Computational analysis for identification of early diagnostic biomarkers and prognostic biomarkers of liver cancer based on GEO and TCGA databases and studies on pathways and biological functions affecting the survival time of liver cancer

Abstract

Background Liver cancer is the sixth most commonly diagnosed cancer and the fourth most common cause of cancer death. The purpose of this work is to find new diagnostic biomarkers or prognostic biomarkers and explore the biological functions related to the prognosis of liver cancer. Methods GSE25097 datasets were firstly obtained and compared with TCGA LICA datasets and an analysis of the overlapping differentially expressed genes (DEGs) was conducted. Cytoscape was used to screen out the Hub Genes among the DEGs. ROC curve analysis was used to screen the Hub Genes to determine the genes that could be used as diagnostic biomarkers. Kaplan-Meier analysis and Cox proportional hazards model screened genes associated with prognosis biomarkers, and further Gene Set Enrichment Analysis was performed on the prognosis genes to explore the mechanism affecting the survival and prognosis of liver cancer patients. Results 790 DEGs and 2162 DEGs were obtained respectively from the GSE25097 and TCGA LIHC data sets, and 102 Common DEGs were identified by overlapping the two DEGs. Further screening identified 22 Hub Genes from 102 Common DEGs. ROC and survival curves were used to analyze these 22 Hub Genes and it was found that there were 16 genes with a value of AUC > 90%. Among these, the expression levels of ESR1,SPP1 and FOSB genes were closely related to the survival time of liver cancer patients. Three common pathways of ESR1, FOBS and SPP1 genes were identified along with seven common pathways of ESR1 and SPP1 genes and four common pathways of ESR1 and FOSB genes. Conclusions SPP1, AURKA, NUSAP1, TOP2A, UBE2C, AFP, GMNN, PTTG1, RRM2, SPARCL1, CXCL12, FOS, DCN, SOCS3, FOSB and PCK1 can be used as diagnostic biomarkers for liver cancer, among which FOBS and SPP1 genes can also be used as prognostic biomarkers. Activation of the cell cycle-related pathway, pancreas beta cells pathway, and the estrogen signaling pathway, while on the other hand inhibition of the hallmark heme metabolism pathway, hallmark coagulation pathway, and the fat metabolism pathway may promote prognosis in liver cancer patients.

Oncogenic role and potential regulatory mechanism of topoisomerase IIα in a pan-cancer analysis

“…The Log-rank test revealed that high expression of TOP2A was a risk factor in ACC, KIRC, KIRP, LGG, LIHC, LUAD, MESO, PAAD and SCKM, and a protective factor in COAD and THYM. Part of these findings are consistent with other studies 8 , 27 – 29 , but the most of these results derived from the analysis of TCGA or GEO transcriptome data. However, some studies verified that the higher expression of TOP2A has nothing to do with the worse prognosis in these cancer types.…”

Evaluate the diagnostic and prognostic value of NUSAP1 in papillary thyroid carcinoma and identify the relationship with genes, proteins, and immune factors

“…The same results are seen in all datasets. In recent years, studies have reported that NUSAP1 was involved in malignant pleural mesothelioma (MPM) [ 34 ], liver cancer [ 35 ], prostate cancer [ 36 ], and other cancers, with diagnostic value. We used the THCA dataset and analyzed the GSE27155, GSE33630, GSE58545, and GSE60542 datasets to demonstrate that NUSAP1 has a better diagnostic value in PTC.…”

Up‐regulated LRRN2 expression as a marker for graft quality in living donor liver transplantation

“…Limited studies have examined the correlation between the expression of these six genes and LT. ATP1A1, which regulates mitochondrial metabolism, is involved in the progression of nonalcoholic fatty liver disease or nonalcoholic steatohepatitis before and after LT. [35,36] LTBP4, which accumulates in the extracellular matrix of patients with stage F3 liver fibrosis, is reportedly involved in the activation of transforming growth factor beta (TGFβ) and induction of liver cirrhosis, while suppression of LTBP4 or FOSB promotes cell proliferation. [37,38] In neuroblastoma, LRRN2 was correlated with cell proliferation in the JNK pathway. [39] This suggested that cell proliferation may be regulated by various factors in the liver, and further studies are needed to determine whether suppression of LTBP4 or FOSB may promote hepatocyte proliferation in grafts and improve graft survival in LDLT.…”