Advances in translational lung cancer research in 2025: a narrative review

Introduction

Lung cancer remains one of the leading causes of cancer-related incidence and mortality worldwide (1). Even with the steady advancements in diagnostic and therapeutic strategies, long-term survival rates are still dismal, mainly due to late diagnoses and the emergence of therapeutic resistance. Translational medicine, being a crucial link between fundamental research and clinical application, is increasingly reshaping the clinical landscape. The year 2025 has witnessed a marked acceleration of the “bench-to-bedside” movement, where numerous scientific findings are being quickly combined with clinical decision-making tools and novel drug regimens.

This article aims to comprehensively review the key breakthroughs in lung cancer translational research in 2025. By combining these multidimensional advances, we intend to provide clinicians and researchers with an updated overview of personalized diagnosis and therapy for lung cancer. We present this article in accordance with the Narrative Review reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0251/rc).

Methods

This study was conducted as a narrative review. PubMed/MEDLINE and Web of Science were searched on 31 January 2026 for studies on lung cancer research published between 1 January 2025 and 31 January 2026. Selected representative pre-2025 studies were additionally included when necessary to provide essential background and landmark context.

The search combined lung cancer-related subject headings and free-text terms, including “lung cancer”, “NSCLC”, and “SCLC”, with keywords covering five predefined themes: early detection and minimal residual disease (MRD) monitoring; biomarkers for targeted therapy and immunotherapy; novel therapeutic approaches; resistance mechanisms and breakthrough strategies; and preclinical models and computational tools. The overall translational precision oncology framework discussed in this review is summarized in Figure 1. Reference lists of selected studies were also screened manually. A summary of the search strategy is provided in Table 1.

Figure 1 The 2025 translational precision oncology loop in lung cancer. This diagram illustrates the overarching framework and developmental logic of translational medical research in lung cancer by 2025. At its core lies the ‘AI and model-driven decision engine’, integrating multi-source data to support precise clinical decision-making. Inner-layer modules surrounding this core decision system. These preclinical models and computational tools collectively form the foundation for multi-omics integration and dynamic modelling. The intermediate ring structure represents key translational directions. This reflects the comprehensive management pathway from early intervention to re-stratification therapy post-drug resistance. The outermost layer presents the five core pillars of lung cancer research by 2025. This model embodies a closed-loop precision medicine system. Created in BioRender. Xu Y. 2026. Available online: https://BioRender.com/7sgijqw. AI, artificial intelligence; CT, computed tomography; MRD, minimal residual disease.

Eligible records included English-language original research articles, clinical trials, reviews, and translational studies relevant to these themes. Selected major conference abstracts were also included when they reported important findings not yet available in full publication. Editorials, commentaries, case reports, duplicate reports, and studies outside the scope of this review were excluded. When both a conference abstract and a full peer-reviewed article were available for the same study, priority was given to the full publication.

Titles, abstracts, and, where necessary, full texts were reviewed by the authors. Any uncertainties regarding eligibility or thematic classification were resolved through discussion and consensus. The final literature was narratively synthesized according to the predefined themes, with attention to clinical relevance, translational significance, and evidence maturity.

Early detection and MRD monitoring

Low-dose computed tomography (LDCT) remains the established cornerstone of lung cancer screening, efficiently detecting small nodules to reduce mortality (2). The prospective SUMMIT study (n=12,773) provided robust evidence for this modality, reporting a 97.0% episode sensitivity and identifying 79.3% of cancers at early stages (I/II), with 77.0% of cases eligible for surgical resection (3). Recent advances in radiomics and artificial intelligence (AI) have facilitated the development of sophisticated tools for lung cancer risk prediction and prognosis (4). Concurrently, AI advances have yielded sophisticated tools like the Medical Multimodal-Multitask Foundation Model (M3FM). By integrating 49 clinical data types with 160,000 CT series, M3FM improved cancer risk prediction by 20% while assessing cardiovascular mortality risk, marking a shift toward scalable, AI-driven clinical management (5).

Beyond imaging, researchers are augmenting the screening landscape with multi-dimensional molecular profiling. The AI-driven LungCanSeek test, analyzing four protein markers (PTMs), achieved 86.2% accuracy in a cohort of 1,814 participants (6). Simulation models suggest a two-step triage strategy—employing such tests followed by LDCT—could reduce false positives and costs compared to standalone LDCT (6). Liquid biopsy has further expanded into airway transcriptomics (7), metabolomics (8,9), and extracellular vesicle (EV) proteomics (10). Regarding the latter, the EVELC-M5 membrane panel demonstrated an area under the curve (AUC) of 0.926 in a 947-individual cohort, identifying EV-SFTPA1 as a tissue-specific marker (10). Coupled with exosomal microRNA (miRNA) analysis (11), these signatures offer robust diagnostic and monitoring potential.

To detect low-abundance biomarkers, novel translational technologies emerged in 2025. A NiCo-heterostructure microfluidic sensor now enables dual-miRNA detection within 30 minutes at an 85 aM limit (12), while CRISPR/Cas12a systems facilitate ultrasensitive miRNA quantification (26 fM) (13). Additionally, multimodal platforms integrating laser-induced graphene (LIG) immunosensors with machine learning have achieved an AUC of 0.936 by synergizing proteomic, imaging, and clinical data (14). Finally, AI-assisted cell-free DNA (cfDNA) “fragmentome” analysis has shown efficacy in identifying asymptomatic non-small cell lung cancer (NSCLC) by capturing genomic and epigenetic shifts (15,16). While circulating tumor cells (CTCs) and multi-marker integration are ongoing areas of research, their clinical utility remains limited by sensitivity constraints (17-19).

Biomarkers for targeted and immune therapies

Biomarkers in targeted therapy

In recent years, significant advances have been made in the field of biomarkers for targeted therapies in lung cancer, particularly in precision medicine and early diagnosis. Actionable genomic alterations remain the foundation of biomarker-guided targeted therapy in lung cancer. In 2025, NTRK fusions continued to represent a typical predictive biomarker that directly informs treatment selection, with larotrectinib and entrectinib showing meaningful activity in patients with fusion-positive disease (20-22). Beyond NTRK, MET alterations and HER2 aberrations also gained increasing clinical relevance, further expanding the spectrum of molecular events that can guide matched targeted treatment (23-25).

In parallel, liquid biopsy-based biomarkers are increasingly important for longitudinal disease assessment. Serial analysis of circulating tumor DNA (ctDNA) and cfDNA can support postoperative surveillance, recurrence prediction, real-time treatment monitoring, and resistance tracking, thereby helping to refine treatment decisions over the course of disease management (26,27). These dynamic biomarkers are particularly valuable when repeated tissue biopsy is impractical or when tumor evolution needs to be captured in a minimally invasive manner. However, their broader clinical translation still faces important challenges, including issues such as inadequate standardization, high cost, and low sensitivity in detecting low tumor burden (28). Therefore, further efforts are needed to improve the sensitivity, analytical accuracy, and reproducibility of liquid biopsy assays before they can be more consistently integrated into routine treatment algorithms.

At the platform level, recent technological progress has improved both the sensitivity and breadth of molecular profiling. RARE-seq, a highly sensitive cfRNA-based approach, has demonstrated the ability to detect rare tumor-derived transcripts and may complement DNA-based assays in NSCLC (29). Meanwhile, with the growing number of actionable alterations, including rare fusions and complex resistance events, broad next-generation sequencing (NGS) panel testing is increasingly preferred over single-gene assays for comprehensive molecular characterization and treatment stratification (30,31).

Biomarkers in immunotherapy

Conventionally, PD-L1 expression levels have been the most widely used predictive markers. However, clinical trials have shown significant spatiotemporal differences in PD-L1 expression, and the results of detection may also be influenced by various factors such as the use of antibody reagents and testing methods, so the predictive value of a single biomarker is limited (32,33). To enhance predictive efficacy, recent research favors combining PD-L1 with other immunological markers, integrating multiple biomarkers such as tumor mutational burden (TMB), microsatellite instability (MSI), and immune cell infiltration patterns (34). Furthermore, employing multi-omics and AI technologies may improve predictive accuracy, thereby refining personalized immunotherapy regimens. For example, the deep learning-based Deep-IO model can predict response to ICIs from tissue sections (33). Besides that, a second-generation proximity ligation assay (PLA) platform for in situ detection of PD-1/PD-L1 binding has been shown to be a more accurate predictor of therapy efficacy than protein expression alone [Tumor Proportion Score (TPS) scoring] (35).

TMB and blood-derived TMB (bTMB) are among the most extensively studied complementary biomarkers. Some studies have shown that higher TMB is associated with improved efficacy of immune checkpoint inhibitors, and when tumor tissue is limited, they provide a non-invasive alternative (36-38). Additionally, TMB is not enough on its own to determine immunotherapy efficacy accurately. The combination with analysis of other immune markers may improve the prediction to a higher level as well as give a possibility of avoided over-treatment (39). MSI-high (MSI-H)/deficient mismatch repair (dMMR) status is another potentially informative marker, but because it is uncommon in NSCLC and currently supported mainly by small retrospective studies, its predictive value in lung cancer still requires further validation (40,41). Validation of its predictive value in lung cancer will be accomplished through several large-scale clinical trials in the future.

The tumor microenvironment (TME) has become a major focus of biomarker research for immunotherapy in NSCLC, and substantial progress has been made over the past few years. Findings indicate that high infiltration of CD8⁺ T cells, natural killer cells, M1 macrophages, and B cells typically correlates with stronger anti-tumor immune responses (42). Conversely, the enrichment of immunosuppressive cells such as regulatory T cells (Tregs) and M2 macrophages may facilitate immune escape and treatment resistance (43). In addition, mature tertiary lymphoid structures (TLS) mostly denote immune responses that lead to T-cell activation and tumor antigen presentation (44). The recent improvements have also led to the multi-omics evaluation of TME. Along with immune cell infiltration, metabolic features, and molecular pathways within TME, AI and deep learning algorithms are introduced to study TME attributes that in turn can yield more accurate biomarkers for immunotherapy responses (45,46).

Translational progress in novel therapeutics

Targeted therapy

EGFR-mutated NSCLC

Translational advances in EGFR-targeted therapy manifest in two primary aspects: (I) advancing the therapeutic window to resectable populations; and (II) reinforcement and re-strategizing of advanced-stage first-line regimens. In resectable early-to-mid-stage NSCLC, studies such as ARTS and APPOINT demonstrate that patients with EGFR-sensitive mutations at stages II–IIIB (and certain stage IA cases with high-risk factors) who receive third-generation EGFR-tyrosine kinase inhibitor (TKI) adjuvant therapy following R0 resection experience significantly reduced recurrence risk and prolonged disease-free survival (DFS). ARTS (phase III) demonstrated that aumolertinib significantly improved DFS [median DFS: not reported (NR) vs. 19.4 months; hazard ratio (HR) =0.17; 95% confidence interval (CI): 0.09–0.29], with 24-month DFS rates of 88.2% vs. 40.6% (47). Furthermore, the small-scale phase II APPOINT study suggested that patients with stage IA EGFR-sensitive mutated NSCLC and high-risk factors achieved 100% 2-year DFS rates with either osimertinib or aumolertinib adjuvant therapy (48). These studies provide exploratory evidence for early risk stratification and earlier intervention.

In advanced-stage first-line therapy, intensified initial treatment has emerged as a clear direction. The FLAURA2 phase III trial demonstrated that osimertinib plus chemotherapy conferred overall survival (OS) benefit over osimertinib monotherapy [median OS (mOS): 47.5 vs. 37.6 months] (49). Concurrently, chemotherapy-free pathways are advancing: the final OS analysis from MARIPOSA demonstrated that amivantamab plus lazertinib significantly prolonged OS compared to osimertinib monotherapy (median follow-up: 37.8 months; HR =0.75; 95% CI: 0.61–0.92; P=0.005), with an absolute gain in 3-year OS rates (50). AENEAS2 provided supplementary evidence suggesting that ametuzumab plus platinum-pemetrexed extended progression-free survival (PFS) compared with ametuzumab monotherapy (28.9 vs. 18.9 months), with a trend towards OS prolongation (51). It is noteworthy that for first-line combination therapies, achieving the optimal balance between therapeutic efficacy and toxicity burden, as well as seamless integration with subsequent treatments, remains a critical challenge in clinical translation.

ALK-mutated NSCLC

Translational advances in ALK-targeted therapy similarly follow two pathways: “ongoing iteration in advanced-stage first-line settings” and “expansion into resectable populations”. Firstly, translational advances in ALK-targeted therapy are evident in the continuous refinement and optimization of advanced-stage first-line regimens. The treatment paradigm evolved from the first-generation TKI crizotinib establishing the foundation for targeted therapy, to the second-generation TKI alectinib establishing international standard status through the ALEX study, which demonstrated superior efficacy and notable intracranial control (52,53). Subsequently, the long-term follow-up results of the third-generation TKI lorlatinib from the CROWN study further reshaped treatment expectations for ALK-positive advanced NSCLC (54). The 2025 CROWN update presented data from Asian and Chinese populations: at 5-year follow-up, median PFS (mPFS) had not been reached in the lorlatinib group, with 5-year PFS rates of 63% and 70%, respectively, consistent with the overall population; with HRs of 0.22 and 0.19, respectively (55). Among patients without baseline brain metastases, the 5-year cumulative incidence of brain metastases in the lorlatinib group was 0%, indicating stable long-term intracranial control.

In the resectable population, the ALINA study provided landmark evidence-based data. Four-year follow-up presented at the European Society for Medical Oncology (ESMO) 2025 showed that in the IB–IIIA stage ITT cohort, median DFS was not reached in the alectinib group vs. 41.4 months in the chemotherapy group (HR =0.35). Concurrently, central nervous system (CNS)-DFS demonstrated significant improvement (4-year CNS-DFS rate: 90.4% vs. 78.1%; HR =0.37) (56). This advancement propelled ALK-positive NSCLC into the era of adjuvant targeted therapy and spurred studies such as ALNEO to further evaluate the potential value of neoadjuvant strategies (57).

In 2025, what deserves emphasis in ALK-positive NSCLC is the extension of the evidence chain: on the one hand, the long-term advantage of first-line treatment for advanced disease is more solid; on the other hand, the value of adjuvant therapy is further supported. This means that ALK-targeted therapy is gradually shifting from a “control of advanced disease” approach to a “throughout the disease course” treatment philosophy. As for the extent of advancement of perioperative strategies and their impact on long-term survival endpoints, these remain key points for subsequent observation

KRAS-mutated NSCLC

KRAS mutations, particularly KRAS G12C, were long recognized as a major therapeutic challenge in NSCLC. The clinical validation of G12C inhibitors (sotorasib and adagrasib) has finally ushered this molecular subtype into an era of intervention. Following confirmation of monotherapy efficacy, research focus rapidly shifted around 2025 towards combination strategies to enhance treatment depth and durability, primarily along three exploratory pathways: (I) KRAS inhibitor + immunotherapy: KRYSTAL-7 demonstrated considerable activity for adagrasib combined with pembrolizumab in first-line KRAS G12C patients, achieving a mPFS of 27.7 months with mOS not reached in the PD-L1 TPS ≥50% cohort; mPFS was 13.5 months in the TPS 1–49% cohort (58). Studies such as LOXO-RAS-20001 and SUNRAY-01 have yielded similar results, indicating that the PD-L1 high-expressing KRAS G12C mutant NSCLC population can achieve significant survival benefits from G12C inhibitor combined with immunotherapy, with an overall favorable tolerability profile (59). (II) KRAS inhibitor + platinum-based chemotherapy: the SCARLET phase II study demonstrated that sotorasib combined with carboplatin + pemetrexed achieved an objective response rate (ORR) of 88.9% in the first-line setting, with a mPFS of 6.6 months, a mOS of 20.6 months (60). (III) Non-chemotherapy dual-targeted combination: The KROCUS study explored flutreonib combined with cetuximab for first-line treatment of advanced KRAS G12C-mutated NSCLC, achieving an ORR of 80.0% and mPFS of 12.5 months (61).

Overall, the treatment paradigm for KRAS-mutated NSCLC is undergoing a fundamental shift: from a past lack of effective targeted options to a phase of diverse exploration driven by combination strategies.

Other rare mutations in NSCLC

The therapeutic changes targeting rare driver genes like HER2 and BRAF V600E are a clear demonstration of the continuous refinement and sophistication in small-molecule TKI development. Research in the HER2 mutation area is tightly focused on creating more selective oral TKIs. For example, studies such as Beamion LUNG-1 (zongertinib) and SOHO-01 (sevabertinib) are identified to offer HER2-mutated patients easier and more sustainable access to oral targeted therapy (62,63). On the whole, treatment regimens for BRAF V600E-mutated NSCLC have reached a fair level of maturity with the dual-targeted inhibition aspect involving a combination of BRAF inhibitors and MEK inhibitors being the standard method of intervention. As an example, CDRB436E2201 was instrumental in confirming the clinical usefulness of the dabrafenib and trametinib combination therapy (56), while PHAROS further revealed survival data over a long period for the combination of encorafenib and binimetinib, thereby consolidating the notion of enduring benefits resulting from the dual blockade of the mitogen-activated protein kinase (MAPK) pathway (64). Overall, these continuous innovations targeting rare targets are providing more precise and efficient treatment options for patients with specific molecular subtypes through the continuous optimization of small molecule drug design.

Antibody-drug conjugates (ADCs)

By 2025, ADCs are gradually revealing a clearer clinical translation pathway: several ADCs have secured regulatory approval, and bispecific ADCs along with ADC combination therapies are progressing towards more frontline treatment settings. Overall, the role of ADCs in NSCLC is shifting from a backline exploratory option to a treatment module with well-defined indication boundaries and sequential therapeutic value. However, concurrently, the precise identification of the beneficiary population, management of toxicities such as interstitial lung disease or myelosuppression, and the risk-benefit balance following combination therapy have become increasingly critical.

New drug approvals and key clinical data

In 2025, the Food and Drug Administration (FDA) successively approved multiple new ADC drugs, significantly expanding the treatment landscape for NSCLC. Among these, the TROP2-ADC datopotamab deruxtecan (Dato-DXd) received accelerated approval on 23 June 2025 for adult patients with locally advanced or metastatic EGFR-mutated NSCLC who had previously received EGFR-targeted therapy and platinum-based chemotherapy (65). Based on a pooled analysis of the TROPION-Lung01 and TROPION-Lung05 trials, Dato-DXd demonstrated an ORR of 43%, disease control rate (DCR) of 86%, mPFS of 5.8 months, and mOS of 15.6 months in this population (25,66,67). In terms of safety, its adverse reaction spectrum is mainly oral mucositis, nausea, hair loss, fatigue, and hematological abnormalities, with ≥3 TRAEs about 23%.

In contrast, the clinical value of telisotuzumab vedotin (Teliso-V) is more pronounced in a precisely defined patient population, namely those with high c-MET protein expression, EGFR wild-type status, and NSCLC. The FDA granted approval for its use in May 2025 based on the LUMINOSITY study, which enrolled 84 patients meeting these criteria. The BICR-assessed ORR was 35%, with a duration of response (DoR) of 7.2 months. This result indicates that the key to Teliso-V lies in achieving stable and reproducible clinical benefits after biomarker enrichment. Common toxicities include peripheral neuropathy, fatigue, decreased appetite, and peripheral edema, while laboratory abnormalities frequently manifest as decreased lymphocyte counts, elevated transaminases, and electrolyte imbalances (68).

In the field of HER2-targeting ADCs, the DESTINY-Lung02 study demonstrated that the trastuzumab deruxtecan (T-DXd, DS-8201) 5.4 mg/kg dose group achieved an ORR of 50%, a median DoR (mDoR) of 12.6 months, a PFS of 10.0 months, and a mOS of 19 months. These findings further solidify the clinical position of T-DXd in the later-line treatment of HER2-mutated NSCLC (69). Concurrently, the phase II HORIZON-Lung study demonstrated the anti-tumor activity of trastuzumab rezetecan (24): as assessed by the Independent Review Committee (IRC), the second-line treatment achieved an ORR of 74.5%, with a mDoR of 9.8 months, mPFS of 11.5 months, and a 12-month OS rate of 88.2%. Overall, these results suggest that HER2-targeted ADCs are taking a clearer position in the treatment sequence for HER2-mutated NSCLC after previous therapy. However, pulmonary toxicity, bone marrow suppression, and gastrointestinal adverse reactions remain significant safety concerns in clinical application.

Bispecific ADCs

In 2025, bispecific ADCs accelerated their advancement in NSCLC, emerging as a key direction for ADC engineering optimization. Based on design principles, they can be broadly categorized into two types: (I) dual-target ADCs, simultaneously recognizing two distinct antigens/targets (e.g., EGFR × HER3, EGFR × c-MET); and (II) dual-epitope ADCs, which recognize distinct epitopes on the same antigen. Compared to conventional monoclonal antibody ADCs, the core translational value of bispecific ADCs lies in enhancing payload delivery certainty by improving binding stability and endocytosis efficiency, thereby expanding the potential beneficiary population and improving the therapeutic window.

A leading candidate currently in advanced development is the EGFR × HER3 bispecific ADC BL-B01D1. Research indicated that BL-B01D1 monotherapy demonstrated high response rates in locally advanced or metastatic EGFR-mutated NSCLC, with generally manageable safety (grade ≥3 adverse events were predominantly hematological toxicities, typically controllable with standard supportive care) (70). At the same time, BL-B01D1 combined with osimertinib also demonstrated strong activity in previously untreated EGFR-sensitive mutant NSCLC (71,72). In the 2.5 mg/kg cohort, the confirmed ORR was 95.0%, and the 12-month PFS rate was 92.1%. However, this combination regimen is more toxic than TKI monotherapy, mainly manifesting as hematological adverse reactions, as well as gastrointestinal, mucosal, and liver function-related toxicities. The treatment-related adverse event (TRAE)-related discontinuation rate was 13.0%. Therefore, this strategy holds promise, but its ultimate clinical value still requires verification in phase III studies.

Combination therapy emerges as a new trend

With the gradual accumulation of single-drug ADC evidence, research in the field of NSCLC will further shift towards combination therapy in 2025 and show a trend of forward movement. There are currently two main paths: one is ADC combined immunotherapy for driver gene negative populations, aimed at improving initial treatment intensity and exploring optimization of existing immunotherapy models; The second is ADC combined targeted therapy for driver gene-positive populations, hoping to deepen remission and delay drug resistance through mechanism complementarity.

ADC combined with immunotherapy has shown clear early activity in driver gene negative advanced NSCLC. The results of TROPION-Lung04 and TROPION-Lung02 suggest that the relevant regimen can bring higher remission rates, and the efficacy signal is more prominent in some subtypes (73,74). However, at the same time, such combination schemes also come with higher toxicity burdens, especially pulmonary toxicity and overall tolerance issues that still require special attention. More significant for verification is OptiTROP-Lung05 (75). This phase III study compared sacituzumab tirumotecan (sac-TMT) combined with pembrolizumab vs. pembrolizumab monotherapy in PD-L1-positive first-line advanced NSCLC, and achieved the primary endpoint in mid-term analysis, indicating that ADC combined with immunotherapy is entering a higher level of clinical validation from early exploration. However, its final clinical positioning still needs to wait for more complete efficacy and safety data.

In contrast, the development logic of ADC combined with TKI in the driver gene-positive population is clearer. Existing early research suggests that this strategy has the potential to move forward as a targeted therapy enhancement module to the front line, but its true value still depends on whether deeper relief can translate into more lasting survival benefits, and whether additional toxicity is within an acceptable range.

Overall, ADC combination therapy has become an important direction in NSCLC transformation research, but whether it can change the existing treatment sequence still depends on further validation through randomized controlled trials.

Immunotherapy expands beyond monotherapy ICIs to bispecific antibodies

In 2025, the research and development focus of immunotherapy for NSCLC will further shift from the traditional monoclonal antibody combination approach to mechanism-integrated bispecific antibodies. Bispecific antibodies can simultaneously target two key pathways within a single molecule, thereby offering the potential for more stable clinical benefits in specific patient populations. It should be noted that the application of bispecific antibodies is not confined to the field of immunotherapy; in EGFR-mutant NSCLC, EGFR/MET bispecific antibodies, represented by amivantamab, have already demonstrated clear value. This section primarily focuses on the ongoing advancement of PD-1/VEGF bispecific antibodies.

Among these, ivonescimab boasts the most comprehensive evidence. The HARMONi-6 phase III study revealed that in the first-line treatment of advanced squamous NSCLC, ivonescimab combined with chemotherapy significantly improved PFS compared to a PD-1 monoclonal antibody combined with chemotherapy, with mPFS periods of 11.1 and 6.9 months, respectively, and a HR of 0.60 (76). Concurrently, the final OS analysis of the HARMONi-A study demonstrated that in EGFR-mutant non-squamous NSCLC that had progressed after EGFR-TKI treatment, ivonescimab combined with platinum-based chemotherapy further enhanced OS compared to the control group, with mOS of 16.8 and 14.1 months, respectively, and a HR of 0.74 (77).

From a safety perspective, PD-1/VEGF bispecific antibodies generally remain manageable, but their toxicity profile differs from that of traditional PD-1 combination regimens. In addition to chemotherapy-related adverse reactions, particular attention should be paid to bleeding and other VEGF-related toxicities. This implies that the clinical adoption of these antibodies depends not only on the establishment of their efficacy but also on the further standardization of toxicity monitoring and management protocols. Besides ivonescimab, other similar drugs such as BNT327 and PM8002 are also advancing through clinical validation in 2025, indicating that this direction has evolved from isolated research signals into a well-defined research and development pathway in NSCLC immunotherapy (78,79).

Overall, bispecific antibodies are becoming an important incremental source of immunotherapy for NSCLC, but the maturity of evidence for different drugs is not consistent. The key to this field in the future lies in further improving the accuracy of beneficiary screening, perfecting safety management processes, and verifying whether existing results can be stably replicated in a wider and multicenter population.

New treatment pathways for small cell lung cancer (SCLC)

By 2025, the evolution of new incremental pathways for SCLC is more apparent due to the establishment of definitive evidence and signals at two major treatment milestones. The approach to treatment after first-line induction therapy has moved to the maintenance phase. The FDA has approved lurbinectedin in combination with atezolizumab as a maintenance therapy for patients with an extensive-stage SCLC (ES-SCLC) who have not shown disease progression (80). This approval is based on the results of the IMforte phase III trial, where the combination therapy was associated with statistically significant improvements in both OS and PFS when compared to atezolizumab monotherapy (81). This progress represents a new therapeutic strategy for ES-SCLC, especially as maintenance therapy becomes more and more prominent in the context of increased treatment resistance. For the treatment of platinum-resistant ES-SCLC, full approval has been granted to the bispecific T cell engager tarlatamab targeting DLL3 and CD3 (65). The DeLLphi-304 phase III trial demonstrated that the tarlatamab group had a mOS of 13.6 months compared to 8.3 months in the chemotherapy group (HR =0.60; P<0.001), thus confirming the survival benefits in SCLC patients (82).

Mechanisms of resistance and overcoming strategies

EGFR

EGFR-mutant NSCLC almost inevitably develops drug resistance following EGFR-TKI therapy. Primary resistance is typically linked to alterations in target conformation, clonal heterogeneity, baseline coexisting genetic abnormalities, and molecular backgrounds influencing cell apoptosis thresholds (83,84). Secondary resistance can be further categorized into three types: firstly, EGFR-dependent on-target resistance, most notably exemplified by the C797S mutation emerging after third-generation EGFR-TKI treatment, which may be accompanied by rare site mutations such as L718Q and G796R/D (85); secondly, EGFR-independent off-target resistance, with common mechanisms encompassing MET amplification or overexpression, RTK fusion, and reactivation of downstream signaling pathways (86); thirdly, histological transformation, particularly towards SCLC or squamous cell carcinoma (SCC), where co-alterations in tumor suppressor genes like RB1 or TP53 generally suggest a heightened risk of transformation (87). This classification framework not only lays the foundation for the biological interpretation of EGFR resistance but also directly guides subsequent treatment strategies.

In terms of overcoming on-target resistance, the most direct strategy currently remains the development of a new generation of EGFR inhibitors capable of covering key resistance sites, especially the fourth-generation EGFR-TKIs targeting C797S. The 2025 WSD0922-102 trial delivered a breakthrough, WSD0922-FU, a phase II clinical trial evaluating locally advanced or metastatic non-small cell lung adenocarcinoma patients with EGFR C797S mutations who progressed on first-line osimertinib (88), demonstrated an investigator-assessed ORR of 60.6% in the evaluable population, with a DCR of 100%. Although its PFS data is not yet mature, this result indicates that reinhibition of dominant target-specific resistance mechanisms remains one of the most biologically plausible pathways in EGFR resistance management. In addition, for the resistance caused by the T790M and C797S trans configuration, under the premise of clear configuration and controllable toxicity, the combined inhibition of the first and third-generation EGFR-TKI still has a certain mechanism basis, and its clinical value depends on accurate identification of the configuration status, rather than empirical dosing (89).

For off-target resistance, the most well-established and operationally feasible pathway is combining EGFR-TKIs with MET inhibition, particularly suitable for molecular subtypes exhibiting MET amplification. The Phase II SAVANNAH study demonstrated that osimertinib combined with savolitinib achieved an approximately 56% ORR in the MET-high cohort, with a mPFS of approximately 7.4 months, establishing a clear mechanism-matching-benefit paradigm (90). Furthermore, the phase III SACHI trial observed a mPFS of 9.8 months in the third-generation EGFR-TKI-naïve subgroup, significantly outperforming chemotherapy 5.4 months (HR =0.34; P<0.0001), further strengthening the rationale for prioritizing mechanism-matching combined inhibition in appropriate molecular subgroups (91). Therefore, for patients with EGFR resistance, the crux does not lie in mechanically switching from targeted therapy to chemotherapy, but in determining, through reclassification, whether the tumor still exhibits exploitable bypass dependencies.

When the mechanism of drug resistance is difficult to define or precise typing cannot be achieved due to insufficient samples, a general strategy that does not rely on a single biomarker still has practical significance. Currently, it mainly includes ADC, anti-angiogenesis combination, and immunotherapy-related schemes. Regarding ADCs (including HER3 and TROP2-targeted agents), the OptiTROP-Lung04 study demonstrated sac-TMT significantly improved PFS compared to chemotherapy (8.3 vs. 4.3 months; HR =0.49) and increased ORR (approximately 60% vs. 43%) (92). For immunotherapy-related combinations following EGFR-TKI resistance, 2025 did not yield new, definitive phase III data sufficient to reshape standard treatment. Previous studies (e.g., IMpower150 and ORIENT-31) have provided biological and clinical references for the IO + anti-angiogenesis + chemotherapy regimen configuration, though its applicable patient populations and benefit thresholds remain dependent on more refined stratification biomarkers and prospective validation (93,94). Meanwhile, from the perspective of preventing the emergence of drug resistance, first-line intensive therapy also holds significant importance. The results of the aforementioned FLAURA2 and MARIPOSA studies suggest that delaying drug resistance through more profound initial inhibition may represent another crucial aspect in the comprehensive management of EGFR.

From the perspective of personalized treatment, management following EGFR resistance should be dynamically adjusted based on re-evaluation of the resistance mechanism. Patients with on-target resistance may be prioritized for treatment with next-generation inhibitors or conformation-targeted combinations; patients with bypass activation should have combination targeted therapy strategies selected according to their molecular characteristics; patients who have undergone histological transformation should, following confirmation via re-biopsy, switch to treatment pathways more aligned with the biological characteristics of SCLC or SCC, whilst assessing whether the original driver mutation still holds therapeutic value. Overall, individualized management following EGFR resistance emphasizes dynamic matching based on repeated typing and continuous assessment.

ALK

Research in 2025 further clarified that following sequential treatment with first-, second-, and third-generation ALK-TKIs, the resistance spectrum in ALK-positive NSCLC is evolving from a predominance of single on-target mutations towards a complex pattern involving concurrent compound ALK mutations, ALK-independent bypass activation and histological transformation (95). Compound mutations become more prevalent following third-generation lorlatinib treatment, with typical examples such as G1202R + L1196M conferring broad cross-resistance to multiple existing ALK-TKIs (96). Small cell transformation has also been systematically identified as a key refractory pathway. Concurrently, two substantive advances emerged in 2025 for overcoming resistance: Firstly, fourth-generation ALK inhibitors accelerated their entry into clinical trials. In November 2025, Nuvalent updated data from the ALKOVE-1 study of NVL-655 (neladalkib): among 253 advanced ALK-positive NSCLC patients previously treated with ALK-TKIs, the BICR-confirmed ORR was 31%, with 12-month and 18-month response durations of 64% and 53%, respectively; among 63 patients not previously treated with lorlatinib, the ORR increased to 46%, with response durations of 80% and 60% at 12 and 18 months, respectively (97). These findings suggest that, for patients whose resistance is still primarily driven by ALK-dependent alterations, higher-generation ALK inhibitors with broader coverage still hold clear prospects for treatment conversion. Secondly, resistance stratification and sequential therapy have become more precise: larger-scale liquid biopsy studies indicate a relative decline in on-target mutations following second/third-generation TKIs, with bypass drivers and compound mechanisms becoming more prominent (98). This drives a personalized pathway centered on dynamic NGS: exploring targeted combination regimens for bypass drivers; and reverting to platinum-based chemotherapy for histological converters, optimized through molecular subtyping and clinical trial selection (99).

KRAS G12C

By 2025, the understanding of resistance mechanisms in KRAS G12C mutant NSCLC has become more systematic than ever before. The existing G12C inhibitors mainly tend to bind to a stable GDP-binding conformation, so tumors can reduce their dependence on this conformation through adaptive signal reprogramming in the early stages of treatment, thereby maintaining MAPK pathway activity; As treatment continues, more stable genetic resistance mechanisms can gradually accumulate, including secondary mutations at target sites and reactivation of bypass or downstream pathways. Furthermore, processes such as epithelial-mesenchymal transition (EMT), enhanced lineage plasticity and histological transformation may further exacerbate the complexity of resistance (100,101).

Regarding overcoming resistance, progress by 2025 will primarily manifest in three more translatable directions: firstly, the development of next-generation G12C-OFF inhibitors with enhanced inhibitory potency and improved pharmacokinetics to deepen suppression and delay resistance. For instance, follow-up data from divarasib in KRAS G12C-positive NSCLC demonstrated sustained anti-tumor activity and manageable safety, clinically reinforcing the evidence chain that deeper suppression may yield more durable control (102). Secondly, mechanism switching involves addressing pocket secondary mutations and structurally insensitive resistance scenarios through RAS (ON) or tri-complex inhibition strategies. For instance, elironrasib (RMC-6291) receiving FDA Breakthrough Therapy Designation in 2025 reflects growing clinical interest in the potential value of non-traditional OFF mechanisms within treatment sequences (103). Thirdly, combination therapies are progressing from conceptual exploration towards clearer patient selection and regimen optimization: the KRAS G12C + SHP2 combination targeting feedback-mediated RAS reactivation reported early safety and preliminary activity signals for divarasib plus migoprotafib at the 2025 AACR meeting, demonstrating high research priority particularly in the retreatment setting following prior G12C inhibitor therapy (104).

From the perspective of individualized treatment, the core issue after KRAS G12C resistance is to determine whether the tumor still relies on the KRAS axis. If the main manifestation is insufficient inhibition depth or adaptive escape, more potent inhibitors may be more suitable; If structural secondary changes have occurred, mechanism switching should be considered even more; If the prominent mechanism is feedback reactivation, then the combination strategy may be more valuable. Therefore, repeated molecular testing and analysis of past medication trajectories are particularly important for the treatment stratification of this population.

Immunotherapy

By 2025, the understanding of immune resistance in lung cancer had broadened substantially, shifting the research focus from mainly PD-L1 expression levels or T-cell exhaustion to tumor cells, TME, and host systemic factors as a holistically interacting network (105,106) (Figure 2).

Figure 2 Mechanisms of immune resistance in lung cancer and mechanism-driven breakthrough strategies. The left panel illustrates the primary mechanisms of immune resistance in lung cancer, while the right panel presents corresponding intervention strategies. Regarding resistance mechanisms, tumor cells achieve immune evasion through multi-tiered pathways, including T-cell exhaustion, impaired antigen presentation, physical barriers formed by CAFs, enrichment of immune-suppressive cells, metabolic suppression, and immature or dysfunctional TLS. Mechanism-driven overcoming strategies encompass: (I) local vaccines to restore antigen presentation and immune priming; (II) chemoimmunotherapy; (III) bispecific antibodies for dual vascular-immune pathway reprogramming; (IV) anti-angiogenic therapies; and (V) TME remodeling. The overall emphasis is on transitioning from single PD-L1 axis therapy towards a precision immunotherapy framework of ‘multi-pathway synergistic regulation’. Created in BioRender. Xu Y. 2026. Available online: https://BioRender.com/fjleu3l. CAF, cancer-associated fibroblast; MDSC, myeloid-derived suppressor cell; MHC, major histocompatibility complex; ROS, reactive oxygen species; TAM, tumor-associated macrophage; TCR, T-cell receptor; TLS, tumor-associated lymphoid tissue; TME, tumor microenvironment; Treg, regulatory T cell.

Firstly, insufficient immune activation and impaired antigen presentation form an important basis for drug resistance. The inactivation of the IFN-γ signaling axis, antigen presentation disorders caused by B2M abnormalities, and immune suppression induced by oncogenic driving signals such as EGFR and ALK can all cause tumors to be in a low-response state before receiving ICI, or gradually lose immune reactivity during treatment (107-109). The corresponding treatment strategy for this mechanism is not simply to continue the inhibition on the PD-1/PD-L1 axis, but to attempt to reconstruct antigen release, innate immune activation, and systemic immune activation. A study reported by World Conference on Lung Cancer (WCLC) in 2025 showed that in advanced NSCLC patients who had previously failed PD-L1 treatment, intratumoral injection of CAN-2409 combined with valacyclovir and intervention on the basis of continuing standard treatment resulted in a mOS extension and systemic immune reactivation signals (110). This suggests that in situ vaccination strategies may become an important pathway for resensitization after immune resistance, which essentially involves repairing the starting link of the immune response chain rather than empirically stacking existing ICI regimens.

Secondly, T cell exclusion and immunosuppressive microenvironment are another key aspect leading to acquired immune resistance and treatment failure. Cancer-associated fibroblasts (CAFs) can restrict the entry of effector T cells into tumor nests by forming extracellular matrix barriers and reshaping matrix structures (45,111); a hypoxic, high-lactate, and acidic microenvironments further inhibit effector T cell proliferation and cytotoxic function, while promoting the expansion of immune suppressive cells such as Tregs (112). The treatment goal for this type of mechanism is to reshape the microenvironment structure and relieve immune exclusion. The higher-level evidence mainly comes from the vascular immune dual pathway reprogramming strategy. The PD-1 × VEGF bispecific antibody represented by ivonescimab has provided strong efficacy and safety evidence in advanced NSCLC, and WCLC has also reported early results of PD-1/CTLA-4 bispecific antibody combined with VEGFR-2 antibody in IO-resistant populations (113). The common logic of such strategies is to establish a mechanism-oriented framework for the treatment of immune-resistant patients that differs from traditional chemotherapy by improving abnormal blood vessels, reducing myeloid suppression, and promoting T cell infiltration.

Thirdly, abnormal TLS status and local immune structural imbalance suggest that immune resistance is not solely determined by the presence of TLS in the TME, but also by its maturity, functional status, and coupling with the surrounding immune cell network. Therefore, TLS can also be further developed as an important stratification dimension to guide personalized combination strategies (114-116). Research on relevant mechanisms in 2025 suggests that simultaneous activation of STING and LTβR can enhance the B cell response within TLS, thereby enhancing anti-tumor immunity. This suggests that future strategies for overcoming immune resistance may need to be more closely integrated with TLS typing and maturity assessment (117).

Finally, systemic factors of the host are also involved in the formation of immune resistance, with gut microbiota dysbiosis being the most representative (118). Although its mechanism significance is increasingly valued, in terms of the maturity of evidence by 2025, this direction still mainly remains in the stage of mechanism research and association analysis, and has not yet entered the mature clinical translation level.

From the perspective of personalized medicine, the management of patients following the development of immune resistance can no longer rely solely on PD-L1 levels or individual clinical characteristics; instead, it should take multiple factors into account. At the same time, negative studies such as LATIFY suggest that not all immune combination regimens are inherently effective; strategies that can truly translate into clinical benefits must still be based on mechanistic matching and precise stratification (119).

Preclinical models and computational tools in clinical decision-making

Preclinical models

Preclinical studies have had an immense impact in the lung cancer drug development cycle, notably in NSCLC research.

Engineered cell models are still vital research tools at the most basic level. By inserting mutations or modulating the pathways, these models allow for a controlled experiment to elucidate the effect of genetic change on drug sensitivity. For instance, with the KRAS pathway, the study of the resistance mechanisms of KRAS G12C inhibitors usually entails initial identification of the genetic alterations related to resistance in the samples of clinical cases (120). Next, the engineered cell models and in vitro drug sensitivity assays are used to functionally validate the candidate alterations and evaluate the inhibitor coverage against these alterations.

As an extension of in vitro studies, xenograft models are still heavily used to demonstrate in vivo anti-tumor activity and thus serve as a further level of validation. For example, in the studies related to KRYSTAL-1, apart from the observation that the molecular states of KEAP1, STK11, and NRF2 were detected at the patient level, the authors also confirmed drug sensitivity and potential combination regimens in the cell lines of KRAS G12C-mutated NSCLC and their xenograft models (121). Such models partially compensate for the limitations of in vitro experiments in pharmacokinetics and tissue architecture.

When the research emphasis moved to immunotherapy and the mechanisms of its resistance, models with functional immune systems became indispensable. Syngeneic transplant models, together with in situ or spontaneously occurring (autochthonous) genetically engineered models, allow the evaluation of treatment responses with the immune background intact. By way of illustrating with the CoREST inhibitor TNG260, relevant studies through in vivo screening identified tolerance factors that are associated with STK11 deficiency. Its anti-tumor effect in combination with anti-PD-1 therapy was recorded in STK11-deficient syngeneic transplant models and orthotopic NSCLC models (122).

In addition, to more accurately reflect the architecture and variable nature of real patient tumors, patient-derived models have been more widely used in recent years. These models, which include PDX, PDO, or organoid culture systems, are especially important in research situations where rare mutations or a small number of clinical samples are involved (123,124). As an example, in the case of NSCLC with rare EGFR mutations, the in vivo proof of the combination therapy effect of lazertinib and amivantamab was clearly confirmed by patient-derived models at different treatment stages and checked against the existing standard therapies, thus providing the rationale for subsequent clinical trials (125).

Computational tools

Alongside advances in preclinical models, computational tools have become increasingly important in lung cancer research. The expanding availability of imaging, digital pathology, spatial molecular profiling, and longitudinal clinical data has made computational analysis essential for characterizing tumor heterogeneity and extracting clinically relevant information from high-dimensional datasets.

Radiomics is one of the most developed application areas. Radiomics methods are used to describe changes in tumor morphology and density by extracting quantitative features from positron emission tomography (PET) or computed tomography (CT) images and to help in the evaluation of the response to immunotherapy (126,127). Recent works have extended the modelling of the tumors to the inclusion of the surroundings, thus using machine learning algorithms to build composite scores predicting the response to immunotherapy of NSCLC patients.

Unsupervised analysis methods are also used to explore latent grouping structures within imaging features beyond outcome-based modelling. By identifying radiomics subtypes with clustering analysis and validating these in independent cohorts, researchers can compare differences in treatment response and immune-related markers across distinct combinations of imaging features (128). This approach helps to evaluate the stability of imaging patterns across different datasets.

Digital pathology analysis at the tissue level is another category of computational support for immunological research. Whole slide image (WSI)-based analytical methods can quantitatively extract morphological features from routine hematoxylin and eosin (H&E) sections, and by combining these with statistical or machine learning models, they can be used to predict biomarkers’ expression status or clinical outcomes (129,130). Some studies also involve pathway or gene set analyses to interpret molecular changes associated with imaging features, thus increasing the biological plausibility of the results.

As research is increasingly concentrating on tumor tissue changes after treatment, spatial omics analysis platforms are being more widely used. Single-cell spatial transcriptomics technologies, with Xenium as an example, provide very detailed molecular detection together with the tissue spatial structure (131). In this way, researchers can examine distribution patterns and interactions of different cell types in tissues.

Overall, the value of AI in lung cancer research lies not only in prediction, but also in its ability to address the complexity of multi-source clinical data. By supporting data harmonization, missing-data handling, multimodal fusion, and cross-cohort validation, AI may help improve integration of imaging, pathology, molecular, and longitudinal clinical information. However, robust external validation, interpretability, and clinically guided model development remain essential if these approaches are to move beyond exploratory analyses and become reliable tools for translational and clinical application.

Perspectives and future directions

Overall, the progress of translational lung cancer research in 2025 is reflected in the parallel advancement of early detection, biomarker stratification, novel therapies, resistance-guided treatment, and computational analysis. Together, these developments are moving lung cancer management toward a more continuous, precise, and mechanism-informed framework.

At the same time, the maturity of evidence remains uneven. Some advances are supported by higher-level evidence with potential to influence clinical practice, whereas many others still rely on conference reports, interim analyses, or early-phase studies and therefore require longer follow-up and broader validation. Their clinical significance should therefore be interpreted with appropriate caution.

This review also has limitations. As a narrative review, literature selection and thematic organization inevitably involve some degree of selectivity. In addition, many important updates in 2025 remain based on immature data, and substantial heterogeneity persists across studies in patient populations, endpoints, testing platforms, and regional settings, limiting direct comparison. Emerging fields such as AI, multi-omics integration, and spatial analysis also remain constrained by insufficient standardization and external validation.

Looking ahead, the priority for translational lung cancer research is not simply to identify more biomarkers or develop more drugs, but to integrate early screening, biological stratification, treatment selection, and post-resistance intervention into a clinically executable pathway. Early detection will likely move toward multimodal frameworks combining LDCT, liquid biopsy, and AI-assisted risk assessment. Biomarker research will increasingly shift from single markers to composite and dynamic stratification systems. At the same time, the development of ADCs, bispecific antibodies, and next-generation targeted therapies will depend on clearer definition of target populations, optimal combinations, and treatment sequencing. For resistance management, future progress will rely on tissue biopsy, liquid biopsy, and dynamic molecular profiling to support repeated reclassification and treatment adjustment. Finally, as digital pathology, radiomics, spatial omics, and AI continue to evolve, improving the standardization, interpretability, and generalizability of multi-source clinical data integration will be essential for translation into routine practice.

Conclusions

2025 advances converged on a unified clinical logic: detect earlier, stratify deeper, treat with rational combinations, and adapt dynamically based on re-typing through tissue and liquid biopsy, supported by improving models and computational tools. Future progress will depend on clinical-grade validation and standardization of MRD/biomarkers and on translating AI and advanced models into robust, generalizable decision support to deliver durable benefit across broader patient populations.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0251/rc

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0251/prf

Funding: This study was supported by the National Natural Science Foundation of China (No. 82272665) and the Clinical Research Special Fund Project of Shanghai Chest Hospital (Project No. 2024IIT-Q010).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0251/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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