Prognostic Biomarker For Hepatocellular Carcinoma Research Articles

Hepatocellular carcinoma risk-stratification based on ASGR1 in circulating epithelial cells for cancer interception.

Purpose: Lack of diagnostic and prognostic biomarkers in hepatocellular carcinoma impedes stratifying patients based on their risk of developing cancer. The aim of this study was to evaluate phenotypic and genetic heterogeneity of circulating epithelial cells (CECs) based on asialoglycoprotein receptor 1 (ASGR1) and miR-122-5p expression as potential diagnostic and prognostic tools in patients with hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Methods: Peripheral blood samples were extracted from LC and HCC patients at different disease stages. CECs were isolated using positive immunomagnetic selection. Genetic and phenotypic characterization was validated by double immunocytochemistry for cytokeratin (CK) and ASGR1 or by in situ hybridization with miR-122-5p and CECs were visualized by confocal microscopy. Results: The presence of CECs increased HCC risk by 2.58-fold, however, this was only significant for patients with previous LC (p = 0.028) and not for those without prior LC (p = 0.23). Furthermore, the number of CECs lacking ASGR1 expression correlated significantly with HCC incidence and absence of miR-122-5p expression (p = 0.014; r = 0.23). Finally, overall survival was significantly greater for patients at earlier cancer stages (p = 0.018), but this difference was only maintained in the group with the presence of CECs (p = 0.021) whereas progression-free survival was influenced by the absence of ASGR1 expression. Conclusion: Identification and characterization of CECs by ASGR1 and/or miR-122-5p expression may be used as a risk-stratification tool in LC patients, as it was shown to be an independent prognostic and risk-stratification marker in LC and early disease stage HCC patients.

PVR-A Prognostic Biomarker Correlated with Immune Cell Infiltration in Hepatocellular Carcinoma.

The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.

P14.5 functions to inhibit cell migration and can be used as a prognostic marker in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with a high mortality rate. P14.5 is a member of the highly conserved YER057c/YIL051c/YjgF subfamily and is highly expressed in the liver. However, its low expression is associated with carcinogenesis in HCC. This study aimed to investigate the role and prognostic significance of P14.5 in HCC. The clinical significance of P14.5 in HCC was examined using ONCOMINE, UALCAN, Human Protein Atlas, and Kaplan-Meier plotter. The DNA methylation profile of the P14.5 promoter was examined in 103 HCC and paired precancerous tissues; the HCC cell lines HepG2, MHCC-97L, SMMC-7721, SK-Hep-1, and Huh7; and the normal hepatic cell line HL-7702 via MALDI-TOF mass spectrometry. In addition, in vitro experiments were performed to examine the effects of P14.5 overexpression on the proliferation and migration of SMMC-7721 cells. Low expression of P14.5 was correlated with shorter overall survival (OS) and disease-free survival (DFS) in HCC. Based on the results of MALDI-TOF mass spectrometry, no difference was observed in the methylation level between HCC cells and normal human hepatic cells and between HCC and paired precancerous tissues. Additionally, P14.5overexpression promoted the proliferation and inhibited the migration of SMMC7721 cells in vitro. P14.5 may serve as a prognostic biomarker in HCC and plays a role in the migration and proliferation of HCC cells. Low expression of P14.5 during hepatocarcinogenesis is not attributed to DNA methylation.

Circulating tumor cells as a prognostic biomarker in patients with hepatocellular carcinoma

Circulating tumor cells (CTCs) have been shown as a surrogate for cancer progression and prognostication. We aimed to determine an association between CTCs and survival of hepatocellular carcinoma (HCC) patients. Peripheral blood was obtained from 73 HCC patients to enumerate for epithelial CTCs/8 mL blood. CTCs were detected by immunoaffinity-based method using epithelial cell adhesion molecule (EpCAM) and mucin1 (MUC1). The CTCs detection rates of BCLC stages A, B, and C patients were 65.4% (17/26), 77.3% (17/22), and 96% (24/25), respectively, p = 0.018. Patients with CTCs < 5 cells/8 mL had significantly longer survival than those with CTCs ≥ 5 cells/8 mL (>36 vs. 4.6 months, p < 0.001). In multivariate analysis, CTP B, BCLC B, BCLC C, AFP ≥ 400 ng/mL, and CTC ≥ 5 cells/8 mL were independently associated with survival, with adjusted HRs (95%CI) of 4.1 (2.0–8.4), 3.5 (1.1–11.4), 4.7 (1.4–15.4), 2.4 (1.1–5.0), and 2.6 (1.2–8.4); p < 0.001, 0.036, 0.011, 0.025 and 0.012, respectively. The combination of CTCs ≥ 5 cells/8 mL and AFP ≥ 400 ng/mL provided additively increased HR to 5.3 (2.5–11.1), compared to HRs of 4.0 (2.0–8.0) and 3.5 (1.8–6.7) for CTCs ≥ 5 cells/8 mL and AFP ≥ 400 ng/mL, p < 0.001, respectively. The larger number of peripheral CTCs is correlated with higher tumor aggressive features and poorer survival of HCC patients. CTCs can potentially become novel prognostic biomarker in HCC.

Comprehensive analysis of ESR1-related ceRNA axis as a novel prognostic biomarker in hepatocellular carcinoma.

Aims: To further understand, detect and treat hepatocellular carcinoma (HCC), it is urgent to conduct more in-depth research on the mechanism of sex-associated differences. Materials & methods: We established a ceRNA triple regulatory axis associated with ESR1 in HCC and performed expression, survival and nuclear-cytoplasmic localization analyses. In addition to this, we performed methylation analysis and immune infiltration analysis of the ceRNA axis. Results: We constructed the LINC01018/hsa-miR-197-3p/GNA14 (lncRNA/miRNA/mRNA) ceRNA axis to further explain the mechanism of sex-related prognosis in the development of HCC and to provide new insights into candidate biomarkers for targeted therapies. Conclusion: Our study is an innovative attempt at demonstrating the mechanism underlying the prognosis associated with sex differences in HCC by constructing a ceRNA axis (LINC01018/hsa-miR-197-3p/GNA14).

LPCAT1 acts as an independent prognostic biomarker correlated with immune infiltration in hepatocellular carcinoma

BackgroundLysophosphatidylcholine acyltransferase 1 (LPCAT1) is overexpressed in multiple human tumors. However, the role of LPCAT1 in hepatocellular carcinoma (HCC) has not been understood. We aim to explore the relationships between LPCAT1 expression and prognosis, clinicopathological features, tumor microenvironment (TME), immune cell infiltration, immune checkpoint gene expression, and related signaling pathways in HCC. Furthermore, we also explored the relationship between LPCAT1 expression and drug sensitivity to HCC treatment.MethodsThe expression profiles were acquired from the Cancer Genome Atlas (TCGA) and the Human Protein Atlas (THPA). Immune status and infiltration in cancer tissues were explored using the single sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm.ResultsLPCAT1 was overexpressed in HCC, and its expression was related to poor prognosis, LPCAT1 was an independent prognostic biomarker in HCC. Expression of LPCAT1 increased statistically with the increase of clinical stage and grade of HCC patients. GO and KEGG network analysis revealed that LPCAT1 positively associated molecules were mostly enriched in functions related to cell adhesion. The TME score of high-LPCAT1 group was significantly higher than that of low-LPCAT1 group. Immune infiltrating cells positively correlated with LPCAT1 expression were Macrophages M0, B cells memory, Dendritic cells activated, T cells regulatory and T cells gamma delta in HCC. We found a positive correlation between LPCAT1 and most immune checkpoint gene expression. The IC50 of 5-Fluorouracil, Gemcitabine, Mitomycin C, Sorafenib and Cabozantinib in patients with high-LPCAT1 expression was lower than that in patients with low-LPCAT1 expression. Our findings provide a wealth of information for further understanding of the biological functions and signaling pathways of LPCAT1 in HCC.ConclusionsLPCAT1 is an independent prognostic biomarker and associated with tumor microenvironment, immune cell infiltration, immune checkpoint expression and drug sensitivity in hepatocellular carcinoma.

Exploring novel independent prognostic biomarkers for hepatocellular carcinoma based on TCGA and GEO databases.

Hepatocellular carcinoma (HCC) has become the fifth most common cancer globally, with the second-highest mortality rate and poor survival outcomes. In our research, we aimed to use The Cancer Genome Atlas and gene expression omnibus databases to identify potential genetic biomarkers to predict and improve the survival rate of HCC patients. In GSE60502, GSE76427, and GSE84402, we performed differential expression analysis to obtain differentially expressed genes (DEGs). In the The Cancer Genome Atlas database, the FPKM expression profile was subjected to weighted gene co-expression analysis to obtain modules closely related to HCC. We received common genes by intersecting the genes in the module with the differential genes. Then, we fused the common genes' expression profiles, survival time, and survival status for univariate, Least Absolute Shrinkage and Selection Operator, and multivariate COX regression analysis to obtain prognostic genes. Predictive genes were performed in K-M survival analysis and combined with clinical data for independent predictive analysis. After differential expression analysis, GSE60502 obtained 1107 DEGs, GSE76427 obtained 424 DEGs, and GSE84402 obtained 1668 DEGs. Through weighted gene co-expression analysis analysis, we can see that the blue and brown modules were closely associated with HCC. After single and multivariate COX regression analysis, we found that suppressor of cytokine signaling 2 (SOCS2) and SERPINF2 were independent prognostic genes for HCC. After survival analysis, HCC patients with high expression of SOCS2 and SERPINF2 had a longer survival time. These 2 genes in normal liver tissues were higher than in HCC at the transcriptional level. SOCS2 and SERPINF2 were new independent prognostic genes of HCC. So, they may provide new treatment methods and measures for diagnosing HCC.

Liver-specific lncRNA FAM99A may be a tumor suppressor and promising prognostic biomarker in hepatocellular carcinoma

BackgroundIncreasing evidence shows that liver-specific long non-coding RNAs (lncRNAs) play important roles in the development of hepatocellular carcinoma (HCC). We identified a novel liver-specific lncRNA, FAM99A, and examined its clinical significance and biological functions in HCC.MethodsThe expression level and clinical value of FAM99A in HCC were examined using The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases, and were further verified using quantitative real-time polymerase chain reaction (qRT–PCR) in our HCC cohort. Univariate and multivariate Cox proportional hazards regression models were also applied to identify independent prognostic indicators for HCC patients. Cell counting kit-8, colony formation, and Transwell assays were performed to evaluate the effects of FAM99A on the proliferation, migration, and invasion abilities of HCC cells in vitro. A subcutaneous xenograft tumor model was implemented to determine the effect of FAM99A on the tumor growth of HCC cells in vivo. RNA pull-down and mass spectrometry assays were performed to reveal the potential molecular mechanisms of FAM99A in HCC.ResultsThe three public online databases and qRT–PCR data showed that FAM99A was frequently downregulated in HCC tissues and inversely correlated with microvascular invasion and advanced histological grade of HCC patients. Kaplan–Meier survival analysis indicated that decreased FAM99A was significantly associated with poor overall survival of HCC patients based on TCGA database (P = 0.040), ICGC data portal (P < 0.001), and our HCC cohort (P = 0.010). A multivariate Cox proportional hazards regression model based on our HCC cohort suggested that FAM99A was an independent prognostic factor of overall survival for HCC patients (hazard ratio: 0.425, P = 0.039). Upregulation of FAM99A suppressed the proliferation, colony formation, migration, and invasion capacities of HCC cells in vitro, and knockdown of FAM99A had the opposite effects. A subcutaneous xenograft tumor model demonstrated that overexpression of FAM99A significantly inhibited the tumor growth of HCC cells in vivo. Seven tumor-related proteins (PCBP1, SRSF5, SRSF6, YBX1, IGF2BP2, HNRNPK, and HNRNPL) were recognized as possible FAM99A-binding proteins by the RNA pull-down and mass spectrometry assays.ConclusionOur results suggest that FAM99A exerts cancer-inhibiting effects on HCC progression, and it may be a promising prognostic indicator for HCC patients.

Deciphering the role of transforming growth factor-beta 1 as a diagnostic-prognostic-therapeutic candidate against hepatocellular carcinoma.

Transforming growth factor-beta (TGF-β) is a multifunctional cytokine that performs a dual role as a tumor suppressor and tumor promoter during cancer progression. Among different ligands of the TGF-β family, TGF-β1 modulates most of its biological outcomes. Despite the abundant expression of TGF-β1 in the liver, steatosis to hepatocellular carcinoma (HCC) progression triggers elevated TGF-β1 levels, contributing to poor prognosis and survival. Additionally, elevated TGF-β1 levels in the tumor microenvironment create an immunosuppressive stage via various mechanisms. TGF-β1 has a prime role as a diagnostic and prognostic biomarker in HCC. Moreover, TGF-β1 is widely studied as a therapeutic target either as monotherapy or combined with immune checkpoint inhibitors. This review provides clinical relevance and up-to-date information regarding the potential of TGF-β1 in diagnosis, prognosis, and therapy against HCC.

The diagnostic and prognostic value of the miR-17-92 cluster in hepatocellular carcinoma: A meta-analysis

Previous studies demonstrated that microRNAs (miRNAs) could serve as biomarkers in various cancers. This meta-analysis aimed to determine the roles of a miR-17-92 cluster in hepatocellular carcinoma (HCC). Here, eligible included studies were searched through PubMed, Embase, and Wan Fang databases up to 1st February 2022. Relevant data were extracted from each eligible study to evaluate the relationship between miRNA-17-92 cluster miRNA expression and the diagnosis and prognosis of HCC. Finally, a total of 21 studies were pooled and included in the meta-analysis, of which four articles were used for diagnostic meta-analysis and eight articles were used for prognostic meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratios (DOR) of the miR17-92 cluster for diagnosis of HCC were 0.75 [95% confidence interval (CI): 0.64–0.83], 0.73 (95% CI: 0.65–0.79), and 7.87 (95% CI: 5.36–11.54), respectively. Also, the area under the curve (AUC) for the miR-17-92 cluster when diagnosing HCC was 0.79 (95% CI: 0.76–0.83). For prognostic analysis, hazard ratios (HRs) with 95% CIs were extracted from the included studies and pooled HRs were determined to assess the associations. Patients with increased expression of miR17-92 cluster miRNA were associated with poor overall survival (OS) and recurrence-free survival (RFS) (HR=1.86, 95% CI: 1.04–3.33; HR = 4.18, 95% CI: 3.02–5.77, respectively), but not progression-free survival (PFS) (HR = 0.43, 95% CI: 0.25–0.73), while no association of the miR-17-92 cluster high-expression was detected with disease-free survival (DFS) (HR: 0.95, 95% CI: 0.21–4.34). In short, current pieces of evidence suggested that the miR-17-92 cluster may serve as a novel diagnostic and prognostic biomarker for HCC. However, given the limited study number, larger-size, multi-center, and higher-quality studies are indispensable in the future.

CDK2AP1 influences immune infiltrates and serves as a prognostic indicator for hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a tumor with high malignancy and poor 5-years survival rate. Excellent tumor markers are very important for early clinical diagnosis and prognosis evaluation. Previous studies have shown that CDK2AP1 (Cyclin-dependent kinase 2-associated protein 1) is involved in cell-cycle and epigenetic regulation. In the present study, we assess CDK2AP1 expression, prognostic value, immunomodulatory and possible influencing pathways in HCC. Method: The Cancer Genome Atlas (TCGA) database was used to analyse gene expression, clinicopathology and prognosis. The protein level of CDK2AP1 in HCC tissues was detected in the Human Protein Atlas (HPA) database. The immune score in HCC to CDKAP1 expression were analyzed using ESTIMATE. Furthermore, we use Tumor IMmune Estimation Resource (TIMER) database to study CDK2AP1 expression and Immune Infiltration Levels in HCC. Co-expressed genes of CDK2AP1 were predicted and elaborated by LinkedOmics. Results: In normal liver tissues, the expression of CDK2AP1 was significantly lower than tumor tissues, and was correlated with the level of clinical stage and histologic grade in HCC patients. Patients with high expression of CDK2AP1 have a poor prognosis than patients with low CDK2AP1 expression. CDK2AP1 expression level exhibits significantly positive correlations with the number of infiltrating B cells, CD4+ T cells, CD8+ T cells, Macrophages, Neutrophils, and DCs in HCC tissues. KEGG enrichment analysis showed that the related pathways affected by CDK2AP1 mainly include: Fc gamma R-mediated phagocytosis, Th1 and Th2 cell differentiation, Cell cycle, etc. Both in vitro and in vivo experiments confirmed that CDK2AP1 promotes the proliferation and metastasis in hepatocellular carcinoma. Our results highlight the role of CDK2AP1 as an important prognostic indicator and immunotherapy target for HCC patients. Conclusion: We found CDK2AP1 as a new prognostic biomarker for HCC, which could help explain changes in the biological processes and immune environment lead to liver cancer development. Therefore, CDK2AP1 is a potential new target for HCC therapy.

Identification of G6PC as a potential prognostic biomarker in hepatocellular carcinoma based on bioinformatics analysis.

Hepatocellular carcinoma (HCC) has high mortality and incidence rates around the world with limited therapeutic options. There is an urgent need for identification of novel therapeutic targets and biomarkers for early diagnosis and predicting patient survival with HCC.Several studies (GSE102083, GSE29722, GSE101685, and GSE112790) from the GEO database in HCC were screened and analyzed by GEO2R, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction network was plotted and the module analysis was performed using Search Tool for the Retrieval of Inter-acting Genes/Proteins database and Cytoscape. The expression and survival of key genes were identified using UALCAN, Kaplan–Meier Plotter and ONCOMINE online databases, and the immune infiltration level of key genes was analyzed via the Tumor Immune Estimation Resource (TIMER) database.Through database analysis, eight key genes were finally screened out, and the expressions of cyclin-dependent kinase regulatory subunit 2 and glucose-6-phosphatase catalytic (G6PC), which were closely related to the survival of HCC patients, was detected by using UALCAN. Further analysis on the differential expression of G6PC in multiple cancerous tumors and normal tissues revealed low expression in many solid tumors by Oncomine and TIMER. In addition, Kaplan–Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of G6PC was significantly associated with poor overall survival in HCC patients. Finally, TIMER database analysis showed a significant negative correlation between G6PC and infiltration levels of six kinds of immune cells. The somatic copy number alterations of G6PC were associated with B cells, CD8+ T cells, CD4+ T cells, macrophages, dentritic cells and neutrophils.These bioinformatic data identified G6PC as a potential key gene in the diagnosis and prognosis of HCC.

Heat-shock protein 90α is a potential prognostic and predictive biomarker in hepatocellular carcinoma: a large-scale and multicenter study

BackgroundAlthough the diagnostic value of plasma heat-shock protein 90α (HSP90α) in hepatocellular carcinoma (HCC) has been previously reported, the causal effect of the plasma HSP90α levels on HCC prognosis remains largely unclear. To this extent, we sought to assess whether the plasma HSP90α acts as a prognostic factor for HCC patients.MethodsA total of 2150 HCC patients were included in this retrospective study between August 2016 and July 2021. Plasma HSP90α levels were tested within a week before treatment and their association with prognosis was assessed.ResultsAn optimal cutoff value of 143.5 for the HSP90α based on the overall survival (OS) was determined using the X-tile software. HCC patients with HSP90α < 143.5 ng/mL (low HSP90α) before and after propensity score matching (PSM) indicated longer median OS (mOS) relative to those with HSP90α ≥ 143.5 ng/mL (high HSP90α) (37.0 vs. 9.0 months, p < 0.001; 19.2 vs. 9.6 months, p < 0.001; respectively). In addition, the high HSP90α plasma level is an independent poor prognostic factor for OS in HCC patients. In our subgroup analysis, including the supportive care group, surgery group, transarterial chemoembolization (TACE) group, adjuvant TACE group, an immune checkpoint inhibitor (ICI) plus targeted therapy group, and TACE plus ICI group, the high HSP90α group demonstrated better OS compared to the low HSP90α group. Moreover, in the supportive care, TACE, ICI plus targeted therapy, TACE plus ICI groups, and high HSP90α levels were also an independent poor prognostic factors for OS.ConclusionsOur study confirmed that the plasma HSP90α level can be used as a prognostic biomarker for HCC.

Differentially expressed liver exosome-related genes as candidate prognostic biomarkers for hepatocellular carcinoma.

BackgroundExosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms.MethodsThe exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy.ResultsForty-eight exosome-related DEGs were obtained; of them, five [exportin 1 (XPO1), lysosomal thiol reductase (IFI30), F-box protein 16 (FBXO16), calmodulin 1 (CALM1), MORC family CW-type zinc finger 3 (MORC3)] were selected to construct a predictive model. Patients with HCC were then divided into low- and high-risk groups using the best cut-off value, as determined by the X-tile software. Prognosis was significantly poorer in the high-risk than in the low-risk group (P=0.009; hazard ratio =2.65). Features related to exosomes were found to positively regulate immune response. Further analysis showed a higher risk score was associated with higher expression of immune checkpoint molecules, including programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), T cell Ig and ITIM domain (TIGIT), and indoleamine-2,3-dioxygenase 1 (IDO1).ConclusionsThis study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.

Prognostic value of exosomal noncoding RNA in hepatocellular carcinoma: a meta-analysis.

High morbidity, recurrence and mortality make hepatocellular carcinoma (HCC) a leading cause of cancer-related burden and deaths. The lack of prognostic evaluation methods weakened the therapeutic efficacy for HCC. Exosomal noncoding RNAs (ncRNAs) play a key role in cancer development. Our meta-analysis aimed to assess the prognostic value of exosome-transferred noncoding RNAs in predicting the outcomes of patients with HCC. We obtained 16 articles from PubMed, Web of Science, Scopus, and EMBASE up to 4 November 2021. The ncRNAs were divided into three parts: microRNAs (miRNA), long noncoding RNAs (lncRNA), and circular RNAs (circRNA). In the pooled hazard ratios (HRs), upregulated miRNAs were 3.06 (95% CI = 2.51-3.73), downregulated miRNAs were 3.28 (95% CI = 2.61-4.11), lncRNAs were 3.34 (95% CI = 1.87-5.96), and circRNAs were 1.76 (95% CI = 1.36-2.14). As the results of subgroup analysis, upregulated miRNAs had a pooled HR of 3.10 (95% CI = 1.66-5.81), and the HR of downregulated miRNAs was 3.04 (95% CI = 2.17-4.28) for multivariate analysis of overall survival (OS). Meanwhile, upregulated miRNAs had a pooled HR of 2.61 (95% CI = 1.89-3.60), and the HR of downregulated miRNAs was 3.77 (95% CI = 1.11-12.73) for multivariate analysis of other endpoints. Remarkably, miR-21 has a pooled HR of 2.48 (95%CI = 1.52-4.05, I2 = 0) for disease-free survival (DFS). In conclusion, the expression of exosomal noncoding RNAs can be used to evaluate the prognosis of patients with HCC. Exosome-transferred miR-21 might serve as a potential prognostic biomarker in HCC.

H2AFX might be a prognostic biomarker for hepatocellular carcinoma.

H2AFX can play a central role in DNA repair, replication, transcription regulation, and chromosomal stability. However, there is little research to explore the expression of H2AFX in cancers. Moreover, the correlation between the expression of H2AFX and tumor immunity, which affects the prognosis of hepatocellular carcinoma (HCC), is not clear. This article aimed to observe the correlation between H2AFX and tumor tissue infiltration biomarkers in HCC and its prognostic potential in HCC. Oncomine and TIMER database were used to assess the expression level of H2AFX mRNA, and GEPIA and Kaplan-Meier databases were used to evaluate its prognostic potential. The TIMER database analyzed the relationship between h2afx expression level and tumor immune cell infiltration markers in liver cancer tissues. The results showed that H2AFX was overexpressed in tumor tissues than normal tissues in HCC via analysis, and its expression level was correlated with the survival rate of HCC. Moreover, the expression level of H2AFX was related to various immune biomarkers. These results show that overexpression of H2AFX would reflect the poor prognosis of HCC, and these would also reflect that the gene H2AFX can affect the infiltration of HCC immune cells and then play a role in regulating tumor immunity. Our study showed that the gene H2AFX might be a potential poor prognostic biomarker in HCC and might be involved in the infiltration of HCC immune cells.

Comprehensive Analysis of Prognostic Value and Immune Infiltration of Ficolin Family Members in Hepatocellular Carcinoma.

Objective: Ficolin (FCN) family proteins are part of the innate immune system, play a role as recognition molecules in the complement system, and are associated with tumor development. The mechanism of its role in immunotherapy of hepatocellular carcinoma (HCC) is unclear. Methods: In this study, we used the TCGA database, HPA database, Gene Expression Profile Interaction Analysis (GEPIA), Kaplan-Meier plotter, TCGAportal, cBioPortal, GeneMANIA, TIMER, and TISIDB to analyze Ficolin family proteins (FCN1, FCN2 and FCN3, FCNs) in patients with hepatocellular carcinoma for differential expression, prognostic value, genetic alterations, functional enrichment, and immune factor correlation analysis. Results: The expression levels of FCN1/2/3 were significantly reduced in patients with HCC. Among them, FCN3 showed significant correlation with Overall Survival (OS), Progressive Free Survival (PFS) and Relapse Free Survival (RFS) in HCC. FCN1 and FCN3 may be potential prognostic markers for survival in patients with HCC. In addition, the functions of differentially expressed FCNs were mainly related to complement activation, immune response, apoptotic cell clearance and phagocytosis. FCNs were found to be significantly correlated with multiple immune cells and immune factors. Expression of FCN1 and FCN3 differed significantly in the immune and stromal cell component scores of HCC. analysis of the tumor mutation burden (TMB) and microsatellite instability (MSI) of FCNs with pan-cancer showed that FCN3 was significantly correlated with both. Conclusions: Our study provides new insights into the link between the FCN family and immunotherapy for HCC, and FCN3 may serve as a prognostic biomarker for HCC.

A ferroptosis-associated lncRNAs signature predicts the prognosis of hepatocellular carcinoma.

Long noncoding RNAs (lncRNAs) have been implicated in the development of hepatocellular carcinoma (HCC). Mounting evidence shows that lncRNAs can be used as prognostic biomarkers of HCC. Here, we developed a multi-lncRNA prognostic signature comprising ferroptosis-related lncRNAs in HCC. Gene expression data and clinical information of HCC were obtained from the TCGA dataset. Differentially expressed genes of ferroptosis (DE-Ferrs) were screened. Correlation analysis was carried between lncRNAs and DE-Ferrs to identify ferroptosis-related lncRNAs. lncRNAs associated with prognosis and ferroptosis were identified using Univariate Cox analysis. Data from a TCGA dataset were randomly grouped into training and verification sets. The least absolute shrinkage and selection operator method analysis was carried out to identify lncRNAs with prognostic value. These lncRNAs were used to construct a prognostic signature using the training set. The signature was validated in the verification set. A total of 90 DE-Ferrs-related lncRNAs were identified which were significantly correlated with HCC prognosis. Seven lncRNAs were used to construct a 7-lncRNA signature. The area under the curves for 1-, 3-, and 5-year overall survival (OS) were 0.748, 0.681, and 0.659 in the training set, and 0.791, 0.731, and 0.815 in the validation set, respectively. The results demonstrated that a high-risk score was significantly associated with a high tumor grade, high infiltration of macrophages and fibroblasts in the tumor, and high expression of m6A methylation regulatory factors. A nomogram was constructed using the risk score and clinical features for predicting the prognosis of HCC. The nomogram showed high prediction accuracy. In conclusion, the established 7 ferroptosis-related lncRNAs signature can accurately predict HCC prognosis.

Abstract 6235: Detection of γ-OHPdG in circulating liver cells and its potential use as a prognostic biomarker in patients with hepatocellular carcinoma recurrence

Abstract Background: Primary liver cancer is the fourth most common cause of cancer-related death. Resection is the most widely used potentially curative treatment for patients with early-stage hepatocellular carcinoma (HCC). Recurrence within 2 years occurs in 30-50% of patients and is a major cause of mortality. A biomarker to predict the risk of HCC and its recurrence is urgently needed. Our studies showed that hepatic levels of γ-OHPdG, an endogenous adduct from lipid peroxidation, closely correlate with hepatocarcinogenesis in various independent animal models, including an obesity model. Importantly, we observed that higher levels of γ-OHPdG in liver specimens from HCC patients who underwent surgical resection were strongly associated with poor survival (p &amp;lt; 0.0001) as well as with poor recurrence-free survival (RFS) (p = 0.007). These finding suggest that γ-OHPdG may serve as a prognostic biomarker of HCC and its recurrence. A non-invasive method to detect γ-OHPdG is highly desirable. There is a surge of interest in using circulating liver cells (CLCs) from patient blood to diagnose cancer stages and predict treatment outcomes, metastatic potential, and recurrence. We developed a non-invasive method for detecting and quantifying γ-OHPdG using CLCs from patient blood. Method: The method was developed by following steps: (i) isolate CLCs from blood samples using a RosetteSep™ Human CD45 Depletion Cocktail and Ficoll Paque, (ii) detect γ-OHPdG by immunocytochemistry, (iii) quantify the images of γ-OHPdG-positive stained CLCs, and (iv) compare with that found in liver biopsies by immunohistochemistry. Results: To determine the specificity of the anti-γ-OHPdG antibody developed previously in our laboratory, we showed that the proportion of γ-OHPdG-positively stained cells and staining intensity increased in HepG2 liver cancer cells upon acrolein treatment. Liver cells were co-stained with asialoglycoprotein receptor 1 (ASGPR1), a cell surface protein expressed solely on the surface of hepatic cells. CLC γ-OHPdG was quantified using Metamorph (BioVision)-based journal software, developed to quantify the percentage of ASGPR1-stained cells that also stain positively, and with what level of intensity, for γ-OHPdG. We then applied this method to 35 HCC patients’ blood samples. This method detects the number of ASGPR1 stained CLC and determines the cellular localization of γ-OHPdG, allowing the quantification of γ-OHPdG in these cells. While the nuclear γ-OHPdG reflects DNA damage, adducts in both the nucleus and the cytosol will be evaluated against IHC staining using biopsies and other clinical endpoints, such as disease stage and recurrence. Conclusion: The CLC method descried above for detecting and quantifying γ-OHPdG can be potentially used to validate this adduct as a prognostic biomarker for predicting HCC risk and recurrence in clinical trials. Citation Format: Monika Aggarwal, Zizhao Zhu, Sophie Gould, Peter Johnson, Samira Beheshtian, Hongbin Fang, Bhaskar Kallakury, Susette C. Mueller, Aiwu Ruth He, Fung-Lung Chung. Detection of γ-OHPdG in circulating liver cells and its potential use as a prognostic biomarker in patients with hepatocellular carcinoma recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6235.

Exonuclease 1 is a Potential Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) represents a global health challenge. Effective biomarkers are required for an early diagnosis to improve the survival rates of HCC patients. Exonuclease 1 (EXO1) plays a significant role in the DNA repair and recombination mechanisms. This study aimed to investigate the diagnostic and prognostic roles of EXO1 in HCC. Methods: We analyzed the EXO1 expression levels in various cancers including HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA sequencing data were analyzed using the R packages to determine differentially expressed genes (DEGs) between high- and low-EXO1 expressing HCC tissues from the TCGA–LIHC database. A Spearman’s correlation analysis was performed to determine the association between EXO1 expression and immune cell infiltration, and immune checkpoint genes and TP53. MethSurv and CBioPortal databases were used to evaluate the DNA methylation changes and genetic alterations in the EXO1 gene. A logistic regression analysis was performed to determine the association between EXO1 expression and the clinicopathological characteristics of the HCC patients. The diagnostic and prognostic predictive values of EXO1 were evaluated using the Kaplan–Meier (K-M) survival curves, diagnostic receiver operating characteristic (ROC) curves, nomogram model, and Cox regression analysis. Results: EXO1 expression levels were significantly higher in the tumor tissues and serums of HCC patients compared to the corresponding controls. The DEGs associated with EXO1 were significantly enriched in the cell proliferation pathways. EXO1 expression levels significantly correlated with immune cell infiltration, immune checkpoint genes, and TP53 in the HCC tissues. The DNA methylation status in five CpG islands of the EXO1 gene was associated with the prognosis of HCC. EXO1 expression levels in the HCC tissues were associated with the tumor grades, alpha-fetoprotein (AFP) levels, and the tumor stages. Cox regression analysis showed that EXO1 was a potential independent risk factor for the overall survival (OS) and disease-specific survival (DSS) of HCC patients. ROC curve analysis showed that EXO1 expression levels accurately distinguished HCC tissues from the adjacent normal liver tissues. Conclusion: Our study demonstrated that EXO1 was a potential diagnostic and prognostic biomarker, and a promising therapeutic target in HCC.