Hepatocellular Carcinoma Liver Tissues Research Articles

Overexpressed Histocompatibility Minor 13 was Associated with Liver Hepatocellular Carcinoma Progression and Prognosis.

Among primary liver carcinoma cases, the proportion of liver hepatocellular carcinoma (LIHC) cases is 75%–85%. Current treatments for LIHC include chemotherapy, surgical excision, and liver transplantation, which are effective for early LIHC treatment. Nevertheless, the early symptoms of liver carcinoma are atypical, so a large proportion of LIHC patients are diagnosed at an advanced stage. Histocompatibility minor 13 (HM13), located in the endoplasmic reticulum, is responsible for catalysing the hydrolysis of some signal peptides after cleavage from the precursor protein. Here, we studied the role of HM13 in LIHC development through bioinformatics analysis. Database analysis showed that HM13 was of great significance for LIHC tumorigenesis. Compared to normal liver tissues, HM13 expression was increased to a greater extent in LIHC tissues. After analysis of Kaplan‒Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA) datasets, we discovered that highly expressed HM13 exhibited an association with shorter overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to analyse HM13-related genes, and the data indicated that these genes obviously participated in rRNA processing, ribosome biogenesis, spliceosome, Huntington's disease, and ATP-dependent helicase activity. The Cell Counting Kit-8 (CCK-8) assay and Transwell assay showed that reducing HM13 expression hindered LIHC cell proliferation, migration, and invasion. In conclusion, these findings indicate that HM13 is a biomarker and is related to the poor prognosis of LIHC. Our results are conducive to discovering new targets for LIHC treatment.

CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma.

Background The specificity and sensitivity of hepatocellular carcinoma (HCC) diagnostic markers are limited, hindering the early diagnosis and treatment of HCC patients. Therefore, improving prognostic biomarkers for patients with HCC is urgently needed. Methods HCC-related datasets were downloaded from the public databases. Differentially expressed genes (DEGs) between HCC and adjacent nontumor liver tissues were then identified. Moreover, the intersection of DEGs in four datasets (GSE138178, GSE77509, GSE84006, and TCGA) was used in the functional enrichment, and module genes were obtained by a coexpression network. Cox and Kaplan-Meier analyses were used to identify overall survival- (OS-) related genes from module genes. Area under the curve (AUC) > 0.9 of OS-related genes was then carried out in order to perform the protein-protein interaction network. The feature genes were identified by least absolute shrinkage and selection operator (LASSO). Furthermore, the hub gene was identified through the univariate Cox model, after which the correlation analysis between the hub gene and pathways was explored. Finally, infiltration in immune cell types in HCC was analyzed. Results A total of 2,227 upregulated genes and 1,501 downregulated DEGs were obtained in all four datasets, which were mainly found to be involved in the cell cycle and retinol metabolism. Accordingly, 998 OS-related genes were screened to construct the LASSO model. Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained. CDC20 was shown to serve as a poor prognostic gene in HCC and was mainly involved in the cell cycle. Moreover, a positive correlation was noted between the high degree of infiltration with Th2 and CDC20. Conclusion High expression of CDC20 predicted poor survival, as potential target in the treatment for HCC.

CENPO is Associated with Immune Cell Infiltration and is a Potential Diagnostic and Prognostic Marker for Hepatocellular Carcinoma.

PurposeTo examine the expression, clinical significance, and potential regulatory mechanism of centromere protein O (CENPO) in hepatocellular carcinoma (HCC).MethodsCENPO expression in pan-cancer was studied using the TCGA-GTEx database, in HCC and normal liver tissues using the GEO and TCGA databases, and in clinical HCC samples by RT-qPCR. The diagnostic value of CENPO was assessed using receiver operating characteristic curves. Univariate and multivariate regression analyses of factors associated with HCC prognosis were performed. CENPO function and its mechanism in HCC were explored using GO, KEGG, and GSEA analyses of differentially expressed genes (DEGs). Association of CENPO expression with immune cell infiltration and immune checkpoint-associated molecules was conducted using TCGA data and the TIMER2.0 database. Relationships between CENPO expression and DNA methylation were analyzed using the UALCAN and cBioPortal databases. CENPO expression in HCC cell lines was detected using RT-qPCR.ResultsCENPO is upregulated in most cancers, including HCC and cell lines, and is a potential biomarker for HCC diagnosis (AUC = 0.936, 95% CI: 0.911–0.960). Higher CENPO expression was associated with poorer outcomes in patients with HCC (OS, p = 0.004; DSS, p = 0.002; PFI, p < 0.001), and CENPO was an independent predictor of factors influencing overall survival in HCC. DEGs between samples with high and low CENPO levels were enriched in various biological processes, including activation of the G2M checkpoint and other signaling pathways, while CENPO expression correlated with HCC immune cell infiltration and immune checkpoint-associated molecules, as well as CENPO promoter methylation (p < 0.001).ConclusionIn HCC and cell lines, CENPO is overexpressed, a potential diagnostic marker and an indicator of poor prognosis. CENPO may regulate HCC development by influencing nuclear division and tumor immune infiltration and is regulated by methylation, making it a potential target for HCC immunotherapy.

In silico and in vivo analysis of TIPE1 expression in diffuse large B cell lymphoma.

TIPE1 is a gene in the TNFAIP8 family involved in immune regulation and tumorigenesis. Although previous studies demonstrated that TIPE1 might play different roles in different tumors, its expression and role in lymphoma are unclear. Here we observed TIPE1 expression in diffuse large B cell lymphoma (DLBCL). Two microarrays containing 96 tumor tissue specimens were obtained from the Affiliated Hospital of Nantong University biobank. All specimens came from patients with a clear pathological diagnosis of lymphoma, lymphadenitis, breast cancer, or bladder cancer, and we performed immunohistochemical experiments on these tissue specimens. GEPIA and TIMER platforms were used for bioinformatic analyses. We found higher TIPE1 expression in tumor tissues from patients with lymphoma compared with those with lymphadenitis, breast cancer, or bladder cancer. The GEPIA and TIMER analyses revealed that TIPE1 was upregulated in DLBCL tissues but not in invasive breast carcinoma, urothelial bladder carcinoma, or liver hepatocellular carcinoma tissues. TIPE1 expression was irrelevant for pathological stage, overall survival, or DLBCL immune infiltration levels. However, TIPE1 expression was correlated with MKI67 expression in DLBCL. Overall, TIPE1’s high expression levels in DLBCL may contribute to tumor growth in DLBCL.

GIV is a promising novel poor prognostic factor in liver hepatocellular carcinoma.

Numerous studies have implicated Gα-interacting, vesicle-associated protein (GIV) in the development and metastasis of various cancers. However, its role remains unclear in liver hepatocellular carcinoma (LIHC). We aimed to demonstrate the relationship between GIV and LIHC based on The Cancer Genome Atlas database. We use the Gene Expression Profiling Interactive Analysis and UALCAN to explore the expression of GIV and the survive analysis of GIV in patients with LIHC, genetic alteration analysis, immune infiltration analysis, functional enrichment, protein-protein interaction network analyses, and transcription factor targets of GIV-correlated genes and GIV-interacting genes were performed this study. GIV expression was significantly elevated in LIHC tissues. Remarkable correlation was established between GIV expression and LIHC pathological stage. Low expression of GIV in tumor tissues had a better prognosis than GIV-high expression. GIV alteration frequency was 1.44% in patients with LIHC. GIV-unaltered patients had better survival than GIV-altered ones. Moreover, GIV expression level in LIHC significantly correlated with the infiltration level of immune cells and cancer-associated fibroblasts. The functions of differentially expressed GIVs are associated with the cell cycle pathway. Our data imply that E2F4, E2F1, MYC, and MYCN are key transcription factors for GIV-correlated genes and GIV-interacted genes. GIV may be an adverse prognostic factor for patients with LIHC; it also can be a potential therapeutic target against LIHC. Further studies are required to validate our findings.

Comprehensive Analysis of SLC17A9 and Its Prognostic Value in Hepatocellular Carcinoma.

BackgroundSolute carrier family 17 member 9 (SLC17A9) encodes a member of a family of transmembrane proteins that are involved in the transport of small molecules. SLC17A9 is involved in the occurrence and development of various cancers, but its biological role in liver hepatocellular carcinoma (LIHC) is unclear.MethodsThe expression level of SLC17A9 was assessed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry of tumor tissues and adjacent normal liver tissues. The receiver operating characteristic (ROC) and R software package performed diagnosis and prognosis. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment and co-expression of SLC17A9, gene–gene interaction (GGI), and protein–protein interaction (PPI) networks were performed using R, GeneMANIA, and STRING. Western blot, real-time quantitative PCR (RT-qPCR), immunofluorescence, colony formation, wound scratch assay, ATP production assays, and high connotation were applied to determine the effect of SLC17A9 knockdown on HEPG2 (hepatocellular liver carcinoma) cells. TIMER, GEPIA, and TCGA analyzed the relationship between SLC17A9 expression and immune cells, m6A modification, and ferroptosis.ResultsSLC17A9 expression in LIHC tissues was higher than in normal liver tissues (p < 0.001), and SLC17A9 was related to sex, DSS (disease-specific survival), and PFI (progression-free interval) (p = 0.015, 0.006, and 0.023). SLC17A9 expression has diagnostic (AUC: 0.812; CI: 0.770–0.854) and prognostic potential (p = 0.015) in LIHC. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) functional enrichment analysis showed that SLC17A9 was closely related to neuronal cell body, presynapse, axonogenesis, PI3K/Akt signaling pathway. GGI showed that SLC17A9 was closely related to MYO5A. PPI showed that SLC17A9 was closely related to SLC18A3. SLC17A9 silencing inhibited HepG2 cells proliferation, migration, colony formation, and reduced their ATP level. SLC17A9 expression level was related to immune cells: B cells (r = 0.094, P = 8.06E-02), CD4+ T cells (r = 0.184, P = 5.95E-04), and macrophages (r = 0.137, P = 1.15E-02); m6A modification: HNRNPC (r = 0.220, p < 0.001), METTL3 (r = 0.180, p < 0.001), and WTAP (r = 0.130, p = 0.009); and ferroptosis: HSPA5 (r = 0.240, p < 0.001), SLC7A11 (r = 0.180, p < 0.001), and FANCD2 (r = 0.280, p < 0.001).ConclusionOur data show that SLC17A9 may influence LIHC progression. SLC17A9 expression correlates with tumor immune infiltration, m6A modification, and ferroptosis in LIHC and may have diagnostic and prognostic value in LIHC.

Panoramic comparison between NK cells in healthy and cancerous liver through single-cell RNA sequencing.

Objective:NK cells play crucial roles in the immune defense mechanisms against viral infections and transformed cells. However, the developmental progression, transcriptomic landscape, and functional subtypes of liver NK cells are not well defined. Hepatocellular carcinoma (HCC) accounts for approximately 80% of primary liver cancer worldwide, yet the biological characteristics of NK cells in the HCC environment are unclear. Therefore, we aimed to determine these cells’ roles in tumorigenesis and prognosis.Methods:We compared the single-cell RNA sequencing profiles of NK cells purified from blood (n = 1), healthy liver tissues (n = 3), HCC tumor tissues (n = 4), and peritumor liver tissues (n = 1) to identify NK cell subsets. Furthermore, we performed bioinformatics analysis by using The Cancer Genome Atlas (TCGA) data to identify prognostic biomarkers simultaneously overexpressed in the blood and tumor tissues of patients with HCC.Results:Transcriptomic analysis revealed 5 NK cell subsets (L1-NK-CD56bright, L2-NK-CD56dim, L3-NK-HLA, L4-LrNK-FCGR3A, and L5-LrNK-XCL1) in the healthy liver tissues. However, the transitional L3 subset and the CXCR6+CD16+ L4 subset with strong anti-tumor activity were absent in the HCC and peritumor liver tissues. Furthermore, 4 common prognosis-associated genes (RHOB, TALDO1, HLA-DPA1, and TKT) were significantly overexpressed in the paired tumor tissue and blood.Conclusions:Our study revealed 5 specific subsets of NK cells in healthy human liver tissues. However, only 3 of the 5 NK cell subsets were present in HCC and peritumor tissues. The cytotoxic NK cell subsets were absent in HCC tissues. Furthermore, we identified 4 potential non-invasive prognostic biomarkers in patients with HCC.

Identification of a Necroptosis-Related Prognostic Signature and Associated Regulatory Axis in Liver Hepatocellular Carcinoma.

Background Liver hepatocellular carcinoma (LIHC) ranks the sixth in global cancer incidence with poor prognosis. Necroptosis is a kind of regulated cell death and has been proved to be of significance in cancer occurrence and progression. However, few studies comprehensively discuss the potential applications of necroptosis-related genes (NRGs) in the prognostic evaluation and immunotherapy of LIHC. Methods The prognostic signature in the present study was built up using LASSO Cox regression analysis. Integrated bioinformatics tools were utilized to explore the potential mRNA-miRNA-lncRNA regulatory axis in LIHC. Furthermore, qRT-PCR method was used to verify the EZH2 expression in LIHC tissues. Furthermore, prognostic performance of EZH2 in LIHC was assessed by Kaplan-Meier method. Results A total of 14 NRGs were differentially expressed in LIHC tissues. The overall genetic mutation status of these NRGs in LIHC was also shown. NRGs were significantly correlated with programmed necrotic cell death, as well as Toll-like receptor signaling pathway in GO and KEGG pathway analysis. Kaplan-Meier analysis revealed that ALDH2, EZH2, NDRG2, PGAM5, RIPK1, and TRAF2 were related to the prognosis. A prognostic signature was constructed by these six genes and showed medium to high accuracy in the prediction of LIHC patients' prognosis. Further analysis revealed that NRGs were correlated with pathological stage, immune infiltration, and drug resistance in LIHC. Moreover, we identified a potential lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis in LIHC, which might affect the progression of LIHC. qRT-PCR suggested a higher mRNA level of EZH2 in LIHC tissues. And a poor overall survival rate was detected in LIHC patients with high EZH2 expression. Moreover, EZH2 expression and cancer stage were identified as the independent risk factors affecting LIHC patients' prognosis. Conclusion In the present study, we conducted comprehensive bioinformatic analyses and built up a necroptosis-related prognostic signature containing four genes (ALDH2, EZH2, NDRG2, and PGAM5) for patients with LIHC, and this prognostic signature showed a medium to high predictive accuracy. And our study also identified a lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis, which might be of great significance in LIHC progression. In addition, based on the data from our center, the result of qRT-PCR and survival analysis showed a higher mRNA level of EZH2 in LIHC tissues and an unfavorable prognosis in high EZH2 expression group, respectively.

Screening and Identification of Key Genes in Hepatitis B Virus-Related Hepatocellular Carcinoma Through an Integrated Bioinformatics Approach

Objective: Primary liver cancer is one of the main causes of cancer mortality globally, with hepatocellular carcinoma (HCC) being the most frequent type. Chronic hepatitis B virus (HBV) infection is leading cause of HCC. This study aimed to identify significant genes for predicting prognosis in HBV-associated HCC. Methods: The GSE121248 gene expression profile was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) for HBV-associated HCC were identified by analyzing this expression profile. Enrichment analyses were performed to discover the role of DEGs in biological processes, cell components, molecular functions, and pathways. Then, protein-protein interaction (PPI) was constructed and 5 hub genes were identified. Finally, survival analysis was conducted to validate the prognostic value of these genes. Results: A total of 20188 official gene symbols were found, and 119 DEGs were identified between HBV-associated HCC and normal liver tissues. The PPI network identified CCNB1, CDK1, TOP2A, RACGAP1, and ASPM as hub genes. Kaplan-Meier curves showed that the high expression of the hub genes had significantly lower survival. Conclusion: CCNB1, CDK1, TOP2A, RACGAP1, and ASPM could be potential prognostic biomarkers and therapeutic targets for HBV-associated HCC.

Bimodal Treatment of Hepatocellular Carcinoma by Targeted Minimally Interventional Photodynamic/Chemotherapy Using Glyco-Covalent-Organic Frameworks-Guided Porphyrin/Sorafenib

Very limited treatment options are available to fight hepatocellular carcinoma (HCC), a serious global health concern with high morbidity and mortality. The integration of multiple therapies into one nanoplatform to exert synergistic therapeutic effects offers advantages over monotherapies. Here, we describe the construction of the nanoplatform Sor@GR-COF-366 for synergistic chemotherapy and photodynamic therapy (PDT) for HCC using a porphyrin-based covalent organic framework (COF-366) coated with N-acetyl-galactosamine (GalNAc) and rhodamine B (RhB), and loaded with the first-line agent, Sorafenib (Sor). The nanoplatform is targeted towards ASGPR-overexpressed HCC cells and liver tissues by GalNAc and observed by real-time imaging of RhB in vitro and in vivo. The nanoplatform Sor@GR-COF-366 exerts an enhanced synergistic tumor suppression effect in a subcutaneous HCC mouse model with a tumor inhibition rate (TGI) of 97% while significantly prolonging survival at very low toxicity. The potent synergistic therapeutic outcome is confirmed in an orthotopic mouse model of HCC with the TGI of 98% with a minimally invasive interventional PDT (IPDT). Sor@GR-COF-366 is a promising candidate to be combined with chemo-IPDT for the treatment of HCC. Statement of significanceThis work describes the construction of covalent-organic frameworks (COFs) modified with glyco-moieties to serve as hepato-targeted multitherapy delivery systems. They combine minimally invasive interventional photodynamic therapy (IPDT) triggered synergism with chemotherapy treatment for hepatocellular carcinoma (HCC). With the aid of minimally invasive intervention, PDT can elicit potent anti-cancer activity for deep solid tumors. This platform shows strong therapeutic outcomes in both subcutaneous and orthotopic mouse models, which can significantly prolong survival. This work showed an effective combination of a biomedical nano-formulation with the clinical operational means in cancer treatment, which is greatly promising in clinical translation.

BUB1 predicts poor prognosis and immune status in liver hepatocellular carcinoma.

Accurate assessment of the tumour immune microenvironment promotes individualized immunotherapy regimens and screens dominant populations suitable for immunotherapy. Therefore, potential molecular markers were investigated to make an overall assessment of the immune microenvironment status of liver hepatocellular carcinoma (LIHC). In this study, a total of 121 differentially expressed genes (DEGs) were identified, and DEGs were enriched in the epithelial-mesenchymal transition, hypoxia, myogenesis, and p53 pathways. A total of 20 hub genes were selected and a strong correlation was identified between these hub genes and prognosis. The expression of budding uninhibited by benzimidazoles 1 (BUB1) was found to be upregulated in LIHC and was strongly related to immune cells and immune checkpoint molecule expression. Immunohistochemistry (IHC) indicated that BUB1 expression was higher in LIHC tissues than in normal liver tissues. BUB1 knockdown resulted in reduced proliferation and vertical migration ability of LIHC cells, and reduced the expression of phospho-SMAD family member 2 and phospho-SMAD family member 3 proteins. IHC showed that BUB1 expression was accompanied by immune cell infiltration into LIHC tissues. These results suggest that BUB1 may serve as a potential prognostic biomarker for LIHC and as an indicator of its immune status.

COMMD2 Upregulation Mediated by an ncRNA Axis Correlates With an Unfavorable Prognosis and Tumor Immune Infiltration in Liver Hepatocellular Carcinoma.

Liver hepatocellular carcinoma (LIHC) seriously endangers the health and quality of life of individuals worldwide. Increasing evidence has underscored that the copper metabolism MURR1 domain (COMMD) family plays important roles in tumorigenesis. However, the specific role, biological function, mechanism and prognostic value of COMMD2 and its correlation with immune cell infiltration in LIHC remain unknown. In this study, we first determined the expression and prognostic potential of COMMD2 in human tumors using The Cancer Genome Atlas (TCGA) data and identified COMMD2 as a potential oncogene in LIHC. High COMMD2 expression was associated with pathological tumor stage and metastasis. Subsequently, noncoding RNAs (ncRNAs) upregulating COMMD2 expression were identified by performing expression, correlation, and survival analyses in combination. The CRNDE/LINC00511/SNHG17/HCG18-miR-29c-3p axis was identified as the most likely ncRNA-associated pathway upstream of COMMD2 in LIHC. Next, the expression profiles of COMMD2 and ncRNAs were validated in LIHC tissues and adjacent normal tissues. Furthermore, COMMD2 was significantly positively correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint molecule expression. Importantly, COMMD2 potentially influenced prognosis by regulating immune cell infiltration in LIHC. Finally, COMMD2 was knocked down in LIHC cell lines using siRNAs for functional assays in vitro, resulting in suppressed cell proliferation and migration. In summary, our findings showed that the ncRNA-mediated upregulation of COMMD2 was associated with an unfavorable prognosis correlated with immune cell infiltration in LIHC.

Cleavage stimulation factor 2 promotes malignant progression of liver hepatocellular carcinoma by activating phosphatidylinositol 3′-kinase/protein kinase B/mammalian target of rapamycin pathway

ABSTRACT Liver hepatocellular carcinoma (LIHC) is the most common type, comprising 75–85% of all liver malignancies. We investigated the roles of cleavage stimulation factor 2 (CSTF2) in LIHC and explored the underlying mechanisms. CSTF2 expression and its association with LIHC patient survival probability were analyzed with The Cancer Genome Atlas. CSTF2 expression in LIHC cells was assessed using western blot and quantitative real-time PCR. Alterations in CSTF2 expression were induced by cell transfection. Cell colony formation, apoptosis, proliferation, invasion, and migration were assessed using colony formation, flow cytometry, 5-ethynyl-2ʹ-deoxyuridine, and transwell assays. Pathway enrichment analysis was performed using gene set enrichment analysis (GSEA). The expression of apoptosis-, metastasis-, and pathway-associated factors was determined via western blot. The pathway rescue assay was further performed using 740Y-P or Wortmannin. CSTF2 upregulation was observed in LIHC tissues and cells. Patients with high CSTF2 expression had a lower probability of overall survival. CSTF2 overexpression enhanced colony formation, proliferation, invasion and migration, while repressing apoptosis in LIHC cells. GSEA revealed that CSTF2 was mainly enriched in the phosphatidylinositol 3′-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) pathway. Western blot analysis proved that CSTF2 overexpression activated this pathway. CSTF2 knockdown yielded the opposite effects. 740Y-P, a PI3K activator, reversed the CSTF2 knockdown-triggered effects on cell proliferation, apoptosis, invasion, and migration. Moreover, Wortmannin, a PI3K inhibitor, also reversed the CSTF2 overexpression-induced effects on cell proliferation, apoptosis, invasion, and migration. These results indicated that CSTF2 overexpression might exacerbate the malignant phenotypes of LIHC cells via activation of PI3K/AKT/mTOR pathway.

Proteomics profiling of nontumor liver tissues identifies prognostic biomarkers in hepatitis B-related hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often occurs following chronic hepatitis B virus (HBV) infection, leading to high recurrence and a low 5-year survival rate. We developed an overall survival (OS) prediction model based on protein expression profiles in HBV-infected nontumor liver tissues. We aimed to demonstrate the feasibility of using protein expression profiles in nontumor liver tissues for survival prediction. A univariate Cox and differential expression analysis were performed to identify candidate prognostic factors. A multivariate Cox analysis was performed to develop the liver gene prognostic index (LGPI). The survival differences between the different risk groups in the training and validation cohorts were also estimated. A total of 363 patients, 159 in the training cohort, and 204 in the validation cohort were included. Of the 6478 proteins extracted from nontumor liver tissues, we identified 1275 proteins altered between HCC and nontumor liver tissues. A total of 1090 out of 6478 proteins were significantly related to OS. The prognostic values of the proteins in nontumor tissues were mostly positively related to those in the tumor tissues. Protective proteins were mainly enriched in the metabolism-related pathways. From the differentially expressed proteins, the top 10 most significant prognosis-related proteins were submitted for LGPI construction. In the training and validation cohorts, this LGPI showed a great ability for distinguishing patients' OS risk stratifications. After adjusting for clinicopathological features, the LGPI was an independent prognostic factor in the training and validation cohorts. We demonstrated the prognostic value of protein expression profiling in nontumor liver tissues. The proposed LGPI was a promising predictive model for estimating OS in HBV-related HCC.

The Transcription of ZIP9 Is Associated With the Macrophage Polarization and the Pathogenesis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common digestive system cancers (DSCs) with a poor prognosis. Zinc‐regulated transporter (ZRT)/iron‐regulated transporter (IRT) like protein transporters (ZIPs) encode membrane transport proteins, which are responsible for the absorption of zinc and play important roles in the pathogenesis of various human cancers. Tumor-associated macrophages (TAMs) are important participants in the regulation of tumor microenvironment and the development of HCC. Individual role of each ZIP involved in hepatocarcinogenesis remains elusive. In this study, the transcription patterns of ZIPs in the DSCs were screened firstly through GEPIA2 database. Interestingly, the analysis of the DSCs data showed the distinct mRNA levels of ZIPs between DSCs tissues and healthy controls. Notably, the transcription levels of ZIP2, ZIP5, ZIP8, ZIP9 and ZIP14 were decreased significantly in the tissues of human liver cancer compared to paracarcinoma liver tissues. To further confirm the mRNA transcriptional changes of Zips in HCC, N-Nitrosodiethylamine (DEN) combined with carbon tetrachloride (CCl4) inducing mouse model of HCC were established. Consistently, the mRNA levels of Zip2, Zip9, and Zip14 in liver tissues of HCC induced mice were also decreased compared with the healthy controls. In addition, mouse peritoneal elucidated macrophages (PEMs)-derived M1/M2 macrophages in vitro, as well as human patients of HCC-derived TAMs, were used to examine the transcription levels of ZIPs. Our results showed that both Zip2 and Zip9 were up-regulated in M2-polarized macrophages. Zip2 transcript was also up-regulated M1-polarized macrophages, but Zip9 was slightly down-regulated. TAMs generated from human liver cancer tissues also displayed a decrease in ZIP9 transcription compared to paracarcinoma tissues. To further explore the role of Zip9 in M1/M2 polarization, the siRNA knockdown results revealed that Zip9, but not Zip2, could promote M2 macrophage polarization and impair M1 macrophage polarization. Mechanistically, Zip9 enhances phosphorylated STAT6 to promote M2 macrophage polarization but suppresses the phosphorylation of IκBα/β to inhibit M1 macrophage polarization. Together, our results indicate that ZIP9 may involve in macrophages polarity in HCC development and may be a potent new biomarker for the diagnosis of HCC.

A Pyroptosis-Related Gene Signature to Predict Patients' Prognosis and Immune Landscape in Liver Hepatocellular Carcinoma.

Background Liver hepatocellular carcinoma (LIHC) is a malignance with high incidence and recurrence. Pyroptosis is a programed cell death pattern which both activates the effective immune response and causes cell damage. However, their potential applications of pyroptosis-related genes (PRGs) in the prognostic evaluation and immunotherapy of LIHC are still rarely discussed. Methods Comprehensive bioinformatics analyses based on TCGA-LIHC dataset were performed in the current study. Results A total of 33 PRGs were selected to perform the current study. Of these 33 PRGs, 26 PRGs with upregulation or downregulation in LIHC tissues were identified. We also summarized the related genetic mutation variation landscape. GO and KEGG pathway analysis demonstrated that these 26 PRGs were primarily associated with pyroptosis, positive regulation of interleukin-1 beta production, and NOD-like receptor signaling pathway. An unfavorable OS appeared in LIHC patients with high CASP3, CASP4, CASP6, CASP8, GPX4, GSDMA, GSDME, NLRP3, NLRP7, NOD1, NOD2, PLCG1, and SCAF11 expression and low NLRP6 expression. A prognostic signature constructed by the above 14 prognostic PRGs had moderate to high accuracy to predict LIHC patients' prognosis. And risk score was correlated with the expression of CASP6, CASP8, GPX4, GSDMA, GSDME, NLRP6, and NOD2. Of these 7 genes, CASP8 was identified as the core gene in PPI network. Moreover, lncRNA MIR17HG/hsa-miRNA-130b-3p/CASP8 regulatory axis in LIHC was also detected. Conclusions The current study indicated the crucial role of PRGs in the prognostic evaluation of LIHC patients and their correlations with tumor microenvironment in LIHC.

Identification of MAD2L1 as a Potential Biomarker in Hepatocellular Carcinoma via Comprehensive Bioinformatics Analysis.

Background Hepatocellular carcinoma (HCC) is widely acknowledged as a malignant tumor with rapid progression, high recurrence rate, and poor prognosis. At present, there is a paucity of reliable biomarkers at the clinical level to guide the management of HCC and improve patient outcomes. Our research is aimed at assessing the prognostic value of MAD2L1 in HCC. Methods Four datasets, GSE121248, GSE101685, GSE85598, and GSE62232, were selected from the GEO database to analyze differentially expressed genes (DEGs) between HCC and normal liver tissues. After functional analysis, we constructed a protein-protein interaction network (PPI) for DEGs and identified core genes in this network with high connectivity with other genes. We assessed the relationship between core genes and the pathogenesis and prognosis of HCC. Finally, we explored the gene regulatory signaling mechanisms involved in HCC pathogenesis. Results 145 DEGs were screened from the intersection of the four GEO datasets. MAD2L1 was associated with most genes according to the PPI network and was selected as a candidate gene for further study. Survival analysis suggested that high MAD2L1 expression in HCC correlated with a worse prognosis. In addition, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC) findings suggested that the expression of MAD2L1 was abnormally increased in HCC tissues and cells compared to paraneoplastic tissues and normal hepatocytes. Conclusion We found that high MAD2L1 expression in HCC was significantly associated with overall patient survival and clinical features. We also explored the potential biological properties of this gene.

Prognostic Value and Immunological Role of KIFC1 in Hepatocellular Carcinoma.

As one of the members of the kinesin family, the role and potential mechanism of kinesin family member C1 (KIFC1) in the development of liver hepatocellular carcinoma (LIHC), especially in the immune infiltration, have not been fully elucidated. In this study, multiple databases and immunohistochemistry were employed to analyze the role and molecular mechanism including the immune infiltration of KIFC1 in LIHC. Generally, KIFC1 mRNA expression was overexpressed in LIHC tissues than normal tissues, and its protein was also highly expressed in the LIHC. KIFC1 mRNA expression was correlated with tumor grade and TNM staging, which was negatively correlated with overall survival and disease-free survival. Moreover, univariable and multivariate Cox analysis revealed that upregulated KIFC1 mRNA is an independent prognostic factor for LIHC. The KIFC1 promoter methylation level was negatively associated with KIFC1 mRNA expression and advanced stages and grade in LIHC. The different methylation sites of KIFC1 had a different effect on the prognosis of LIHC. Specifically, the KIFC1 mRNA expression level showed intense correlation with tumor immunity, such as tumor-infiltrating immune cells and immune scores as well as multiple immune-related genes. Moreover, KIFC1 co-expressed with some immune checkpoints and related to the responses to immune checkpoint blockade (ICB) and chemotherapies. Significant GO analysis showed that genes correlated with KIFC1 served as catalytic activity, acting on DNA, tubulin binding, histone binding, ATPase activity, and protein serine/threonine kinase activity. KEGG pathway analysis showed that these genes related to KIFC1 are mainly enriched in signal pathways such as cell cycle, spliceosome, pyrimidine metabolism, and RNA transport. Conclusively, KIFC1 was upregulated and displayed a prognostic value in LIHC. Moreover, KIFC1 may be involved in the LIHC progression partially through immune evasion and serve as a predictor of ICB therapies and chemotherapies.

Identification and Validation of DEPDC1B as an Independent Early Diagnostic and Prognostic Biomarker in Liver Hepatocellular Carcinoma.

Liver hepatocellular carcinoma (LIHC) is one of the most lethal tumors worldwide, and while its detailed mechanism of occurrence remains unclear, an early diagnosis of LIHC could significantly improve the 5-years survival of LIHC patients. It is therefore imperative to explore novel molecular markers for the early diagnosis and to develop efficient therapies for LIHC patients. Currently, DEPDC1B has been reported to participate in the regulation of cell mitosis, transcription, and tumorigenesis. To explore the valuable diagnostic and prognostic markers for LIHC and further elucidate the mechanisms underlying DEPDC1B-related LIHC, numerous databases, such as Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier plotter, and The Cancer Genome Atlas (TCGA) were employed to determine the association between the expression of DEPDC1B and prognosis in LIHC patients. Generally, the DEPDC1B mRNA level was highly expressed in LIHC tissues, compared with that in normal tissues (p < 0.01). High DEPDC1B expression was associated with poor overall survival (OS) in LIHC patients, especially in stage II, IV, and grade I, II, III patients (all p < 0.05). The univariate and multivariate Cox regression analysis showed that DEPDC1B was an independent risk factor for OS among LIHC patients (HR = 1.3, 95% CI: 1.08–1.6, p = 0.007). In addition, the protein expression of DEPDC1B was validated using Human Protein Atlas database. Furthermore, the expression of DEPDC1B was confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) assay using five pairs of matched LIHC tissues and their adjacent noncancerous tissues. The KEGG pathway analysis indicated that high expression of DEPDC1B may be associated with several signaling pathways, such as MAPK signaling, the regulation of actin cytoskeleton, p53 signaling, and the Wnt signaling pathways. Furthermore, high DEPDC1B expression may be significantly associated with various cancers. Conclusively, DEPDC1B may be an independent risk factor for OS among LIHC cancer patients and may be used as an early diagnostic marker in patients with LIHC.

The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and lethal types of cancer. This study aimed to identify the expression regulatory network and a prognostic signature of HCC. RNA-seq data from The Cancer Genome Atlas were used to identify the differentially expressed genes (DEGs) between HCC and normal liver tissues. DEGs were subjected to the construction of protein-protein interaction (PPI) network and enrichment analysis of Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The results showed that most of the DEGs were enriched in the cell cycle pathway, and the top 10 hub genes in the PPI network belong to the cell cycle pathway. A ceRNA network was constructed using starBase database, including one lncRNA (SNHG1), seven miRNAs (miR-195-5p, miR-199a-3p, miR-199a-5p, miR-199b-3p, miR-383-5p, miR-424-5p and miR-654-3p) and six of the top 10 hub genes (BUB1, CCNA2, CCNB1, KIF11, NCAPG, and TOP2A). In vitro experiments showed that knockdown of SNHG1 in the HCC cell lines (Huh7 and HepG2) decreased the expression of the six hub genes and cell viability, leading to cell cycle arrest at the G1 phase. These findings indicate that SNHG1 promotes cell proliferation by regulating cell cycle-related genes as a ceRNA. Additionally, Kaplan-Meier's survival and multivariate Cox regression analysis identified a prognostic signature of seven genes (including SNHG1 and the six SNHG1-regulated hub genes) for overall survival of HCC patients. In conclusion, this study identified a novel regulatory network in HCC and a potential independent prognostic factor for overall survival of HCC patients.