Progression To Liver Hepatocellular Carcinoma Research Articles

The comprehensive roles of lncRNA FAM99A/FAM99B in hepatocellular carcinoma: Expressions, regulatory mechanisms and functional pathway analysis

AimsThe incidence and mortality of liver hepatocellular carcinoma (LIHC) were increasing year by year. The aim of this study was to investigate the comprehensive roles of lncRNA FAM99A and FAM99B in LIHC. Main methodsAccording to the data of TCGA and GTEx, the expression levels of FAM99A and FAM99B in LIHC were evaluated, and the overall survival (OS), disease-free survival (DFS), immune cell infiltration and tumor stage were analyzed. The subcellular localization of FAM99A and FAM99B in various cancer cell lines was predicted by lncATLAS database. In addition, we also used ENCORI, KEGG, LinkedOmics, Metascape and other databases. It was verified by in vivo and in vitro experiments. Key findingsCompared with adjacent normal tissues, FAM99A and FAM99B were down-regulated in LIHC tissues, and significantly correlated with immune cell infiltration. With the progression of tumor stage and grade, the expression of FAM99A and FAM99B showed a decreasing trend, and the prognosis of patients were also poor. In addition, the biological functions, signaling pathways and protein interactions of FAM99A and FAM99B in LIHC were enriched to study the potential molecular mechanisms. The overlapping RNA binding proteins (RBP) of FAM99A and FAM99B mainly included CSTF2T, BCCIP, RBFOX2 and SF3B4. Finally, experiments showed that overexpression of FAM99A attenuated the proliferation, invasion, colony formation and tumor growth of LIHC cells. SignificanceTaken together, the above studies demonstrated that FAM99A and FAM99B had an inhibitory effect on the progression of LIHC, which might be promising diagnostic biomarkers and therapeutic targets for LIHC patients.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis.

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Abstract 3402: Integration of microRNAs and transcriptome signatures identifies the persistent infection of hepatitis C virus-induced hepatocellular carcinoma

Abstract MicroRNAs (miRNAs) are short non-coding RNAs (ncRNAs) of ~22 nucleotides that mediate gene expression through various functions, including gene silencing, which can lead to translation repression and degradation of target mRNAs. Dysregulation of miRNA function has been associated with numerous diseases, particularly cancer, including hepatocellular carcinoma (HCC). During the progression of HCV-HCC, the function of miRNAs may be altered thereby altering gene expression to favor HCC. Therefore, the involved miRNA-mRNA interaction needs to be further studied. In addition, there are many clinical studies have shown that HCV patients who do not adequately control their diet which are prone to fatty liver accumulation (steatosis), it may increase the possibility of liver cirrhosis. In the current study, we aim to investigate the function and effects of persistent HCV-induced miRNAs expression in liver hepatocellular carcinoma progression and gene expression and to explore the mechanisms and regulatory genes of liver steatosis caused by HCV patients in a high-fat environment. We used the Huh751 cell line and the infected with the HCV JFH1 replicon of low-viral load S2 cells. We used an HCV miRNA array for initial identification of potential candidates. These miRNAs were analyzed for KEGG pathways via DIANA. Next, we identified miRNA-mRNA targets in 3 databases (miRDB; miRPathDB; TargetScan) and analyzed the targets for KEGG pathways using ShinyGO. The target miRNA-mRNA candidate genes were then compared with long-term JFH1 replicon infectious cell (L-HCV) NGS mRNA data to integrate miRNA-mRNA. The identified genes were analyzed in The Cancer Genome Atlas (TCGA) for survival, biological process, and expression in LIHC Big Data. Hsa-miR-215, hsa-mir-10b, and hsa-let-7a of L-HCV miRNAs group showed high significance for LIHC overall survival with a hazard ratio >1.0. Moreover, miRNAs associated with L-HCV survival were LIHC-specific but not in other cancers. Through systematic integration of these findings, we identified HMOX1 and BMF genes as being specifically associated with HCC and regulated by hsa-miR-215-5p, hsa-miR-10b-5p, and hsa-miR-7a-5p. In addition, we also found that the expression of the adipogenesis genes, FABP4 and adipogenesis gene, SREBP1, as well as the viral non-structural protein, NS3, was significantly increased in the HCV-high-fat group; and the expression of the gene IRS1, which is involved in hyperinsulinemia, showed a decreasing trend. The main cause of HCC is that HCV inhibits the expression of hsa-miR-215-5p, hsa-miR-10b-5p, and hsa-miR-7a-5p, leading to alter the expression of target genes, these have a significant effect on survival, suggesting that an essential role in virus-related liver cancer. In the future, we will further explore the regulatory mechanisms between these genes and HCV in a high-fat environment. Citation Format: Wen-Hsiu (Vivian) Su, Ciniso Sylvester Shabangu, Shu-Chi Wang. Integration of microRNAs and transcriptome signatures identifies the persistent infection of hepatitis C virus-induced hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3402.

AMPKα2 promotes tumor immune escape by inducing CD8+ T-cell exhaustion and CD4+ Treg cell formation in liver hepatocellular carcinoma

BackgroundAdenosine monophosphate-activated protein kinase (AMPK) is associated with the development of liver hepatocellular carcinoma (LIHC). AMPKα2, an α2 subunit of AMPK, is encoded by PRKAA2, and functions as the catalytic core of AMPK. However, the role of AMPKα2 in the LIHC tumor immune environment is unclear.MethodsRNA-seq data were obtained from the Cancer Genome Atlas and Genotype-Tissue Expression databases. Using the single-cell RNA-sequencing dataset for LIHC obtained from the China National Genebank Database, the communication between malignant cells and T cells in response to different PRKAA2 expression patterns was evaluated. In addition, the association between PRKAA2 expression and T-cell evolution during tumor progression was explored using Pseudotime analysis, and the role of PRKAA2 in metabolic reprogramming was explored using the R “scMetabolis” package. Functional experiments were performed in LIHC HepG2 cells.ResultsAMPK subunits were expressed in tissue-specific and substrate-specific patterns. PRKAA2 was highly expressed in LIHC tissues and was associated with poor patient prognosis. Tumors with high PRKAA2 expression displayed an immune cold phenotype. High PRKAA2 expression significantly promoted LIHC immune escape. This result is supported by the following evidence: 1) the inhibition of major histocompatibility complex class I (MHC-I) expression through the regulation of interferon-gamma activity in malignant cells; 2) the promotion of CD8+ T-cell exhaustion and the formation of CD4+ Treg cells in T cells; 3) altered interactions between malignant cells and T cells in the tumor immune environment; and 4) induction of metabolic reprogramming in malignant cells.ConclusionsOur study indicate that PRKAA2 may contribute to LIHC progression by promoting metabolic reprogramming and tumor immune escape through theoretical analysis, which offers a theoretical foundation for developing PRKAA2-based strategies for personalized LIHC treatment.

Analysis and Validation of Tyrosine Metabolism-related Prognostic Features for Liver Hepatocellular Carcinoma Therapy.

To explore tyrosine metabolism-related characteristics in liver hepatocellular carcinoma (LIHC) and to establish a risk signature for the prognostic prediction of LIHC. Novel prognostic signatures contribute to the mining of novel biomarkers, which are essential for the construction of a precision medicine system for LIHC and the improvement of survival. Tyrosine metabolism plays a critical role in the initiation and development of LIHC. Based on the tyrosine metabolism-related characteristics in LIHC, this study developed a risk signature to improve the prognostic prediction of patients with LIHC. To investigate the correlation between tyrosine metabolism and progression of LIHC and to develop a tyrosine metabolism-related prognostic model. Gene expression and clinicopathological information of LIHC were obtained from The Cancer Genome Atlas (TCGA) database. Distinct subtypes of LIHC were classified by performing consensus cluster analysis on the tyrosine metabolism-related genes. Univariate and Lasso Cox regression were used to develop a RiskScore prognosis model. Kaplan-Meier (KM) survival analysis with log-rank test and area under the curve (AUC) of receiver operating characteristic (ROC) were employed in the prognostic evaluation and prediction validation. Immune infiltration, tyrosine metabolism score, and pathway enrichment were evaluated using single-sample gene set enrichment analysis (ssGSEA). Finally, a nomogram model was developed with the RiskScore and other clinicopathological features. Based on the tyrosine metabolism genes in the TCGA cohort, we identified 3 tyrosine metabolism-related subtypes showing significant prognostic differences. Four candidate genes selected from the common differentially expressed genes (DEGs) between the 3 subtypes were used to develop a RiskScore model, which could effectively divide LIHC patients into high- and lowrisk groups. In both the training and validation sets, high-risk patients tended to have worse overall survival, less active immunotherapy response, higher immune infiltration and clinical grade, and higher oxidative, fatty, and xenobiotic metabolism pathways. Multivariate analysis confirmed that the RiskScore was an independent indicator for the prognosis of LIHC. The results from pan-- cancer analysis also supported that the RiskScore had a strong prognostic performance in other cancers. The nomogram demonstrated that the RiskScore contributed the most to the prediction of LIHC prognosis. Our study developed a tyrosine metabolism-related risk model that performed well in survival prediction, showing the potential to serve as an independent prognostic predictor for LIHC treatment.

The diagnostic, prognostic, drug sensitivity and ceRNA internet of PPP4R1 in liver hepatocellular carcinoma (LIHC).

Recent studies have reported a role of protein phosphatase 4 regulatory subunit 1 (PPP4R1) in cancer development. However, its expression, diagnostic significance, prognostic value and biological function in liver hepatocellular carcinoma (LIHC) are not known. The expression level of PPP4R1 in pan-cancer was evaluated by analyzing publicly accessible data from the University of California Santa Cruz (UCSC) Xena database. The diagnostic value of PPP4R1 for tumors was assessed using receiver operating characteristic (ROC) curves, whereas the impact of PPP4R1 on tumor prognosis was determined using Kaplan-Meier survival curves, and a prognostic model for LIHC was established using cox regression analysis. In addition, analysis of the correlation between PPP4R1 and anti-cancer drugs using Spearman's correlation coefficient was carried out. Four databases, miRWalk (mRNA-miRNA interactions), MicroT-CDS (mRNA-miRNA interactions), LncBase (miRNA-lncRNA interactions) and Encyclopedia of RNA Interactomes (ENCORI), were used to predict the competitive endogenous RNA (ceRNA) regulatory network of PPP4R1. Finally, the expression of PPP4R1 protein levels was verified using experiments. The findings indicated that the PPP4R1 expression level in cancerous tissues was notably greater than in adjacent tissues (P<0.05). PPP4R1 showed diagnostic significance for 14 tumors based on the ROC curves results area under the curve >0.7. Furthermore, the Kaplan-Meier survival plots demonstrated that PPP4R1 exhibited prognostic significance for all five tumors (P<0.05). According to the cox regression analysis, LIHC patients' prognosis was independently influenced by pathological stage, M stage, and PPP4R1 (P<0.05). The drug sensitivity analysis revealed a positive correlation between the expression level of PPP4R1 and the half maximal inhibitory concentration (IC50) of fludarabine. Additionally, the ceRNA network prediction indicated that the FGD5 antisense RNA 1 (FGD5-AS1)-hsa-miR-22-3p-PPP4R1 ceRNA network could potentially contribute to the progression of LIHC. The experimental results showed that the expression level of PPP4R1 protein was higher in cancer tissues than in paracancerous tissues. PPP4R1 has diagnostic value in most cancers, and high expression of PPP4R1 is associated with poor prognosis, drug resistance and natural killer cell-mediated toxicity, particularly in LIHC. Therefore, PPP4R1 may be a prognostic biomarker and a potential target for immunotherapy in LIHC.

Fanconi Anemia Complementary Group A (FANCA) Facilitates the Occurrence and Progression of Liver Hepatocellular Carcinoma.

Liver hepatocellular carcinoma (LIHC) is a serious liver disease worldwide, and its pathogenesis is complicated. This study investigated the potential role of FANCA in the advancement and prognosis of LIHC. Public databases, quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blot(WB)and immunohistochemistry (IHC) were employed to measure FANCA expression between tumor and normal samples. The relationship between FANCA expression and prognosis of LIHC patients were examined. Functional enrichment of FANCA-related genes was performed. Furthermore, univariate and multivariate analyses were conducted to determine the independent prognosis value of FANCA in LIHC. Finally, influence of FANCA knockout on the proliferation, migration, and invasion of HepG2 cell was validated with cloning formation, CCK8, and Transwell assays. Expression analysis presented that FANCA had high expression level in LIHC tissues and cells. Receiver operating characteristic (ROC) curve analysis showed that FANCA was of great diagnosis value in LIHC. Clinicopathological analysis revealed that FANCA was significantly greater expressed in the advanced stage than in the early stage of LIHC. Univariate, multivariate, and Kaplan-Meier survival analysis confirmed that high expression of FANCA was strongly associated with poor survival of LIHC patients. In addition, high level of FANCA in LIHC showed a negative association with immunoinfiltrated B cells, T cells, and stromal scores. Moreover, Knockout of FANCA significantly inhibited HepG2 cell proliferative activity, migration, and invasion ability. Our data revealed that high level of FANCA was closely associated with LIHC malignant progression, suggesting its potential utility as a diagnostic, predictive indicator, and therapeutic target.

HOMER3 promotes liver hepatocellular carcinoma cancer progression by -upregulating EZH2 and mediating miR-361/GPNMB axis

Liver hepatocellular carcinoma (LIHC) is among the most lethal human cancers. Studies have shown that Homer scaffold protein 3 (HOMER3) plays important roles in various diseases and cancers, but its biological function and molecular mechanism in LIHC have never been investigated. Our study discovered the aberrantly high expression of HOMER3 and its promising diagnostic and prognostic significance in LIHC. Functionally, HOMER3 knockdown inhibited the proliferative and migrative abilities of LIHC cells and tumor growth in vivo. Mechanically, HOMER3 mediated the aggressiveness of LIHC cells via GPNMB. Meanwhile, miR-361 directly targeted GPNMB and attenuated LIHC progression by suppressing GPNMB expression. The regulatory effect of HOMER3 during LIHC progression was exerted through the miR-361/GPNMB axis. Furthermore, EZH2 supplementation or miR-361 depletion effectively abated the tumor-suppressive effect of HOMER3 knockdown on LIHC progression. In conclusion, HOMER3 mediated LIHC progression through the EZH2/miR-361/GPNMB axis.

ALYREF-mediated RNA 5-Methylcytosine modification Promotes Hepatocellular Carcinoma Progression Via Stabilizing EGFR mRNA and pSTAT3 activation.

5-Methylcytosine (m5C) is one of the most ubiquitous modifications of mRNA and contributes to cancer pathogenesis. Aly/REF export factor (ALYREF), an m5C reader, is associated with the prognosis of liver hepatocellular carcinoma (LIHC). However, the effects of ALYREF on the progression of LIHC and the underlying molecular mechanisms remains elusive. Through an analysis of an online database and 3 independent LIHC cohorts, we found that ALYREF was markedly elevated in human liver cancer tissues and was significantly correlated with LIHC clinicopathological parameters, including Ki67+ cell rate, high-grade TNM stage, and poor prognosis. Several experiments were conducted to investigate the molecular basis and functional role of ALYREF-related progression in this study. ALYREF could enhance LIHC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro and tumor formation in vivo. Mechanistically, ALYREF promoted the progression of human LIHC through EGFR pathways. Furthermore, ALYREF could directly bind to the m5C modification site of EGFR 3' untranslated region (3' UTR) to stabilize EGFR mRNA. Collectively, ALYREF played a crucial oncogenic role in LIHC via the stabilization of EGFR mRNA and subsequent activation of the STAT3 signaling pathway. Our results may help to elucidate the potential mechanisms of ALYREF-induced m5C modification in the progression of human LIHC.

KIAA1429 facilitates progression of hepatocellular carcinoma by modulating m6A levels in HPN

BackgroundMost N6-methyladenosine (m6A)-associated modulatory proteins are involved in the pathogenesis of various cancers. The roles of m6A-related genes in liver hepatocellular carcinoma (LIHC) and the associated mechanisms remain unknown. MethodsGEO and GEPIA2 databases were used to identify the m6A modification-related genes which were differentially expressed in LIHC and adjacent non-tumor tissues, and quantitative PCR was used to evaluate the expression of KIAA1429, a major m6A methyltransferase, in LIHC cells. The effect of KIAA1429 on the malignant phenotypes of LIHC cells was evaluated in vitro. The UALCAN, GEPIA, and GEO databases and western blotting assays were used to identify the target genes of KIAA1429. ResultsKIAA1429 expression was markedly elevated in LIHC tissues, and patients with LIHC who had high KIAA1429 expression had a worse prognosis than those who had low expression. KIAA1429 silencing attenuated LIHC metastasis and proliferation. KIAA142 regulates m6A levels in HPN to intensify LIHC progression. ConclusionOur study suggests a KIAA1429-HPN modulatory model based on m6A modifications, that offers insights into the occurrence and development of LIHC.

Comprehensive intratumoral heterogeneity landscaping of liver hepatocellular carcinoma and discerning of APLP2 in cancer progression.

As the sixth most common type of cancer worldwide, liver hepatocellular carcinoma (LIHC) emerges as grave public health danger owing to its chemotherapy-resistant feature. Disulfidoptosis is a newly discovered programmed cell death process affecting the normal actin cytoskeleton structure. Single-cell RNA (scRNA)-seq data were procured from GSE149614 and GSE202642 datasets. We utilized uniform manifold approximation and projection and clustering algorithm Louvian for dimensionality reduction and FindAllMarkers function for determining the differentially expressed genes (DEGs). Monocle2 and SCENIC were utilized to perform pseudo-time series and transcription factor analysis for selected subgroups. A series of in vitro experiments, including colony formation assay (CFA), flow cytometry targeting apoptosis and cell cycle, was applied to investigate how APLP2 regulated the LIHC progression. Two cell lines of LIHC cells, HepG2, and Huh7, were used for si-APLP2 transfection. Tumor heterogeneity landscape of LIHC was depicted by detailed subgroup analysis. We found T and B cells were enriched with POU2F1 and HES1 activity. Inflammatory cancer-associated fibroblasts interacted with the cancer cells, uniquely through COL1A1/SDC1, COL1A2/SDC1 and LUM/ITGB1 pathways. The transformation from normal hepatocytes to malignant cells was displayed by cell trajectory analysis. State4, which was determined as malignant cells, was enriched in PI3K, hypoxia, and Epidermal growth factor receptor pathway, and enriched with Nuclear Receptor Subfamily 2 Group F Member 1 transcription factor activity. We observed an intense communication from the cancer cells to endothelial cells, mainly through the Vitronectin (VTN) to Kinase Insert Domain Receptor (KDR) pathway. A prognostic model targeting LIHC was constructed based on the disulfidoptosis-based DEGs, namely APLP2, PDIA6, YBX1, SPP1, whose accuracy was validated in multiple cohorts. Knockdown of APLP2 significantly increased the apoptosis and delayed cell cycle progression of LIHC cell line. A prognostic model targeting LIHC was constructed based on the disulfidoptosis-related DEGs, which displayed high stability and accuracy in multiple cohorts. APLP2 played an active role in the carcinogenesis of LIHC by regulating the apoptosis and cell cycle.

A novel signature incorporating lipid metabolism- and immune-related genes to predict the prognosis and immune landscape in hepatocellular carcinoma.

Liver hepatocellular carcinoma (LIHC) is a highly malignant tumor with high metastasis and recurrence rates. Due to the relation between lipid metabolism and the tumor immune microenvironment is constantly being elucidated, this work is carried out to produce a new prognostic gene signature that incorporates immune profiles and lipid metabolism of LIHC patients. We used the "DEseq2" R package and the "Venn" R package to identify differentially expressed genes related to lipid metabolism (LRDGs) in LIHC. Additionally, we performed unsupervised clustering of LIHC patients based on LRDGs to identify their subgroups and immuno-infiltration and Gene Ontology (GO) enrichment analysis on the subgroups. Next, we employed multivariate, LASSO and univariate Cox regression analyses to determine variables and to create a prognostic profile on the basis of immune- and lipid metabolism-related differential genes (IRDGs and LRDGs). We separated patients into low- and high-risk groups in accordance with the best cut-off value of risk score. We conducted Decision Curve Analysis (DCA), Receiver Operating Characteristic curve analysis as a function of time as well as Survival Analysis to evaluate this signature's prognostic value. We incorporated the clinical characteristics of patients into the risk model to obtain a nomogram prognostic model. GEO14520 and ICGC-LIRI JP datasets were employed to externally confirm the accuracy and robustness of signature. The gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied for investigating the underlying mechanisms. Immune infiltration analysis was implemented to examine the differences in immune between both risk groups. Single-cell RNA sequencing (scRNA-SEQ) was utilized to characterize the genes that were involved in the distribution of signature and expression characteristics of different LIHC cell types. The patients' sensitivity in both risk groups to commonly used chemotherapeutic agents and semi-inhibitory concentrations (IC50) of the drugs was assessed using the GDSC database. On the basis of the differentially expressed genes (DEGs) in the two groups, the CMAP database was adopted for the prediction of potential small-molecule compounds. Small-molecule compounds were molecularly docked with prognostic markers. Lastly, we investigated the prognostic gene expression levels in normal and LIHC tissues with immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction(qRT-PCR). We built and verified a prognostic signature with seven genes that incorporated immune profiles and lipid metabolism. Patients were classified as low- and high-risk groups depending on their prognostic profiles. The overall survival (OS) was markedly lower in the high-risk group as compared to low-risk group. Time-dependent ROC curves more precisely predicted patients' survival at 1, 3 and 5 years; the area under the ROC curve was 0.81 (1 year), 0.75 (3 years) and 0.77 (5 years). The DCA curves showed the value of the prognostic genes in this signature for clinical applications. We included the patients' clinical characteristics in the risk model for both multivariate and univariate Cox regression analyses, and the findings revealed that the risk model represents an independent factor that influences OS in LIHC patients. With immune analysis, GSVA and GSEA, we identified that there are remarkable differences between the two risk groups in immune pathways, lipid metabolism, tumor development, immune cell infiltration and immune microenvironment, response to immunotherapy, and sensitivity to chemotherapy. Moreover, those with higher risk scores presented greater sensitivity to the chemotherapeutic agents. Experiments in vitro further elucidated the roles of SPP1 and FLT3 in the LIHC immune microenvironment. Furthermore, four small-molecule drugs that could target LIHC were screened. In vitro qRT-PCR , IHC revealed that the SPP1,KIF18A expressions were raised in LIHC in tumor samples, whereas FLT3,SOCS2 showed the opposite trend. We developed and verified a new signature comprising immune- and lipid metabolism-associated markers and to assess the prognosis and the immune status of LIHC patients. This signature can be applied to survival prediction, individualized chemotherapy, and immunotherapeutic guidance for patients with liver cancer. This study also provides potential targeted therapeutics and novel ideas for the immune evasion and progression of LIHC.

A novel prognostic biomarker: GINS3 is correlated with methylation and immune escape in liver hepatocellular carcinoma.

Liver cancer remains one of the tricky malignancies nowadays. GINS complex subunit 3 (GINS3), part of the GINS tetrameric complex, is significantly upregulated in many cancers, including liver hepatocellular carcinoma (LIHC). With the development of liver cancer treatment, immune and molecular targeted therapy gradually becomes a promising treatment. However, the key target for liver cancer is still indistinct. Herein, the underneath mechanism of GINS3 was investigated to verify its role as a biomarker in LIHC. Genomic expression, genetic alteration, and methylation analyses were obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), The University of Alabama at Birmingham CANcer (UALCN), and Human Protein Atlas (HPA), cBioPortal, and MethSurv databases. Subsequently, the diagnostic and prognostic role of GINS3 in LIHC were analyzed based on data from receiver operating characteristic (ROC), Kaplan-Meier plotter (KM-plotter), and univariate and multivariate cox regression analyses. The functional analyses were conducted with GeneMANIA and STRING databases, gene-gene, and protein-protein interaction (PPI) networks, Gene Ontology (GO) term, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Tumor Immune Estimation Resource (TIMER), Tumor-Immune System Interaction Database (TISIDB), and Gene Expression Profiling Interactive Analysis (GEPIA) were utilized to explore the internal connection with the immune escape. Through the analyses of genomic expression, GINS3 was significantly upregulated in LIHC and positively correlated with higher T classification. ROC analysis indicated GINS3 as a potential biomarker in the diagnosis of LIHC. KM-plotter, univariate and multivariate cox regression analyses both associated GINS3 with poor prognosis in LIHC patients. GINS3 genetic alteration, gene-gene interaction, PPI networks, and enrichment analysis further revealed that GINS3 played a pivotal role in the progression of LIHC. Furthermore, hypermethylation of GINS3 at different cytosine-guanine (CpG) sites was correlated with better or worse overall survival (OS) in LIHC and GINS3 was also closely correlated with m6A modification. Moreover, results supported that GINS3 could influence the tumor microenvironment and relate to the immune checkpoints. Taken together, comprehensive analyses from this study supported GINS3 as a novel targeted biomarker in LIHC.

Pan-cancer analysis of the oncogenic role of HNRNPR in human tumors.

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are potential cancer biomarkers. Little is known about the role of HNRNPR, an essential member of the hnRNP family, in human tumours. This study aims to explore the potential value of HNRNPR across cancers, based on The Cancer Genome Atlas (TCGA). The expression level, mutation, DNA methylation, phosphorylation status, survival status, pathological stage, tumor mutation burden (TMB), microsatellite instability (MSI), immune cell infiltration, and immune signature related to HNRNPR were analyzed. HNRNPR expression level was increased in several types of cancer and was associated with poor prognosis, especially in liver hepatocellular carcinoma (LIHC). HNRNPR was also correlated with antitumour immunity, and associated with TMB, MSI, and immune cell activation status across cancers. Furthermore, nomograms were established to predict the prognosis of LIHC, based on HNRNPR and other clinical characteristics. Functional enrichment analysis showed the mechanisms of HNRNPR-mediated LIHC progression. Loss-of-function experiments demonstrated that inhibition of HNRNPR could remarkably suppress hepatocellular carcinoma (HCC) cell proliferation, migration, invasion, and Epithelial-Mesenchymal Transition abilities. Our study offers a comprehensive understanding of the oncogenic roles of HNRNPR across different tumours, and demonstrates that HNRNPR might foster the proliferation, migration, and invasion abilities of HCC cells.

Comprehensive analysis of the correlation of the pan-cancer gene HAUS5 with prognosis and immune infiltration in liver cancer

Liver hepatocellular carcinoma (LIHC) is one of the most common malignancies and places a heavy burden on patients worldwide. HAUS augmin-like complex subunit 5 (HAUS5) is involved in the occurrence and development of various cancers. However, the functional role and significance of HAUS5 in LIHC remain unclear. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and Gene Expression Omnibus (GEO) databases were used to analyze the mRNA expression of HAUS5. The value of HAUS5 in predicting LIHC prognosis and the relationship between HAUS5 and clinicopathological features were assessed by the Kaplan–Meier plotter and UALCAN databases. Functional enrichment analyses and nomogram prediction model construction were performed with the R packages. The LinkedOmics database was searched to reveal co-expressed genes associated with HAUS5. The relationship between HAUS5 expression and immune infiltration was explored by searching the TISIDB database and single-sample gene set enrichment analysis (ssGSEA). The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA) databases were used to evaluate HAUS5 protein expression. Finally, the effect of HAUS5 on the proliferation of hepatoma cells was verified by CCK-8, colony formation and EdU assays. HAUS5 is aberrantly expressed and associated with a poor prognosis in most tumors, including LIHC. The expression of HAUS5 is significantly correlated with clinicopathological indicators in patients with LIHC. Functional enrichment analysis showed that HAUS5 was closely related to DNA replication, cell cycle and p53 signaling pathway. HAUS5 may serve as an independent risk factor for LIHC prognosis. The nomogram based on HAUS5 had area under the curve (AUC) values of 0.74 and 0.77 for predicting the 3-year and 5-year overall survival (OS) of LIHC patients. Immune correlation analysis showed that HAUS5 was significantly associated with immune infiltration. Finally, the results of in vitro experiments showed that when HAUS5 was knocked down, the proliferation of hepatoma cells was significantly decreased. The pan-oncogene HAUS5 is a positive regulator of LIHC progression and is closely associated with a poor prognosis in LIHC. Moreover, HAUS5 is involved in immune infiltration in LIHC. HAUS5 may be a new prognostic marker and therapeutic target for LIHC patients.

Ferroptosis regulator SLC7A11 is a prognostic marker and correlated with PD-L1 and immune cell infiltration in liver hepatocellular carcinoma.

Background: Liver hepatocellular carcinoma (LIHC) is a complicated disease with poor survival and lack of viable treatment options. The roles of ferroptosis and immunotherapy in LIHC are increasingly prominent, but the interplay of ferroptosis with the tumor microenvironment (TME) in LIHC is currently under-investigated. Methods: In this study, we analyzed normal liver tissues and tumor tissues from the TCGA and GTEx databases to obtain differentially expressed ferroptosis-related genes (FRGs). We then clustered LIHC based on the expression levels of selected FRGs and acquired distinct subtypes with significant heterogeneity regarding survival prognoses, PD-L1 expression, and immune cell infiltration. The correlation of those FRGs with TME in LIHC and pan-cancer analysis was also investigated. GO functional annotations and KEGG pathway analyses were performed to investigate the potential reactions of the obtained differentially expressed genes (DEGs). Further external validation was performed using microarrays on the GEO database and the key ferroptosis regulator SLC7A11 expression between LIHC and normal cells was detected by Western blotting. Results: A large proportion of genes were upregulated in the LIHC group. Among three clusters, cluster 3 had the worst prognosis combined with the highest PD-L1 expression and was positively correlated with various immune cells. Subsequently, survival analysis and Cox regression analysis screened out SLC7A11 as an independent prognostic factor in LIHC featured strong PD-L1 expression and unfavorable survival time. We filter out SLC7A11 as an independent prognostic signature in LIHC patients with strongly associated PD-L1 expression and unfavorable survival probability. In the pan-cancer analysis, high expression of SLC7A11 showed poor overall survival in seven cancers, while the correlation between immune checkpoints (ICs) and SLC7A11 varied by cancer type, indicating the potential therapeutic effects of SLC7A11 in cancers other than LIHC. Western blot was further employed to verify the expression of SLC7A11 in LIHC in vitro. Conclusion: Ferroptosis and TME synergistically play key roles in oncogenesis and progression of LIHC, and SLC7A11 can be used as a predictive biomarker for customized immunotherapy.

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.

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.

Comprehensive Analysis on the Specific Role and Function of Mitochondrial Inner Membrane Protein MPV17 in Liver Hepatocellular Carcinoma.

Background Liver hepatocellular carcinoma (LIHC) is the predominant type of liver cancer, and its treatment still faces great challenges presently. Mitochondrial inner membrane protein MPV17 is reported to be involved in multiple biological activities of cancers. Here, we seek to investigate the specific role and functions of MPV17 in LIHC progression. Methods Firstly, MPV17 expressions in various tumors and corresponding normal samples and LIHC groups with various clinical features were analyzed, respectively. Next, the relationship between MPV17 expression and LIHC survival was analyzed and verified by AUC curves. Besides, differentially expressed genes (DEGs) for LIHC were screened from TCGA and then analyzed by GO and KEGG. Then, MPV17 was analyzed by prognostic model, Cox analysis, predictive nomogram, pathway correlation, and immunoassay. Finally, the functions of MPV17 were determined by CCK-8 and Tranwell assays. Results In most tumors, MPV17 expression was higher than that in the normal group, and it was related to LIHC clinical features. In the LIHC survival analysis, highly expressed MPV17 was associated with a poor prognosis. Besides, 314 upregulated and 193 downregulated DEGs are mainly involved in the TNF signaling pathway and tyrosine metabolism. Through prognostic model, Cox analysis, and predictive nomogram, MPV17 had the prognostic value for LIHC. Gene-pathway correlation analysis showed that MPV17 had the strongest correlation with the G2M_checkpoint pathway. In an immunoassay, MPV17 had a strong correlation with many immune cells. Functional assays showed that MPV17 reduction in LIHC cells could inhibit cell invasion, migration, and proliferation. Conclusion MPV17, as a tumor promoter, could be a new biomarker for LIHC diagnosis and prognosis and probably shed new light on the exploration of LIHC therapies.

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.