Cuproptosis-Related lncRNA Gene Signature Establishes a Prognostic Model of Gastric Adenocarcinoma and Evaluate the Effect of Antineoplastic Drugs.

BACKGROUND: One of the most frequent malignancies of the digestive system is stomach adenocarcinoma (STAD). Recent research has demonstrated how cuproptosis (copper-dependent cell death) differs from other cell death mechanisms that were previously understood. Cuproptosis regulation in tumor cells could be a brand-new treatment strategy. Our goal was to create a cuproptosis-related lncRNA signature. Additionally, in order to evaluate the possible immunotherapeutic advantages and drug sensitivity, we attempted to study the association between these lncRNAs and the tumor immune microenvironment of STAD tumors. METHODS: The TCGA database was accessed to download the RNA sequencing data, genetic mutations, and clinical profiles for TCGA STAD. To locate lncRNAs related to cuproptosis and build risk-prognosis models, three techniques were used: co-expression network analysis, Cox-regression techniques, and LASSO techniques. Additionally, an integrated methodology was used to validate the models' predictive capabilities. Then, using GO and KEGG analysis, we discovered the variations in biological functions between each group. The link between the risk score and various medications for STAD treatment was estimated using the tumor mutational load (TMB) and tumor immune dysfunction and rejection (TIDE) scores. RESULT: We gathered 22 genes linked to cuproptosis based on the prior literature. Six lncRNAs related to cuproptosis were used to create a prognostic marker (AC016394.2, AC023511.1, AC147067.2, AL590705.3, HAGLR, and LINC01094). After that, the patients were split into high-risk and low-risk groups. A statistically significant difference in overall survival between the two groups was visible in the survival curves. The risk score was demonstrated to be an independent factor affecting the prognosis by both univariate and multivariate Cox regression analysis. Different risk scores were substantially related to the various immunological states of STAD patients, as further evidenced by immune cell infiltration and ssGSEA analysis. The two groups had differing burdens of tumor mutations. In addition, immunotherapy was more effective for STAD patients in the high-risk group than in the low-risk group, and risk scores for STAD were substantially connected with medication sensitivity. CONCLUSIONS: We discovered a marker for six cuproptosis-associated lncRNAs linked to STAD as prognostic predictors, which may be useful biomarkers for risk stratification, evaluation of possible immunotherapy, and assessment of treatment sensitivity for STAD.

IFNL4, ACE1, PKR, IFNG, MBL2 genetic polymorphisms and severe COVID-19: A protocol for systematic review and meta-analysis.

BACKGROUND: Corona virus disease 2019 (COVID-19) is caused by SARS-CoV-2, the pathogenic process of SARS-Cov-2 is related to the angiotensin-2 converting enzyme (ACE-2) on host cells. The genetic polymorphisms among different populations may influence the progression of COVID-19. However, the effects of IFNL4, ACE1, PKR, IFNG, and MBL2 in severe COVID-19 have not been systematically assessed. METHODS: We will include all relevant English and Chinese studies by searching the following electronic databases: PubMed, MEDLINE, Embase, Web of Science, Scopus, the Cochrane Library, and Google Scholar before March 31, 2022. Two researchers will independently screen and extract the literature. The methodological quality of the included studies will be evaluated by the Cochrane Handbook for Systematic Reviews of Interventions. RESULT: This systematic review and meta-analysis will summarize the association of IFNL4, ACE1, PKR, IFNG, MBL2 genetic polymorphisms, and severe COVID-19. The results will be submitted to a peer-reviewed journal once completed. CONCLUSION: The conclusion of our study will provide evidence for the early prevention of severe COVID-19. PROSPERO REGISTRATION NUMBER: CRD42022301735.