Establishment of a 7-gene expression panel to improve the prognosis classification of gastric cancer patients

Identification of idiopathic pulmonary fibrosis hub genes and exploration of the mechanisms of action of Jinshui Huanxian formula

Idiopathic pulmonary fibrosis (IPF) is a common and heterogeneous chronic disease, and the mechanism of Jinshui Huanxian formula (JHF) on IPF remains unclear. For a total of 385 lung normal tissue samples from the Gene Expression Omnibus database, 37,777,639 gene pairs were identified through microarray and RNA-seq platforms. Using the individualized differentially expressed gene (DEG) analysis algorithm RankComp (FDR < 0.01), we identified 344 genes as DEGs in at least 95 % (n = 81) of the IPF samples. Of these genes, IGF1, IFNGR1, GLI2, HMGCR, DNM1, KIF4A, and TNFRSF11A were identified as hub genes. These genes were verified using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in mice with pulmonary fibrosis (PF) and MRC-5 cells, and they were highly effective at classifying IPF samples in the independent dataset GSE134692 (AUC = 0.587-0.788) and mice with PF (AUC = 0.806-1.000). Moreover, JHF ameliorated the pathological changes in mice with PF and significantly reversed the changes in hub gene expression (KIF4A, IFNGR1, and HMGCR). In conclusion, a series of IPF hub genes was identified, and validated in an independent dataset, mice with PF, and MRC-5 cells. Moreover, the abnormal gene expression was normalized by JHF. These findings provide guidance for further exploration of the pathogenesis and treatment of IPF.

Transcription Analysis of the THBS2 Gene through Regulation by Potential Noncoding Diagnostic Biomarkers and Oncogenes of Gastric Cancer in the ECM-Receptor Interaction Signaling Pathway: Integrated System Biology and Experimental Investigation

Background

Gastric cancer (GC) is the second most frequent cause of cancer-related death worldwide and the fourth most common malignancy. Despite significant improvements in patient survival over the past few decades, the prognosis for patients with GC remains dismal because of the high recurrence rate. In this comprehensive system biology and experimental investigation, we aimed to find new novel diagnostic biomarkers of GC through a regulatory RNA interaction network.

Methods

Gene expression, coexpression, and survival analyses were performed using microarray and RNAseq datasets (analyzed by RStudio, GEPIA2, and ENCORI). RNA interaction analysis was performed using miRWalk and ENCORI online databases. Gene set enrichment analysis (GSEA) was performed to find related signaling pathways of up- and downregulated genes in the microarray dataset. Gene ontology and pathway enrichment analysis were performed by the enrichr database. Protein interaction analysis was performed by STRING online database. Validation of expression and coexpression analyses was performed using a qRT-PCR experiment.

Results

Based on bioinformatics analyses, THBS2 (FC: 7.14, FDR < 0.0001) has a significantly high expression in GC samples. lncRNAs BAIAP2-AS1, TSIX, and LINC01215 have RNA interaction with THBS2. BAIAP2-AS1 (FC: 1.44, FDR: 0.018), TSIX (FC: 1.34, FDR: 0.038), and LINC01215 (FC: 1.19, FDR: 0.046) have significant upregulation in GC samples. THBS2 has a significant role in the regulation of the ECM-receptor signaling pathway. miR-4677-5p has a significant RNA interaction with THBS2. The expression level of THBS2, BAIAP2-AS1, TSIX, and LINC01215 has a nonsignificant negative correlation with the survival rate of GC patients (HR: 0.28, logrank p: 0.28). qRT-PCR experiment validates mentioned bioinformatics expression analyses. BAIAP2-AS1 (AUC: 0.7136, p value: 0.0096), TSIX (AUC: 0.7456, p value: 0.0029), and LINC01215 (AUC: 0.7872, p value: 0.0005) could be acceptable diagnostic biomarkers of GC.

Conclusion

BAIAP2-AS1, lncRNA LINC01215, lncRNA TSIX, and miR-4677-5p might modulate the ECM-receptor signaling pathway via regulation of THBS2 expression level, as the high-expressed noncoding RNAs in GC. Furthermore, mentioned lncRNAs could be considered potential diagnostic biomarkers of GC.