Objective To investigate obesity signature genes as potential biomarkers of pancreatic cancer and their possible molecular regulatory mechanisms. Methods Based on the mRNA-Seq data of obesity and pancreatic cancer from GEO and TCGA-GTEx databases, we screened four obesity signature genes using a random forest tree algorithm and analyzed their expression in pancreatic cancer, and constructed a nomogram risk prediction model and performed preliminary validation of the predictive efficiency of the model. Then the tumor immune profile of pancreatic cancer was assessed based on the CIBERSORT algorithm, and the correlation between the four obesity genes and the abundance of tumor immune cell infiltration, and immune checkpoints in pancreatic cancer was discussed. Results The diagnostic ROC curves suggested that the four obesity genes showed good diagnostic efficacy for pancreatic cancer, hinting that they may be potential predictive targets for pancreatic cancer, and the pancreatic cancer risk prediction model based on the four obesity-related genes showed good risk prediction efficacy for pancreatic cancer in the obese population, which has good potential for clinical application. The study also found that the upregulation of COL1A2 expression may activate the PI3K/ART signaling pathway through the mediation of integrin IGTA to promote the development of pancreatic cancer, closely associated with the developm- ent and progression of pancreatic cancer. Conclusion The obesity signature genes CCDC80, COL1A2, DPYSL3 and BCAT1 are potential predictive targets for new pancreatic cancer in obese people, and the upregulation of COL1A2 expression may promote pancreatic cancer development by activating the PI3K/ART signaling pathway.

Background: Numerous genetic sequencing projects have demonstrated that alterations in Polε (DNA polymerase epsilon ) due to various causes are associated with the development of multiple human cancers. However, the biological functions of its four core genes, POLE1/2/3/4/, in the occurrence, progression, and prognosis of hepatocellular carcinoma(HCC) remain poorly understood to date. Methods: Multi-omics, multi-level deep mining of HCC data from TCGA and other publicly available databases by using online analysis tools from GEPIA2, TIMER2.0, DAVID, Kaplan-Meier plotter, cBioPortal and MethSurv databases, as well asthe R package to assess Polε family members in HCC for their potential biological functions. Results: We found that the four target genes were significantly upregulated in HCC (P<0.001), their high expression was associated with a lower survival rate (P<0.05), and both diagnostic ROC curves and disease-specific survival time-dependent ROC curves suggested that POLE2/3 showed better disease predictive efficacy, and the four genes were significantly associated with immune infiltration, and drug sensitivity analysis suggested that the high expression groups of four target genes showed higher drug sensitivity in some chemotherapeutic drugs(P<0.001). Conclusion: The POLE1/2/3/4are potential prognostic predictive molecules for HCC and correlate with immune infiltration,and high expression of POLE may serve as a potential predictor of the effect of targeted therapies. POLE2/3 may be the potential diagnostic biomarkers for HCC, and the expression level of POLE3 may serve as a biological predictive target for HCC chemotherapy sensitivity.

Objective To investigate the activation of hepatic embryonic stem cell factor in hepatocellular carcinoma and its characteristic effect on hepatocellular carcinoma. Methods Based on mRNA-seq data of hepatocellular carcinoma and matched clinical data in the TCGA database, and mRNA-seq data of hepatic embryonic stem cell genes screened by laboratory sequencing, we used the R package and some online analysis tools to find activated hepatic embryonic stem cell genes in hepatocellular carcinoma, and used support vector machine (SVM) and LASSO regression analysis to further screen out significantly differentially expressed hepatic embryonic stem cell genes, and to investigate their functional characteristics and clinical significance in hepatocellular carcinoma based on the expression of these hepatic embryonic stem cell genes. Finally, the expression of five embryonic stem cell factors in HCC tissues was detected based on immunohistochemical methods. Results Five liver embryonic stem cell genes, TYW3/CKLF/P2RY6/TUBA1B and RSU1 were significantly upregulated in hepatocellular carcinoma, showed good diagnostic efficacy for hepatocellular carcinoma, and were significantly associated with a poorer survival prognosis of patients. The prognostic model based on the five hepatic embryonic cell genes showed good predictive efficacy and has good potential for clinical application, immunohistochemical expression validation results also showed high expression of TYW3/CKLF/P2RY6/TUBA1B, and RSU1 in HCC, and were highly expressed in HCC and mainly expressed in the cytoplasm. Conclusion The activation of five hepatic germ cell genes, TYW3/CKLF/P2RY6/TUBA1B, and RSU1 are important diagnostic targets and prognostic markers for hepatocellular carcinoma, which significantly correlated with patient clinical prognosis. And the prognostic model of HCC based on TYW3/CKLF/P2RY6/TUBA1B, and RSU1 has a good clinical application potential for hepatocellular carcinoma.

Objective To explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms. Methods Based on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated. Results The expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma. Conclusion LY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma.

Objective To investigate the common ferroptosis signature genes in two cancers based on the disease commonality between hepatocellular carcinoma and renal clear cell carcinoma. MethodsBased on the mRNA-seq data and matched clinical data of the two cancers in the GEO database and TCGA database, we used R package and part of online analysis tools to find the differentially expressed ferroptosis genes in the two cancers, and then used LASSO regression analysis to further screen the ferroptosis signature genes in the two cancers, and explored their functional characteristics and clinical significance in the two cancers based on the expression of the ferroptosis signature genes. Results Four ferroptosis genes G6PD/NRAS/CDCA3, and NDRG1 were significantly upregulated in hepatocellular carcinoma and renal clear cell carcinoma, showed good diagnostic efficacy for both cancers, and were significantly associated with patient survival prognosis. The risk model based on the four characteristic genes showed good predictive efficacy and has potential clinical application, and upregulation of NRAS expression may contribute to the pathogenesis and progression of HCC through activation of MAPK/ERK signaling pathway. Conclusions G6PD/NRAS/CDCA3, and NDRG1 are common ferroptosis signature genes for hepatocellular carcinoma and renal clear cell carcinoma, and have good diagnostic and prognostic predictive efficacy for both cancers, and upregulation of NRAS expression may contribute to the pathogenesis and progression of HCC through activation of MAPK/ERK signaling pathway.