关键词: 人钙腔蛋白, 肝细胞癌, 生物信息学, 单细胞测序分析, 癌症预后

Abstract:

Objective To analyze the relationship between the expression level of calumenin （CALU） and the prognosis of hepatocellular carcinoma （HCC） patients by bioinformatics tools and establish the prognostic prediction nomogram， and to clarify its possible mechanism. Methods The data of 374 HCC tissue samples were downloaded from The Cancer Genome Atlas （TCGA） database and the data of 160 normal tissue samples were down loaded from Genotype-Tissue Expression（GTEx） database. Paired sample t-test was used to analyze the difference in CALU expression between the HCC tissue samples and the paired adjacent normal tissue samples. Human Protein Atlas （HPA） database was used to verify the results. DESeq2 package was used to screen the differentially expressed genes （DEGs） between CALU low expression group and CALU high expression group in the HCC tissue samples. R package pROC was used to analyze the receiver operating characteristic（ROC） curve. Univariate and multivariate Cox regression analyses were used to confirm the prognosis value of CALU in the HCC patients with different clinicopathological characteristics， and ggplot2 package was used to construct the forest plot. R packages rms and survival were used to construct the nomogram and its calibration curve， and the diagnostic value of CALU in distinguishing HCC tissue from normal tissue was analyzed. The data from Kaplan-Meier Plotter database were used to further verify the relationship between CALU and the prognosis of HCC patients. The gene transcriptional expression data of 216 HCC samples obtained from GSE14520 dataset were used to verify the prediction accuracy of the nomogram. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses were used to determine the function and enrichment pathways of the DEGs， and Gene Set Enrichment Analysis （GSEA） was used to obtain the significantly enriched gene sets of the DEGs. Single-cell sequencing data of 10 HCC tissue samples and 8 adjacent normal tissue samples obtained from GSE149614 dataset were used to verify the relationship between CALU and the prognosis of HCC patients and its mechanism. Results Compared with normal tissue， the expression level of CALU mRNA in HCC tissue was significantly increased （P<0.001）， and the expression level of CALU protein in HCC samples was also increased. A total of 928 DEGs were identified between CALU low expression group and CALU high expression group in the HCC samples， including 784 upregulated DEGs and 144 downregulated DEGs. The ROC analysis results indicated that CALU showed high diagnostic value in distinguishing cancer tissue from adjacent non-cancer tissue with an area under curve（AUC） of 0.839. Kaplan-Meier survival analysis showed that the survival rate of HCC patients in CALU high expression group was significantly lower than that in CALU group low expression（P<0.001）. Univariate and multivariate Cox regression analyses results demonstrated that high expression of CALU was an independent risk factor of the prognosis in HCC patients， and a prognosis prediction nomogram was constructed. The applicability of nomogram on the prognosis of HCC was verified by GSE14520 dataset. The GO enrichment analysis results showed that DEGs were mainly enriched in pathways related to the oxidative stress， ferroptosis and cuproptosis （P<0.05）. The KEGG enrichment analysis results showed that DEGs were mainly enriched in the pathways related to extracellular matrix（ECM） receptor interaction， linoleic acid metabolism and neuroactive ligand receptor interaction （P<0.05）. The GSEA results showed that high expression of CALU may promote the G₁-S phase transition of the cell cycle， ubiquitination protein polymerization and HCC progression， while low expression of CALU may activate oxidative stress， ferroptosis and cuproptosis in HCC cells. Single-cell sequencing analysis results showed that the expression level of CALU mRNA was significantly increased in HCC cells with advanced tumor stages. HCC_CALU_High cell subset was mainly related to ubiquitination， p53 and cell cycle （P<0.01）， and HCC_CALU_Low cell subset was mainly related to oxidative stress， ferroptosis， and histone binding （P<0.01）. Conclusion The high expression of CALU may be related to the poor prognosis of HCC patients. The constructed nomogram of HCC prognosis shows favourable effect in predicting the survival rate of the HCC patients. The up-regulation of CALU may promote HCC progression by regulating the G₁-S phase of the cell cycle and ubiquitination of protein， while down-regulation of CALU may inhibit HCC progression by inducing oxidative stress， ferroptosis and cuproptosis in cells.

Key words: Calumenin, Hepatocellular carcinoma, Bioinformatics, Single-cell sequencing, Cancer prognosis