RESUMEN
Background: Colorectal cancer (CRC) remains the most common gastrointestinal malignancy. Despite multimodal therapy, its mortality is high due to recurrence and metastasis. This study developed and verified a risk model consisting of 14 N6-methyladenosine (m6A) long noncoding RNAs (lncRNAs) to assess the prognosis of patients with CRC and investigated its relevance to immune regulation and drug sensitivity. Methods: The gene expression profiles and clinical data of 446 patients with CRC were retrieved from The Cancer Genome Atlas (TCGA). 14 lncRNAs were screened using the Gene Co-expression Network (corFilter =0.5, P<0.001), and univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct the optimal risk model. The predictive performance and clinical applicability of the model were next verified. In addition, we performed Gene Ontology (GO) enrichment analysis to identify potential biological functions and detected the difference in tumor mutational burden (TMB), immune function, and sensitivity to immunotherapy and other drugs between the high- and low-risk groups to evaluate the application of the constructed risk model in depth. Results: The model was found to be an appropriate marker for predicting the prognosis of patients with CRC, independent of other clinical features, and demonstrated good precision and broad clinical applicability. It correlated with pathways in the development of cancer and immune-related functions, and patients in the high-risk group had higher tumor immune dysfunction and escape (TIDE) scores. Furthermore, we found significant differences in the overall survival (OS) between patients in the high- and low-tumor mutation burden (TMB) groups, which may work in conjunction with the constructed model to better predict patients' prognosis. Finally, we identified 12 drugs, including A-443654 and sorafenib, with lower half maximal inhibitory concentration (IC50) values in the high-risk group. Conversely, 21 drugs, including gemcitabine and rapamycin, had lower IC50 values in the low-risk group. Conclusions: We constructed a risk model based on 14 m6A-related lncRNAs that could predict the prognosis of patients with CRC and provided additional therapeutic ideas for their treatment. These findings may additionally serve as a foundation for further studies on regulating CRC via m6A-related lncRNAs.
RESUMEN
Background: Despite the significant survival benefits of anti-PD-1/PD-L1 immunotherapy, non-small cell lung cancer (NSCLC) remains one of the most common tumors and major causes of cancer-related deaths worldwide. Thus, there is an urgent need to identify new therapeutic targets for this refractory disease. Methods: In this study, microarray datasets GSE27262, GSE75037, GSE102287, and GSE21933 were integrated by Venn diagram. We performed functional clustering and pathway enrichment analyses using R. Through the STRING database and Cytoscape, we conducted protein-protein interaction (PPI) network analysis and identified the key genes, which were verified by the GEPIA2 and UALCAN portal. Validation of actin-binding protein anillin (ANLN) was performed by quantitative real-time polymerase chain reaction and Western blotting. Additionally, Kaplan-Meier methods were used to compute the survival analyses. Results: In total, 126 differentially expressed genes were identified, which were enriched in mitotic nuclear division, mitotic cell cycle G2/M transition, vasculogenesis, spindle, and peroxisome proliferator-activated receptor signaling pathway. 12 central node genes were identified in the PPI network complex. The survival analysis revealed that high transcriptional levels were associated with inferior survival in NSCLC patients. The clinical implication of ANLN was further explored; its protein expression showed a gradually increasing trend from grade I to III. Conclusion: These Key genes may be involved in the carcinogenesis and progression of NSCLC, which may serve as useful targets for NSCLC diagnosis and treatment.
RESUMEN
Although disease susceptibility is known to differ between men and women, it is controversial whether the efficacy of immune checkpoint inhibitors for malignancies also differs between the sexes. We conducted a meta-analysis to explore the impact of sex on immune checkpoint inhibitor treatment outcomes. We searched PubMed, Embase and the Cochrane Library databases from inception to October 1, 2020 for randomized controlled trials of immune checkpoint inhibitors with hazard ratios (HRs) stratified by sex. We calculated the pooled HRs for men and women using the ln(HR), and assessed the heterogeneity between the two estimates through an interaction test. In total, 22,268 patients from 39 randomized controlled trials were included. Immune checkpoint inhibitors yielded better overall survival than conventional agents in both men (HR: 0.75, 95% confidence interval [CI]: 0.71-0.80) and women (HR: 0.77, 95% CI: 0.70-0.85). Progression-free survival benefits were also observed in both men (HR: 0.64, 95% CI: 0.58-0.70) and women (HR: 0.67, 95% CI: 0.58-0.77) treated with immune checkpoint inhibitors. No sex differences in the response to immune checkpoint inhibitors were found when overall survival and progression-free survival were used as the endpoints.