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Abstract Background Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures. Methods This study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD. Results Unsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients. Conclusions ICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.

Abstract Background Exosomes have emerged as critical mediators of intercellular communication. Hypoxia is widely recognized as a key regulator of tumor aggressiveness, and significantly affects exosome release by tumor cells. However, the effects of exosomes derived from hypoxic lung adenocarcinoma (LUAD) cells are poorly understood. Methods Samples of miRNA isolated from hypoxic LUAD cell-derived exosomes (HExo) and normoxic LUAD cell-derived exosomes (NExo) were sequenced to identify miRNAs that might mediate tumor progression. Exosomal miRNA was co-cultured with LUAD cells to assess its biological effects on cell migration and metastasis both in vitro and in vivo. The cellular target of exosomal miRNA was confirmed by dual-luciferase assays. Western blot studies showed that exosomal miRNA regulated the related pathway. The availability of circulating exosomal miRNA derived from plasma was also evaluated. Results We found that HExo could significantly enhance the migration and invasion of normoxic LUAD cells. MiRNA sequencing results suggested that miR-31-5p was largely internalized within HExo and could be taken up by normoxic LUAD cells. Exosomal miR-31-5p was found to directly target Special AT-Rich Sequence-Binding Protein 2 (SATB2)-revered epithelial mesenchymal transition and significantly increase activation of MEK/ERK signaling, thereby contributing to tumor progression both in vitro and in vivo. Furthermore, higher levels of circulating exosomal miR-31-5p were detected in LUAD patients, especially in patients with metastatic disease. Conclusions Our findings demonstrate that exosomal miR-31-5p exerts a crucial role in LUAD progression, and could serve as a diagnostic biomarker for LUAD.