There is a known link between DNA methylation and cancer immunity/immunotherapy; however, the effect of DNA methylation on immunotherapy in lung adenocarcinoma (LUAD) remains to be elucidated. In the current study, we aimed to screen key markers for prognostic analysis of LUAD based on DNA methylation regulatory factor clustering. We classified LUAD using the NMF clustering method, and as a result, we obtained 20 DNA methylation regulatory genes. These 20 regulatory genes were used to determine the pattern of DNA methylation regulation, and patients were grouped for further analysis. The risk score model was analyzed in the TCGA dataset and an external validation set, and the correlation between the risk score and DNA methylation regulatory gene expression was explored. We analyzed the correlation between the prognostic model and immune infiltration and checkpoints. Finally, we analyzed the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functions of the prognosis model and established the nomogram model and decision tree model. The survival analyses of ClusterA and ClusterB were significantly different. Survival analysis showed that patients with a high risk score had a poor prognosis. Survival models (tobacco, T, N, M, stage, sex, age, status, and risk score) were abnormally correlated with T cells and macrophages. The higher the risk score associated with smoking was and the higher the stage was, the more severe the LUAD and the more maladjusted the immune system were. Immune infiltration and abnormal expression of immune checkpoint genes in the prognostic model of LUAD were associated with the risk score. The prognostic models were mainly enriched in the cell cycle and DNA replication. Characterization of DNA methylation regulatory patterns is helpful to improve our understanding of the immune microenvironment in LUAD and to guide the development of a more personalized immunotherapy strategy in the future.

A 40-year-old male with EML4-ALK (E6:A20) fusion variant 3 and previously unreported PLEKHA7-ALK (P3:A20) fusion in lung adenocarcinoma exhibited resistance to alectinib and chemotherapy. Subsequent next-generation sequencing (NGS) from the plasma specimen revealed the co-existing mutation in the KEAP1 gene, which may represent an intrinsic resistance to ALK-TKI. Furthermore, the presence of double fusion PLEKHA7-ALK (P3:A20) may also have played a critical role in the resistance to alectinib. KEAP1 mutation (p.E244K) was also founded in this patient which may lead to resistance to standard chemotherapy. The patient was then treated with brigatinib, which effectively halted the rapid progression. Unfortunately, the patient deceased to uncontrollable, rapidly progressing pleural effusion and pulmonary embolism, resulting in an overall survival of 9 months. This represents the rare case of NSCLC with a double fusion of EML4-ALK and PLEKHA7-ALK, exhibiting resistance to alectinib and chemotherapy. Our case suggests that the double fusion of EML4-ALK and PLEKHA7-ALK and co-existing KEAP1 mutation may serve as an adverse prognostic factor. Additionally, brigatinib may offer a potential treatment option for lung adenocarcinoma patients with PLEKHA7-ALK (P3:A20) fusion.

Purpose: It is still unclear whether KEAP1 mutation is detrimental to immunotherapy of lung adenocarcinoma (LUAD) patients, we try to analyse the exact changes in the TME in LUAD patients with KEAP1 mutations and to identify key factors influencing prognosis.Experimental design: A total of 1,029 patients with lung squamous carcinoma (LUSC) or LUAD with data obtained from The Cancer Genome Atlas were included in this study. The TME and OS of patients with LUAD stratified by mutant versus wild-type KEAP1 status were comprehensively measured. Moreover, we classified LUAD patients with KEAP1 mutations into three subtypes, by unsupervised consensus clustering. We further analysed the TME, OS, commutated genes and metabolic pathways of different subgroups. A total of 40 LUAD patients underwent immunotherapy were collected and classified into mutant KEAP1 group and wild-type KEAP1 group. We also conducted immunohistochemical staining in KEAP1-MT groups.Result: Suppressed TME was observed not only in LUAD patients but also in LUSC patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than wild-type KEAP1. Unsupervised consensus clustering analysis suggested that the three subtypes of patients exhibited different densities of neutrophil infiltration and had different OS results: cluster 2 patients had significantly higher levels of neutrophils had significantly worse prognoses than those of patients in clusters 1 and 3 and patients with wild-type KEAP1. Univariate and multivariate Cox analyses proved that a high density of neutrophils was significantly associated with worse OS and immunohistochemical staining proved that shorter PFS showed high density of neutrophils.Conclusion: KEAP1 mutation significantly suppresses the tumour immune microenvironment in LUAD patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than with wild-type KEAP1. Neutrophils may play an important role in the prognosis of LUAD patients with KEAP1 mutations and may provide a promising therapeutic target.

Purpose: In recent studies, mutation in the Kelch-like ECH-associated protein 1 (KEAP1) was found to be associated with resistance tochemotherapy and immunotherapy in lung adenocarcinoma (LUAD) patients. Nevertheless, some studies have shown that KEAP1 mutation correlates with better objective survival (OS) following immunotherapy. Although it is unclear whether KEAP1 mutation is detrimental to LUAD patients, increasing evidence suggests that KEAP1 mutation enables a suppressed tumour immune microenvironment (TME) in LUAD. The purpose of our study was to analyse the exact changes in the TME in LUAD patients with KEAP1 mutations and to identify key factors influencing prognosis. Experimental design: A total of 1011 patients with lung squamous carcinoma (LUSC) or LUAD with data obtained from The Cancer Genome Atlas (TCGA) were included in this study. The TME and OS of patients with LUAD and LUSC stratified by mutant versus wild-type KEAP1 status were comprehensively measured. Moreover, we classified LUAD patients with KEAP1 mutations into three subtypes, clusters 1, 2 and 3, by unsupervised consensus clustering. We further analysed the TME, OS, commutated genes and metabolic pathways of patients in cluster 2 and clusters 1 and 3 and LUAD patients with wild-type KEAP1. A total of 40 patients who were confirmed lung adenocarcinoma pathologically underwent immunotherapy were collected and classified into KEAP1-MT(mutant KEAP1) groups (n=10)and KEAP1-WT (wild-type KEAP1) groups(n=30). We also conducted immunohistochemical staining in KEAP1-MT groups. Result: The presence of KEAP1 mutations correlated with a significantly lower density of infiltrated immune cells,including CD8+ T cells, CD4+ T lymphocytes, B lymphocytes, macrophages and natural killer cells, and suppressed TME was observed not only in LUAD patients but also in LUSC patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than with wild-type KEAP1. Despite, the difference in OS between patients from TGCA with mutant and wild-type KEAP1 was not statistically significant in either LUAD or LUSC patients. Unsupervised consensus clustering analysis suggested that the three subtypes of patients exhibited different densities of neutrophil and type 2 T helper cell (Th2) infiltration and had different OS results: cluster 2 patients had significantly higher levels of neutrophils and Th2 cells and had significantlyworse prognoses than those of patients in clusters 1 and 3 and patients with wild-type KEAP1. Enrichment analysis of differentially expressed genes demonstrated that the nitrogen metabolism pathway may play an important role in thehigh density of infiltrated neutrophils observed in cluster 2 patients. Univariate and multivariate Cox analyses proved that a high density of neutrophils was significantly associated with worse OS and immunohistochemical staining proved that shorter PFS showed high density of neutrophils. Conclusion: KEAP1 mutation significantly suppresses the tumour immune microenvironment in both LUAD and LUSC patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than with wild-type KEAP1.Neutrophils and Th2 cells may play a more important role in the prognosis of LUAD patients with KEAP1 mutations and may provide a promising therapeutic target.

Introduction: Digitally recorded respiratory sounds provide a practical source of physiological information for computer-assisted auscultation. Their acoustic presentation varies across subjects, recording locations, devices, filtering conditions, and environmental noise. Most classification models map acoustic representations directly to disease labels, which provides limited access to the auscultation findings associated with each prediction. This study investigated whether respiratory acoustic representations could be organized into structured evidence for classification across different label settings and evaluation levels. Methods: We developed Evi-CARD to organize respiratory sound representations into structured evidence for classification. A frozen Open Respiratory Acoustic Foundation Model (OPERA) encodes overlapping 8 s segments, from which a concept-aligned pathway estimates wheeze, crackle, inspiration, and expiration together with learned evidence weights. An attention-constrained residual pathway preserves complementary acoustic information, although its attention ceiling does not strictly bound the residual pathway’s contribution to the final logits. Separate disease-query layers adapt the shared evidence representation to each classification setting. We assessed BRACETS A2 and A3 by subject-independent five-fold validation at the recording level and KAUH-primary by subject-independent five-fold validation at the patient level for Healthy vs. Obstructive classification. Each assessment was conducted within its source cohort and was not an external-validation experiment. Results: On BRACETS, Evi-CARD achieved balanced accuracies of 77.8% for the A2 three-class task and 70.2% for the more granular A3 five-class task. On KAUH-primary, pooled patient-level out-of-fold evaluation yielded an area under the receiver operating characteristic curve of 95.1%, a balanced accuracy of 88.0%, a Macro F1 of 88.1%, and an expected calibration error of 5.1%. Across HF_Lung_V1, SPRSound, and ICBHI, the complete concept layer also provided more accurate and better-calibrated concept predictions than the evaluated acoustic-probe and concept-readout baselines. Discussion: These findings show that protocol-specific respiratory sound classification can be based on concept-associated latent evidence while retaining a constrained route for information outside the predefined concept set. However, Evi-CARD is not a strict scalar concept bottleneck, and no clinical meaning is assigned to its residual-memory slots. The evidence is limited to within-cohort cross-validation; independent-cohort testing, device- and site-stratified evaluation, and clinician review remain necessary before considering clinical deployment.