Aim: This study is aimed at constructing the competing endogenous RNA (ceRNA) network in chromophobe renal cell carcinoma (ChRCC).
Methods: Clinical and RNA sequence profiles of patients with ChRCC, including messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs), were obtained from The Cancer Genome Atlas (TCGA) database. "edgeR" and "clusterProfiler" packages were utilized to obtain the expression matrices of differential RNAs (DERNAs) and to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was performed to screen the highly related RNAs, and miRcode, StarBase, miRTarBase, miRDB, and TargetScan datasets were used to predict the connections between them. Univariate and multivariate Cox proportional hazards regressions were performed in turn to elucidate prognosis-related mRNAs in order to construct the ceRNA regulatory network.
Results: A total of 1628 DElncRNAs, 104 DEmiRNAs, and 2619 DEmRNAs were identified. WGCNA showed significant correlation in 1534 DElncRNAs, 98 DEmiRNAs, and 2543 DEmRNAs, which were related to ChRCC. Fourteen DEmiRNAs, 113 DElncRNAs, and 43 DEmRNAs were screened. Nine mRNAs (ALPL, ARHGAP29, CADM2, KIT, KLRD1, MYBL1, PSD3, SFRP1, and SLC7A11) significantly contributed to the overall survival (OS) of patients with ChRCC ( < 0.05). Furthermore, two mRNAs (CADM2 and SFRP1) appeared to be independent risk factors for ChRCC.
Conclusion: The findings revealed the molecular mechanism of ChRCC and potential therapeutic targets for the disease.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213485 | PMC |
| http://dx.doi.org/10.1155/2021/5589101 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
MYT1L syndrome is a newly recognized disorder characterized by intellectual disability, speech and motor delay, neuroendocrine disruptions, ADHD, and autism. In order to study this gene and its association with these phenotypes, our lab recently created a heterozygous mutant mouse inspired by a clinically relevant mutation. This model recapitulates several of the physical and neurologic abnormalities seen in humans with MYT1L syndrome, such as weight gain, microcephaly, and behavioral disruptions.
View Article and Find Full Text PDFWhile most pregnancies are affected by nausea and vomiting, hyperemesis gravidarum (HG) is at the severe end of the clinical spectrum and is associated with dehydration, undernutrition, and adverse maternal, fetal, and child outcomes. Herein we performed a multi-ancestry genome-wide association study (GWAS) of severe nausea and vomiting of pregnancy of 10,974 cases and 461,461 controls across European, Asian, African, and Latino ancestries. We identified ten significantly associated loci, of which six were novel ( , , , , , and and confirmed previous genome-wide significant associations with risk genes , , , and .
View Article and Find Full Text PDFTropomyosin is an actin-binding protein that plays roles ranging from regulating muscle contraction to controlling cytokinesis and cell migration. The simple nematode provides a useful model for studying the core functions of tropomyosin in an animal, having a relatively simple anatomy, and a single tropomyosin gene, , that produces seven isoforms. Three higher molecular weight isoforms (LEV-11A, D, O) regulate contraction of body wall and other muscles, but comparatively less is known of the functions of four lower molecular weight isoforms (LEV-11C, E, T, U).
View Article and Find Full Text PDFIdentification of the locus controlling leaf rolling and its application in maize breeding.
Mol Breed
January 2025
Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007 Guangxi China.
Unlabelled: Increasing planting density is one of the most important strategies for generating higher maize yields. Moderate leaf rolling decreases mutual shading of leaves and increases the photosynthesis of the population and hence increases the tolerance for high-density planting. Few genes that control leaf rolling in maize have been identified, however, and their applicability for breeding programs remains unclear.
View Article and Find Full Text PDFTwo-Step Transfer Learning Improves Deep Learning-Based Drug Response Prediction in Small Datasets: A Case Study of Glioblastoma.
Bioinform Biol Insights
January 2025
Department of Pathology & Clinical Bioinformatics, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
While deep learning (DL) is used in patients' outcome predictions, the insufficiency of patient samples limits the accuracy. In this study, we investigated how transfer learning (TL) alleviates the small sample size problem. A 2-step TL framework was constructed for a difficult task: predicting the response of the drug temozolomide (TMZ) in glioblastoma (GBM) cell cultures.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!