Nanoplastics, including polystyrene nanoplastics (PS-NPs), are widely existed in the atmosphere, which can be directly and continuously inhaled into the human body, posing a serious threat to the respiratory system. Therefore, it is urgent to estimate the potential pulmonary toxicity of airborne NPs and understand its underlying mechanism. In this research, we used two types of human lung epithelial cells (bronchial epithelium transformed with Ad12-SV40 2B, BEAS-2B) and (human pulmonary alveolar epithelial cells, HPAEpiC) to investigate the association between lung injury and PS-NPs. We found PS-NPs could significantly reduce cell viability in a dose-dependent manner and selected 7.5, 15 and 30 μg/cm² PS-NPs as the exposure dosage levels. Microarray detection revealed that 770 genes in the 7.5 μg/cm² group and 1951 genes in the 30 μg/cm² group were distinctly altered compared to the control group. Function analysis suggested that redox imbalance might play central roles in PS-NPs induced lung injury. Further experiments verified that PS-NPs could break redox equilibrium, induce inflammatory effects, and triggered apoptotic pathways to cause cell death. Importantly, we found that PS-NPs could decrease transepithelial electrical resistance by depleting tight junctional proteins. Result also demonstrated that PS-NPs-treated cells increased matrix metallopeptidase 9 and Surfactant protein A levels, suggesting the exposure of PS-NPs might reduce the repair ability of the lung and cause tissue damage. In conclusion, nanoplastics could induce oxidative stress and inflammatory responses, followed by cell death and epithelial barrier destruction, which might result in tissue damage and lung disease after prolonged exposure.

The digestive system cancers are aggressive cancers with the highest mortality worldwide. In this study, we undertook a systematic investigation of the tumor immune microenvironment to identify diagnostic and prognostic biomarkers. The fraction of 22 immune cell types of patients were estimated using CIBERSORT. The least absolute shrinkage and selection operator (LASSO) analysis was carried out to identify important immune predictors. By comparing immune cell compositions in 801 tumor samples and 46 normal samples, we constructed the diagnostic immune score (DIS), showing high specificity and sensitivity in the training (area under the receiver operating characteristic curve [AUC] = 0.929), validation (AUC = 0.935), and different cancer type cohorts (AUC > 0.70 for all). We also established the prognostic immune score (PIS), which was an effective prognostic factor for relapse‐free survival in training, validation, and entire cohorts (P < .05). In addition, PIS provided a higher net benefit than TNM stage. A composite nomogram was built based on PIS and patients' clinical information with well‐fitted calibration curves (c‐index = 0.84). We further used other cohorts from Gene Expression Omnibus databases and obtained similar results, confirming the reliability and validity of the DIS and PIS. In addition, the unsupervised clustering analysis using immune cell proportions revealed 6 immune subtypes, suggesting that the immune types defined as having relatively high levels of M0 or/and M1 macrophages were the high‐risk subtypes of relapse. In conclusion, this study comprehensively analyzed the tumor immune microenvironment and identified DIS and PIS for digestive system cancers.