Progression To Liver Hepatocellular Carcinoma Research Articles

Role of CALCR expression in liver cancer: Implications for the immunotherapy response.

Liver hepatocellular carcinoma (LIHC) is a prevalent and lethal malignancy with a complex molecular landscape. Fibrosis and ferroptosis are implicated in LIHC progression, yet their roles remain to be elucidated. The present study investigated the expression and prognostic significance of calcitonin receptor (CALCR), a gene that intersects the pathways of fibrosis and ferroptosis, across LIHC and other types of cancer. Data were obtained from The Cancer Genome Atlas and the Molecular Signatures Database. LIHC patients were classified into two clusters based on fibrosis‑related gene expression using ConsensusClusterPlus. Single‑sample gene set enrichment analysis was employed to quantify fibrosis and ferroptosis levels. Correlation, survival and nomogram analyses were performed to assess the prognostic value of CALCR. Additionally, single‑cell RNA sequencing data from the Tumor Immune Single Cell Hub 2 (TISCH2) and pan‑cancer analyses of genomic heterogeneity features were incorporated. The present study also identified a putative regulatory role for CALCR in LIHC cell migration, proliferation and apoptosis. CALCR was identified as a significant prognostic marker for LIHC. Patients with high CALCR expression exhibited shortened overall survival (OS) and disease‑specific survival (DSS). Specifically, the hazard ratios (HRs) for OS and DSS were 1.76 [95% confidence interval (CI): 1.23=2.49) and 1.77 (95% CI: 1.13=2.78], respectively, with corresponding P‑values of 0.002 for OS and 0.013 for DSS. Analyses of immune cell infiltration revealed a more complex immune environment in patients with low CALCR expression, suggesting differential responses to immunotherapy. Furthermore, in HepG‑2 and HuH‑7 cells, small interfering (si)‑CALCR increased apoptosis while reducing proliferation and migration compared with si‑negative control. CALCR serves as a significant prognostic biomarker for LIHC, influencing both molecular pathways and the immune landscape. Its expression is associated with improved survival outcomes and distinct genomic features, positioning it as a potential therapeutic target and predictor of immunotherapy efficacy.

The impact of cathepsins on liver hepatocellular carcinoma: Insights from genetic and functional analyses

Liver Hepatocellular Carcinoma (LIHC), ranked as the second deadliest cancer globally, poses a major health challenge because of its widespread occurrence and poor prognosis. The mechanisms underlying LIHC development and progression remain unclear. Cathepsins are linked to tumorigenesis in other cancers, but their role in LIHC is underexplored. This study employed integrative analyses, including Mendelian Randomization (MR), bulk RNA-sequencing (bulk-seq), single-cell RNA sequencing (scRNA-seq), immunohistochemical (IHC) analysis, and cellular experiments with siRNA technology, to investigate the role of cathepsin E (CTSE) in LIHC. MR analysis identified CTSE as a factor associated with increased LIHC risk. Prognostic analysis using TCGA data showed that higher CTSE levels are linked to poorer survival, establishing CTSE as an independent prognostic risk factor. Integrative transcriptome analysis revealed close relation of CTSE to the extracellular matrix. scRNA-seq from TISCH2 demonstrated that CTSE is predominantly expressed in malignant LIHC cells. IHC confirmed higher CTSE expression in LIHC tissues compared to peritumoral tissues. Functional assays, such as qRT-PCR, Western blot, cell proliferation, and colony formation experiments, demonstrated that siRNA-mediated CTSE knockdown in HepG2 and Huh7 cell lines notably suppressed cell proliferation and altered the FAK/Paxillin/Akt signaling cascade. This research enhances our comprehension of LIHC development, emphasizing CTSE as a promising prognostic marker and potential therapeutic target. Inhibiting CTSE could slow the progression of LIHC, presenting novel opportunities for therapeutic approaches.

Optimizing Prognostic Predictions in Liver Cancer with Machine Learning and Survival Analysis.

This study harnesses RNA sequencing data from the Cancer Genome Atlas to unearth pivotal genetic markers linked to the progression of liver hepatocellular carcinoma (LIHC), a major contributor to cancer-related deaths worldwide, characterized by a dire prognosis and limited treatment avenues. We employ advanced feature selection techniques, including sure independence screening (SIS) combined with the least absolute shrinkage and selection operator (Lasso), smoothly clipped absolute deviation (SCAD), information gain (IG), and permutation variable importance (VIMP) methods, to effectively navigate the challenges posed by ultra-high-dimensional data. Through these methods, we identify critical genes like MED8 as significant markers for LIHC. These markers are further analyzed using advanced survival analysis models, including the Cox proportional hazards model, survival tree, and random survival forests. Our findings reveal that SIS-Lasso demonstrates strong predictive accuracy, particularly in combination with the Cox proportional hazards model. However, when coupled with the random survival forests method, the SIS-VIMP approach achieves the highest overall performance. This comprehensive approach not only enhances the prediction of LIHC outcomes but also provides valuable insights into the genetic mechanisms underlying the disease, thereby paving the way for personalized treatment strategies and advancing the field of cancer genomics.

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

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.

Comprehensive Analysis of the Prognostic Implications and Biological Function of HDACs in Liver Hepatocellular Carcinoma.

Background: The prognostic significance and biological functions of the histone deacetylases (HDACs) gene family in liver hepatocellular carcinoma (LIHC) have not been fully investigated. Methods: Using Kaplan-Meier and Cox regression analysis, this study determined if HDAC genes were relevant for prognosis in LIHC. A regression model utilizing HDAC genes and the least absolute shrinkage and selection operator (LASSO) was created to foretell LIHC risk. A selective inhibitor of endogenous HDACs, CKD-581, was studied in vitro and in vivo to determine its effects on the development, invasion, migration, and proliferation of LIHC cell lines. Results: Six HDACs were identified as correlating with the prognosis of LIHC. Overall survival (OS) was found to be shorter in individuals with higher risk scores when compared to those with lower risk scores, according to survival study. Natural killer cell infiltration was higher in individuals with lower risk ratings, which was mainly explained by the type II interferon (IFN) response. Limiting the activity of endogenous HDACs caused LIHC cell death by preventing their migration, invasion, and proliferation. In vivo studies confirmed that blocking HDAC expression inhibited tumor growth in mice. Further mechanistic studies showed that inhibition of HDACs expression elevates the protein levels of P21 and P27, and reduces those of cyclins A2, B1, D1 and E1. Conclusions: The risk score prognostic model based on HDAC genes could provide a valuable prognostic biomarker for LIHC. CKD-581 prohibits LIHC progression via inhibiting the cell cycle signaling pathway. CKD-581 holds promise as a therapeutic agent for the clinical management of LIHC.

PPIH as a poor prognostic factor increases cell proliferation and m6A RNA methylation in hepatocellular carcinoma.

RNA-binding proteins (RBPs) play a crucial role in the biological processes of liver hepatocellular carcinoma (LIHC). Peptidyl-prolyl cis-trans isomerase H (PPIH), an RBP, possesses prolyl isomerase activity and functions as a protein chaperone. The relationship between PPIH and LIHC has not yet been fully elucidated. This study elucidated potential mechanisms through which PPIH affects the prognosis of LIHC. Bioinformatics analysis and in vitro experiments revealed that PPIH expression was higher in LIHC tissues than in normal tissues. PPIH was identified as an independent prognostic factor, with high PPIH expression being associated with worse prognoses. Moreover, PPIH increased the m6A RNA methylation level and promoted cell proliferation by modulating DNA replication and the expression of cell cycle-related genes in LIHC cells. Bioinformatics analysis also revealed that PPIH expression increased immune cell infiltration and the expression of immune checkpoint proteins. Collectively, these findings indicate that PPIH might promote LIHC progression by enhancing the m6A RNA methylation level, increasing cell proliferation, and altering the tumor immune microenvironment. Our study demonstrates that PPIH, as a poor prognostic factor, may lead to LIHC malignancy through multiple pathways. Further in-depth research on this topic is warranted.

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.