Value In Hepatocellular Carcinoma Patients Research Articles

The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in the past decades, the overall survival (OS) of liver cancer is still disappointing. Machine learning models have several advantages over traditional cox models in prognostic prediction. This study aimed at designing an optimal panel and constructing an optimal machine learning model in predicting prognosis for HCC. A total of 941 HCC patients with completed survival data and preoperative clinical chemistry and immunology indicators from two medical centers were included. The OCC panel was designed by univariate and multivariate cox regression analysis. Subsequently, cox model and machine-learning models were established and assessed for predicting OS and PFS in discovery cohort and internal validation cohort. The best OCC model was validated in the external validation cohort and analyzed in different subgroups. In discovery, internal and external validation cohort, C-indexes of our optimal OCC model were 0.871 (95% CI, 0.863-0.878), 0.692 (95% CI, 0.667-0.717) and 0.648 (95% CI, 0.630-0.667), respectively; the 2-year AUCs of OCC model were 0.939 (95% CI, 0.920-0.959), 0.738 (95% CI, 0.667-0.809) and 0.725 (95% CI, 0.643-0.808), respectively. For subgroup analysis of HCC patients with HBV, aged less than 65, cirrhosis or resection as first therapy, C-indexes of our optimal OCC model were 0.772 (95% CI, 0.752-0.792), 0.769 (95% CI, 0.750-0.789), 0.855 (95% CI, 0.846-0.864) and 0.760 (95% CI, 0.741-0.778), respectively. In general, the optimal OCC model based on RSF algorithm shows prognostic guidance value in HCC patients undergoing individualized treatment.

The cell death-related genes machine learning model for precise therapy and clinical drug selection in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the prevailing subtype of hepatocellular malignancy. While previous investigations have evidenced a robust link with programmed cell death (PCD) and tumorigenesis, a comprehensive inquiry targeting the relationship between multiple PCDs and HCC remains scant. Our aim was to develop a predictive model for different PCD patterns in order to investigate their impact on survival rates, prognosis and drug response rates in HCC patients. We performed functional annotation and pathway analysis on identified PCD-related genes (PCDRGs) using multiple bioinformatics tools. The prognostic value of these PCDRGs was verified through a dataset obtained from GEO. Consensus clustering analysis was utilized to elucidate the correlation between diverse PCD clusters and pertinent clinical characteristics. To comprehensively uncover the distinct PCD regulatory patterns, our analysis integrated gene expression profiling, immune cell infiltration and enrichment analysis. To predict survival differences in HCC patients, we established a PCD model. To enhance the clinical applicability for the model, we developed a highly accurate nomogram. To address the treatment of HCC, we identified several promising chemotherapeutic agents and novel targeted drugs. These drugs may be effective in treating HCC and could improve patient outcomes. To develop a cell death feature for HCC patients, we conducted an analysis of 12 different PCD mechanisms using eligible data obtained from public databases. Through this analysis, we were able to identify 1254 PCDRGs likely to contribute to cell death on HCC. Further analysis of 1254 PCDRGs identified 37 genes with prognostic value in HCC patients. These genes were then categorized into two PCD clusters A and B. The categorization was based on the expression patterns of the genes in the different clusters. Patients in PCD cluster B had better survival probabilities. This suggests that PCD mechanisms, as represented by the genes in cluster B, may have a protective effect against HCC progression. Furthermore, the expression of PCDRGs was significantly higher in PCD cluster A, indicating that this cluster may be more closely associated with PCD mechanisms. Furthermore, our observations indicate that patients exhibiting elevated tumour mutation burden (TMB) are at an augmented risk of mortality, in comparison to those displaying low TMB and low-risk statuses, who are more likely to experience prolonged survival. In addition, we have investigated the potential distinctions in the susceptibility of diverse risk cohorts towards emerging targeted therapies, designed for the treatment of HCC. Moreover, our investigation has shown that AZD2014, SB505124, LJI308 and OSI-207 show a greater efficacy in patients in the low-risk category. Conversely, for the high-risk group patients, PD173074, ZM447439 and CZC24832 exhibit a stronger response. Our findings suggest that the identification of risk groups and personalized treatment selection could lead to better clinical outcomes for patients with HCC. Furthermore, significant heterogeneity in clinical response to ICI therapy was observed among HCC patients with varying PCD expression patterns. This novel discovery underscores the prospective usefulness of these expression patterns as prognostic indicators for HCC patients and may aid in tailoring targeted treatment for those of distinct risk strata. Our investigation introduces a novel prognostic model for HCC that integrates diverse PCD expression patterns. This innovative model provides a novel approach for forecasting prognosis and assessing drug sensitivity in HCC patients, driving a more personalized and efficacious treatment paradigm, elevating clinical outcomes. Nonetheless, additional research endeavours are required to confirm the model's precision and assess its potential to inform clinical decision-making for HCC patients.

Identification of prognostic risk model based on plasma cell markers in hepatocellular carcinoma through single-cell sequencing analysis.

Hepatocellular carcinoma (HCC) represents a substantial global health burden. Tumorinfiltrating B lymphocytes (TIL-Bs) contribute to tumor progression and significantly impact the efficacy of tumor therapy. However, the characteristics of TIL-Bs in HCC and their effect on HCC therapy remain elusive. Single-cell RNA sequencing (scRNAseq) was applied to investigate the heterogeneity, cellular differentiation and cell-cell communication of TIL-Bs in HCC. Further, the Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC) and liver cancer institutes (LCI) cohorts were applied to construct and validate the plasma cell marker-based prognostic risk model. The relationship between the prognostic risk model and the responsiveness of immunotherapy and chemotherapy in patients with HCC were estimated by OncoPredict and tumor immune dysfunction and exclusion (TIDE) algorithm. Finally, we established nomogram and calibration curves to evaluate the precision of the risk score in predicating survival probability. Our data identified five subtypes of TIL-Bs in HCC, each exhibiting varying levels of infiltration in tumor tissues. The interactions between TIL-Bs and other cell types contributed to shaping distinct tumor microenvironments (TME). Moreover, we found that TIL-Bs subtypes had disparate prognostic values in HCC patients. The prognostic risk model demonstrated exceptional predictive accuracy for overall survival and exhibited varying sensitivities to immunotherapy and chemotherapy among patients with HCC. Our data demonstrated that the risk score stood as an independent prognostic predictor and the nomogram results further affirmed its strong prognostic capability. This study reveals the heterogeneity of TIL-Bs and provides a prognostic risk model based on plasma cell markers in HCC, which could prove valuable in predicting prognosis and guiding the choice of suitable therapies for patients with HCC.

High expression of ENPP2 is an independent predictor of poor prognosis in liver cancer

Ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2) has been identified as a potential biomarker in lung and prostate cancers; however, its expression and clinical relevance in hepatocellular carcinoma (HCC) remain incompletely understood. This study comprehensively assessed ENPP2 expression in pan-cancer using bioinformatics. We analyzed the expression of ENPP2 mRNA in primary liver cancer and adjacent tissues of patients with HCC using data from the TCGA database. Cox regression and Kaplan–Meier methods were used to identify clinicopathological factors associated with survival, and the diagnostic value of ENPP2 expression was evaluated using receiver operating characteristic curve analysis. We also validated our findings by performing real-time PCR on clinical liver cancer samples. Furthermore, we conducted gene set enrichment analysis using the Cancer Genome Atlas dataset to gain additional insights into the biological significance of ENPP2 in HCC. High ENPP2 expression in HCC patients is associated with gender and clinical stage, and is a significant prognostic factor for worse outcomes. ENPP2 expression is an independent risk factor for progression-free and disease-specific survival in both cohorts, suggesting its potential as an HCC biomarker. ENPP2’s diagnostic value in HCC patients was confirmed by the area under the receiver operating characteristic curve, which was 0.806. real-time PCR analysis validated the higher expression of ENPP2 in clinical liver cancer tissues. Gene set enrichment analysis identified pathways enriched in HCC patients with high ENPP2 expression, including those related to the cell cycle, MTOR and T cell receptor signaling, and phosphatidylinositol signaling systems. We have demonstrated that ENPP2 is highly expressed in HCC and is a potential independent molecular marker for the diagnosis and prognosis of HCC.

AUF1 promotes hepatocellular carcinoma progression and chemo-resistance by post-transcriptionally upregulating alpha-fetoprotein expression.

The target genes of AU-rich Element RNA-binding Protein 1 (AUF1), which is an RNA binding protein, and its role in the progression of hepatocellular carcinoma (HCC) is still elusive. This study aims to investigate the biological function and the underlying target genes of AUF1 in HCC. RNA sequencing data and the Liver Cancer Institute (LCI) database were used to screen candidate targets of AUF1. LCI database, TCGA database, and a retrospective HCC cohort were used to investigate the correlation between AUF1 and alpha-fetoprotein (AFP) and their prognostic values in HCC patients. Huh-7, HepG2, and HepAD38 cell lines were used to investigate the underlying mechanism of AUF1 regulating the AFP expression. Cell Counting Kit-8, colony formation, EdU incorporation, and flow cytometry assays were performed to detect the effect of AUF1-AFP axis on the progression and doxorubicin resistance of HCC cells. A combined analysis of the transcriptome data from Huh-7 cells after knockdown of AUF1 and gene expression data from LCI database revealed that AFP was the most significantly downregulated gene after AUF1 depletion. AUF1 expression was positively associated with AFP expression in HCC tissues and the high expression of both AUF1 and AFP were correlated with a worse prognosis in HCC patients of LCI and TCGA databases, as well as our retrospective cohort. Mechanistically, AUF1 bound to the 3' untranslation region (UTR) of AFP mRNA to enhance the mRNA stability of AFP, thereby upregulating AFP. Functional tests showed that AFP knockdown inhibited tumor growth and doxorubicin resistance of HCC cells induced by AUF1. AFP may be an important target gene of AUF1. AUF1 promoted HCC progression and doxorubicin resistance by upregulating AFP expression via increasing its mRNA stability.

Six-Transmembrane Epithelial Antigen of Prostate 4: An Indicator of Prognosis and Tumor Immunity in Hepatocellular Carcinoma.

The six-transmembrane epithelial antigen of prostate 4 (STEAP4) has been linked to tumor progression via its involvement in inflammatory responses, oxidative stress, and metabolism. However, STEAP4 has rarely been studied in hepatocellular carcinoma (HCC). We explored STEAP4 expression associated with tumor prognosis to understand its role in tumor biology in HCC. STEAP4 mRNA and protein expressions were primarily analyzed using bioinformatics tools based on The Cancer Genome Atlas database to understand the expression pattern, molecular mechanism, prognostic impact, and association with immune cell infiltration. We further investigated the association between STEAP4 protein expression and clinicopathological parameters and their predictive value in HCC patients using immunohistochemical staining of tissue microarrays. The expression of STEAP4 mRNA and protein in HCC tissues was significantly lower than in normal liver tissues. Reduced expression of STEAP4 was linked to advanced HCC stages, poor recurrence-free survival (RFS), and overall survival. Furthermore, reduced STEAP4 expression was a significant predictor of worse RFS in univariate and multivariate analyses in the immunohistochemical cohort. GO, KEGG, and GSEA analyses revealed that STEAP4 is related to numerous biological processes and pathways, including drug metabolism, DNA replication, RNA metabolism, and immune response. In terms of the immune system, the decreased level of STEAP4 was correlated with the immunosuppressive microenvironment. Our data indicated that reduced STEAP4 expression was significantly associated with tumor aggressiveness and poor prognosis, possibly because of its link to various biological processes and induction of HCC immune evasion. Therefore, STEAP4 expression may serve as a potential prognostic biomarker for cancer progression and immunity, as well as a therapeutic target in HCC.

Establishment and validation of a cuproptosis-related lncRNA signature that predicts prognosis and potential targeted therapy in hepatocellular carcinoma

ABSTRACT Background: Cuproptosis is a recently identified form of programmed cell death and could be a new direction for tumour therapy, and it has important clinical implications. Long non-coding RNAs (lncRNAs) can intervene in diverse biological processes and have a decisive role in hepatocellular carcinoma (HCC). However, how cuproptosis-related lncRNAs (CRLs) participate in regulating HCC has yet to be recognised. This study aimed to establish and validate a prognostic signature of CRLs and to analyse their clinical value in HCC patients. Methods: To analyse the function of CRLs in the prognosis of HCC, RNA sequencing data, mutation data, and clinically relevant data were collected from the Cancer Genome Atlas Database (TCGA). Then, TCGA cohort was randomly divided into training and test sets. The training set was utilized to define prognostic signature of CRLs using bioinformatics methods. Subsequently, we verified the accuracy of this prognostic signature in the test set. Finally, we performed immune-related analysis, the half-maximal inhibitory concentration (IC50) prediction, gene set enrichment analysis, and tumour mutational burden (TMB) analysis. Results: We established a prognostic signature for the CRLs (SNHG4, AC026412.3, AL590705.3, and CDKN2A-DT). This signature-based risk group displayed an accurate predictive ability for the survival time of patients with HCC. We observed discrepancies in immune cells, immune function, the expression level of genes related to immune checkpoints, and TMB in high- and low-risk groups. Conclusion: This CRLs prognostic signature could predict clinical outcomes in patients with HCC as well as the efficacy of targeted and therapy immunotherapy.

KIN17 promotes cell migration and invasion through stimulating the TGF-β/Smad2 pathway in hepatocellular carcinoma.

KIN17 DNA and RNA binding protein (Kin17) is involved in the regulation of tumorigenesis of diverse human cancers. However, its role in the cancer progression and metastasis in hepatocellular carcinoma (HCC) remains largely unknown. Bioinformatics and immunohistochemistry staining were used to investigate the expression pattern of KIN17 and its prognostic value in HCC patients. The transwell, wound-healing assay was employed to determine the effects of KIN17 on migration and invasion of HCC cells in vitro. The tail veins model was employed to determine the effects of KIN17 on lung metastasis in vivo. The biological mechanisms involved in cell migration and invasion regulated by KIN17 were determined with Western blot analysis method.KIN17 expression was significantly increased in HCC tissues compared with adjacent normal tissues, with particularly higher in portal vein tumor thrombus and intrahepatic metastasis tissues. Patients with higher KIN17 expression experienced poor overall and disease free survival. KIN17 knockdown in HuH7 and HepG2 cells significantly reduced cell migration and invasion abilities, whereas its overexpression promoted migration and invasion in MHCC-97L and HepG2 cells in vitro and in vivo. In HuH7 and HepG2 cells, KIN17 knockdown inhibited the TGF-β/Smad2 pathway. In contrast, KIN17 overexpression stimulated TGF-β/Smad2 pathway in MHCC-97L and HepG2 cells, along with the genes involved in the epithelial-mesenchymal transition.These findings suggest that KIN17 promotes migration and invasion in HCC cells by stimulating the TGF-β/Smad2 pathway. KIN17 could be a promising prognostic biomarker, as well as a potential therapeutic target in HCC.

Association between vessels that encapsulate tumour clusters vascular pattern and hepatocellular carcinoma recurrence following liver transplantation.

Vessels that encapsulate tumor clusters (VETC) is a novel vascular pattern seen on hepatocellular carcinoma (HCC) histology which has been shown to independently predict tumor recurrence and survival after liver resection. Its prognostic value in HCC patients receiving liver transplantation (LT) is unclear. We retrospectively studied consecutive adults who underwent deceased-donor LT with active HCC found on explant between 2010-2019. Tumor tissue was stained for CD34 and quantified for VETC. Primary and secondary endpoints were time to recurrence (TTR) and recurrence-free survival (RFS). During the study period, 158 patients received LT where HCC was present on explant. VETC pattern was seen in 76.5% of explants. Patients with VETC-positive tumors spent longer on the waitlist (6.4 vs. 4.1 months, P=0.048), had higher median tumor numbers (2 vs. 1, P=0.001) and larger tumor sizes (20mm vs. 13mm, P<0.001) on explant pathology compared to those with VETC-negative tumors. Correspondingly, VETC-positive patients were more likely to be outside of accepted LT criteria for HCC. After 56.4 months median follow-up, 8.2% of patients developed HCC recurrence post-LT. On multivariable Cox regression, presence of VETC pattern did not predict TTR or RFS. However, the number of VETC-positive tumors on explant was an independent predictor of TTR (hazard ratio [HR] 1.411, P=0.001) and RFS (HR 1.267, P=0.014) after adjusting for other significant variables. VETC pattern is commonly observed in HCC patients undergoing LT. The number of VETC-positive tumors, but not its presence, is an independent risk factor for TTR and RFS post-LT.

Homeobox B9 Promotes the Progression of Hepatocellular Carcinoma via TGF-β1/Smad and ERK1/2 Signaling Pathways.

Objectives Homeobox B9 (HOXB9), a homeodomain-containing transcription factor, may play a role in hepatocellular carcinoma (HCC) progression. However, the exact mechanisms underlying its action remain unclear. Materials and methods. Immunohistochemistry was used to investigate the expression of HOBX9 and its prognostic values in HCC patients. HCC cells were transfected with pBabe-HOXB9 and shHOXB9 plasmids, and MTT assay, Transwell assays, and xenograft mouse models were employed to determine the effects of HOXB9 on HCC cell proliferation, migration, and invasion in vitro and in vivo. The biological mechanisms involved in the role of HOXB9 were determined with Western blot and RT-qPCR methods. Results HOXB9 expression was significantly increased in HCC tissues and cell lines. Patients with higher HOXB9 levels were associated with poor prognosis. Overexpression of HOXB9 in BEL-7405 cells promoted proliferation, migration, and invasion, whereas knockdown of HOXB9 in HepG2 cells significantly reduced cell proliferation, migration, and invasion abilities. Mechanically, a positive correlation was found between HOXB9 expression and transforming growth factor-β1 (TGF-β1) and extracellular signal-regulated kinase (ERK)1/2 pathway in HCC tissues. HOXB9 overexpression stimulated TGF-β1/Smads signaling pathway in BEL-7405 cells. In contrast, HOXB9 knockdown inhibited the TGF-β1/Smads signaling pathway in HepG2 cells. In addition, the treatment with TGF-β1 inhibitor, LY364947, significantly reserved HOXB9 overexpression-induced cell proliferation, migration, and invasion abilities. Conclusions These findings validated that HOXB9 promoted proliferation, migration, and invasion in HCC cells by stimulating the TGF-β1/Smads and ERK1/2 signaling pathway. HOXB9 could be a promising prognostic biomarker and a potential therapeutic target in HCC.

Bioinformatics analysis and experimental verification of the prognostic and biological significance mediated by fatty acid metabolism related genes for hepatocellular carcinoma.

BackgroundLiver cancer is among the leading causes of death related to cancer around the world. The most frequent type of human liver cancer is hepatocellular carcinoma (HCC). Fatty acid (FA) metabolism is an emerging hallmark that plays a promoting role in numerous malignancies. This study aimed to discover a FA metabolism-related risk signature and formulate a better model for HCC patients’ prognosis prediction.MethodsWe collected mRNA expression data and clinical parameters of patients with HCC using the TCGA databases, and the differential FA metabolism-related genes were explored. To create a risk prognostic model, we carried out the consensus clustering as well as univariate and multivariate Cox regression analyses. 16 genes were used to establish a prognostic model, which was then validated in the ICGC dataset. The accuracy of the model was performed using receiver operating characteristic (ROC) analyses, decision curve analysis (DCA) and nomogram. The immune cell infiltration level of risk genes was evaluated with single-sample GSEA (ssGSEA) algorithm. To reflect the response to immunotherapy, immunophenoscore (IPS) was obtained from TCGA-LIHC. Then, the expression of the candidate risk genes (p < 0.05) was validated by qRT-PCR, Western blotting and single-cell transcriptomics. Cellular function assays were performed to revealed the biological function of HAVCR1.ResultsAccording to the TCGA-LIHC cohort analysis, the majority of the FA metabolism-related genes were expressed differentially in the HCC and normal tissues. The prognosis of patients with high-risk scores was observed to be worse. Multivariate COX regression analysis confirmed that the model can be employed as an independent prognosis factor for HCC patients. Furthermore, ssGSEA analysis revealed a link between the model and the levels of immune cell infiltration. Our model scoring mechanism also provides a high predictive value in HCC patients receiving anti-PDL1 immunotherapy. One of the FA metabolism-related genes, HAVCR1, displays a significant differential expression between normal and HCC cell lines. Hepatocellular carcinoma cells (Huh7, and HepG2) proliferation, motility, and invasion were all remarkably inhibited by HAVCR1 siRNA.ConclusionOur study identified a novel FA metabolism-related prognostic model, revealing a better potential treatment and prevention strategy for HCC.

Association of a Novel DOCK2 Mutation-Related Gene Signature With Immune in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality worldwide. Many studies have shown that dedicator of cytokinesis 2 (DOCK2) has a crucial role as a prognostic factor in various cancers. However, the potentiality of DOCK2 in the diagnosis of HCC has not been fully elucidated. In this work, we aimed to investigate the prognostic role of DOCK2 mutation in HCC. The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) cohorts were utilized to identify the mutation frequency of DOCK2. Then, univariate Cox proportional hazard regression analysis, random forest (RF), and multivariate Cox regression analysis were performed to develop the risk score that was significantly related to DOCK2 mutation. Moreover, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune correlation analysis were conducted for an in-depth study of the biological process of DOCK2 mutation involved in HCC. The results revealed that the mutation frequency of DOCK2 was relatively higher than that in non-cancer control subjects, and patients with DOCK2 mutations had a low survival rate and a poor prognosis compared with the DOCK2-wild group. In addition, the secretin receptor (SCTR), tetratricopeptide repeat, ankyrin repeat and coiled-coil domain-containing 1 (TANC1), Alkb homolog 7 (ALKBH7), FRAS1-related extracellular matrix 2 (FREM2), and G protein subunit gamma 4 (GNG4) were found to be the most relevant prognostic genes of DOCK2 mutation, and the risk score based on the five genes played an excellent role in predicting the status of survival, tumor mutation burden (TMB), and microsatellite instability (MSI) in DOCK2 mutant patients. In addition, DOCK2 mutation and the risk score were closely related to immune responses. In conclusion, the present study identifies a novel prognostic signature in light of DOCK2 mutation-related genes that shows great prognostic value in HCC patients; and this gene mutation might promote tumor progression by influencing immune responses. These data may provide valuable insights for future investigations into personalized forecasting methods and also shed light on stratified precision oncology treatment.

The Prognostic Value of Lysine Acetylation Regulators in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and mortality worldwide. lysine acetylation regulators (LARs) dynamically regulate Lysine acetylation modification which plays an important regulatory role in cancer. Therefore, we aimed to explore the potential clinical prognostic value of LARs in HCC. Methods: Differentially expressed LARs in normal liver and HCC tissues were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. To identify genes with prognostic value and establish the risk characteristics of LARs, consensus clustering was employed. We used univariate Cox regression survival analysis and LASSO Cox regression based on LARs to determine the independent prognostic signature of HCC. CIBERSORT and Gene Set Enrichment Analysis (GSEA) were used to estimate immune infiltration and functional enrichment analysis respectively. The expression of LAR was detected by Real-time quantitative polymerase chain reaction (RT-qPCR). statistical analyses were conducted using SPSS and R software. Results: In this study, the 33 LARs expression data and corresponding clinical information of HCC were obtained using TCGA and ICGC datasets. We found majority of the LARs were differentially expressed. Consensus cluster analysis was carried out based on the TCGA cohort, and three HCC subtypes (cluster 1, 2, and 3) were obtained. The LA3 subgroup had the worst clinical outcomes. Nine key LARs were identified to affect prognosis. The results showed that LARs signature has a strong independent prognostic value in HCC patients, whether in the training datasets or in the testing datasets. GSEA results showed that various tumor-related processes and pathways were abundant in the high-risk groups. RT-qPCR results showed that HAT1, HDAC1, HDAC2, HDAC4, and HDAC11 were highly expressed in HCC cells. Conclusion: Our results suggest that LARs play critical roles in HCC and are helpful for individual prognosis monitoring and clinical decision-making of HCC.

Prognostic biomarker SMARCC1 and its association with immune infiltrates in hepatocellular carcinoma

BackgroundEpigenetic alterations contribute greatly to metastasis and dissemination in hepatocellular carcinoma (HCC). SMARCC1, as a SWI/SNF chromatin remodeling factor, has been reported to play important roles in many cancers. For the first time, with the bioinformatics analysis and wet-bench experiments, we explored the biological significance of SMARCC1 and its potential as putative therapeutic target in HCC.MethodsThe mRNA expression profiles and prognostic value of SMARCC1 were analyzed in the Oncomine, UALCAN and Kaplan–Meier Plotter databases. The expression of SMARCC1 and associated clinicopathological factors were further evaluated using a tissue microarray. Differentially expressed genes associated with SMARCC1 in HCC were obtained and analyzed via the LinkedOmics and GEPIA databases and Cytoscape software. To verify the important role of SMARCC1 in HCC, we knocked down and overexpressed SMARCC1 in different hepatic cell lines and conducted several functional experiments. Then, we evaluated the mutation profiles and transcriptional regulators of SMARCC1 using the cBioPortal, COSMIC, CistromeDB and TCGA databases. Finally, we addressed the relationship of SMARCC1 expression with immune cell infiltration via TIMER database analysis.ResultsThrough data mining and tissue microarray verification, we found that the protein and mRNA levels of SMARCC1 are high in tumor tissues, which has remarkable diagnostic value in HCC patients. SMARCC1 and its hub genes showed prognostic value in HCC. Furthermore, we confirmed that SMARCC1 influenced the proliferation, migration, and invasion of HCC cells. Moreover, correlation analyses revealed that SMARCC1 expression was positively correlated with ZBTB40 transcription factors and negatively correlated with the DNA methylation level. Overall, we found that SMARCC1 affects immune infiltration and plays a tumor-promoting role in HCC.ConclusionsSMARCC1 is overexpressed and is a putative prognostic predictor in HCC. Due to the tumor-promoting role of SMARCC1, treatments inhibiting DNA methyltransferases and transcription factors or weakening the role of SMARCC1 in immune infiltration might improve the survival of HCC patients.

Cyclin E1 in Murine and Human Liver Cancer: A Promising Target for Therapeutic Intervention during Tumour Progression

Simple SummaryThe cell cycle regulator Cyclin E1 is a key mediator and biomarker of liver cancer progression in mice and man independent of its canonical interacting partner Cyclin-dependent kinase 2. Over-expression of Cyclin E1 during hepatocarcinogenesis modulates several distinct biological processes such as proliferation, DNA damage response, stemness, invasion and the tumour microenvironment. Interventional depletion of Cyclin E1 in the course of liver cancer progression significantly reduces tumour burden. In contrast, the expression of Cyclin-dependent kinase 2 is dispensable for the progression of liver cancer in mice and lacked diagnostic or prognostic value in patients. Thus, specific inhibition of Cyclin E1 expression represents a promising strategy for the treatment of liver cancer.Cyclin E1 (CCNE1) is a regulatory subunit of Cyclin-dependent kinase 2 (CDK2) and is thought to control the transition of quiescent cells into cell cycle progression. Recently, we identified CCNE1 and CDK2 as key factors for the initiation of hepatocellular carcinoma (HCC). In the present study, we dissected the contributions of CCNE1 and CDK2 for HCC progression in mice and patients. Therefore, we generated genetically modified mice allowing inducible deletion of Ccne1 or Cdk2. After initiation of HCC, using the hepatocarcinogen diethylnitrosamine (DEN), we deleted Ccne1 or Cdk2 and subsequently analysed HCC progression. The relevance of CCNE1 or CDK2 for human HCC progression was investigated by in silico database analysis. Interventional deletion of Ccne1, but not of Cdk2, substantially reduced the HCC burden in mice. Ccne1-deficient HCCs were characterised by attenuated proliferation, impaired DNA damage response and downregulation of markers for stemness and microinvasion. Additionally, the tumour microenvironment of Ccne1-deficient mice showed a reduction in immune mediators, myeloid cells and cancer-associated fibroblasts. In sharp contrast, Cdk2 was dispensable for HCC progression in mice. In agreement with our mouse data, CCNE1 was overexpressed in HCC patients independent of risk factors, and associated with reduced disease-free survival, a common signature for enhanced chromosomal instability, proliferation, dedifferentiation and invasion. However, CDK2 lacked diagnostic or prognostic value in HCC patients. In summary, CCNE1 drives HCC progression in a CDK2-independent manner in mice and man. Therefore, interventional inactivation of CCNE1 represents a promising strategy the treatment of liver cancer.

Identification and validation of a novel immune-related signature associated with macrophages and CD8 T cell infiltration predicting overall survival for hepatocellular carcinoma

BackgroundAlthough the effects of macrophages and CD8 T cell infiltration on clinical outcome have been widely reported, the association between immunity-associated gene with them for hepatocellular carcinoma (HCC) remains unclear.Materials and methodsThe ssGSEA served for quantifying the macrophages as well as CD8 T cell infiltration in the HCC samples obtained from TCGA database. Kaplan–Meier (KM) survival assay was used to determine the associations between macrophages and CD8 T cell infiltration with OS. LASSO Cox regressive method assisted in developing an immune gene signature as well as building a risk score. The performance was evaluated by the time-dependent ROC together with the KM survival analysis. The ICGC database were adopted for external verification. CIBERSORT was applied to the correlation analysis on the immune-related signature and the immunocyte infiltration. GSEA were employed exploring the underlying molecular mechanisms.ResultsIncreased CD8+ T cell infiltration was associated with longer OS, whereas a greater infiltration of macrophages was related to shorter OS. There were 398 differential expression genes (DEGs) between the high- and low infiltration groups with the “edgeR” package. An prognostic signature consisted of 10 immune genes was built in TCGA and examined in ICGC. The uniform cutoff (0.927) was adopted for separating sufferers into the high-risk (HR) and low-risk (LR) groups. The ROC curves revealed that the AUC data for this signature predicting 1, 2, 3, 4 and 5 year were all above 0.7 in both TCGA and ICGC cohort and patients in the HR group exhibited an evidently weaker prognostic results compared with the LR group. The HR group presented evidently greater Tregs and Macrophage M0 relative to the LR group, whereas the LR group saw the enrichment of CD8 T cells.ConclusionThe immune signature associated with macrophages as well as CD8 T cell infiltration has reliable prognostic and predictive value for HCC patients.

MiR-424 Acts as a Novel Biomarker in the Diagnosis of Patients with Hepatocellular Carcinoma

Objective: MicroRNA-424 (MiR-424) is proved to be a tumor suppressor against many malignancies, including hepatocellular carcinoma (HCC). Nevertheless, its role in diagnosing HCC remained poorly understood. The authors' research investigated diagnostic value of serum miR-424 in HCC. Materials and Methods: Relative expression levels of serum miR-424 in HCC patients and healthy individuals were measured via quantitative real-time polymerase chain reaction. χ2 test was applied to analyze the correlation between miR-424 expression and clinical features of HCC cases. Diagnostic value was estimated via plotting a receiver operating characteristic (ROC) curve. Results: Serum miR-424 expression was obviously downregulated in HCC cases in comparison to healthy persons (p < 0.001). miR-424 expression presented strong correlation with tumor node metastasis stage (p = 0.022), Barcelona Clinic Liver Cancer stage (p < 0.001), metastasis (p = 0.037), and vein invasion (p = 0.033). ROC curve analysis manifested an area under the curve of 0.768 with a sensitivity of 75.0% and a specificity of 72.4%, suggesting that serum miR-424 had high diagnostic value in HCC patients. Conclusions: The data suggest that serum miR-424 may represent a biomarker in early detection of HCC.

Abstract No. 152 Aspartate aminotransferase-lymphocyte ratio: utility in hepatocellular carcinoma patients undergoing radioembolization

The aspartate aminotransferase-lymphocyte ratio (ALRI) has been found to be a general predictor of outcomes in patients with Hepatocellular Carcinoma (HCC). However, data on its utility in those undergoing radioembolization is lacking. The purpose of this study was to evaluate the usefulness of ALRI in the prediction of radiologic response and overall survival (OS) following radioembolization for hepatocellular carcinoma (HCC). A total of 159 patients who underwent radioembolization for the treatment of HCC were reviewed. The patient’s electronic medical records were evaluated for pre and post procedural laboratory values as well as radiologic response according to the European Association for the Study of the Liver (EASL) criteria. Overall radiologic response (ORR) was defined as those who showed a partial or complete response. Survival was measured from the initial radioembolization to time of death and patients were censored for transplant. Patients were separated into cohorts utilizing an ALRI of 100. The average pretreatment ALRI was 99.9 ± 195.3. When comparing those who had an ORR to those who did not the ALRI was not significantly different (93.2 ± 215.7 vs 111.2 ± 156.3, P = 0.28). When looking at those with an ALRI< 100 and ≥100 there was no significant difference in the OS (1.04 ± 0.99 vs 0.85 ± 0.7 years, P = 0.17). The percentage of patients with ALRI < 100 who had an ORR was 83.7% (77/92) and with those >100 it was 71.9% (23/32) (P = 0.14). Of those patients with both pre and post TACE ALRI values, those that demonstrated a decrease in ALRI did not differ in OS from those who did not have an increase in ALRI (1.02 ± 0.99 vs 1.13 ± 0.64 years, P = 0.39). Similarly, there was no significant difference in the ORR in those who did (68/86, 79.1%) and those who did not (18/22, 81.8%) have an increase in their ALRI following treatment (P = 0.77). ALRI does not appear to have predictive value in HCC patients undergoing treatment with radioembolization, an interesting finding as it departs from its value in patients being treated with other locoregional therapies for the same disease.

TANK-Binding Kinase 1 (TBK1) Serves as a Potential Target for Hepatocellular Carcinoma by Enhancing Tumor Immune Infiltration.

BackgroundNumerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear.MethodsThe expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated via analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist.ResultsThe level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, P=0.038; Kaplan–Meier plotter: HR=1.87, P<0.001; CPTAC: HR=2.23, P=0.007; Our cohort: HR=2.92, P=0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8+ T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. In vivo experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells.ConclusionsThe up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC.

Prognostic implications of cell division cycle protein 45 expression in hepatocellular carcinoma.

BackgroundThe overall prognosis of hepatocellular carcinoma (HCC) is poor and novel prognostic biomarkers might better monitor the progression of HCC. Cell division cycle protein 45 (CDC45) plays a key role in DNA replication and considered to be involved in tumorigenesis. This study investigated CDC45 expression in tumour tissues and defined its prognostic value in HCC patients.MethodsWe used immunohistochemistry (IHC) staining to examine the expression of CDC45 in tumour tissue specimens and compare them with adjacent normal tissue specimens using a constructed tissue microarray (TMA) and analyzed how clinical features are related to HCC prognosis. Functional enrichment analyses were used to describe significantly involved hallmark pathways of differentially expressed genes (DEGs, which were screened out according to the high or low expression of CDC45 in tumour tissues).ResultsOur findings showed that the proteome expression of CDC45 was evidently downregulated in HCC tissues compared with matched normal tissues (P < 0.0001). Although we did not find any differences in terms of vascular invasion, metastasis, lymphatic infiltration, or Edmondson grade between patients with high and low CDC45 expression, low CDC45 expression was significantly correlated with microvascular invasion (P = 0.046). Multivariate analysis indicated that CDC45 expression (P = 0.035) was an independent prognostic factor for the overall survival (OS) rate of HCC patients. Patients with CDC45 expression was positively correlated with OS rates among HCC patients (P < 0.05). Functional annotations indicated that CDC45 is involved in the most significant pathways, including the cell cycle, DNA replication, chemical carcinogenesis and drug metabolism–cytochrome P450 pathways.DiscussionOur findings showed that low proteomic level of CDC45 was associated with a poor prognosis in HCC patients, indicating that CDC45 might be a novel prognostic marker.