World J Oncol. 2026 Sep 4;17(5):683-704. doi: 10.14740/wjon2815. eCollection 2026 Oct.

ABSTRACT

BACKGROUND: Lung cancer (LC) and venous thromboembolism (VTE) are closely associated, with VTE contributing to morbidity and mortality among patients with LC. We aimed to identify and characterize a mitochondrial-related transcriptomic signature shared between LC and VTE and to explore its association with immune microenvironment features.

METHODS: We applied a multiomics approach focused on mitochondrial-related signaling pathways. Publicly available transcriptomic datasets were analyzed using differential expression profiling and weighted gene co-expression network analysis to identify key regulatory genes. These genes were intersected with a mitochondrial gene set and subjected to functional enrichment analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to identify candidate diagnostic genes validation. Immune cell infiltration was quantified, and associated regulatory mechanisms were explored.

RESULTS: Thirty-nine shared crosstalk genes were identified and were primarily enriched in mitochondrial metabolic processes. LASSO regression identified a five-gene candidate signature (ACAA1, HSD17B10, MTIF2, THOP1, and PDE2A). The model exhibited promising discriminatory performance (area under the curve > 0.9 in LC dataset and 0.7-0.9 in VTE dataset). These genes were significantly dysregulated and were associated with altered immune cell infiltration, particularly in dendritic cell and T cell subsets.

CONCLUSION: We identified a mitochondrial-related gene signature reflecting shared transcriptomic correlates between LC and VTE. The signature showed variable performance across disease contexts and correlative associations with immune features, supporting its role as a candidate biomarker for further investigation. Prospective validation in independent clinical cohorts is required before any translational application.

PMID:42730163 | PMC:PMC13568737 | DOI:10.14740/wjon2815

World J Oncol. 2026 Sep 4;17(5):683-704. doi: 10.14740/wjon2815. eCollection 2026 Oct.

ABSTRACT

BACKGROUND: Lung cancer (LC) and venous thromboembolism (VTE) are closely associated, with VTE contributing to morbidity and mortality among patients with LC. We aimed to identify and characterize a mitochondrial-related transcriptomic signature shared between LC and VTE and to explore its association with immune microenvironment features.

METHODS: We applied a multiomics approach focused on mitochondrial-related signaling pathways. Publicly available transcriptomic datasets were analyzed using differential expression profiling and weighted gene co-expression network analysis to identify key regulatory genes. These genes were intersected with a mitochondrial gene set and subjected to functional enrichment analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to identify candidate diagnostic genes validation. Immune cell infiltration was quantified, and associated regulatory mechanisms were explored.

RESULTS: Thirty-nine shared crosstalk genes were identified and were primarily enriched in mitochondrial metabolic processes. LASSO regression identified a five-gene candidate signature (ACAA1, HSD17B10, MTIF2, THOP1, and PDE2A). The model exhibited promising discriminatory performance (area under the curve > 0.9 in LC dataset and 0.7-0.9 in VTE dataset). These genes were significantly dysregulated and were associated with altered immune cell infiltration, particularly in dendritic cell and T cell subsets.

CONCLUSION: We identified a mitochondrial-related gene signature reflecting shared transcriptomic correlates between LC and VTE. The signature showed variable performance across disease contexts and correlative associations with immune features, supporting its role as a candidate biomarker for further investigation. Prospective validation in independent clinical cohorts is required before any translational application.

PMID:42730163 | PMC:PMC13568737 | DOI:10.14740/wjon2815

J Transl Med. 2026 Jun 8;24(1):776. doi: 10.1186/s12967-026-08382-w.

ABSTRACT

BACKGROUND: The molecular distinction between benign and malignant pulmonary nodules remains a significant diagnostic challenge. While genomic drivers are well studied, multiomic integration of the epigenetic-transcriptional landscape and its translation into noninvasive tools are lacking.

METHODS: We performed a multiomic characterization (genomic, epigenomic, and transcriptomic) of 158 pulmonary nodules. Unsupervised factor analysis integrated these layers to identify core regulatory axes. A 9-gene cell-free DNA (cfDNA) methylation classifier was developed and validated in blood and tissue cohorts.

RESULTS: Genomic profiling revealed EGFR mutations (exclusive to malignant nodules) and MYC amplification as fundamental initiators of malignancy. Multiomic factor analysis (Factor 1) revealed profound genetic‒epigenetic synergy, in which these alterations dictate a permissive methylome, leading to aberrant epigenetic programming of chromatin accessibility, as well as epigenetic-transcriptional effects: hypomethylation at the promoters of cell cycle genes that augments their expression, and hypermethylation at immune related pathways gene loci that silences their transcription. This effect orchestrates formation of proproliferative (E2F target/G2M checkpoint) and "immune-cold" malignant phenotype, characterized by elevated Treg/CD8+ ratios and fibroblast recruitment. Notably, we observed a gradual accumulation of methylation aberrations along the premalignant-to-invasive continuum (adenocarcinoma in situ [AIS]→minimally invasive adenocarcinoma [MIA]→adenocarcinoma [ADC]), identifying progressive epigenetic dysregulation as a hallmark of tumor aggressiveness. Global methylome remodeling drives ADC progression through hypermethylation-mediated silencing of tumor suppressors (RASA3 and PPARG) and hypomethylation-activated oncogenic axes, specifically the GDF15 axis, which independently predict poor survival in patients with lung ADC in the TCGA cohort. We translated these tissue-derived insights into a 9-gene cfDNA methylation classifier, which achieved exceptional diagnostic accuracy across independent cohorts (training AUC = 1.00; test AUC = 0.93; tissue AUC = 0.96). Rooted in the biological "ground truth" of tissue dysregulation, this classifier functions specifically as a functional readout of the core cell cycle and proliferative pathways, offering a robust, noninvasive tool for the biology-informed risk assessment of pulmonary nodules.

CONCLUSIONS: This study delineates an epigenetic-transcriptional regulatory network that drives nodule malignancy. Our findings provide a robust theoretical foundation and a high-performance liquid biopsy tool for the precise, noninvasive diagnosis of pulmonary nodules.

PMID:42260586 | PMC:PMC13274191 | DOI:10.1186/s12967-026-08382-w

Cell Commun Signal. 2026 Mar 14. doi: 10.1186/s12964-026-02793-4. Online ahead of print.

NO ABSTRACT

PMID:41826981 | DOI:10.1186/s12964-026-02793-4