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PubMed2026

Characterization of the genomic and transcriptomic landscape of invasive non-mucinous lung adenocarcinoma based on IASLC grading.

BACKGROUND: The IASLC grading system has prognostic utility and potential therapeutic implications in invasive non-mucinous lung adenocarcinoma (LUAD), but the molecular basis underlying the grading spectrum remains unclear. METHODS: We performed whole-genome sequencing in 138 Chinese patients with invasive non-mucinous LUAD and RNA sequencing of 96 matched tumor-normal tissue pairs to systematically characterize the molecular features across grades, including coding driver events, mutational signatures, non-coding regulatory disruptions, and transcriptional programs. RESULTS: Compared with Grade 1-2 tumors, Grade 3 LUADs exhibited heightened invasive potential, manifested by more advanced stage, more frequent spread through air spaces, and independently worse survival. Grade 3 tumors had elevated tumor mutational burden and were enriched for alterations in genome maintenance and cell-cycle genes, including TP53, as well as genes implicated in DNA damage response, including ZFHX4. APOBEC-associated mutagenesis was selectively enriched in Grade 3 tumors independent of smoking status, consistent with an instability-associated phenotype. Recurrent non-coding regulatory disruptions affected lung lineage-defining genes, particularly surfactant-associated genes, and were correlated with reduced expression. Transcriptomic profiling revealed epithelial dedifferentiation, loss of pulmonary homeostatic programs, and activation of proliferative and stress-related pathways. Notably, MUC16 emerged as a convergent event linking genomic and transcriptional dysregulation, with coding mutations associated with higher expression and increased expression in Grade 3 tumors correlating with the proportion of high-grade histologic patterns. CONCLUSIONS: These findings provide a molecular framework for the IASLC grading spectrum and identify Grade 3 LUAD as a distinct instability-associated and dedifferentiated biological state.

IASLC grading↗

PubMed2024

Loss of Fbxo45 in AT2 cells leads to insufficient histone supply and initiates lung adenocarcinoma.

Dysregulation of histone supply is implicated in various cancers, including lung adenocarcinoma (LUAD), although the underlying mechanisms remain poorly understood. Here, we demonstrate that knockout of Fbxo45 in mouse alveolar epithelial type 2 (AT2) cells leads to spontaneous LUAD. Our findings reveal that FBXO45 is a novel cell-cycle-regulated protein that is degraded upon phosphorylation by CDK1 during the S/G2 phase. During the S phase or DNA damage repair, FBXO45 binds to UPF1 and recruits the phosphatase PPP6C, thereby inhibiting UPF1 phosphorylation. This process is crucial for preventing the degradation of replication-dependent (RD) histone mRNAs and ensuring an adequate histone supply. In the absence of FBXO45, the impaired interaction between PPP6C and UPF1 results in sustained hyperphosphorylation of UPF1 throughout the cell cycle, leading to an insufficient histone supply, chromatin relaxation, genomic instability, and an increased rate of gene mutations, ultimately culminating in malignant transformation. Notably, analysis of clinical LUAD specimens confirms a positive correlation between the loss of FBXO45 and genomic instability, which is consistent with our findings in the mouse model. These results highlight the critical role of FBXO45 as a genomic guardian in coordinating histone supply and DNA replication, providing valuable insights into potential therapeutic targets and strategies for the treatment of LUAD.

Animals↗

PubMed2026

Exploring the mechanism of Shengmai San in treating lung adenocarcinoma based on bioinformatics and molecular dynamics simulation.

To investigate the mechanism of Shengmai San (SMS) in the treatment of lung adenocarcinoma (LUAD) based on an integrated strategy combining "network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation," aiming to provide a precise combination therapy strategy and identify potential bioactive compounds. Differentially expressed genes in LUAD were identified from the Gene Expression Omnibus database using R (originally developed at Bell Laboratories and currently managed by Lucent Technologies). SMS components (ginseng, Ophiopogon japonicus, and Schisandra chinensis) were retrieved from encyclopaedia of traditional Chinese medicine, with Lipinski-compliant compounds selected. Compound targets were predicted via SwissTargetPrediction and Similarity Ensemble Approach. Intersecting targets between differentially expressed genes and compound targets were identified for "herbs-compounds-targets-disease" network construction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Hub targets were identified by analyzing the protein-protein interaction network. High-prognostic relevance targets were screened from The Cancer Genome Atlas. Compounds targeting these were identified through the herbs-compounds-targets-disease network, and absorption, distribution, metabolism, excretion, and toxicity-compliant compounds were selected using SwissADME (a web-based tool provided by the Molecular Modeling Group of the Swiss Institute of Bioinformatics). Core regulatory targets were identified through molecular docking, with complex stability assessed by molecular dynamics simulations. The key bioactive compounds of SMS for treating LUAD were identified as 7-hydroxy-2,5-dimethyl-4H-1-benzopyran-4-one, N-trans-feruloyltyramine, paprazine, and (E)-N-[(2S)-2-hydroxy-2-(4-hydroxyphenyl)ethyl]-3-(4-hydroxyphenyl)prop-2-enamide. Hub targets included AURKA, CCNA2, CCNB1, CDK1, CHEK1, KIF11, NEK2, PLK1, TTK, and TYMS. Among these, CDK1, CHEK1, and PLK1 demonstrated both high-prognostic relevance and strong binding affinity with SMS, emerging as core regulatory targets for SMS in LUAD treatment. Mechanistically, SMS exerts its anticancer effects primarily by modulating the tumor necrosis factor, interleukin-17, cell cycle, and Lipid and atherosclerosis signaling pathways. The active components of SMS, such as paprazine, may exert antitumor effects partly through downregulating CDK1, CHEK1, and PLK1 expression. Although the present study did not examine drug-resistance models or combination regimens, our findings raise the possibility that, in patients with high expression of these genes, combining SMS with standard chemotherapy or targeted therapy could potentially enhance chemosensitivity and mitigate the development of resistance. This hypothesis, however, requires formal testing in appropriate preclinical models and functional validation studies.

Molecular Dynamics Simulation↗

PubMed2026

Human Variation-Informed Prioritization of MPHOSPH6 in Lung Adenocarcinoma: A Source-Aware Multiomics Evidence Framework.

Moving from an association signal to a clinically credible biomarker requires several links that are often conflated: verified variant identity, aligned allelic effects, reproducible gene-level association, relevant cellular expression, and a plausible functional consequence. We developed a source-aware multiomics framework to assess MPHOSPH6 in lung adenocarcinoma (LUAD) while keeping those evidence classes separate. Six prespecified rsIDs were recovered from the harmonized TRICL LUAD dataset, of which five reached p < 5 × 10 - 8. Only rs112333466 and rs76474922 were available with alignable alleles in FinnGen R10, and both showed concordant directions. Fixed-effect estimates were OR = 1.592 for rs112333466-T (95% CI, 1.401-1.809; p = 9.91 × 10 - 13) and OR = 0.819 for rs76474922-C (95% CI, 0.773-0.867; p = 1.03 × 10 - 11). In a prespecified two-variant GTEx v8 lung model, genetically predicted MPHOSPH6 expression was positively associated with LUAD in TRICL (Z = 3.341, p = 8.35 × 10 - 4) and FinnGen (Z = 2.697, p = 0.0070). This gene-level result did not establish colocalization or connect MPHOSPH6 to the six susceptibility rsIDs. Patient-level analysis of 89,241 immune cells from six paired tumor and normal-adjacent lung samples found no significant difference in MPHOSPH6 pseudobulk abundance (exact paired Wilcoxon p = 0.3125). None of 688 lung-lineage pharmacogenomic tests remained significant after false-discovery-rate correction. Ten recorded MPHOSPH6 missense alleles, including five ClinVar variants of uncertain significance, were curated; structural analysis identified I58 at an experimental RNA-exosome interface and defined a focused perturbation series. MPHOSPH6 is therefore supported as a human-variation-informed candidate for functional evaluation, not as a validated LUAD biomarker, pathogenic gene, drug-response predictor, or therapeutic target.

Humans↗

PubMed2026

RAS signaling in lung adenocarcinoma is defined by lineage context and DUSP4 loss.

BACKGROUNDThe molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-oncogene pie chart, but identical mutations exhibit heterogeneous signaling shaped by comutations, transcriptional programs, and lineage context. We propose a lineage-integrated signaling framework using an EGFR mutation signature (mSig).METHODSWe defined EGFR mSig using differentially expressed genes in EGFR-mutant (EGFR-mt) LUADs. Semisupervised clustering and machine learning models were used to test reproducibility in different combinations of datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and EGFR copy number alterations in EGFR mSig-defined subtypes of LUAD.RESULTSEGFR mSig showed robust classification performance (area under receiver operating characteristic curve = 0.83-0.95; mean negative predictive value = 96.3%). Validated gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. Most EGFR mSig+ tumors, including many without EGFR mutations, belonged to the bronchioid subtype. A subset of canonical RAS mutations were mSig+ and mirrored the EGFR mutation pattern. EGFR WT/mSig- tumors were enriched for nonbronchioid subtypes and had comutations in TP53 or RAS/RAF/RTKs. We highlight a parsimonious collection of coordinated mutations, including RAS, KEAP1, STK11, TP53, and CDKN2A, that taken together suggest coordination of tumor signaling previously suggested but now reproduced and expanded.CONCLUSIONA potentially novel EGFR mSig that captures the transcriptional footprint of EGFR activation revealed a subset of EGFR WT LUADs with mt-like features. mSig refines LUAD taxonomy beyond mutation-only pie-chart models by incorporating lineage and comutation context. Lineage-directed stratification with coalteration identifies clinically relevant groups across EGFR and RAS states and highlights treatment opportunities for patients currently considered oncogene-negative.FUNDINGNational Cancer Institute (NCI) U01CA272541, R01CA262296, U24CA264021, UG1CA233333, R01CA211939.

Humans↗

PubMed2024

A case of Ph+ acute lymphoblastic leukemia and EGFR mutant lung adenocarcinoma synchronous overlap: may one TKI drug solve two diseases?

BACKGROUND: Philadelphia chromosome positive (Ph+) acute lymphoblastic leukemia (ALL) refers to ALL patients with t(9;22) cytogenetic abnormalities, accounting for about 25% of ALL. Lung adenocarcinoma (LUAD) is the most common pathological type of non-small-cell lung cancer, which has a frequency of approximately 45% cases with mutations in EGFR. Both Ph+ ALL and EGFR mutant LUAD are involved in the pathogenesis of the abnormal activation of the tyrosine kinase pathway. Although the second primary hematological malignancy after the treatment of solid tumors is common in clinics, the synchronous multiple primary malignant tumors of hematological malignancy overlap solid tumors are uncommon, even both tumors involved in the pathogenesis of the abnormal activation of the tyrosine kinase pathway are extremely rare. CASE PRESENTATION: An 84-year-old man with fatigue and dizziness was diagnosed with Ph+ ALL. Meanwhile, a chest CT indicated a space-occupying lesions, characterized by the presence of void, in the right lower lope with the enlargement of mediastinal lymph node and right pleural effusion. After a few weeks, the patient was diagnosed with LUAD with EGFR exon 19 mutation. Both tyrosine kinase inhibitors (TKI) (Flumatinib) and EGFR-TKI (Oxertinib) was used for the patients, and finally have controlled both diseases. CONCLUSION: As far as we know, we for the first time reported a case of Ph+ ALL and EGFR mutant LUAD synchronous overlap, of which pathogenesis is related to abnormal tyrosine kinase activation. This patient was successfully treated with two different TKIs without serious adverse events.

Humans↗

PubMed2026

Efferocytosis related KCTD12 is a clinico-immune target in lung adenocarcinoma.

BACKGROUND: Efferocytosis, the clearance of apoptotic cells by phagocytes, contributes to immune homeostasis but may also promote tumor immune tolerance. However, its transcriptional landscape and clinical relevance in lung adenocarcinoma (LUAD) remain incompletely understood. METHODS: We systematically analyzed efferocytosis-associated genes across TCGA and multiple GEO datasets to classify LUAD subtypes and construct a prognostic risk model. The prognostic and immunological relevance of this model was validated in four independent cohorts and further assessed through immune infiltration, genomic, and immunotherapy datasets. Functional and pharmacogenomic analyses were performed to identify potential therapeutic vulnerabilities, and the efferocytosis-associated signature gene KCTD12 was subsequently validated in vitro. RESULTS: Unsupervised clustering identified two efferocytosis-based LUAD subtypes with distinct prognostic and immune-metabolic characteristics. The derived risk model robustly predicted overall survival across validation cohorts. Among the model genes, KCTD12 emerged as an efferocytosis-associated candidate linked to an immune-active tumor microenvironment. Across the analyzed single-cell, spatial transcriptomic, and immunotherapy-treated cohorts, higher KCTD12 expression was associated with enhanced cytotoxic T-cell activity and more favorable treatment outcomes. Functional experiments confirmed that KCTD12 suppresses tumor cell proliferation, reduces colony formation, and enhances OT-1 CD8+ T-cell activation and cytotoxicity. CONCLUSIONS: Our study identifies an efferocytosis-associated transcriptional program linked to immune heterogeneity and prognosis in LUAD. The efferocytosis-related risk signature provides a framework for prognostic and immune stratification, while KCTD12 represents a candidate biomarker associated with immune activation and clinical outcomes in immunotherapy-treated cohorts. Its treatment-specific predictive value requires prospective validation in appropriately controlled studies.

KCTD12↗

PubMed2026

Phosphoproteomic Profiling of Early-Stage Non-Small Cell Lung Cancer Provides Preliminary Evidence of Phosphorylation-Regulated Rho GTPase Signaling Driving Cytoskeletal Remodeling, Angiogenesis, and Cell Cycle Progression.

Non-small cell lung cancer (NSCLC) is the primary cause of cancer-related deaths worldwide. This can be attributed to the difficulty in early detection and the limited efficacy of available treatments, partly due to an incomplete understanding of the disease biology. Identification of key proteins involved in early-stage progression and understanding the underlying mechanisms can greatly contribute to the development of diagnostic and treatment strategies for NSCLC. Quantitative phosphoproteomic analysis was done on paired tumor tissues and adjacent normal lung tissues from early-stage NSCLC adenocarcinoma (LUAD) patients to allow for the identification of proteins with differential phosphorylation and their associated pathways. A total of 6483 phosphoproteins were identified, with 1229 proteins having significantly higher phosphorylation and 701 proteins having significantly lower phosphorylation in the tumor tissues. All MS data were deposited in ProteomeXchange with the identifier PXD071583. Function enrichment analysis showed that the differentially phosphorylated proteins and phosphosites were primarily involved in Rho GTPase signaling and cytoskeleton remodeling. Analysis of protein interaction networks suggests that the predicted kinase activity likely drives malignant transformation in NSCLC LUAD, presumably through Rho GTPase-mediated angiogenesis and cell cycle progression. More importantly, this study identified several protein phosphosites with differential phosphorylation and inferred kinase-phosphosite activities that have not previously been reported in NSCLC LUAD.

Humans↗

PubMed2026

Machine learning prognostic model and drug survival analysis for lung adenocarcinoma in the context of radiotherapy.

BACKGROUND: Patients with lung adenocarcinoma (LUAD) receiving radiotherapy represent an important but underexplored clinical subgroup. These patients often undergo concomitant pharmacologic treatments, yet the prognostic impact and underlying determinants of such combined regimens remain poorly understood. OBJECTIVE: This retrospective observational study aimed to develop and validate a radiotherapy-specific machine learning prognostic model for LUAD and to compare survival across concomitant pharmacologic regimens. METHODS: In this retrospective observational study, using genomic and clinical data from TCGA, a radiotherapy-specific prognostic model for LUAD was developed and validated through ten machine learning algorithms. Survival analyses were conducted across distinct concomitant pharmacologic strategies, followed by functional enrichment to elucidate molecular mechanisms underlying differential outcomes. RESULTS: Demonstrating robust prognostic abilities, the model efficiently sorted patients into high- and low-risk categories. Both treatment type and risk score independently predicted overall survival, with significant interaction effects. Low-risk patients receiving targeted or combination therapy-mainly erlotinib, gefitinib, or bevacizumab-exhibited substantially improved survival compared with those receiving conventional chemotherapy. Enrichment of "Exogenous peptide presentation," "MHC class II assembly," "Peptide-MHC II assembly," and "Symbiotic interaction" pathways indicated immune modulation and host-tumor crosstalk as key mediators of treatment efficacy. CONCLUSION: This study establishes a radiotherapy-specific prognostic model for lung adenocarcinoma, demonstrating distinct molecular and therapeutic heterogeneity and highlighting the superior survival benefit of targeted combination therapy in low-risk patients.

Humans↗

PubMed2023

MCT4-dependent lactate secretion suppresses antitumor immunity in LKB1-deficient lung adenocarcinoma.

Inactivating STK11/LKB1 mutations are genomic drivers of primary resistance to immunotherapy in KRAS-mutated lung adenocarcinoma (LUAD), although the underlying mechanisms remain unelucidated. We find that LKB1 loss results in enhanced lactate production and secretion via the MCT4 transporter. Single-cell RNA profiling of murine models indicates that LKB1-deficient tumors have increased M2 macrophage polarization and hypofunctional T cells, effects that could be recapitulated by the addition of exogenous lactate and abrogated by MCT4 knockdown or therapeutic blockade of the lactate receptor GPR81 expressed on immune cells. Furthermore, MCT4 knockout reverses the resistance to PD-1 blockade induced by LKB1 loss in syngeneic murine models. Finally, tumors from STK11/LKB1 mutant LUAD patients demonstrate a similar phenotype of enhanced M2-macrophages polarization and hypofunctional T cells. These data provide evidence that lactate suppresses antitumor immunity and therapeutic targeting of this pathway is a promising strategy to reversing immunotherapy resistance in STK11/LKB1 mutant LUAD.

Animals↗

PubMed2026

Spatial transcriptomics of primary and metastatic ALK-rearranged NSCLC reveals site-specific adaptations.

INTRODUCTION: Genetic alterations and the tumor microenvironment (TME) influence treatment response in anaplastic lymphoma kinase-rearranged non-small cell lung cancer (ALK+ NSCLC). This study maps site-specific TME adaptations and exploratory risk-associated signatures in lymph node metastases (LNT) to investigate metastatic evolution. METHOD: We applied spatial transcriptomics to profile tumor (PanCK+) and stromal (PanCK-) compartments in a pilot cohort of 16 cases: primary lung tumors (LT, n = 3), LNT (n = 10), and brain metastases (BT, n = 3), with three site-matched non-tumor controls. LNT-derived prognostic signatures were evaluated using The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA LUAD) cohorts. RESULTS: Distinct, site-specific TME features were observed. LNT stroma was enriched in fibroblasts and macrophages, while tumor segments showed increased neutrophils. BT exhibited a macrophage-associated immunosuppressive TME. Tumor cells evolved divergently: LT retained pulmonary identity and showed trend towards translation-associated programs, LNT cells shifted toward senescence and epigenetic remodeling, and BT cells showed activation of Class A/1 (Rhodopsin-like) receptor, GPCR and drug metabolism pathways. In LNT, exploratory risk-associated differences were observed. Low-risk cases (n = 6) showed adaptive immune signatures, whereas high-risk cases (n = 4) showed enrichment for stromal MET signaling and stress-response pathways. Because treatment exposure differed markedly between the risk groups, these observations should be interpreted as hypothesis-generating. TCGA LUAD analysis suggested the broader biological relevance of immune-associated markers, but reflected general LUAD rather than ALK+ specific biology. Discordant associations for GCLC and TIMP1 underscored the importance of spatial context. CONCLUSION: Site-specific microenvironments may influence tumor adaptation across metastatic niches in ALK+ NSCLC. The exploratory risk-associated findings require validation in larger, uniformly treated cohorts.

Humans↗

PubMed2026

Molecular Profiling Across 80,000 Patients With Lung Cancer.

INTRODUCTION: Biomarker testing is an essential component of optimal therapeutic management in NSCLC, enabling the use of both Food and Drug Administration-approved and emerging targeted therapies. Despite well-established biomarker testing guidelines and the availability of many approved targeted therapies, a substantial proportion of patients with advanced NSCLC are not benefiting from precision oncology. In this study, we analyze the distribution of actionable genomic alterations across histologic subtypes and clinicodemographic subgroups of NSCLC using data in 82,328 samples profiled with a single comprehensive genomic profiling assay, aiming to support universal molecular testing across all NSCLC subtypes to ensure equitable access to available therapeutics. METHODS: This is an observational retrospective analysis on histologically confirmed NSCLC cases tested with comprehensive genomic profiling by next-generation sequencing between 2014 and 2022 using Foundation One/Foundation CDx. All cases were centrally reviewed by board-certified anatomic pathologist to determine histologic type and subtype. RESULTS: A total of 82,328 patients with NSCLC were included. An actionable genomic alteration (GA) was found in 35.1% of the cases. Lung adenocarcinoma (LUAD) and adenosquamous carcinoma were more frequently associated with actionable GA (45.8% and 40.9%, respectively) as compared with sarcomatoid (29.1%), not otherwise specified (27.6%), large cell (21.1%), and squamous cell (6.5%) histologies. Sarcomatoid histology had the highest METex14 skipping mutation (mut) frequency (9.95% versus 2.43% in LUAD). Tumor mutation burden more than or equal to 10 mut/Mb was associated with histology (50.91% in large cell, 40.79% in not otherwise specified, 39.08% in squamous cell, and 36.30% in sarcomatoid versus 31.22% in LUAD and 29.22% in adenosquamous carcinoma). Patients with actionable GA had usually a low tumor mutation burden (80.88%). A significant correlation (p < 0.005) between age and actionable GA was reported for BRAF/ERBB2 muts, ALK/RET/ROS1 rearrangements, and MET amplification. EGFR actionable muts and KRAS G12C were more frequently observed in females, whereas no significant correlation between sex and other GA was observed. Finally, genetic ancestry analyses revealed a strong correlation for EGFR actionable muts and South/East Asia and America, but not for other GA. CONCLUSIONS: This is the largest NSCLC data set analyzed for biomarker distribution across histologies, age, sex, and genetic ancestry. This data set confirms sufficient enough biomarker prevalence across many histologic subtypes of NSCLC, providing reassurance that all NSCLC cases should be considered for biomarker workup.

Humans↗

PubMed2026

Distinct spatial immune microenvironment features of different EGFR mutation subtypes in early-stage lung adenocarcinoma.

Epidermal growth factor receptor (EGFR) mutations are common in lung adenocarcinoma (LUAD), yet their influence on the spatial tumor immune microenvironment (TIME) in early-stage disease remains unclear. We characterized the spatial TIME in 144 treatment-naïve, early-stage LUADs using integrated genomic sequencing and multiplex immunohistochemistry (mIHC). Although EGFR-mutant tumors overall displayed reduced CD8 + T-cell infiltration compared with EGFR-wild-type tumors, substantial heterogeneity was observed among EGFR subtypes. Specifically, L858R and rare-variant subtypes exhibited higher tumor mutational burden, greater CD8 + T-cell density, and enrichment of T-cell-dominant cellular neighborhoods relative to 19del subtype, consistent with a comparatively immune-infiltrated phenotype. In contrast, 19del tumors showed lower T-cell infiltration. TP53 co-mutation was also associated with enhanced CD8 + T-cell infiltration. These cross-sectional findings identify hypothesis-generating spatial immune phenotypes across EGFR-mutant LUAD subtypes; their potential relevance to perioperative treatment selection requires prospective validation in outcome-annotated treatment cohorts.

Humans↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2026

Circulating tumor-associated autoantibody signatures for diagnosis and prognosis in small-cell lung cancer and lung adenocarcinoma.

BACKGROUND: Tumour-associated autoantibodies (TAAbs) are promising biomarkers for cancer detection, but their induction and clinical relevance in lung cancer remain unclear. METHODS: Serum samples from 695 individuals were analysed for TAAb profiling by protein-array screening and two-stage ELISA validation. Diagnostic models were constructed with identified TAAbs and compared with conventional tumour markers. Potential mechanisms, clinical and prognostic features of TAAb seropositivity were analysed and its presence in prediagnostic sera was evaluated to assess the potential for early detection. RESULTS: Six TAAbs for small cell lung cancer (SCLC) and four for lung adenocarcinoma (LUAD) were identified, demonstrating excellent diagnostic performance (AUC > 0.8) and outperforming ProGRP and CEA. TAAb induction correlated with antigen overexpression, somatic mutations and HLA class II amino acid polymorphisms. TAAb panel seropositivity was associated with older age and advanced stage in both subtypes, and predicted poor survival in SCLC but a favourable outcome in advanced LUAD. In prediagnostic sera, the TAAb concentration increased progressively, with detectability up to 2 years before clinical diagnosis. CONCLUSIONS: Distinct TAAb panels were identified for SCLC and LUAD, serving as accurate diagnostic markers that enable early detection and as indicators of prognosis in different clinical contexts.

Humans↗

PubMed2026

Histone variant H2A.J is an epigenetic regulator of metastasis in lung adenocarcinoma.

Metastasis is a major contributor to poor patient survival in lung adenocarcinoma (LUAD); however, the underlying mechanisms remain incompletely understood. Unlike tumorigenesis-associated mutations, recurrent genetic alterations specifically linked to metastasis have not been identified, suggesting that epigenetic mechanisms may play a key role. In this study, we report that histone H2A variant H2A.J expression is significantly down-regulated in LUAD, and that low H2A.J levels are associated with unfavorable survival outcomes. Functional assays revealed that H2A.J overexpression suppresses cancer cell invasion and metastatic potential by modulating the expression of metastasis-associated genes, including TMEM158. Mechanistically, H2A.J is deposited in the promoter region of TMEM158, where it alters the local chromatin status to suppress transcriptional activity. Taken together, our findings suggest that H2A.J functions as an epigenetic suppressor of metastasis in LUAD and highlights its potential as both a prognostic biomarker and a therapeutic target to metastatic progression.

Humans↗

PubMed2025

A prognostic signature for lung adenocarcinoma in people who have never smoked.

Knowledge of tumor cell dynamics can inform prognosis and treatment yet is largely lacking for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA-seq data from 684 NS-LUAD and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histological data further characterized the subtypes. 'Steady', marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver genes' alterations, is linked to prolonged survival and low immune evasion. 'Proliferative' shows high proliferation markers, TP53 mutations, and gene fusions. 'Chaotic', with high epithelial-to-mesenchymal transition markers, has the worst prognosis even within stage I tumors. Lacking known molecular or histological characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the overall classification and strongly predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving NS-LUAD prognostication in clinical settings.

Journal Article↗

PubMed2026

A weakly supervised deep learning-based recurrence prediction and risk stratification of lung adenocarcinoma from pathology whole-slide images.

BACKGROUND: Accurate prediction of postoperative recurrence in lung adenocarcinoma (LUAD) is essential for guiding clinical decision-making and improving patient outcomes. Although various predictive models have been developed, most rely on complex genomic analyses and high-dimensional clinical data. The complexity of these approaches substantially limits their feasibility for routine clinical use. To address this clinical challenge, this study aims to predict postoperative recurrence using routinely available hematoxylin and eosin (H&E)-stained images and characterize the associated biological features. METHODS: A total of 329 patients who underwent curative resection at the First Affiliated Hospital of Wenzhou Medical University (FHWMU) were retrospectively enrolled and randomly assigned to training and internal validation cohorts in a 7:3 ratio. An independent external validation cohort comprising 70 patients from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) was included. Three patch-level feature extractors (Inception_V3, ResNet18, and DenseNet121) were evaluated within a weakly supervised multiple-instance learning (MIL) framework incorporating automated region-of-interest (ROI) detection on segmented whole-slide images (WSIs). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), Kaplan-Meier (KM) survival analysis, and multivariable Cox proportional hazards regression. Transcriptomic profiling and gene set enrichment analysis (GSEA) were conducted to investigate biological differences between risk groups. RESULTS: The model achieved AUCs of 0.923 in the training cohort, 0.891 in the internal validation cohort, and 0.847 in the external validation cohort. The model effectively stratified patients into high- and low-risk groups with significantly different recurrence-free survival (RFS) across all cohorts (all P < 0.001) and retained prognostic value within AJCC stages I-III. Transcriptomic analyses revealed consistent enrichment of cell cycle-related pathways and neutrophil extracellular trap (NET) formation in high-risk patients across both institutional and CPTAC cohorts, aligning with distinct biological profiles of the model-derived risk stratification. CONCLUSIONS: This weakly supervised deep learning framework enables accurate and externally validated prediction of postoperative recurrence in LUAD using routinely available histopathological images, and integration of histopathological features with molecular analyses enhances biological interpretability. This work provides a clinically accessible and cost-effective tool for postoperative risk assessment in LUAD patients.

Humans↗