BackgroundMultiple risk factors of stroke have been identified in previous studies; however, the causal role of snoring in the onset of stroke is less investigated. To clarify the causal association of snoring on stroke and its subtypes, this study is performed.MethodsThe single nucleotide polymorphisms in relation to snoring were retrieved from the UK biobank cohort with 408,317 participants. The data for stroke and its subtypes of European ancestry (67,162 cases and 453,702 controls) were obtained from the MEGASTROKE consortium. In single-variable Mendelian randomization (SVMR) and multivariable MR (MVMR) analyses, inverse variance weighting was used as the primary estimate, complemented with sensitivity analyses more robust to pleiotropy.ResultsGenetically predicted snoring increased the risk of stroke (odds ratio [OR] = 2.69, 95% confidence interval [CI] = 1.19–6.08, P = 0.016) and ischemic stroke (IS) (OR = 2.82, 95% CI = 1.23–6.44, P = 0.013), but not large artery stroke (LAS) (OR = 3.02, 95% CI = 0.31–29.44, P = 0.339), cardioembolic stroke (CES) (OR = 1.51, 95% CI = 0.58–3.92, P = 0.395). We provide novel genetic evidence that snoring increases the risk of stroke and IS, but not LAS, CES, and SVS.ConclusionOur findings provide novel genetic evidence that snoring increases the risk of stroke and IS, but not LAS, CES, and SVS.
Background The current study set out to identify the miRNA-mRNA regulatory networks that influence the radiosensitivity in esophageal cancer based on the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Methods Firstly, esophageal cancer-related miRNA-seq and mRNA-seq data were retrieved from the TCGA database, and the mRNA dataset of esophageal cancer radiotherapy was downloaded from the GEO database to analyze the differential expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in radiosensitive and radioresistant samples, followed by the construction of the miRNA-mRNA regulatory network and Gene Ontology and KEGG enrichment analysis. Additionally, a prognostic risk model was constructed, and its accuracy was evaluated by means of receiver operating characteristic analysis. Results A total of 125 DEmiRNAs and 42 DEmRNAs were closely related to the radiosensitivity in patients with esophageal cancer. Based on 47 miRNA-mRNA interactions, including 21 miRNAs and 21 mRNAs, the miRNA-mRNA regulatory network was constructed. The prognostic risk model based on 2 miRNAs (miR-132-3p and miR-576-5p) and 4 mRNAs (CAND1, ZDHHC23, AHR, and MTMR4) could accurately predict the prognosis of esophageal cancer patients. Finally, it was verified that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR could affect the radiosensitivity in esophageal cancer. Conclusion Our study demonstrated that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR were critical molecular pathways related to the radiosensitivity of esophageal cancer.
Background: RET fusion has reported in 1–2% of lung adenocarcinomas, and it is one of the key driver mutations and an actionable target. Non-small cell lung cancer (NSCLC) patients harboring RET fusion can obtained clinical benefit from the therapy with multi-kinase inhibitors like cabozantinib and potent and highly selective RET inhibitors like selpercatinib (LOXO-292) and pralsetinib (BLU-667). In NSCLC, several partners of RET have been reported. However, to the best of our knowledge, no report is available on the golgi-associated PDZ and coiled-coil motif containing gene (GOPC) as a partner of RET fusion in NSCLC. Case presentation: Here, we identified a novel GOPC-RET fusion in a 63-year-old female patient with lung adenocarcinoma by next-generation sequencing (NGS). The GOPC-RET fusion is composed of exon 1–4 of GOPC and exon 12–20 of RET that retains the intact RET kinase domain. Conclusions: To the best of our knowledge, this represents the first report of GOPC-RET fusion in a patient with lung adenocarcinoma. The novel GOPC-RET fusion has immediate clinical implications for patients with malignancy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.