Objective To investigate the biological characteristics and clinical significance of cuproptosis-related genes in lung adenocarcinoma (LUAD) based on the multi-omics data from The Cancer Genome Atlas. Methods The cuproptosis-related genes were obtained from a study published in Science in March 2022. The whole genome data were used to reveal the mutation spectrum and copy number variation landscape of cuproptosis-related genes in LUAD and analyze its effects on transcriptome expression. Cuproptosis-related genes were annotated using Metascape analysis to further understand the pathways or functions in which these genes were involved. Subsequent univariate Cox analysis and Kaplan-Meier methods determined the prognosis of these genes in LUAD patients, and CellMiner analysis were used to identify those potential anticancer drugs for potentially targeting cuproptosis-related genes. Results Cuproptosis-related genes were less frequently mutated in LUAD, and the effect of gene mutations on transcriptomic expression may depend on the type of mutation. Gene copy number variation was an important factor resulting in the disordered expression of cuproptosis-related genes. The 16 cuproptosis-related genes were mainly involved in glyoxylate metabolism and glycine degradation, copper ion entry, proteolitidylation, cellular amino acid catabolism process, oxidative stress response, etc. Among them, 6 genes (DLD, FDX1, DLAT, DLST, PDHA1, CDKN2A) were prognostic risk genes in LUAD. The CellMiner analysis suggested that 13 drugs were associated with 7 cuproptosis-related genes and they might be potential anticancer drugs for potentially targeting cuproptosis. Conclusion This study reveals the biological characteristics and clinical significance of cuproptosis-related genes in LUAD, and provides some reference and theoretical basis for the subsequent research of cuproptosis in cancer.
ObjectiveTo construct a prognostic model of esophageal squamous cell carcinoma (ESCC) based on immune checkpoint-related genes and explore the potential relationship between these genes and the tumor microenvironment (TME). Methods The transcriptome sequencing data and clinical information of immune checkpoint genes of samples from GSE53625 in GEO database were collected. The difference of gene expression between ESCC and normal paracancerous tissues was evaluated, and the drug sensitivity of differentially expressed genes in ESCC was analyzed. We then constructed a risk model based on survival-related genes and explored the prognostic characteristics, enriched pathway, immune checkpoints, immune score, immune cell infiltration, and potentially sensitive drugs of different risk groups. ResultsA total of 358 samples from 179 patients were enrolled, including 179 ESCC samples and 179 corresponding paracancerous tissues. There were 33 males and 146 females, including 80 patients≤60 years and 99 patients>60 years. 39 immune checkpoint genes were differentially expressed in ESCC, including 14 low expression genes and 25 high expression genes. Drug sensitivity analysis of 8 highly expressed genes (TNFRSF8, CTLA4, TNFRSF4, CD276, TNFSF4, IDO1, CD80, TNFRSF18) showed that many compounds were sensitive to these immunotherapy targets. A risk model based on three prognostic genes (NRP1, ICOSLG, HHLA2) was constructed by the least absolute shrinkage and selection operator analysis. It was found that the overall survival time of the high-risk group was significantly lower than that of the low-risk group (P<0.001). Similar results were obtained in different ESCC subtypes. The risk score based on the immune checkpoint gene was identified as an independent prognostic factor for ESCC. Different risk groups had unique enriched pathways, immune cell infiltration, TME, and sensitive drugs. Conclusion A prognostic model based on immune checkpoint gene is established, which can accurately stratify ESCC and provide potential sensitive drugs for ESCC with different risks, thus providing a possibility for personalized treatment of ESCC.