Cysteine-rich 61-associated gene expression profile alterations in human glioma cells

Identification of key differentially expressed immune related genes in patients with persistent atrial fibrillation: an integrated bioinformation analysis

OBJECTIVE

We aimed to investigate key differentially expressed immune related genes in persistent atrial fibrillation.

METHODS

Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) using "GEO query" package. "limma" package and "sva" package were used to conduct normalization and eliminate batch effects, respectively. We screened out differentially expressed genes (DEGs) based on "limma" package with the standard of |log fold change (FC)| ≥ 1.5 and false discovery rate (FDR) < 0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed by "clusterProfler" package. We further applied LASSO to select key DEGs, and intersected key DEGs with immune related genes from ImmPort database. The ROC curve of each DEIRG was constructed to evaluate its diagnostic efficiency for AF.

RESULTS

A total of 103 DEGs we were screened out, of them, 48 genes were down-regulated and 55 genes were up-regulated. Result of functional enrichment analysis show that, most of DEGs were related to immune response, inflammation, and oxidative stress. Ultimately, CYBB, RORB, S100A12, and CHGB were determined as key DEIRGs, each of which displayed a favor efficiency for diagnosing persistent AF.

CONCLUSION

CYBB, RORB, S100A12, and CHGB were identified as key DEIRGs in persistent AF, and future studies are needed to further explore the underlying roles of CYBB, RORB, S100A12, and CHGB in persistent AF.

Integrated Genomic and Transcriptomic Analysis reveals key genes for predicting dual-phenotype Hepatocellular Carcinoma Prognosis

Dual-phenotype hepatocellular carcinoma (DPHCC) expresses both hepatocyte and cholangiocyte markers, and is characterized by high recurrence and low survival rates. The underlying molecular mechanisms of DPHCC pathogenesis are unclear.

We performed whole exome sequencing and RNA sequencing of three subtypes of HCC (10 DPHCC, 10 CK19-positive HCC, and 14 CK19-negative HCC), followed by integrated bioinformatics analysis, including somatic mutation analysis, mutation signal analysis, differential gene expression analysis, and pathway enrichment analysis. Cox proportional hazard regression analyses were applied for exploring survival related characteristics.

We found that mutated genes in DPHCC patients were associated with carcinogenesis and immunity, and the up-regulated genes were mainly enriched in transcription-related and cancer-related pathways, and the down-regulated genes were mainly enriched in immune-related pathways. CXCL9 was selected as the hub gene, which is associated with immune cells and survival prognosis. Our results showed that low CXCL9 expression was significantly associated with poor prognosis, and its expression was significantly reduced in DPHCC samples.

In conclusion, we explored the molecular mechanisms governing DPHCC development and progression and identified CXCL9, which influences the immune microenvironment and prognosis of DPHCC and might be new clinically significant biomarkers for predicting prognosis.