ABSTRACT
Objective:To construct a prognostic model of hepatocellular carcinoma (HCC) with differential expression of autophagy genes.Method:Autophagy genes expression data of HCC and normal liver tissues were obtained from The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) database respectively. The gene expression data from different platforms is normalized into log 2(FPKM value + 1). Differentially expressed autophagy-related genes of HCC were identified by using R program limma package from the TCGA-GTEx combined data set, the criteria of |logFC| > 1 and FDR < 0.05 was deemed to be of statistically significance. The Gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by using R program clusterProfiler package, as criteria of P<0.05. Univariate and multivariate Cox proportional hazards regression analyses were performed by using R program survival package to identify the HCC potential prognostic differentially expressed autophagy-related genes. Furthermore, the statistically significant ( P<0.05) autophagy genes in the univariate Cox regression analysis were included in the multivariate Cox regression analysis, and the expression of each differentially expressed autophagy gene and the corresponding regression coefficient coef value based on this, the autophagy gene prognosis model of HCC was constructed: expmRNA1×βmRNA1+ expmRNA2×βmRNA2+ …+ expmRNAn×βmRNAn (exp: gene expression level; β: regression coefficient coef of multivariate Cox regression analysis). Draw the receiver operating characteristic (ROC) curve of the predictive model and calculate the area under curve (AUC) to evaluate the predictive value of the model. Results:The genes expression data and clinical information of 374 HCC samples and 160 normal liver tissue samples were obtained from TCGA and GTEx databases. Total 205 autophagy genes expression data was obtained from the TCGA-GTEx combined sequence. Among them, SPNS1, DIRAS3, TMEM74, NRG2, NRG1, IRGM, IKBKE, NKX2-3, BIRC5, CDKN2A, TP73 are differentially expressed autophagy genes that meet the screening criteria. GO analysis mainly enriched in "regulation of protein serine/threonine kinase activity" , "ErbB 2 signaling pathway" , "protein kinase regulator activity" and "kinase regulator activity" ; KEGG analysis enriched frequently in "EGFR tyrosine kinase inhibitor resistance" , "Hippo signaling pathway" . After integrating and deleting samples with missing survival information, a total of 418 sample expressions were included in the Cox regression analysis. After univariate and multivariate Cox risk regression analysis, the two autophagy genes NRG1 ( HR=1.5565, 95% CI: 1.1793-2.0543) and IKBKE ( HR=1.7502, 95% CI: 1.2093-2.5330) were screened out and a prognostic prediction model was established: (0.44247 × NRG1 expression level) + (0.55977 × IKBKE expression level). The ROC of the prognosis model shows that the AUC of the overall seven-year survival is 0.711. Conclusion:The prognosis model of HCC based on NRG1 and IKBKE has high predictive value for the long-term survival rate of hepatocellular carcinoma patients.
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Objective To study the correlations between tumor mutation burden (TMB) and the prognosis of hepatocellular carcinoma (HCC) patients,and to investigate the effect of TMB on differential expression genes of HCC and the proportion of invasive immune cells in tumor tissues.Methods The somatic variation data,gene transcriptional expression data and clinical information of HCC patients were obtained from the cancer genome atlas (TCGA) database.The R program language (version 3.6.1)maftools function package was used to analyze the gene mutation data characteristics of the samples.The TMB value of each sample was calculated using the full-exon sequencing data of patients with hepatocellular carcinoma on the VarScan2 platform,sorted by TMB value,and the median value was used to divide all samples into high TMB and low TMB groups.Kaplan-Meier method was used to draw the survival curves of two groups of patients and log-rank test was performed to determine the correlation between tumor mutation load and prognosis.The Limma function package of R language was used to screen the differentially expressed genes between the two groups (FDR =0.05 and logFC =1),and the clusterProfiler function package of R language was used to perform gene ontology (GO) enrichment analysis of the differential genes and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis (screening criteria were all P ＜ 0.05).Then the CIBERSORT tool was used to compare and analyze the difference in the proportion of invasive immune cells between the two groups.Results A total of 364 patients with HCC from TCGA database were included in the study.Mutations were found in 327 (84％) samples,and there was a synergistic correlation between OBSCN and FLG mutations (P ＜ 0.05),while mutations in CTNNB1 and AXIN1 are mutually exdusive (P ＜ 0.05).A total of 363 patients were included in the TMB survival analysis,sorted by the size of TMB value.All samples were divided into high TMB group (182 cases) and low TMB group (181 cases) with the median value.We found that TMB had no significant effect on the prognosis of HCC patients (P ＞ 0.05).A total of 198 with differentially expressed genes (28 up-regulated genes and 170 down-regulated genes) were screened between the high TMB group and the low TMB group.In GO analysis,it was found that the differentially expressed genes were mainly enriched in extracellular matrix tissues,extracellular structural tissues,extracellular matrix,extracellular matrix containing collagen,extracellular matrix structural components and other functions.In KEGG analysis,differential genes were highly enriched in extracellular matrix receptor interaction pathway and adhesive plaque pathway.In the correlation analysis of the proportion of infiltrating immune cells,CD4 + memory T cells were more infiltrating in the low TMB group (P ＜ 0.05).Monocytes showed a higher degree of infiltration in the high TMB group (P ＜ 0.05).Conclusion There was no correlation between TMB and the prognosis of HCC patients.TMB has significant influence on the differential expression genes of HCC and the proportion of invasive immune cells in tumor tissues.
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Objective:To study the relative proportion of tumorinfiltrating immune cells (TIICs) in colorectal adenocarcinoma (CRC), and to explore the correlation between TIICs and CRC in prognosis and clinical staging.Methods:CRC gene transcriptional expression data and clinical information were obtained from TCGA database. The CIBERSORT software was used to calculate the relative proportions of 22 TIICs in each sample. R software was used to compare the proportion of TIICs between CRC and normal tissues. Single factor survival analysis was performed for each TIICs. Finally, the correlation between each TIICs and CRC clinical stage was studied.Results:A total of 514 gene transcriptional expression data and clinical information were obtained from TCGA database, including 473 CRC and 41normal adjacent tissues.The relative proportions of 22 TIICs in each sample were calculated using the CIBERSORT software "deconvolution method" . In the study, 12 TIICs including naive B cells were found to have statistically significant differences between CRC and normal tissues (all P<0.05). After matching the clinical information of the samples, a total of 222 cases were included in the survival analysis.The relative proportion of each TIICs was arranged in descending order, and all samples were divided into high and low infiltration groups according to the median value. Then, univariate survival analysis was performed for each TIICs, and it was found that memory B cells had a statistically significant effect on the prognosis of CRC ( P<0.05). It was found that the proportion of four types of TIICs, including activated CD 4 memory T cells, in different CRC clinical staging was statistically differe (all P<0.05). Conclusion:TIICs is related to the prognosis and clinical stage of CRC.