Advances in Lung Cancer Basic and Translational Research in 2025 – Overview and Perspectives Focusing on NSCLC

REVIEW ARTICLE Advances in Lung Cancer Basic and Translational Research in 2025 –Overview and Perspectives Focusing on NSCLC Celine Mascaux, MD, PhD, a,b Triparna Sen, PhD, c Montse Sanchez-Cespedes, PhD, d Sandra Ortiz-Cuaran, PhD, e Yohan Bossé, PhD, f,g Floris Dammeijer, MD, PhD, h Milena Cavic, PhD, i Martin P. Barr, PhD, j,k Surein Arulananda, MD, PhD, l Ricardo Armisen, MD, PhD, m Alice H. Berger, PhD, n Fabrizio Bianchi, PhD, o David P. Carbone, MD, PhD, p,q Ferdinando Cerciello, MD, PhD, r William W. Lockwood, PhD, s Tetsuya Mitsudomi, MD, PhD, t,u Shuta Ohara, MD, PhD, u Katerina Politi, PhD, v Sida Qin, MD, PhD, w Laila C. Roisman, PhD, x,y Robert Samstein, MD, PhD, z Ferdinandos Skoulidis, MD, PhD, aa Aaron C. Tan, MD, PhD, bb Anish Thomas, MD, cc Jianjun Zhang, MD, PhD, aa Murry W. Wynes, PhD, dd Thomas John, M.B.B.S., PhD, ee Ming Sound Tsao, MD, FRCPC, ff,gg, *on behalf of the IASLC Basic and Translational Science Committee a Department of Pulmonology, University Hospital of Strasbourg, Strasbourg, France b Institut National De La Santé et De La Recherche Médicale (INSERM), Unité Mixte de Recherche (UMR)_1260, Regenerative Nanomedicine (NanoRegMed), Strasbourg University, Strasbourg, France c Department of Oncological Sciences, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York d Cancer Genetics Group, Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Spain e Univ Lyon, Claude Bernard Lyon 1 University, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, France f Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Quebec City, Quebec, Canada g Department of Molecular Medicine, Université Laval, Quebec City, Quebec, Canada h Department of Pulmonary Medicine, Erasmus Medical Center, Rotterdam, The Netherlands i Department of Experimental Oncology, Institute for Oncology and Radiology of Serbia, Belgrade, Serbia j Thoracic Oncology Research Group, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland k Trinity St James’s Cancer Institute, St James’s Hospital, Dublin, Ireland l Department of Medical Oncology, Monash Health, Clayton, Australia m Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana Universidad del Desarrollo, Santiago, Chile n Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington o Unit of Cancer Biomarkers, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy p Department of Medical Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio q Pelotonia Institute for Immuno-Oncology, Columbus, Ohio r Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland s Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada t Izumi City General Hospital, Izumi, Japan u Division of Thoracic Surgery, Department of Surgery, Kindai University, Osaka, Japan v Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut w Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China *Corresponding author. Address for correspondence: Ming Sound Tsao, MD, FRCPC, Princess Margaret Cancer Centre, 101 College Street, Toronto, Ontario M5G 1L7, Canada and University of Toronto Pathology, 610 University Avenue, Toronto, Ontario M5G 2M9, Canada. E-mail: ming.tsao@ uhn.ca Cite this article as: Mascaux C, Sen T, Sanchez-Cespedes M, et al. Advances in Lung Cancer Basic and Translational Research in 2025 – Overview and Perspectives Focusing on NSCLC. J Thorac Oncol. 2025;20:1369-1391. ª2025 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. ISSN: 1556-0864 https://doi.org/10.1016/j.jtho.2025.05.024 Journal of Thoracic Oncology Vol. 20 No. 10: 1369–1391 x Cancer Research Institute, Samson Assuta Hospital, Ashdod, Israel y Faculty of Health Sciences - Microbiology and Immunology, Ben Gurion University, Beer Sheva, Israel z Department of Radiation Oncology, Department of Immunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York aa Department of Thoracic Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas bb Division of Medical Oncology, National Cancer Centre Singapore, Singapore cc Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland dd International Association for the Study of Lung Cancer, Denver, Colorado ee Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia ff University Health Network-Princess Margaret Cancer Centre, Toronto, Canada gg Department of Laboratory Medicine, Department of Medical Biophysics, University of Toronto, Toronto, Canada Received 24 April 2025; accepted 13 May 2025 Available online - 3 June 2025 ABSTRACT Basic and translational research in lung cancer is a rapidly evolving field with a transformational impact on early detection, diagnosis, therapeutic development, and personalization of care. Recent advances have greatly increased our understanding of the molecular genomics, proteomics, pathogenesis, and cellular biology of this deadly malignancy. The International Association for the Study of Lung Cancer (IASLC) recently formed a Basic and Translational Science (BaTS) Committee to further enhance the scientificleadership of IASLC in thoracic cancer research. This review by members of the committee highlights the breadth of current research in NSCLC, with a focus on molecular risk factors and processes in tumorigenesis, heterogeneity, phenotypic plasticity, metabolic reprogramming, immunobiology, the immune microenvironment, and microbiome. This review also identifies future research areas that may lead to further improvement in survival outcomes and curative therapies especially for patients with advanced NSCLC. 2025 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Keywords: Genomics; Early lung cancer; Tumor heterogeneity; Immune microenvironment; Cancer metabolism; State of Science Introduction Lung cancer is marked by complex genomic and epigenomic aberrations dysregulating the cellular signaling mechanisms and functions of tumor cells, and their interaction with the tumor microenvironment (TME). NSCLC is typically driven by a complex interplay of many biologic pathways, including among others, signal transduction, DNA repair, chromatin modifications, metabolism, and immune checkpoint pathways. Breakthroughs that have occurred in basic and translational research during the past decades have not only enhanced our understanding of the biology and disease mechanisms in lung cancer, but they have also translated into the development of novel and personalized therapeutic strategies, which have improved the overall survival and quality of life for lung cancer patients. In this context, the Basic and Translational Science (BaTS) Committee of the International Association for the Study of Lung Cancer (IASLC) provides a review of the recent advances in our understanding of NSCLC at a cellular and molecular level and its interactions with the TME. We highlight the breadth of current lung cancer research and identify future directions toward advancing scientific innovation to improve patient outcomes and curative therapies. Inherited Susceptibility to Lung Cancer Major progress has been made to elucidate both single-gene and polygenic inheritance of lung cancer. 1,2 A considerable proportion (4%–15%) of patients with lung cancers harbor pathogenic germline variants in cancer genes. 3–5 These are low-frequency variants with high or moderate-penetrance genes, such as BRCA1, BRCA2, CHEK2, ATM, BAP1, EGFR, and TP53. The genome-wide association studies (GWAS) have identified more than 60 lung cancer susceptibility loci. 1,6,7 The potential clinical applications of these GWAS results are the development of polygenic risk scores (PRSs), which aggregate information from multiple genetic variants to quantify an individual’s genetic predisposition to lung cancer. Different PRSs were found as predictors of lung cancer independent of conventional clinical risk factors. 8,9 A genome-wide PRS, leveraging the full GWAS data to quantify genetic predisposition, was recently found to outperform previously reported PRSs. 10 Although the predictive power of the best-performing PRS does not surpass smoking history, it is comparable to other factors used in lung cancer risk models, such as age and sex. 8,10 Moreover, the polygenic background has been found to modulate the risk associated with smoking. However, it remains controversial whether the risk 1370 Mascaux et al Journal of Thoracic Oncology Vol. 20 No. 10 stratification benefits of PRSs are more meaningful in neverorever-smokers. 11–14 Nevertheless, advances in germline genetic testing and PRS provide new opportunities to identify individuals at high risk of lung cancer and we expect this emerging genetic knowledge to be increasingly integrated into lung cancer screening programs. 2,15–17 Carcinogenesis and Early Cancer Interception Early lung carcinogenesis is a complex process involving the sequential accumulation of molecular and genetic abnormalities. Putative preinvasive lesions have been identified for NSCLC: squamous dysplasia and carcinoma in situ as precursors of lung squamous cell carcinomas (LUSC), and atypical adenomatous hyperplasia for lung adenocarcinomas (LUAD). 18 Risk Factors The dominant risk factor associated with lung cancer is tobacco exposure, with over two-thirds of cases attributable to smoking. 19 With the rising incidence of lung cancer in nonsmokers, additional risk factors have emerged including exposure to ionizing radiation (e.g., radon), occupational carcinogens (e.g., asbestos), and air pollution. 20 Although mutagenic potential is a common feature among these exposures along with accumulating age-related mutations, chronic inflammation is likely also a critical component for lung cancer development and progression, as increased risk has been observed in chronic obstructive pulmonary disease and studies of particulate matter air pollution. 21,22 At the same time, adaptive immune surveillance likely limits cancer development by means of recognition of mutations as foreign neoantigens, evidenced for instance by increased lung cancer incidence in immune-suppressed populations and immunogenetic associations with cancer risk. 23,24 As mentioned, family history is also an important risk factor. Taken together, these factors likely contribute in concert to influence lung cancer risk, but greater mechanistic understanding will provide further insights for improved cancer screening and prevention. Squamous Carcinogenesis LUSC accounts for 30% to 40% of lung cancers worldwide and its pathogenesis is significantly linked to tobacco smoking. 25 In North America, LUSC prevalence has dropped to approximately 20%, with more LUSC occurring in peripheral lung, in association with a decline in smoking. 18 Central LUSCs are proceeded by preneoplastic bronchial changes ranging from hyperplasia and metaplasia to mild, moderate, and severe dysplasia, culminating in carcinoma in situ (CIS) (Fig. 1). Preinvasive lesions including dysplasia and CIS typically persist or progress locally within the bronchial tree and are often linked to the development of invasive cancer in distant lung areas, supporting the concept of field cancerization. Recent molecular studies have revealed significant chromosomal instability and methylation changes in bronchial preneoplastic lesions, leading to increased expression of cell cycle pathways and DNA damage response genes, along with transitory metabolic reprogramming and immune sensing and unleashing of tissue-resident immune cells. In high-grade preinvasive lesions, the activation and mobilization of immune cells of both innate and adaptive immunity develop. However, concomitant inhibition of immune response occurs before invasion 26 and is associated with the risk of progression. 27 Even in CIS lesions that regress spontaneously, genomic, epigenomic, and transcriptomic characteristics resembling advanced invasive LUSC are observed. 28 This process involves the simultaneous expression of immune checkpoint molecules and suppressive interleukins, raising hope for the possibility of intercepting progression to invasive cancer by inhibiting the blocking factors of antitumor immune response. Adenocarcinoma Carcinogenesis Atypical adenomatous hyperplasia (AAH) is recognized as the only precursor of LUAD. 29 AAH may progress through preinvasive adenocarcinoma in situ, minimally invasive adenocarcinoma (MIA), and culminating in fully invasive LUAD (Fig. 1). 18,30–33 LUAD precursors present radiologically as ground-glass opacity–predominant pulmonary nodules. The detection of these nodules has increased because of the widespread adoption of low-dose computed tomography (CT) in lung cancer screening and the use of high-resolution CT scans for various medical purposes. 34 Over the past decade, extensive analyses of AAH, adenocarcinoma in situ, and MIA have revealed a progressive increase in the complexity of their molecular evolution and associated immune responses, 35–38 with an increase in total mutation burden, copy number variant burden and cancer gene mutations in later-stage lesions. 35–38 Canonical cancer gene mutations such as KRAS, EGFR, and BRAF seem to be early genomic events during LUAD carcinogenesis, 35–38 in parallel with a gradual suppression of immunity, indicating ongoing “immunoediting.” 37–39 Preclinical studies found that reprogramming the TME may promote antitumor immunity and reduce the burden of invasive adenocarcinoma in mouse models. 40 More recently, single-cell technologies have revealed the complexity of tumor evolution with unparalleled resolution and have pinpointed alveolar type 2–like cells as contributors to LUAD progression. 41,42 How the spatial context October 2025 Overview on Advances in NSCLC Research 1371 within the TME changes during different stages of disease progression remains to be clarified. Biomarkers of Early Detection Small nodules in lung parenchyma can be efficiently detected by low-dose CT to allow early diagnosis of lung cancer and reduction of lung cancer mortality. 43 Recent advances in this field included the application of radiomics and artificial intelligence (AI) to develop noninvasive biomarkers for lung cancer risk prediction, early detection, and prognosis prediction. 44 Analysis of the airway transcriptome of minimally invasive collected bronchial and nasal epithelial cells has proven effective for early diagnosis of lung cancer. 45 Likewise, the detection and molecular profiling of circulating tumor cells (CTC) in blood has been the objective of many studies to identify CTC biomarkers, although their application in lung cancer screening was questioned because of reported low sensitivity in prospective studies. 46,47 Cell-free nucleic acids (DNA and RNA), which can be passively or actively released by tumor cells and by other cells in the TME 48 have been the focus of many studies for early diagnosis, prognosis, and prediction of therapy response. Low-pass whole genome sequencing of cell-free DNA (cfDNA) fragmentation profiles with the aid of AI has exhibited promising results in asymptomatic NSCLC. 49 Indeed, changes to the genomic and epigenetic architecture of cells during carcinogenesis result in a varied cfDNA “fragmentome”in the peripheral blood. 50 Circulating cellfree microRNA in serum or plasma has also been investigated as a diagnostic tool and was validated in lung cancer screening trials. 51,52 More recently, comprehensive proteomic analysis in plasma samples has provided biomarkers for the early prediction of lung cancer. 53 Finally, the integration of multiple types of biomarkers (e.g., nucleic acids and proteins) has also been attempted to detect various cancer types, including lung cancer. Although the specificity seemed high (>99%), the sensitivity was low (w20%–30%), limiting its application as a first-line diagnostic tool in high-risk patients. 54 Tumor Heterogeneity Heterogeneity is an inherent characteristic of all cancers, including NSCLC. It may refer to differences among tumors from different patients, known as intertumoral heterogeneity, which reflects distinct Squamous carcinogenesis A denomatous carcinogenesis Histological stages Histological stages Molecular abnormalies Molecular abnormalies INCREASED PROLIFERATION LOSS OF DNA REPAIR METABOLIC MODIFICATIONS EPITHELIO_ MESENCHEMAL TRANSITION IMMUNE ACTIVATION AND ESCAPE INITIATION OF MMUNE RESPONSE Normal. Hyperplasia. Metaplasia. Mild dysplasia Moderate dys. Severe dysplasia. CIS Invasive SQCC Figure 1. Multistage lung carcinogenesis. The chronologic histologic changes observed in lung squamous and adenomatous carcinogenesis and their cumulative molecular changes. Hypomethylation and Hypermethylation refer to aberrant methylation changes compared with matched normal lung tissues. Dys, dysplasia; CIS, carcinoma in situ; SQCC, squamous cell carcinoma; TMB, tumor mutation burden; SCNA, somatic copy number alteration; AAH, atypical adenomatous hyperplasia; AIS, adenocarcinoma in situ; MIA, minimally invasive adenocarcinoma; IAC, invasive adenocarcinoma. 1372 Mascaux et al Journal of Thoracic Oncology Vol. 20 No. 10 carcinogenic pathways in each tumor. Alternatively, it can describe variation within a single tumor, termed intratumoral heterogeneity (ITH). The latter involves the presence of multiple and diverse clonal cancer cell populations within a single tumor. This diversity underpins the evolution and remarkable adaptability of tumors to various environments, which may lead to progressive invasiveness and aggressiveness, contributing to treatment resistance. A greater understanding of ITH in NSCLC from molecular and histopathologic perspectives is cumulatively impacting patient clinical management (Fig. 2). Intratumor Molecular Heterogeneity The coexistence of molecular and phenotypically distinct subclones within tumors is thought to develop under the so-called branched model of tumor evolution. 55 According to this model, tumors arise from a common ancestor eventually diverging and proliferating simultaneously, each with varying levels of efficacy. The punctuated model is a variant of the latter shaped by macroevolution in which, after an extended stable period, many genomic aberrations occur within short bursts of time. Some tumors may evolve according to a neutral evolution model, in which cancer-driving alterations accumulate randomly within the cancer cell population without having a functional role in promoting tumor growth. 56 TRAcking Cancer Evolution through therapy [Rx] (TRACERx) is a prospective study that sought to define the role of genetic ITH on patient survival and disease characteristics. 57,58 Inference of the clonal architecture in the tumors in the study revealed that cancer driver mutations are under positive selection, not only when they occur as truncal mutations, but also when present in tumor subclones. 59,60 In the same study, a higher subclonal somatic copy number alteration burden, but not mutational burden, was associated with worse disease-free survival. 59 Additional biologic consequences of genetic ITH include increasing neoantigen burden and subsequent immune response 61 in addition to the generation of drug resistance mutations. 62 Epigenetic alterations (e.g., DNA methylation and histone modifications) are crucial for tumor development and contribute to ITH. The most studied epigenetic deregulation in the context of ITH is DNA methylation. Extensive ITH in DNA promoter hypermethylation, driven by changes in DNA copy number, was found to contribute to the molecular and phenotypic heterogeneity of LUAD and lymph node metastases. 63 Further, genomic and DNA methylation changes seem to follow similar ITH evolutionary trajectories with a strong impact on cancer genes and pathways. 64 Given that drug development targeting epigenetic factors is underway, a deep understanding of epigenetic alterations in NSCLC will be essential for their effective implementation in the clinics. 65 ITH can also be observed at gene expression and protein levels, which does not always originate from genomic ITH. 66 Transcriptomic diversity has been found between primary tumors and metastasis and contributes to tumor progression. 66,67 Although multiregion sequencing provided foundational insights into ITH, 35,68 advancements in single-cell sequencing and spatial transcriptomics have elevated ITH research to a new level and have provided comprehensive datasets. 69 Intratumor spatial distribution of immune-related proteins and patterns of proteins functionally involved in cell adhesion or endothelial-cell interaction have been observed, some of which may be prognostic. 70,71 Deciphering the link between the static cancer genotype and its dynamic transcription and protein expression offers novel multilayer insights into the mechanisms of cancer adaptation. 72,73 The development of effective strategies to integrate ITH at the genomic, transcriptomic, and proteomic levels may provide opportunities for enhanced dynamic biologic insights and the identification of novel therapeutic targets in lung cancer. 74,75 Histologic Heterogeneity The current WHO classification of lung cancers includes more than 20 entities, each defined by the unique histopathological appearances of the tumor cells and their growth pattern. 76 Morphologic ITH is best observed in LUADs in which the relative abundance of the different patterns of growth (lepidic, acinar, papillary, micropapillary, and solid) is prognostic (Fig. 3AF). 77,78 Lepidic patterns (Fig. 3A) are considered in situ tumors and, thus, associated with good prognosis. 79 In contrast, nonmucinous LUADs with predominantly micropapillary (Fig. 3D) and solid (Fig. 3E) growth patterns are associated with poor prognosis. 80 On the basis of the IASLC grading system, any tumor with predominant or greater than or equal to 20% of solid, micropapillary, and complex glandular patterns is considered grade 3 (high-grade). 81 More importantly, previous gene expression-based subtypes of LUADs 82 have not been correlated with the morphologic classification, possibly suggesting a more complex multiomics determinant of tumor growth patterns. The molecular mechanisms underlying morphologic features of LUAD remain largely unknown, as do the molecular features associated with the development of lung cancers of mixed types (Fig. 3G). 83 A recent study implementing microdissection of October 2025 Overview on Advances in NSCLC Research 1373 tumor regions in 19 LUADs with mixed histologic patterns or subtypes suggested an association of specific transcriptomic pathways with the different morphologies. 84 Other studies have reported that high-grade histologic patterns are associated with increased chromosomal complexity, a higher burden of genomic aberrations, and lower clonal diversity. 85,86 Clinical Impact of Tumor Heterogeneity Intertumoral heterogeneity and ITH also represent a major hurdle in the effectiveness of therapeutic strategies to treat lung cancer. Regarding intertumoral heterogeneity, even within defined histopathology, co-mutations and molecular differences among tumors can profoundly influence prognosis, tumor plasticity, and therapeutic Figure 2. Molecular regulators and potential therapeutic targets of tumor heterogeneity and plasticity in lung cancer. Graphical representation of genetic, epigenetic, transcriptional, and posttranscriptional mechanisms that promote tumor progression, metastasis, and resistance to therapy. SCNA, Somatic copy number alterations; ITH, intratumor heterogeneity; TME, tumor microenvironment; CNV, copy number variations; TMB, tumor mutational burden; SAC, spindle assembly checkpoint proteins; CAFs, cancer-associated fibroblasts. 1374 Mascaux et al Journal of Thoracic Oncology Vol. 20 No. 10 sensitivity. 87–89 The concomitant RB1 inactivation in EGFR-mutant LUADs may facilitate histopathologic transformation in response to targeted therapy 88 and TP53 mutations co-occurring with EGFR are more likely to induce mixed responses. 90 Similarly, STK11 mutations are linked to reduced sensitivity to immune checkpoint inhibitors (ICIs) in KRAS-driven LUAD, 91 although mutations in KEAP1/NFE2L2 decrease sensitivity to different treatments and are associated with poorer prognosis. 92 These data highlight the importance of determining molecular clonal heterogeneity in otherwise uniform NSCLC populations. Radiomics has recently opened avenues for better imaging assessment of intertumoral heterogeneity. The visualization and assessment of the whole tumor and the metastatic sites for radiomic features using machine learning may become an effective prognostic tool for the prediction of response to immunotherapies. 93 Radiomic data may also lead to opportunities to escalate or change treatment or consider multimodality treatment options. Figure 3. Heterogeneous growth patterns observed in LUADs. (A) Lepidic pattern is considered in-situ noninvasive growth, although (B) acinar, (C) papillary, (D) micropapillary, and (E) solid patterns are regarded as invasive growth patterns. (F) Mucinous adenocarcinoma is distinguished for its finely vacuolated cytoplasm that contains mucin substances. (G) Up to 80% of nonmucinous LUAD contains a mixture of multiple patterns. The predominant pattern is used to subtype nonmucinous LUAD, and their relative abundance is used for grading the tumor. Scale bar, 100 mm. LUAD, lung adenocarcinoma; lep, lepidic; acn, acinar; pap, papillary; sol, solid. October 2025 Overview on Advances in NSCLC Research 1375 Similarly, cfDNA has been used as another noninvasive alternative for tracking molecular heterogeneity and determining clinical management. Analysis of cfDNA in the TRACERx cohort over multiple time points revealed that about 40% of patients had tumors with ITH, in which a dominant clone emerged and replaced others between surgical resection of their primary tumor and disease recurrence. 94 Tumor Cell Plasticity Cellular lineage plasticity (LP) refers to the ability of cells to switch phenotypes to distinct developmental lineages; it is integral to processes such as embryogenesis, tissue repair, and homeostasis. 95 However, cancer cells may hijack these mechanisms to adapt to stimuli or aid tumor progression and metastasis. LP is increasingly recognized as a resistance mechanism to targeted therapies in lung cancer. Notable lineage states in LUAD include cancer stem cell phenotypes, epithelialmesenchymal transition states, and histologic transformation to neuroendocrine characteristics often with SCLC morphology, and transformation to LUSC phenotypes. The mechanisms of LP in lung cancer are still poorly understood, which poses therapeutic challenges in the management of NSCLC at high risk of LP. Although there are distinctions between various forms of plasticity, such as Epithelial-mesenchymal transition (EMT) or adenoneuroendocrine and adenosquamous transformation, there is substantial overlap in the features and mediators of these phenomena. These changes are generally associated with hybrid metastable states characterized by elevated cellular plasticity and stem-like features. Single-cell RNA sequencing in genetically engineered mouse models of LUAD revealed that longitudinal transcriptional heterogeneity with disease progression was stereotypic and reproducible. 96 Certain factors that govern cell fate decisions during development and organ formation have resurfaced in cancer biology as key regulators of ITH and LP. Lineage tracing studies have played a crucial role in mapping the connections between progenitor and differentiated cells, uncovering varying degrees of plasticity across different stages of differentiation. The presence of these cell states may predict poorer survival and are more resistant to chemotherapy 97 and immunotherapy. 98 Histologic Transformation The histologic transformation of LUAD to SCLC or LUSC, with or without therapeutic pressure, epitomizes the LP observed in lung cancer. 99 This transformation process likely involves a complex interplay of genetic, transcriptomic, epigenetic, and immune factors. 100,101 The cell of origin, such as alveolar type 2 cells for LUAD, may play a key role in determining the predilection for certain oncogenic pathways. The biallelic inactivation of key tumor suppressor genes, TP53 and RB1, is associated with histologic transformation from LUAD to SCLC in tumors under tyrosine kinase inhibitors anti-EGFR therapy. 102 A "third hit”such as FGF9 upregulation is associated with SCLC transdifferentiation. 99 However, the exact mechanisms remain unknown. Recently, through genetically engineered mouse models and single-cell RNA sequencing, the upregulation of transcriptional programs induced by expression of Myc in cooperation with RB1 loss has been implicated. 96 In addition, an intermediate basal stemlike cell state induced by EGFR inhibition may facilitate a tolerance to Myc-driven histologic transformation. Histologic transformation of LUAD to LUSC, whereby de novo deficient Stk11 triggers extracellular matrix remodeling and p63 up-regulation, 103 may similarly be characterized by an intermediate cell state with predisposing genetic alterations governing LP in response to therapy. In response to KRAS-targeted therapy, concurrent STK11 mutations may alter the regulation of chromatin accessibility. Consequently, modulation of lineage-related transcription factors and the ELF5DNp63 axis may drive histologic transformation. 104 Finally, cell-extrinsic factors may also play a crucial role in shaping lineage cell states by providing a permissive microenvironment for histologic transformation, 105,106 although this remains underexplored to date. Drug-Tolerant Persister Cells Residual cancer cells that persist during treatment serve as the reservoir for the emergence of drug resistance. This has prompted research into the cellular and molecular basis of drug tolerance, the evolution of drugtolerant persister (DTP) cells, and the identification of therapeutic vulnerabilities to target them, mostly in the context of targeted therapies. In EGFR-driven LUAD patient-derived xenograft models, the transcriptional profile of DTP cells to tyrosine kinase inhibitors has been identified in subpopulations of treatment-naive tumors suggesting that, in some cases, these cells are present before treatment. 107,108 A role for epigenetic processes in maintaining the drug-tolerant state, including alterations in histone methylation patterns linked to repression of LINE-1 elements was uncovered. 109,110 Additional mechanisms that lead to activation of NFkB and JAK-STAT pathways, the antioxidant KEAP1-NRF2 pathway, EMT, senescence, translation reprogramming, impaired cell death, and alveolar regeneration contribute to reduced treatment sensitivity in DTP and constitute a common mechanism by which lung cancer cells 1376 Mascaux et al Journal of Thoracic Oncology Vol. 20 No. 10 withstand therapy-induced stress. 92,107,111–117 Understanding when specific mechanisms of drug tolerance occur and how they can be targeted will be necessary to identify new approaches to mitigate or forestall the emergence of resistance. 118–120 EMT EMT is a highly dynamic and reversible cellular program in which epithelial cells lose cell-cell junctions, display altered apical-basal polarity, and acquire increased migratory capacity. 121 EMT histologically may manifest in poorly differentiated NSCLC with sarcomatoid or spindle cell features. Recent efforts have contributed to uncovering the molecular mechanisms associated with EMTmediated resistance. ZEB1 directly binds the promoter of BIM, a positive regulator of apoptosis, repressing its transcription. 122 Similarly, Aurora kinase B mitigates BIMinduced apoptosis to promote cell survival to treatment. 123 Activation of the YAP/FOXM1 axis promotes an increased abundance of spindle assembly checkpoint effectors and mediates EMT-associated EGFR inhibitor resistance. 124 Concordantly, model systems of osimertinib resistance caused by EMT display activation of ATRCHK1-Aurora kinase B signaling. 123 EMT-mediated resistance has also been attributed to the reactivation of downstream signaling pathways, including sustained activation of AXL, 125–127 FGFR1, 128,129 and SRC. 130 More recently CD70, which is highly expressed in NSCLC with mesenchymal phenotype, 131 was reported to be a targetable mechanism of EMT-associated EGFR inhibitor resistance. 132 In-depth molecular characterization of baseline, on-treatment, and resistant tumors and CTC, together with functional analyses, might also help capture the diversity and dynamics of EMT and contribute to uncovering the molecular alterations underlying its role in resistance to therapy. 121 These findings may reveal targetable dependencies and therapeutic combination rationales to resensitize mesenchymal lung cancers to targeted therapy in preclinical models. 122,123,126,128,129,132 TME Tumors, including NSCLC, consist of a diverse ecosystem of cells which, in addition to cancer cells, include a plethora of host cells with widely different and often opposing functions in oncogenesis. The importance of the immune cell contexture in NSCLC has been well established and draws from studies exhibiting the TME to be strongly prognostic and the marked success of cancer immunotherapy increasingly becoming part of first-line care. 75,133,134 Many of the principles governing the immuneand cancer cell interrelationship seem to be well preserved across NSCLC stages, and histologic and molecular subtypes with certain exceptions, further bolstering the broad use of immunotherapy clinically. However, durable benefits to cancer immunotherapy occur in a minority of patients with NSCLC for reasons still incompletely understood, warranting a better understanding of tumor-immune cell dynamics in NSCLC to spark a new wave of effective therapeutic strategies resulting in long-lasting tumor control. NSCLC Immunogenicity and T-cell Recognition Intratumoral immune cells sculpt NSCLC genomic heterogeneity and vice versa, NSCLC cells influence immune cells through various mechanisms. Earlier findings in preclinical models revealed increased tumorigenesis in the lack of key immune cells or antitumor effector molecules. This led to the understanding that tumors are constantly surveilled by cytotoxic Tand natural killer (NK) cells with immunogenic tumor cell clones being lysed in a process called “immuno-editing.” In the past decade, increasing evidence points to a role for T-cells in shaping tumor cell heterogeneity in patients with NSCLC. Seminal studies including those from the TRACERx consortium have reported increased T-cell infiltration in patient tumors with high tumor mutation burden (TMB), tumor areas exhibiting highly clonal neoantigen expression, as opposed to low neoantigen and clonally heterogenous tumor areas. 61,135 These cells, however, are found to be dysfunctional bearing an “exhausted”phenotype characterized by the expression of multiple immune regulatory molecules including LAG-3 and programmed cell death protein 1 (PD-1). 61,136 Anti–PD-1 was especially effective in these patients and, to a lesser extent, in those with a more Tcell and neoantigen-devoid TME. 61,135–137 Latter studies further exhibited compelling evidence of T cells driving genomic tumor evolution, exhibiting decreased neoantigen recognition potential in high T-cell–infiltrated tumor regions through genomic, transcriptional, and epigenetic mechanisms inducing immune evasion (e.g., loss of human leukocyte antigens (HLA) alleles). 138–140 Whereas, in established tumors, immune evasion leads to further tumor outgrowth, earlier CIS lesions in LUSC that spontaneously regressed exhibited increased T-cell presence and inflammation. 141 A significant proportion of CIS, however, still progresses to overt NSCLC, exemplifying that immune evasion is a critical step early in tumorigenesis (Fig.4). 26,141 These studies highlight the impact of T-cells and other immune cells in driving ITH after the recognition and killing of immunogenic tumor cells. This process, in turn, can be reinvigorated by ICI, leading to potentially long-lasting and even complete responses in a subset of patients. Further research is needed to understand what determines tumor behavior and response to ICI and to learn from cells in and outside October 2025 Overview on Advances in NSCLC Research 1377 personal fees/support from Abbvie, Lilly, GSK, Iovance, Biotherapeutics, Arcus Biosciences, Roche, Regeneron, Genentech, Novocure, OncoHost, AstraZeneca (AZ), Amgen, Daiichi Sankyo, Lilly, Pfizer, Janssen/Johnson&Johnson (JNJ), BMS, Iovance, Merck KGaA, and Synthekine, Inc. Dr. Cavic reports receiving personal fees/support from Roche and AZ. Dr. Cerciello reports receiving personal fees/support from BMS, PharmaMar, and Takeda. Dr. Skoulidis reports receiving research grants from Amgen, Mirati Therapeutics/BMS, Revolution Medicines, Novartis, Merck & Co; and personal fees/support from Tango Therapeutics, Medscape LLC, Intellisphere LLC, RV Mais Promocao, Eventos LTDS, MJH Life Sciences, IDEOlogy Helath, MI&T, PER LLC, CURIO LLC, DAVA Oncology, AZ, Revolution Medicines, Novartis, Guardant Health, Novocure, Regeneron, BridgeBio, Beigene, BergenBio, BMS, Calithera Biosciences, Merck Sharp&Dome,Genentech/Roche,andGenMab.Dr.John reports receiving personal fees/support from BMS, AZ, Amgen, Roche, Pfizer, Takeda, Boehringer-Ingelheim, MSD, Merck, Puma, Specialised Therapeutics, Gilead, Seagen, JNJ, Bayer, and Beigene. Dr. Mascaux receiving personal fees/support from AZ, Roche, MSD, Sanofi, BMS, Regeneron, Pfizer, Takeda, Janssen, Amgen, and Daichii-Sankyo. Dr. Ortiz-Cuaran reports receiving personal fees/support from Pierre Fabre. Dr. Politi reports receiving grants from AZ, Roche/Genentech, D2G Oncology, Boehringer-Ingelheim, and Wojcicki Foundation; and personal fees/support from Revelio Therapeutics, Pfizer, AstraZeneca, and Janssen. Dr. Roisman reports receiving grants from ThermoFisher, and ISLAC VIKTOR Platform. Dr. Samstein reports receiving a grant from Merck. Dr. Sanchez-Cespedes reports receiving a grant from Merck KGA. Dr. Sen reports receiving grants from Jazz Pharmaceuticals, and Debiopharm; and personal fees/support from Regeneron and BMS. Dr. Tan reports receiving grants from AZ and Takeda; and personal fees/support from Amgen, Pfizer, Bayer, Roche, AZ, Guardant, Merck, and Takeda. Dr. Thomas reports receiving grants from EMD Serono, AZ, Immunomedics, Prolynx, Immunomedics, and Tarveda. Dr. Zhang reports receiving personal fees/support from JNJ, AZ, Novartis, BMS, GenePlus, Innovent, Oncohost, Hengrui, Catalyst, Merck, Summit, and Helius. 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