Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.

Liu L ，Yin P ，Yang R ，Zhang G ，Wu C ，Zheng Y ，Wu S ，Liu M ... -  《Frontiers in Immunology》

Integrated analysis of key microRNAs /TFs /mRNAs/ in HPV-positive cervical cancer based on microRNA sequencing and bioinformatics analysis.

Cervical squamous cell carcinoma (CESC) is one of the most common malignancies associated with mortality in females. Its onset and prognosis are primarily concerned with persistent infection with high-risk types of human papillomavirus (HPV). However, the molecular mechanisms of HPV-positive CESC remain unclear. In this study, we conducted a high-throughput sequencing to identify differentially expressed miRNAs (DEMs). Besides, three series were selected from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Then the miRNA-TF-gene regulatory network was constructed using bioinformatic methods. Genes in the network were performed functional enrichment analysis and protein-protein interaction (PPI) network analysis. Ultimately, the expression levels of six key miRNAs, TFs, and mRNAs were validated by 20 HPV-positive CESC tissues and 15 normal cervical samples. A total of 52 DEMs and 300 DEGs differed between the HPV-positive CESC and normal cervical samples. Then the miRNA-TF-gene regulatory network was constructed consisting of 22 miRNAs, 6 TFs, and 76 corresponding genes, among which miR-149-5p, miRNA-1248 and E2F4 acted as key regulators. PPI network analysis showed that ten genes including TOP2A, AURKA, CHEK1, KIF11, MCM4, MKI67, DTL, FOXM1, SMC4, and FBXO5 were recognized as hub genes with the highest connectivity degrees. Besides, five key molecules miRNA-149-5p, E2F4, KIF11, DTL, and SMC4 were suggested to play crucial roles in the development of HPV-positive CESC. These results present a unique insight into the pathological mechanisms of HPV-positive CESC and possibly provides potential therapeutic targets.

Yuan Y ，Shi X ，Li B ，Peng M ，Zhu T ，Lv G ，Liu L ，Jin H ，Li L ，Qin D ... -  《-》

Prediction of a miRNA-mRNA functional synergistic network for cervical squamous cell carcinoma.

Cervical squamous cell carcinoma (CSCC) accounts for a significant proportion of cervical cancer; thus, there is a need for novel and noninvasive diagnostic biomarkers for this malignancy. In this study, we performed integrated analysis of a dataset from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between CSCC, cervical intraepithelial neoplasia (CIN) and healthy control subjects. We further established protein-protein interaction and DEmiRNA-target gene interaction networks, and performed functional annotation of the target genes of DEmiRNAs. In total, we identified 1375 DEGs and 19 DEmiRNAs in CIN versus normal control, and 2235 DEGs and 33 DEmiRNAs in CSCC versus CIN by integrated analysis. Our protein-protein interaction network indicates that the common DEGs, Cyclin B/cyclin-dependent kinase 1 (CDK1), CCND1, ESR1 and Aurora kinase A (AURKA), are the top four hub genes. P53 and prostate cancer were identified as significantly enriched signaling pathways of common DEGs and DEmiRNA targets, respectively. We validated that expression levels of three DEGs (TYMS, SASH1 and CDK1) and one DEmiRNA of hsa-miR-99a were altered in blood samples of patients with CSCC. In conclusion, a total of four DEGs (TYMS, SASH1, CDK1 and AURKA) and two DEmiRNAs (hsa-miR-21 and hsa-miR-99a) may be involved in the pathogenesis of CIN and the progression of CIN into CSCC. Of these, TYMS is predicted to be regulated by hsa-miR-99a and SASH1 to be regulated by hsa-miR-21.

Sun D ，Han L ，Cao R ，Wang H ，Jiang J ，Deng Y ，Yu X ... -  《FEBS Open Bio》

Identification of potential crucial genes and key pathways shared in Inflammatory Bowel Disease and cervical cancer by machine learning and integrated bioinformatics.

Recently, Inflammatory Bowel Disease (IBD) has been proven as a risk factor for the increasing incidence of cervical cancer (CC) development. In this study, we identify these potential hub genes and their significant pathways that commonly interact between IBD and CC and these pathological mechanisms. To this end, we use bioinformatics and systems biology approaches to analyze the miRNA-mRNA, TFs-mRNA regulatory network. The reanalysis dataset from Gene Expression Omnibus (GEO) and the cancer genome atlas (TCGA) found these common differentially expressed genes (DEGs) between IBD and CC, clustered via weighted gene co-expression network analysis, and the vital modules significantly related to cervical cancer were identified. These hub genes of the key module were identified and explored in biological mechanism pathway analysis. Organelle fission, nuclear envelope, protein serine/threonine kinase activity, and the Human T-cell leukemia virus 1 infection pathway were the major enriched pathways for the common DEGs. Due to the high connectivity, the common DEGs with protein-protein interaction (PPI) network disclosed hub proteins (CDK1, MAD2L1, and CCNB1). This study also showed the classification algorithms of ten hub genes (MAD2L1, CCNB2, CDK1, CCNA2, BUB1B, KIF11, TTK, BUB1, CCNB1, ASPM) with accuracy >0.90 suggesting the novel biomarker potential of the hub genes. The microRNAs (miRNA), and transcription factors (TFs) mRNA regulatory network, five transcription factors, and twelve miRNAs are strongly linked to three hub genes. Gene drug interaction analysis found seven drugs compound that interacts with the hub gene. In the current study, our procedure has hypothesized the comprehensive understanding of disease mechanisms vital for both CC and IBD that may mediate their interaction. Our results suggest the further investigation of the molecules for the treatment of IBD and CC.

Nguyen TB ，Do DN ，Nguyen-Thi ML ，Hoang-The H ，Tran TT ，Nguyen-Thanh T ... -  《-》

Exploration of the shared diagnostic genes and mechanisms between periodontitis and primary Sjögren's syndrome by integrated comprehensive bioinformatics analysis and machine learning.

Accumulating evidence has showed a bidirectional link between periodontitis (PD) and primary Sjögren's syndrome (pSS), but the mechanisms of their occurrence remain unclear. Hence, this study aimed to investigate the shared diagnostic genes and potential mechanisms between PD and pSS using bioinformatics methods. Gene expression data for PD and pSS were acquired from the Gene Expression Omnibus (GEO) database. Differential expression genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were utilized to search common genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore biological functions. Three machine learning algorithms (least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF)) were used to further identify shared diagnostic genes, and these genes were assessed via receiver operating characteristic (ROC) curves in discovery and validation datasets. CIBERSORT was employed for immune cell infiltration analysis. Transcription factors (TFs)-genes and miRNAs-genes regulatory networks were conducted by NetworkAnalyst. Finally, relevant drug targets were predicted by DSigDB. Based on DEGs, 173 overlapping genes were obtained and primarily enriched in immune- and inflammation-related pathways. WGCNA revealed 34 common disease-related genes, which were enriched in similar biological pathways. Intersecting the DEGs with WGCNA results yielded 22 candidate genes. Moreover, three machine learning algorithms identified three shared genes (CSF2RB, CXCR4, and LYN) between PD and pSS, and these genes demonstrated good diagnostic performance (AUC>0.85) in both discovery and validation datasets. The immune cell infiltration analysis showed significant dysregulation in several immune cell populations. Regulatory network analysis highlighted that WRNIP1 and has-mir-155-5p might be pivotal co-regulators of the three shared gene expressions. Finally, the top 10 potential gene-targeted drugs were screened. CSF2RB, CXCR4, and LYN may serve as potential biomarkers for the concurrent diagnosis of PD and pSS. Additionally, we identified common molecular mechanisms, TFs, miRNAs, and candidate drugs between PD and pSS, which may provide novel insights and targets for future research on the pathogenesis, diagnosis, and therapy of both diseases.

Wang S ，Wang Q ，Zhao K ，Zhang S ，Chen Z ... -  《-》