Res. 2016;14(10):1019–29.
Vasan N, Baselga J, Hyman DM. A view on drug resistance in cancer. Nature. 2019;575(7782):299–309.
Hu F, Lito P. Insights into how adeno-squamous transition drives KRAS inhibitor resistance. Cancer Cell. 2024;42(3):330–2.
Adachi Y, Ito K, Hayashi Y, et al. Epithelial-to-Mesenchymal transition is a cause of both intrinsic and acquired resistance to KRAS G12C inhibitor in KRAS G12C-Mutant Non-Small cell lung cancer. Clin Cancer Res. 2020;26(22):5962–73.
Ning W, Marti TM, Dorn P, et al. Non-genetic adaptive resistance to KRAS(G12C) inhibition: EMT is not the only culprit. Front Oncol. 2022;12:1004669.
Wang Y, Ngo VN, Marani M, et al. Critical role for transcriptional repressor Snail2 in transformation by oncogenic RAS in colorectal carcinoma cells. Oncogene. 2010;29(33):4658–70.
Mahmoud A, Elkhalifa D, Alali F, et al. Novel polymethoxylated Chalcones as potential compounds against KRAS-Mutant colorectal cancers. Curr Pharm Des. 2020;26(14):1622–33.
Ash LJ, Busia-Bourdain O, Okpattah D, et al. Biology, inhibition, and mechanisms of inhibitor resistance. Curr Oncol. 2024;31(4):2024–46.
Quintanal-Villalonga A, Taniguchi H, Zhan YA, et al. Multiomic analysis of lung tumors defines pathways activated in neuroendocrine transformation. Cancer Discov. 2021;11(12):3028–47.
Kawada K, Toda K, Sakai Y. Targeting metabolic reprogramming in KRAS-driven cancers. Int J Clin Oncol. 2017;22(4):651–9.
Ma Q, Zhang W, Wu K, et al. The roles of KRAS in cancer metabolism, tumor microenvironment and clinical therapy. Mol Cancer. 2025;24(1):14.
Lee CK, Jeong SH, Jang C, et al. Tumor metastasis to lymph nodes requires YAP-dependent metabolic adaptation. Science. 2019;363(6427):644–9.
Afonso J, Gonçalves C, Costa M et al. Glucose metabolism reprogramming in bladder cancer: hexokinase 2 (HK2) as prognostic biomarker and target for bladder cancer therapy. Cancers (Basel) 2023; 15(3).
Moss DY, McCann C, Kerr EM. Rerouting the drug response: overcoming metabolic adaptation in KRAS-mutant cancers. Sci Signal. 2022;15(756):eabj3490.
Jiang Z, Ye S, Wu Y, et al. Cyclopeptide RA-V from rubia yunnanensis restores activity of adagrasib against colorectal cancer by reducing the expression of Nrf2. Pharmacol Res. 2024;206:107252.
Chong W, Zhu X, Ren H, et al. Integrated multi-omics characterization of KRAS mutant colorectal cancer. Theranostics. 2022;12(11):5138–54.
Tian L, Liu C, Zheng S, et al. KEAP1 mutations as key crucial prognostic biomarkers for resistance to KRAS-G12C inhibitors. J Transl Med. 2025;23(1):82.
Ho CSL, Tüns AI, Schildhaus UH, et al. HER2 mediates clinical resistance to the KRAS(G12C) inhibitor sotorasib, which is overcome by co-targeting SHP2. Eur J Cancer (Oxford England: 1990). 2021;159:16–23.
Zhang Y, Liu L, Pei J, et al. Tissue factor overexpression promotes resistance to KRAS-G12C Inhibition in non-small cell lung cancer. Oncogene. 2024;43(9):668–81.
Lin P, Cheng W, Qi X et al. Bioinformatics and experimental validation for identifying biomarkers associated with AMG510 (Sotorasib) resistance in KRAS(G12C)-Mutated lung adenocarcinoma. Int J Mol Sci 2024, 25 (3).
Bian Y, Shan G, Bi G, et al. Targeting ALDH1A1 to enhance the efficacy of KRAS-targeted therapy through ferroptosis. Redox Biol. 2024;77:103361.
Dilly J, Hoffman MT, Abbassi L, et al. Mechanisms of resistance to oncogenic KRAS Inhibition in pancreatic cancer. Cancer Discov. 2024;14(11):2135–61.
Solanki HS, Welsh EA, Fang B, et al. Cell Type-specific adaptive signaling responses to KRAS(G12C) Inhibition. Clin Cancer Res. 2021;27(9):2533–48.
Riedl JM, de la Fece F, Lin JJ et al. Genomic landscape of clinically acquired resistance alterations in patients treated with KRAS(G12C) inhibitors. Ann Oncol 2025.
Knetki-Wróblewska M, Tabor S, Płużański A, et al. Efficacy of immunotherapy in Second-Line treatment of KRAS-Mutated patients with Non-Small-Cell lung Cancer-Data from daily practice. Curr Oncol (Toronto Ont). 2022;30(1):462–75.
Olsen A, Lebedeva A, Nosova P, et al. Impact of the STK11/KRAS co-mutation on the response to immunotherapy in a real-world pan-cancer cohort. Tumori. 2024;110(2):146–52.
Yang B, Li X, Fu Y, et al. MEK Inhibition remodels the immune landscape of mutant KRAS tumors to overcome resistance to PARP and immune checkpoint inhibitors. Cancer Res. 2021;81(10):2714–29.
Modica C, Tortarolo D, Comoglio PM, et al. MET/HGF Co-Targeting in pancreatic cancer: A tool to provide insight into the tumor/stroma crosstalk. Int J Mol Sci. 2018;19:12.
Yaeger R, Uboha NV, Pelster MS, et al. Efficacy and safety of adagrasib plus cetuximab in patients with KRASG12C-Mutated metastatic colorectal cancer. Cancer Discov. 2024;14(6):982–93.
Meriggi F, Vermi W, Bertocchi P, et al. The emerging role of NRAS mutations in colorectal cancer patients selected for Anti-EGFR therapies. Rev Recen Clin Trial. 2014;9(1):8–12.
Ríos-Hoyo A, Monzonís X, Vidal J, et al. Unveiling acquired resistance to anti-EGFR therapies in colorectal cancer: a long and winding road. Front Pharmacol. 2024;15:1398419.
van Brummelen EMJ, Huijberts S, van Herpen C, et al. Phase I study of Afatinib and selumetinib in patients with KRAS-Mutated colorectal, Non-Small cell lung, and pancreatic cancer. Oncologist. 2021;26(4):290–e545.
Migliarese C, Sadeh Y, Torrini C, et al. Combination therapy of adagrasib and abemaciclib in non-small cell lung cancer brain metastasis models genomically characterized by KRAS-G12C and homozygous loss of CDKN2A. Acta Neuropathol Commun. 2025;13(1):88.
Duan X, Zhang T, Feng L, et al. A pancreatic cancer organoid platform identifies an inhibitor specific to mutant KRAS. Cell Stem Cell. 2024;31(1):71–e888.
Harris E, Thawani R. Current perspectives of KRAS in non-small cell lung cancer. Curr Probl Cancer. 2024;51:101106.
Zhang M, Zhang YY, Chen Y, et al. TGF-β signaling and resistance to cancer therapy. Front Cell Dev Biology. 2021;9:786728.
Yaeger R, Weiss J, Pelster MS, et al. Adagrasib with or without cetuximab in colorectal cancer with mutated KRAS G12C. N Engl J Med. 2023;388(1):44–54.
Falchook G, Li BT, Marrone KA et al. OA03.03 Sotorasib in combination with RMC-4630, a SHP2 inhibitor, in KRAS p.G12C-Mutated NSCLC and other solid tumors. 2022;17(9-Sup):1.
Ramalingam S, Fakih M, Strickler J et al. Abstract P05-01: A phase 1b study evaluating the safety and efficacy of sotorasib, a KRASG12C inhibitor, in combination with trametinib, a MEK inhibitor, in KRAS p.G12C-Mutated solid tumors. 2021;20(12-Sup):1.
Li BT, Falchook GS, Durm GA, et al. OA03.06 codebreak 100/101: first report of safety/efficacy of Sotorasib in combination with pembrolizumab or Atezolizumab in advanced KRAS p.G12C NSCLC. J Thorac Oncol. 2022;17(9):S10–1.
Zhou J, Li Q, Cao Y. Spatiotemporal heterogeneity across metastases and Organ-Specific response informs drug efficacy and patient survival in colorectal cancer. Cancer Res. 2021;81(9):2522–33.
Kosmidou V, Oikonomou E, Vlassi M, et al. Tumor heterogeneity revealed by KRAS, BRAF, and PIK3CA pyrosequencing: KRAS and PIK3CA intratumor mutation profile differences and their therapeutic implications. Hum Mutat. 2014;35(3):329–40.
Berg M, Soreide K. EGFR and downstream genetic alterations in KRAS/BRAF and PI3K/AKT pathways in colorectal cancer: implications for targeted therapy. Discov Med. 2012;14(76):207–14.
Long SA, Amparo AM, Goodhart G, et al. Evaluation of KRAS inhibitor-directed therapies for pancreatic cancer treatment. Front Oncol. 2024;14:1402128.
Amino Y, Low SK, Ninomiya H, et al. Clinical characteristics of patients with KRAS mutation detected by liquid biopsy. Thorac Cancer. 2023;14(33):3317–22.
Mardinian K, Okamura R, Kato S, et al. Temporal and Spatial effects and survival outcomes associated with concordance between tissue and blood KRAS alterations in the pan-cancer setting. Int J Cancer. 2020;146(2):566–76.
Valentini AM, Cavalcanti E, Di Maggio M, et al. RAS-expanded mutations and HER2 expression in metastatic colorectal cancer: A new step of precision medicine. Appl Immunohistochem Mol Morphol AIMM. 2018;26(8):539–44.
Strickler JH, Yoshino T, Stevinson K, et al. Prevalence of KRAS G12C mutation and Co-mutations and associated clinical outcomes in patients with colorectal cancer: A systematic literature review. Oncologist. 2023;28(11):e981–94.
Abbott C, Bedi N, Wang J et al. 20 Tumor-informed liquid biopsy monitoring of evolving therapeutic resistance mechanisms in head and neck squamous cell carcinoma patients receiving anti-PD-1 therapy. 2021.
Addeo A, Banna GL, Friedlaender A. KRAS G12C mutations in NSCLC: from target to resistance. Cancers. 2021;13:11.
Shrestha R, Llaurado Fernandez M, Dawson A, et al. Multiomics characterization of Low-Grade serous ovarian carcinoma identifies potential biomarkers of MEK inhibitor sensitivity and therapeutic vulnerability. Cancer Res. 2021;81(7):1681–94.
Sánchez-Bayona R, Catalán C, Cobos MA et al. Pharmacogenomics in solid tumors: A comprehensive review of genetic variability and its clinical implications. Cancers 2025, 17 (6).
Kerr KM, Bibeau F, Thunnissen E, et al. The evolving landscape of biomarker testing for non-small cell lung cancer in Europe. Lung Cancer (Amsterdam Netherlands). 2021;154:161–75.
Felipe I, Real FX. PDAC heterogeneity resolved spatially at the single-cell level: new biological answers, new questions on optimal translation(†). J Pathol. 2024;263(4–5):397–9.
Prahallad A, Weiss A, Voshol H, et al. CRISPR screening identifies mechanisms of resistance to KRASG12C and SHP2 inhibitor combinations in Non-Small cell lung cancer. Cancer Res. 2023;83(24):4130–41.
Bettegowda C, Sausen M, Leary RJ, et al. Detection of Circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med. 2014;6(224):224ra24.
Junca A, Tachon G, Evrard C et al. Detection of colorectal cancer and advanced adenoma by liquid biopsy (Decalib Study): The ddPCR Challenge. Cancers 2020;12(6).
Hu A, Zhang J, Zhang L, et al. Efficient cancer biomarker screening and multicancer detection enabled by a multidimensional serum proteomic strategy. Anal Chem. 2024;96(49):19294–303.
Patkulkar PA, Subbalakshmi AR, Jolly MK, et al. Mapping Spatiotemporal heterogeneity in tumor profiles by integrating High-Throughput imaging and omics analysis. ACS Omega. 2023;8(7):6126–38.
Sreter KB, Catarata MJ, von Laffert M, et al. Resistance to KRAS Inhibition in advanced non-small cell lung cancer. Front Oncol. 2024;14:1357898.
Schöneck M, Rehbach N, Lotter-Becker L et al. Machine Learning-Based radiomics analysis for identifying KRAS mutations in Non-Small-Cell lung cancer from CT images: challenges, insights and implications. Life (Basel Switzerland) 2025;15(1).
Misale S, Yaeger R, Hobor S, et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature. 2012;486(7404):532–6.
Nema R. An omics-based tumor microenvironment approach and its prospects. Rep Practical Oncol Radiother. 2024;29(5):649–50.
Srivastava S, Anand A, Kandhula AG et al. Precision medicine in colorectal cancer: targeted therapies and biomarker insights. Curr Cancer Drug Targets 2025.
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This study was supported by Scientific research project of Henan National Center for inheritance and innovation of traditional Chinese medicine in 2023 under Grant number 2023ZXZX1067.
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L.W. designed the study outline, selected related literature and drafted the manuscript. D.W. and S.L. contributed to content organization based on the draft. S.J. conceived the review, supervised the work, and finalized the manuscript. All authors approved the final version.
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Wang, L., Wei, D., Li, S. et al. Advances in biomarkers of resistance to KRAS mutation-targeted inhibitors. Discov Onc 16, 1834 (2025). https://doi.org/10.1007/s12672-025-03569-x
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DOI: https://doi.org/10.1007/s12672-025-03569-x