High levels (> 100 ug/L) of arsenic are known to cause lung cancer; however, whether low (≤ 10 ug/L) and medium (10 to 100 ug/L) doses of arsenic will cause lung cancer or other lung diseases, and whether arsenic has dose-dependent or threshold effects, remains unknown. Summarizing the results of previous studies, we infer that low- and medium-concentration arsenic cause lung diseases in a dose-dependent manner. Arsenic trioxide (ATO) is recognized as a chemotherapeutic drug for acute promyelocytic leukemia (APL), also having a significant effect on lung cancer. The anti-lung cancer mechanisms of ATO include inhibition of proliferation, promotion of apoptosis, anti-angiogenesis, and inhibition of tumor metastasis. In this review, we summarized the role of arsenic in lung disease from both pathogenic and therapeutic perspectives. Understanding the paradoxical effects of arsenic in the lungs may provide some ideas for further research on the occurrence and treatment of lung diseases.

Immune cells, vital components of tumor microenvironment, regulate tumor survival and progression. Lung adenocarcinoma (LUAD), the tumor with the highest mortality rate worldwide, reconstitutes tumor immune microenvironment (TIME) to avoid immune destruction. Data have shown that TIME influences LUAD prognosis and predicts immunotherapeutic efficacy. The related information about the role of TIME's characteristics in LUAD is limited. We performed unsupervised consensus clustering via machine-learning techniques to identify TIME clusters among 1906 patients and gathered survival data. The characteristics of TIME clusters of LUAD were visualized by multi-omics analysis, pseudo-time dynamic analysis, and enrichment analysis. TIME score model was constructed by principal component analysis. Comprehensive analysis and validation were conducted to test the prognostic efficacy and immunotherapeutic response of TIME score. TIME clusters (A, B and C) were constructed and exhibited different immune infiltration states. Multi-omics analyses included significant mutated genes (SMG), copy number variation (CNV) and cancer stemness that were significantly different among the three clusters. TIME cluster A had a lower SMG, lower CNV, and lower stemness but a higher immune infiltration level compared to TIME clusters B and C. TIME score showed that patients in low TIME score group had higher overall survival rates, higher immune infiltration level and high expression of immune checkpoints. In validation cohorts, low TIME score subgroup had better drug sensitivity and favorable immunotherapeutic response. We constructed a stable model of LUAD immune microenvironment characteristics that may improve the prognostic accuracy of patients, provide improved explanations of LUAD responses to immunotherapy, and provide new strategies for LUAD treatment.