A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients

Serological Responses to Human Virome Define Clinical Outcomes of Italian Patients Infected with SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the pandemic respiratory infectious disease COVID-19. However, clinical manifestations and outcomes differ significantly among COVID-19 patients, ranging from asymptomatic to extremely severe, and it remains unclear what drives these disparities. Here, we studied 159 hospitalized Italian patients with pneumonia from the NIAID-NCI COVID-19 Consortium using a phage-display method to characterize circulating antibodies binding to 93,904 viral peptides encoded by 1,276 strains of human viruses. SARS-CoV-2 infection was associated with a marked increase in individual's immune memory antibody repertoires linked to trajectories of disease severity from the longitudinal analysis also including anti-spike protein antibodies. By applying a machine-learning-based strategy, we developed a viral exposure signature predictive of COVID-19-related disease severity linked to patient survival. These results provide a basis for understanding the roles of memory B-cell repertoires in COVID-19-related symptoms as well as a predictive tool for monitoring its clinical severity.

The genomic landscape of Mongolian hepatocellular carcinoma

Mongolia has the highest incidence of hepatocellular carcinoma (HCC) in the world, but its causative factors and underlying tumor biology remain unknown. Here, we describe molecular characteristics of HCC from 76 Mongolian patients by whole-exome and transcriptome sequencing. We present a comprehensive analysis of mutational signatures, driver genes, and molecular subtypes of Mongolian HCC compared to 373 HCC patients of different races and ethnicities and diverse etiologies. Mongolian HCC consists of prognostic molecular subtypes similar to those found in patients from other areas of Asia, Europe, and North America, as well as other unique subtypes, suggesting the presence of distinct etiologies linked to Mongolian patients. In addition to common driver mutations (TP53, CTNNB1) frequently found in pan-cancer analysis, Mongolian HCC exhibits unique drivers (most notably GTF2IRD2B, PNRC2, and SPTA1), the latter of which is associated with hepatitis D viral infection. These results suggest the existence of new molecular mechanisms at play in Mongolian hepatocarcinogenesis.

Integrated Bioinformatics Analysis Reveals Key Candidate Genes and Pathways Associated With Clinical Outcome in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for approximately 85-90% of all liver cancer cases and has poor relapse-free survival. There are many gene expression studies that have been performed to elucidate the genetic landscape and driver pathways leading to HCC. However, existing studies have been limited by the sample size and thus the pathogenesis of HCC is still unclear. In this study, we performed an integrated characterization using four independent datasets including 320 HCC samples and 270 normal liver tissues to identify the candidate genes and pathways in the progression of HCC. A total of 89 consistent differentially expression genes (DEGs) were identified. Gene-set enrichment analysis revealed that these genes were significantly enriched for cellular response to zinc ion in biological process group, collagen trimer in the cellular component group, extracellular matrix (ECM) structural constituent conferring tensile strength in the molecular function group, protein digestion and absorption, mineral absorption and ECM-receptor interaction. Network system biology based on the protein-protein interaction (PPI) network was also performed to identify the most connected and important genes based on our DEGs. The top five hub genes including osteopontin (SPP1), Collagen alpha-2(I) chain (COL1A2), Insulin-like growth factor I (IGF1), lipoprotein A (LPA), and Galectin-3 (LGALS3) were identified. Western blot and immunohistochemistry analysis were employed to verify the differential protein expression of hub genes in HCC patients. More importantly, we identified that these five hub genes were significantly associated with poor disease-free survival and overall survival. In summary, we have identified a potential clinical significance of these genes as prognostic biomarkers for HCC patients who would benefit from experimental approaches to obtain optimal outcome.

Prognostic value and underlying mechanism of KIAA0101 in hepatocellular carcinoma: database mining and co-expression analysis

Although KIAA0101 is involved in many diseases, its expression and prognostic value in HCC remain undefined. According to CCLE, KIAA0101 is highly expressed in HCC, with a weak positive correlation between copy number and gene expression. Four studies involving 760 samples in ONCOMINE report elevated KIAA0101 expression in HCC (p=3.11E-22). The KM plotter revealed high KIAA0101 expression to be associated with worse overall survival in HCC (HR=2.09, p=4.1e-05); this prognostic power was stronger for male than female, early-stage than advanced-stage, and Asian than Caucasian patients. RNA sequencing data for 8 pairs of HCC and adjacent tissue samples validated the significantly high KIAA0101 level (p=0.00497). Moreover, functional annotations of 31 KIAA0101-coexpressed genes show enrichment of terms associated with mitosis, cytoskeleton construction, and chromosome segregation. Among 9 genes having STRING-validated protein-protein interactions with KIAA0101, two are involved in virus-related pathways. Alternative splicing analysis indicated higher expression of variant 1 and variant 2 in HCC and no significant differences in exon usage of KIAA0101 between cancer and normal tissues. These findings support that KIAA0101 is a potential prognostic biomarker for HCC and highlight the association between virus infection and the mechanism underlying the process by which KIAA0101 contributes to poor prognosis of patients.

Systemic Expression Analysis Reveals Prognostic Significance of WIPI3 in Hepatocellular Carcinoma

Introduction

WD repeat domain phosphoinositide-interacting protein 3 (WIPI3) is a member of the WIPI protein family, autophagy marker, that is associated with the malignant progression of various human cancers, but its role in hepatocellular carcinoma (HCC) is still unclear.

Materials and Methods

Firstly, we collected the mRNA expression of WIPI3 in HCC through the platform of Oncomine, as well as the DNA copy number variations (CNVs), and verified it on human HCC cell line and the GEO database. Then, the subgroups and prognosis of HCC were performed by the UALCAN web tool. The mutation of WIPI3 was analyzed by cBioPortal. The coexpression of WIPI3 in HCC was identified from the LinkedOmics database, and function enrichment analysis was done using the LinkFinder module in LinkedOmics. Coexpression gene network was constructed through the STRING database, and the MCODE plug-in of which was used to build the gene modules; both of them were visualized by the Cytoscape software. Finally, the top modular genes in the same patient cohort were constructed through data mining in The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) by using the UCSC Xena browser.

Results

The results indicated that WIPI3 was frequently overexpressed in HCC, which could lead to a poor prognosis through the Kaplan-Meier (KM) analysis. Moreover, there existed mutations of WIPI3 in HCC, and the prognosis of WIPI3-altered group was significantly poor based on KM plotter data. Coexpression analysis showed that the coexpression gene of WIPI3 was associated with cell cycle and spliceosome. Further analysis suggested that WIPI3 and eukaryotic translation initiation factor 4A3 (EIF4A3) coordinately regulated the cancer cell cycle by spliceosome as a result of the strong positive correlation between them.

Conclusion

In summary, WIPI3 is constantly overexpressed in HCC tissues, resulting in a poor prognosis; therefore, we can identify it as an effective target for the treatment of HCC.

Sirt3 promotes hepatocellular carcinoma cells sensitivity to regorafenib through the acceleration of mitochondrial dysfunction

Regorafenib, a multiple kinase inhibitor, is recently approved for treatment of patients with advanced hepatocellular carcinoma (HCC). Previous studies demonstrated that regorafenib was a mitochondrial toxicant, which associated with the impairment of mitochondria. Sirt3 is involved in the regulation of mitochondrial function in cancers. This study aimed to investigate the mechanism of Sirt3 involved in the mitochondrial dysfunction which associated with regorafenib treatment in liver cancer cells. We found regorafenib inhibited Sirt3 and p-ERK expression in HCC cells in a dose-dependent manner. Bioinformatics analysis showed that Sirt3 expression was down-regulated in liver cancer tissues and its low expression was correlated with worse overall survival (OS) in liver cancer patients. After transfected with Sirt3 overexpression plasmid, we found that Sirt3 sensitized liver cancer cells to regorafenib and resulted in much more apoptosis with a significant increase of ROS level. However, exogenous antioxidant could not weaken the apoptosis. Mitochondrial membrane potential assay indicated that Sirt3 overexpression accelerated the mitochondrial depolarization process induced by regorafenib and aggravated mitochondrial injury. Cellular oxygen consumption assay showed that mitochondrial dysfunction was caused by the damage of the electron transport chain. The results demonstrated that Sirt3 overexpression promoted the increase of ROS and apoptosis induced by regorafenib through the acceleration of mitochondrial dysfunction by impairing function of the electron transport chain in liver cancer cells. Our studies verified the functional role of Sirt3 in regorafenib treatment and suggested that regorafenib accompanied with Sirt3 activator as a novel treatment strategy for HCC.

The diagnostic and prognostic value of cell division cycle associated gene family in Hepatocellular Carcinoma

Cell division cycle associated (CDCA) gene family plays an important role in cells. However, some researchers revealed that overexpression of CDCAs might contribute to the tumor progression in several cancers. Here, we analyzed the role of this gene family in hepatocellular carcinoma (HCC). We used several web tools and found that most of CDCAs were highly expressed in tumor tissues compared to the paracancer tissues in HCC. We then used RT-qPCR to confirm our results. The results showed that CDCA2, CDCA3, CDCA5 and CDCA8 were up-regulated in HCC. We also found that these genes were associated with poor overall survival and relapse free survival except CDCA7. The functional analysis showed that this gene family might take part in many processes, including cell division, apoptosis, DNA damage and DNA repair, which might contribute to the tumor progression. The KEGG pathway analysis showed that these genes participated in several important pathways such as PI3K-Akt signaling pathway and hippo signaling pathway. In conclusion, our findings suggested that CDCA2, CDCA3, CDCA4, CDCA5, and CDCA8 might have potential diagnostic and prognostic values for hepatocellular carcinoma.

Integrated Bioinformatic Analysis Identifies Networks and Promising Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma

Chronic infection with hepatitis B virus (HBV) has long been recognized as a dominant hazard factor for hepatocellular carcinoma (HCC) and accounts for at least half of HCC instances globally. However, the underlying molecular mechanism of HBV-linked HCC has not been completely elucidated. Here, three microarray datasets, totally containing 170 tumoral samples and 181 adjacent normal tissues from the liver of patients suffering from HBV-related HCC assembled from the Gene Expression Omnibus (GEO) database, were subjected to integrated analysis of differentially expressed genes (DEGs). Subsequently, the analysis of function and pathway enrichment as well as the protein-protein interaction network (PPI) was performed. The ten hub genes screened out from the PPI network were further subjected to expression profile and survival analysis. Overall, 329 DEGs (67 upregulated and 262 downregulated) were identified. Ten DEGs with the highest degree of connectivity included cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), PDZ-binding kinase (PBK), abnormal spindle microtubule assembly (ASPM), nuclear division cycle 80 (NDC80), aurora kinase A (AURKA), targeting protein for xenopus kinesin-like protein 2 (TPX2), kinesin family member 2C (KIF2C), and centromere protein F (CENPF). Kaplan-Meier analysis unveiled that overexpression levels of KIF2C and TPX2 were relevant to both the poor overall survival and relapse-free survival. In summary, the hub genes validated in the present study may provide promising targets for the diagnosis, prognosis, and therapy of HBV-associated HCC. Additionally, our work uncovers various crucial biological components (e.g., extracellular exosome) and signaling pathways that participate in the progression of HCC induced by HBV, serving comprehensive knowledge of the mechanisms regarding HBV-related HCC.

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression

Tumor‐specific metabolic rewiring, acquired to confer a proliferative and survival advantage over nontransformed cells, represents a renewed focus in cancer therapy development. Hepatocellular carcinoma (HCC), a malignancy that has hitherto been resistant to compounds targeting oncogenic signaling pathways, represents a candidate cancer to investigate the efficacy of selectively antagonizing such adaptive metabolic reprogramming. To this end, we sought to characterize metabolic changes in HCC necessary for tumorigenesis. We analyzed gene expression profiles in three independent large‐scale patient cohorts who had HCC. We identified a commonly deregulated purine metabolic signature in tumors with the extent of purine biosynthetic enzyme up‐regulation correlated with tumor grade and a predictor of clinical outcome. The functional significance of enhanced purine metabolism as a hallmark in human HCC was then validated using a combination of HCC cell lines, patient‐derived xenograft (PDX) organoids, and mouse models. Targeted ablation of purine biosynthesis by knockdown of the rate‐limiting enzyme inosine‐5′‐monophosphate dehydrogenase (IMPDH) or using the drug mycophenolate mofetil (MMF) reduced HCC proliferation in vitro and decreased the tumor burden in vivo. In comparing the sensitivities of PDX tumor organoids to MMF therapy, we found that HCC tumors defined by high levels of IMPDH and guanosine nucleosides were most susceptible to treatment. Mechanistically, a phosphoinositide 3‐kinase (PI3K)–E2F transcription factor 1 (E2F1) axis coordinated purine biosynthetic enzyme expression, deregulation of which altered the activity of mitogen‐activated protein kinase/RAS signaling. Simultaneously abolishing PI3K signaling and IMPDH activity with clinically approved inhibitors resulted in greatest efficacy in reducing tumor growth in a PDX mouse model. Conclusion: Enhanced purine metabolic activity regulated by PI3K pathway‐dependent activation of E2F1 promotes HCC carcinogenesis, suggesting the potential for targeting purine metabolic reprogramming as a precision therapeutic strategy for patients with HCC.

Identification of APEX2 as an oncogene in liver cancer

BACKGROUND

DNA damage is one of the critical contributors to the occurrence and development of some cancers. APEX1 and APEX2 are the most important molecules in the DNA damage, and APEX1 has been identified as a diagnostic and prognostic biomarker in liver hepatocellular carcinoma (LIHC). However, the expression of APEX2 and its functional mechanisms in LIHC are still unclear.

AIM

To examine the expression of APEX2 and the potential mechanism network in LIHC.

METHODS

We conducted a pan-cancer analysis of the expression of APEX1 and APEX2 using the interactive TIMER tool. GEO datasets, including GSE14520, GSE22058, and GSE64041, were used to compare the APEX2 expression level in tumor tissues and adjacent non-tumor tissues. Then, we calculated the 5-year survival rate according to the web-based Kaplan-Meier analysis. We included the TCGA liver cancer database in GSEA analysis based on the high and low APEX2 expression, showing the potential mechanisms of APEX2 in LIHC. After that, we conducted Pearson correlation analysis using GEPIA2. Next, we performed quantitative polymerase chain reaction (qPCR) assay to examine the APEX2 levels in normal liver cell line LO2 and several liver cancer cell lines, including HepG2, Huh7, SMMC7721, and HCCLM3. APEX2 in HCCLM3 cells was knocked down using small interfering RNA. The role of APEX2 in cell viability was confirmed using CCK-8. Dual-luciferase reporter assay was performed to examine the promoter activity of CCNB1 and MYC.

RESULTS

APEX1 and APEX2 are both highly expressed in the tumor tissues of BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, READ, and STAD. APEX2 overexpression in LIHC was validated using GSE14520, GSE22058, and GSE64041 datasets. The survival analysis showed that LIHC patients with high expression of APEX2 had a lower overall survival rate, even in the AJCC T1 patients. High level of APEX2 could indicate a lower overall survival rate in patients with or without viral hepatitis. The GSEA analysis identified that kinetochore and spindle microtubules are the two main cellular components of APEX2 in GO Ontology. APEX2 was also positively associated with molecular function regulation of chromosome segregation and DNA replication. The results of KEGG analysis indicated that APEX2 expression was positively correlated with cell cycle pathway and pro-oncogenic MYC signaling. Pearson correlation analysis showed that APEX2 had a significant positive correlation with CCNB1 and MYC. APEX2 level was higher in liver cancer cell lines than in normal liver LO2 cells. Small interfering RNA could knock down the APEX2 expression in HCCLM3 cells. Knockdown of APEX2 resulted in a decrease in the viability of HCCLM3 cells as well as the expression and promoter activity of CCNB1 and MYC.

CONCLUSION

APEX2 is overexpressed in LIHC, and the higher APEX2 level is associated with a worse prognosis in overall survival. APEX2 is closely involved in the biological processes of chromosome segregation and DNA replication. APEX2 expression is positively correlated with the pro-oncogenic pathways. Knockdown of APEX2 could inhibit the cell viability and CCNB1 and MYC pathways, suggesting that APEX2 is an oncogene in LIHC, which could be a potential pharmaceutic target in the anti-tumor therapy.

ASTN1 is associated with immune infiltrates in hepatocellular carcinoma, and inhibits the migratory and invasive capacity of liver cancer via the Wnt/β‑catenin signaling pathway

Astrotactin 1 (ASTN1) is known to serve a physiological role in neuronal migration; however its role in liver cancer remains to be determined. In the present study, ASTN1 levels were lower in liver cancer tissues compared with those in matching normal tissue. ASTN1 levels were negatively associated with microscopic vascular invasion, advanced clinical stage and a less favorable prognosis in patients with hepatocellular carcinoma (HCC). Furthermore, ASTN1 overexpression in a liver cancer cell line reduced the migratory and invasive capacity of the cells. Based on bioinformatics analysis, ASTN1 levels were negatively associated with the Wnt signaling pathway. In addition, ASTN1 downregulated the protein expression levels of β-catenin, T-cell factor (TCF)1, TCF4, Jun proto-oncogene (C-jun), Myc proto-oncogene (C-myc), cyclooxygenase-2 (COX2), metalloproteinase (MMP)2, MMP9 and vascular endothelial growth factor (VEGF) protein levels, indicative of suppression of Wnt signaling. Furthermore, XAV939-induced Wnt signaling suppression reversed the ASTN1-mediated inhibition of invasion and migration in cells. Overexpression of ASTN1 in xenografts reduced cancer development as well as Wnt signaling. TIMER analysis showed that ASTN1 expression was negatively correlated with B cell, macrophage and neutrophil infiltrating levels in HCC. Together, the results of the present study showed that ASTN1 reduced the migratory and invasive capacity of liver cancer cells, potentially served as a candidate biomarker for diagnosis and prediction of the prognosis of HCC, and was associated with immune infiltration. Understanding the underlying mechanisms of action of ASTN1 may facilitate the development of novel strategies for prevention and treatment of liver cancer.

Genetic Alterations and Transcriptional Expression of m6A RNA Methylation Regulators Drive a Malignant Phenotype and Have Clinical Prognostic Impact in Hepatocellular Carcinoma

Background: N6-methyladenosine (m⁶A) RNA methylation, associated with cancer initiation and progression, is dynamically regulated by the m⁶A RNA regulators. However, its role in liver carcinogenesis is poorly understood.

Methods: Three hundred seventy-one hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas database with sequencing and copy number variations/mutations data were included. Survival analysis was performed using Cox regression model. We performed gene set enrichment analysis to explore the functions associated with different HCC groups. Finally, we used a machine-learning model on selected regulators for developing a risk signature (m⁶Ascore) The prognostic value of m⁶Ascore was finally validated in another two GEO datasets.

Results: We demonstrated that 11 m⁶A RNA regulators are significantly differentially expressed among 371 HCC patients stratified by clinicopathological features (P<0.001). We then identified two distinct HCC clusters by applying consensus clustering to m⁶A RNA regulators. Compared with the cluster2 subgroup, the cluster1 subgroup correlates with poorer prognosis (P < 0.001). Moreover, the cell cycle, splicesome and notch signaling pathway are significantly enriched in the cluster1 subgroup. We further derived m⁶Ascore, using four m⁶A regulators, predicting HCC prognosis well at three (AUC = 0.7) or 5 years (AUC=0.7) in validation. The prognostic value of m⁶Ascore also was validated successfully in two GEO datasets (P < 0.05). Finally, we discovered that mutations and copy number variations of m⁶A regulators, conferring worse survival, are strongly associated with TP53 mutations in HCC.

Conclusions: We find a significant relationship between the alterations and different expressions causing increased m⁶A level and worse survival, especially in TP53-mutated HCC patients. Genetic alterations of m⁶A genes might cooperate with TP53 and its regulator targets in the HCC pathogenesis. Our m⁶Ascore may be applied in the clinical trials for patient stratification in HCC.

Transcriptomic analysis on the effects of melatonin in gastrointestinal carcinomas

BACKGROUND

Melatonin has been shown with anticancer property and therapeutic potential for tumors. However, there lacks a systematic study on the molecular pathways of melatonin and its antitumor effects in gastrointestinal carcinomas.

METHODS

Using the gene expression profiles of four cancer cell lines from three types of gastrointestinal carcinomas before and after melatonin treatment, including gastric carcinoma (GC), colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), differentially expressed genes (DEGs) and biological pathways influenced by melatonin were identified. The qRT-PCR analyses were performed to validate the effects of melatonin on 5-FU resistance-related genes in CRC.

RESULTS

There were 17 pathways commonly altered by melatonin in the three cancer types, including FoxO signaling pathways enriched by the upregulated DEGs and cell cycle signaling pathways enriched by the downregulated DEGs, confirmed the dual role of melatonin to tumor growth, pro-apoptosis and anti-proliferation. DEGs upregulated in the three types of cancer tissues but reversely downregulated by melatonin were commonly enriched in RNA transport, spliceosome and cell cycle signaling pathways, which indicate that melatonin might exert antitumor effects through these pathways. Our results further showed that melatonin can downregulate the expression levels of 5-FU resistance-related genes, such as thymidylate synthase in GC and ATR, CHEK1, BAX and MYC in CRC. The qRT-PCR results demonstrated that melatonin enhanced the sensitivity of CRC 5-FU resistant cells by decreasing the expression of ATR.

CONCLUSIONS

Melatonin exerts the effects of pro-apoptosis and anti-proliferation on gastrointestinal carcinomas, and might increase the sensitivity of 5-FU in GC and CRC patients.

A Novel Ten-Gene Signature Predicting Prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has a dismal long-term outcome. We aimed to construct a multi-gene model for prognosis prediction to inform HCC management. The cancer-specific differentially expressed genes (DEGs) were identified using RNA-seq data of paired tumor and normal tissue. A prognostic signature was built by LASSO regression analysis. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. A 10-gene signature was constructed to stratify the TCGA and ICGC cohorts into high- and low-risk groups where prognosis was significantly worse in the high-risk group across cohorts (P < 0.001 for all). The 10-gene signature outperformed all previously reported models for both C-index and the AUCs for 1-, 3-, 5-year survival prediction (C-index, 0.84 vs 0.67 to 0.73; AUCs for 1-, 3- and 5-year OS, 0.84 vs 0.68 to 0.79, 0.81 to 0.68 to 0.80, and 0.85 vs 0.67 to 0.78, respectively). Multivariate Cox regression analysis revealed risk group and tumor stage to be independent predictors of survival in HCC. A nomogram incorporating tumor stage and signature-based risk group showed better performance for 1- and 3-year survival than for 5-year survival. GSEA revealed enrichment of pathways related to cell cycle regulation among high-risk samples and metabolic processes in the low-risk group. Our 10-gene model is robust for prognosis prediction and may help inform clinical management of HCC.

CLEC4M overexpression inhibits progression and is associated with a favorable prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains the most common malignant cancer worldwide. Numerous studies have indicated that C-type lectin domain family 4 member M (CLEC4M) is associated with tumor progression; however, the biological functions of CLEC4M in HCC have not been investigated. In the present study, CLEC4M overexpression was observed to be associated with a favorable patient overall, relapse-free, progression-free and disease-specific survival by using the KMplot™ database. The present study then concentrated specifically on the functions of CLEC4M by performing cell counting kit-8 proliferation, 5-Ethynyl-2′-deoxyuridine and flow cytometric assays. CLEC4M overexpression inhibited proliferation and enhanced apoptosis in Huh7 and PLC/PRF/5 cells. Furthermore, the results demonstrated by using western blotting that CLEC4M overexpression inhibited the Janus kinase 1/signal transducer and activator of transcription 3 pathway, which is involved in various types of tumors including HCC. In conclusion, the present study reported that CLEC4M may be considered as a novel indicator of HCC and may provide a theoretical basis for improving the survival of patients with HCC.

Systematic summarization of the expression profiles and prognostic roles of the dishevelled gene family in hepatocellular carcinoma

Background

Dishevelled (DVL) family members are crucial to Wnt‐induced signaling transduction, and their expression is highly correlated with the progression of multiple malignant cancers. However, the expression profiles and exact prognostic values of DVLs in hepatocellular carcinoma (HCC) have not been explored until now.

Methods

The expression of DVL isoforms was assessed using the Oncomine, HCCDB and UALCAN databases. The prognostic roles of DVLs were further evaluated using the GEPIA database. The relationship between the expression of DVLs and immune infiltration of HCC was investigated using the Timer and ImmuCellAI tools. Furthermore, protein–protein interaction (PPI) networks were built and enrichment analyses were conducted.

Results

We found that the expression levels of DVL2 (OMIM accession number: 602151) and DVL3 (OMIM accession number: 601368) were upregulated in HCC tissues as revealed by the Oncomine and HCCDB databases. Additionally, the expression of DVLs tended to be associated with advanced clinical features in the UALCAN database. Prognostic analysis revealed that the expression levels of DVL1 (OMIM accession number: 601365) and DVL3 were remarkably associated with a poor prognosis in HCC patients. The results also revealed that the DVL expression level was correlated with the infiltration levels of multiple immune cells. By constructing the PPI network and enrichment analyses, the DVL1‐3 gene was identified to interact with 20 key genes and participate in several pathways.

Conclusion

In summary, DVL2 and DVL3 are highly expressed in HCC, and DVL1 and DVL3 are related to a poor prognosis, which might be used as candidate targets for targeted therapy and reliable prognostic biomarkers in HCC.

Cell Cycle Genes Are Potential Diagnostic and Prognostic Biomarkers in Hepatocellular Carcinoma

BACKGROUND

The cell cycle pathway genes are comprised of 113 members which are critical to the maintenance of cell cycle and survival of tumor cells. This study was performed to investigate the diagnostic and prognostic values of cell cycle gene expression in hepatocellular carcinoma (HCC) patients.

METHODS

Clinical features and cell cycle pathway gene expression data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases. Differentially expressed genes (DEGs) were determined by the student t-test between HCC and noncancerous samples. Kaplan-Meier survival, univariate, and multivariate survival analyses and validation analysis were performed to characterize the associations between cell cycle gene expression and patients' overall survival and recurrence-free survival.

RESULTS

47 and 5 genes were significantly upregulated and downregulated genes in HCC samples, respectively. The high expression of BUB3, CDK1, and CHEK1 was associated with increased mortality (adjusted P value = 0.04, odds ratio (OR): 1.89 (95% confidence interval (CI): 1.04-3.46); adjusted P value = 0.02, OR: 2.06 (95% CI:1.15-3.75); and adjusted P value = 0.04, OR: 1.84 (%95 CI: 1.03-3.32), respectively). The expression of PTTG2 and RAD21 was significantly associated with cancer recurrence (adjusted P value = 0.01, OR: 2.17 (95% CI: 1.24-3.86); adjusted P value = 0.03, OR: 1.88[95% CI:1.08-3.28], respectively), while the low expression of MAD1L1 was associated with cancer recurrence (adjusted P value = 0.03, OR: 0.53 (%95 CI: 0.3-0.93)).

CONCLUSIONS

The present study demonstrated that BUB3, CDK1, and CHEK1 may serve as a prognostic biomarker for HCC patients. PTTG2, RAD21, and MAD1L1 expression is a major factor affecting the recurrence of HCC patients.

PKM2 inhibition may reverse therapeutic resistance to transarterial chemoembolization in hepatocellular carcinoma

BACKGROUND

Therapeutic options for patients with hepatocellular carcinoma (HCC) are limited. Transarterial chemoembolization (TACE) is an interventional procedure used to deliver chemotherapy and embolizing agents directly to the tumor and is the procedure of choice for patients with intermediate stage HCC. While effective, more than 40% of patients do not respond to therapy, highlighting the need to investigate possible mechanisms of resistance. We sought to evaluate mechanisms of TACE resistance and evaluate a potential therapeutic target to overcome this resistance.

METHODS

Using a prognostic gene signature which predicts TACE response (TACE Navigator) in a cohort of HCC patients who received TACE, patients were classified as responders and non-responders. Transcriptomic and gene pathway analysis were used to identify potential drivers of TACE resistance. Knockdown of the gene encoding rate limiting enzyme PKM2 using shRNA in HCC cell lines, as well as pharmacologic inhibition of PKM2 with shikonin using an in vitro TACE model measured response to chemotherapy under hypoxia. Finally, we replicated the TACE model with shikonin using patient derived cell line organoids (PDC). Functional studies were performed in vitro using immunoblotting, quantitative polymerase chain reaction, glycolysis and hypoxia assays.

RESULTS

In patient non-responders, we identified enrichment of the glycolysis pathway, specifically of the gene encoding the rate-limiting enzyme PKM2. We identified four HCC cell lines which recapitulated a TACE responder-like and non-responder-like phenotype. PKM2 knockdown in HCC cell lines demonstrated a less proliferative and aggressive phenotype as well as improved drug sensitivity to both doxorubicin and cisplatin. In vitro TACE model demonstrated that TACE non-responder-like cells overcame therapeutic resistance and rendered them susceptible to therapy through PKM2 knockdown. Lastly, we obtained similar results using a pharmacologic PKM2 inhibitor, shikonin in both cell lines, and PDC organoids.

CONCLUSION

Elevated PKM2 is associated with treatment resistance and abbreviated survival in patients receiving TACE. Elevated PKM2 in vitro is associated with increased utilization of the glycolysis pathway, resulting in oxygen independent cell metabolism. Through PKM2 knockdown as well as with pharmacologic inhibition with shikonin, non-responder cells can be reprogrammed to act as responders and could improve TACE efficacy in patients.

A genome-wide gain-of-function screen identifies CDKN2C as a HBV host factor

Chronic HBV infection is a major cause of liver disease and cancer worldwide. Approaches for cure are lacking, and the knowledge of virus-host interactions is still limited. Here, we perform a genome-wide gain-of-function screen using a poorly permissive hepatoma cell line to uncover host factors enhancing HBV infection. Validation studies in primary human hepatocytes identified CDKN2C as an important host factor for HBV replication. CDKN2C is overexpressed in highly permissive cells and HBV-infected patients. Mechanistic studies show a role for CDKN2C in inducing cell cycle G1 arrest through inhibition of CDK4/6 associated with the upregulation of HBV transcription enhancers. A correlation between CDKN2C expression and disease progression in HBV-infected patients suggests a role in HBV-induced liver disease. Taken together, we identify a previously undiscovered clinically relevant HBV host factor, allowing the development of improved infectious model systems for drug discovery and the study of the HBV life cycle.

An Individualized Immune Prognostic Index is a Superior Predictor of Survival of Hepatocellular Carcinoma

Background

The tumor microenvironment is largely orchestrated by the immune cells. Considerable evidence has shown their excellent clinicopathological application value in assessment of clinical outcomes and immunotherapy efficacy. Hence, a moderate, individualized prognostic signature based on immune cells that can estimate prognosis and reflect the immune microenvironment in hepatocellular carcinoma (HCC) patients is greatly needed.

Material/Methods

Here, we systematically analyzed the expression differences and survival prediction value of tumor infiltrating immune cells by analyzing 638 HCC patients from 3 public cohorts, including 2 microarray datasets and 1 RNA sequencing dataset. CIBERSORT software, a computational algorithm, was used to calculate the relative levels of immune cells. Three immune microenvironment subtypes were defined via ConsensuClusterPlus package. Univariate and multivariate survival analyses were used to develop an individualized immune prognostic index based on immune cell pairs.

Results

Notably, HCC patients with higher immune signatures score, utterly appreciable, suffered inferior prognosis (hazard ratio=2.742; 95% confidence interval: 1.887–3.983; P<0.001). Subgroup analysis suggested that the prognostic signature did particularly well in early-stage patients. Furthermore, moderate survival prediction value was also confirmed in another two independent cohorts GSE14520 and GSE76427.

Conclusions

This study provides a systematic view of the immune cells characteristics in HCC and suggests their superior survival monitoring performance.

Bioinformatics profiling identifies seven immune-related risk signatures for hepatocellular carcinoma

Background

Density of tumor infiltrating lymphocytes (TIL) and expressions of certain immune-related genes have prognostic and predictive values in hepatocellular carcinoma (HCC); however, factors determining the immunophenotype of HCC patients are still unclear. In the current study, the transcript sequencing data of liver cancer were systematically analyzed to determine an immune gene marker for the prediction of clinical outcome of HCC.

Methods

RNASeq data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and the samples were assigned into high-stage and low-stage groups. Immune pathway-related genes were screened from the Molecular Signatures Database v4.0 (MsigDB) database. LASSO regression analysis was performed to identify robust immune-related biomarkers in predicting HCC clinical outcomes. Moreover, an immune gene-related prognostic model was established and validated by test sets and Gene Expression Omnibus (GEO) external validation sets.

Results

We obtained 319 immune genes from MsigDB, and the genes have different expression profiles in high-stage and low-stage of HCC. Univariate survival analysis found that 17 genes had a significant effect on HCC prognosis, among them, 13 (76.5%) genes were prognostically protective factors. Further lasso regression analysis identified seven potential prognostic markers (IL27, CD1D, NCOA6, CTSE, FCGRT, CFHR1, and APOA2) of robustness, most of which are related to tumor development. Cox regression analysis was further performed to establish a seven immune gene signature, which could stratify the risk of samples in training set, test set and external verification set (p < 0.01), and the AUC in both training set and test set was greater than 0.85, which also greater compared with previous studies.

Conclusion

This study constructed a 7-immunogenic marker as novel prognostic markers for predicting survival of HCC patients.

Insulin-like growth factor 1-induced enolase 2 deacetylation by HDAC3 promotes metastasis of pancreatic cancer

Enolase 2 (ENO2) is a key glycolytic enzyme in the metabolic process of glycolysis, but its potential function in pancreatic ductal adenocarcinoma (PDAC) is unclear. In this study, we observed a significant overexpression of ENO2 in PDAC tissues, and its expression was correlated with metastasis and poor prognosis in PDAC patients. K394 was identified as a major acetylation site in ENO2 that regulates its enzymatic activity, cell metabolism and PDAC progression. Knockdown of ENO2 suppressed tumor growth and liver metastasis in PDAC. Re-expression of wild-type (WT) ENO2, but not the K394 acetylation mimetic mutant, could reverse the decreased tumor malignancy. We further characterized histone deacetylase 3 (HDAC3) and P300/CBP-associated factor (PCAF) as the potential deacetylase and acetyltransferase for ENO2, respectively. HDAC3-mediated deacetylation was shown to lead to ENO2 activation and enhancement of glycolysis. Importantly, insulin-like growth factor-1 (IGF-1) was found to decrease K394 acetylation and stimulate ENO2 activity in a dose- and time-dependent manner. The PI3K/AKT/mTOR pathway facilitated the phosphorylation of HDAC3 on S424, which promoted K394 deacetylation and activation of ENO2. Linsitinib, an oral small-molecule inhibitor of IGF-1R, could inhibit IGF-1-induced ENO2 deacetylation by HDAC3 and the PI3K/AKT/mTOR pathway. Furthermore, linsitinib showed a different effect on the growth and metastasis of PDAC depending on the overexpression of WT versus K394-mutant ENO2. Our results reveal a novel mechanism by which acetylation negatively regulates ENO2 activity in the metastasis of PDAC by modulating glycolysis. Blockade of IGF-1-induced ENO2 deacetylation represents a promising strategy to prevent the development of PDAC.

NCOA5 deficiency promotes a unique liver protumorigenic microenvironment through p21WAF1/CIP1 overexpression, which is reversed by metformin

Prevention and treatment options for hepatocellular carcinoma (HCC) are presently limited, underscoring the necessity for further elucidating molecular mechanisms underlying HCC development and identifying new prevention and therapeutic targets. Here, we demonstrate a unique protumorigenic niche in the livers of Ncoa5+/- mouse model of HCC, which is characterized by altered expression of a subset of genes including p21WAF1/CIP1 and proinflammatory cytokine genes, increased putative hepatic progenitors, and expansions of activated and tissue-resident memory (TRM) CD8+ T lymphocytes, myeloid-derived suppressor cells (MDSCs), and alternatively activated M2 macrophages. Importantly, prophylactic metformin treatment reversed these characteristics including aberrant p21WAF1/CIP1 expression and subsequently reduced HCC incidence in Ncoa5+/- male mice. Heterozygous deletion of the p21WAF1/CIP1 gene alleviated the key features associated with the protumorigenic niche in the livers of Ncoa5+/- male mice. Moreover, transcriptomic analysis reveals that preneoplastic livers of Ncoa5+/- mice are similar to the livers of nonalcoholic steatohepatitis patients as well as the adjacent noncancerous liver tissues of a subset of HCC patients with a relatively poor prognosis. Together, our results suggest that p21WAF1/CIP1 overexpression is essential in the development of protumorigenic microenvironment induced by NCOA5 deficiency and metformin prevents HCC development via alleviating p21WAF1/CIP1 overexpression and protumorigenic microenvironment.

LGR5 marks targetable tumor-initiating cells in mouse liver cancer

Cancer stem cells (CSCs) or tumor-initiating cells (TICs) are thought to be the main drivers for disease progression and treatment resistance across various cancer types. Identifying and targeting these rare cancer cells, however, remains challenging with respect to therapeutic benefit. Here, we report the enrichment of LGR5 expressing cells, a well-recognized stem cell marker, in mouse liver tumors, and the upregulation of LGR5 expression in human hepatocellular carcinoma. Isolated LGR5 expressing cells from mouse liver tumors are superior in initiating organoids and forming tumors upon engraftment, featuring candidate TICs. These cells are resistant to conventional treatment including sorafenib and 5-FU. Importantly, LGR5 lineage ablation significantly inhibits organoid initiation and tumor growth. The combination of LGR5 ablation with 5-FU, but not sorafenib, further augments the therapeutic efficacy in vivo. Thus, we have identified the LGR5⁺ compartment as an important TIC population, representing a viable therapeutic target for combating liver cancer.

Predictive value of hypoxia, metabolism and immune factors for prognosis in hepatocellular carcinoma: a retrospective analysis and multicenter validation study

The tumor microenvironment (TME), as a potent and pervasive factor of tumorigenesis and tumor progression, has a profound impact on the clinical outcomes of hepatocellular carcinoma (HCC). A systematic analysis of TME factors in HCC is still lacking and urgently needed. In this retrospective analysis and multicenter validation study, a total of 987 HCC patients with RNA-seq or microarray data and the corresponding clinical information from five cohorts were included. A TME risk score was developed based on five factors (hypoxia, nucleotide, TCA cycle, T helper cells and activated CD8 T cells). We also identified various types of clinical parameters and molecular features associated with the TME risk score. The TME risk factor network depicts close associations among the factors. Our TME risk score could be a practical and reliable predictor that can stratify patients according to distinct clinical outcomes and was validated by integrating five HCC patient cohorts (HR= 2.27, 95% CI: 1.79-2.86, P<0.001). Pan-cancer analysis also suggested that the prognostic signature was an effective prognostic indicator in 9,122 patients across 30 types of cancer. Correlation analysis revealed that the TME risk score was significantly associated with tumor progression-related clinical factors and molecular factors. TME factors are perturbations in HCC patients, and these alterations are vital determinants of both clinical outcomes and biological characteristics. The TME risk score we proposed is valuable for deciphering the molecular characteristics of the TME in HCC and is an effective prognostic predictor for HCC prognosis evaluation.

The Oncogenic Role of CENPA in Hepatocellular Carcinoma Development: Evidence from Bioinformatic Analysis

OBJECTIVE

This study is aimed at investigating the predictive value of CENPA in hepatocellular carcinoma (HCC) development.

METHODS

Using integrated bioinformatic analysis, we evaluated the CENPA mRNA expression in tumor and adjacent tissues and correlated it with HCC survival and clinicopathological features. A Cox regression hazard model was also performed.

RESULTS

CENPA mRNA was significantly upregulated in tumor tissues compared with that in adjacent tissues, which were validated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (all P < 0.01). In the Kaplan-Meier plotter platform, the high level of CENPA mRNA was significantly correlated with overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and progression-free survival (PFS) in HCC patients (all log rank P < 0.01). For validation in GSE14520 and pan-TCGA dataset, HCC patients with CNEPA mRNA overexpression had poor OS compared with those with low CENPA mRNA (log rank P = 0.025 and P < 0.0001, respectively), and those with high CENPA had poor DFS in TCGA (log rank P = 0.0001). Additionally, CENPA mRNA were upregulated in HCC patients with alpha-fetoprotein (AFP) elevation, advanced TNM stage, larger tumor size, advanced AJCC stage, advanced pathology grade, and vascular invasion (all P < 0.05). A Cox regression model including CENPA, OIP5, and AURKB could predict OS in HCC patients effectively (AUC = 0.683).

CONCLUSION

Overexpressed in tumors, CENPA might be an oncogenic factor in the development of HCC patients.

Genome-wide CRISPR knockout screens identify ADAMTSL3 and PTEN genes as suppressors of HCC proliferation and metastasis, respectively

PURPOSE

It is important for hepatocellular carcinoma (HCC) treatment that the targets related to its progression are identified. Clustered regularly interspaced short palindromic repeat (CRISPR)-associated nuclease 9 (Cas9)-based genetic screening is a powerful tool for identifying genes with loss-of-function mutations that are critical for tumour growth and metastasis.

METHODS

We transduced the human SMMC7721 HCC cell line expressing Cas9 with a human genome-scale CRISPR-Cas9 knockout (GeCKO) lentiviral library A (hGeCKOa) of 65,383 single-guide RNAs (sgRNAs) targeting 19,050 human genes; we then subcutaneously transplanted the transduced cells into nude mice.

RESULTS

The transduced cells were found to proliferate and metastasize faster than the untransduced cells. Through next-generation sequencing, the genes potentially related to HCC proliferation and metastasis were identified. The sgRNAs targeting the ADAMTSL3 and PTEN genes appeared twice on the list of genes related to HCC proliferation and metastasis, respectively. Analysis based on the data mining of Oncomine revealed that the ADAMTSL3 and PTEN genes were expressed at lower levels in HCC cells than they were in normal liver cells, indicating their tumour-suppressive roles. Downregulation of ADAMTSL3 and PTEN displayed poor overall survival (OS) and predicted poor relapse-free survival (RFS), further supporting their tumour-suppressive roles. Moreover, knocking out either the ADAMTSL3 or PTEN genes promoted either the proliferation or metastasis of HCC cells, respectively.

CONCLUSIONS

Using both in vitro and in vivo approaches, we described the profound role of the ADAMTSL3 and PTEN genes. This study indicates novel candidate targets for use in HCC treatment and therapy.

Expression and gene regulation network of RBM8A in hepatocellular carcinoma based on data mining

RNA binding motif protein 8A (RBM8A) is an RNA binding protein in a core component of the exon junction complex. Abnormal RBM8A expression is associated with carcinogenesis. We used sequencing data from the Cancer Genome Atlas database and Gene Expression Omnibus, analyzed RBM8A expression and gene regulation networks in hepatocellular carcinoma (HCC). Expression was analyzed using Oncomine^TM and Gene Expression Profiling Interactive Analysis tools, while RBM8A alterations and related functional networks were identified using cBioPortal. LinkedOmics was used to identify differential gene expression with RBM8A and to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. Gene enrichment analysis examined target networks of kinases, miRNAs and transcription factors. We found that RBM8A is overexpressed and the RBM8A gene often amplified in HCC. Expression of this gene is linked to functional networks involving the ribosome and RNA metabolic signaling pathways. Functional network analysis suggested that RBM8A regulates the spliceosome, ribosome, DNA replication and cell cycle signaling via pathways involving several cancer-related kinases, miRNAs and E2F Transcription Factor 1. Our results demonstrate that data mining efficiently reveals information about RBM8A expression and potential regulatory networks in HCC, laying a foundation for further study of the role of RBM8A in carcinogenesis.

The phosphatidylethanolamine biosynthesis pathway provides a new target for cancer chemotherapy

BACKGROUND & AIMS

Since human induced pluripotent stem cells (iPSCs) develop into hepatic organoids through stages that resemble human embryonic liver development, they can be used to study developmental processes and disease pathology. Therefore, we examined the early stages of hepatic organoid formation to identify key pathways affecting early liver development.

METHODS

Single-cell RNA-sequencing and metabolomic analysis was performed on developing organoid cultures at the iPSC, hepatoblast (day 9) and mature organoid stage. The importance of the phosphatidylethanolamine biosynthesis pathway to early liver development was examined in developing organoid cultures using iPSC with a CRISPR-mediated gene knockout and an over the counter medication (meclizine) that inhibits the rate-limiting enzyme in this pathway. Meclizine's effect on the growth of a human hepatocarcinoma cell line in a xenotransplantation model and on the growth of acute myeloid leukemia cells in vitro was also examined.

RESULTS

Transcriptomic and metabolomic analysis of organoid development indicated that the phosphatidylethanolamine biosynthesis pathway is essential for early liver development. Unexpectedly, early hepatoblasts were selectively sensitive to the cytotoxic effect of meclizine. We demonstrate that meclizine could be repurposed for use in a new synergistic combination therapy for primary liver cancer: a glycolysis inhibitor reprograms cancer cell metabolism to make it susceptible to the cytotoxic effect of meclizine. This combination inhibited the growth of a human liver carcinoma cell line in vitro and in a xenotransplantation model, without causing significant side effects. This drug combination was also highly active against acute myeloid leukemia cells.

CONCLUSION

Our data indicate that phosphatidylethanolamine biosynthesis is a targetable pathway for cancer; meclizine may have clinical efficacy as a repurposed anti-cancer drug when used as part of a new combination therapy.

LAY SUMMARY

The early stages of human liver development were modeled using human hepatic organoids. We identified a pathway that was essential for early liver development. Based upon this finding, a novel combination drug therapy was identified that could be used to treat primary liver cancer and possibly other types of cancer.

Bioinformatics analyses and biological function of lncRNA ZFPM2-AS1 and ZFPM2 gene in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most lethal malignant tumors worldwide; however, the etiology of HCC still remains poorly understood. In the present study, cancer-omics databases, including The Cancer Genome Atlas, GTEx and Gene Expression Omnibus, were systematically analyzed in order to investigate the role of the long non-coding RNA (lncRNA) zinc finger protein, FOG family member 2-antisense 1 (ZFPM2-AS1) and the zinc finger protein, FOG family member 2 (ZFPM2) gene in the occurrence and progression of HCC. It was identified that the expression levels of lncRNA ZFPM2-AS1 were significantly increased in HCC tissues, whereas expression levels of the ZFPM2 gene were significantly decreased in HCC tissues compared with normal liver tissues. Higher expression levels of ZFPM2-AS1 were significantly associated with a less favorable prognosis of HCC, whereas higher expression levels of the ZFPM2 gene were associated with a more favorable prognosis of HCC. Genetic alterations in the ZFPM2 gene may contribute to a worse prognosis of HCC. Validation of the GSE14520 dataset also demon stared that ZFPM2 gene expression levels were significantly decreased in HCC tissues (P<0.001). The receiver operating characteristic (ROC) analysis of the ZFPM2 gene indicated high accuracy of this gene in distinguishing between HCC tissues and non-tumor tissues. The areas under the ROC curves were >0.8. Using integrated strategies, the present study demonstrated that lncRNA ZFPM2-AS1 and the ZFPM2 gene may contribute to the occurrence and prognosis of HCC. These findings may provide a novel understanding of the molecular mechanisms underlying the occurrence and prognosis of HCC.

APEX1 is a novel diagnostic and prognostic biomarker for hepatocellular carcinoma

In this study, we analyzed the expression and clinical significance of apyrimidinic endodeoxyribonuclease 1 (APEX1) in hepatocellular carcinoma (HCC). The APEX1 mRNA and protein levels were significantly higher in HCC than adjacent normal liver tissues in multiple datasets from the Oncomine, GEO and TCGA databases. APEX1 levels were significantly higher in early-stage HCC patients with low alpha-fetoprotein expression. The positive predictive value (PPV) for APEX1 was significantly higher than the PPV for alpha-fetoprotein (67.91% vs. 55.22%) in HCC patients. High APEX1 expression correlated with resistance to sorafenib and anti-programmed death 1 (PD-1) therapies in HCC patients, and it associated with poorer overall survival, disease-specific survival, progression-free survival, and relapse-free survival in early- and advanced-stage HCC patients. High APEX1 expression also associated with poor prognosis in non-alcoholic, vascular invasion-negative, and hepatitis virus-negative HCC patients. These data suggest that APEX1 is a better diagnostic and prognostic biomarker than alpha-fetoprotein in HCC. Gene set enrichment analysis (GSEA) showed that APEX1 expression correlated with the DNA damage repair pathway in HCC tissues. These findings demonstrate that APEX1 is a potential diagnostic and prognostic biomarker in HCC.

High Levels of BMP2 Promote Liver Cancer Growth via the Activation of Myeloid-Derived Suppressor Cells

Bone morphogenetic protein 2 (BMP2) signaling had significant roles in diverse pathological processes, such as cancer. Nevertheless, the interaction between BMP2 and carcinoma development remained largely unknown. In particular, the roles that BMP2 play in the development of liver cancer remained controversial, and mechanisms were unclear. BMP2 with strong osteogenic potential had been manufactured into various bone materials. However, cancer risk concerns were raised in recent years. Thus, we focused on analyzing the effects of exogenous BMP2 on the growth of liver cancer and the detailed mechanisms. We found that both intravenous injection of rhBMP2 and in vivo implantation of rhBMP2 materials could lead to the expansion of myeloid-derived suppressor cells (MDSCs) in peripheral blood and subsequently enhanced the infiltration of MDSCs into tumor in vivo. Furthermore, BMP2 signaling-activated MDSCs could secrete IL6 to enhance cell proliferation of liver cancer cells in vitro and facilitate liver cancer growth in vivo. Our study indicated that increased concentration of BMP2 within the peripheral blood could enhance liver cancer growth via the activation of MDSCs. In this study, the roles that BMP2 played in liver cancer growth were further confirmed and the detailed mechanisms about how BMP2 enhanced liver cancer growth were also elucidated.

Biglycan as a potential diagnostic and prognostic biomarker in multiple human cancers

Biglycan (BGN), a key member of the small leucine-rich proteoglycan family, is an important component of the extracellular matrix. Clinical studies have demonstrated that upregulation of BGN is associated with poor prognosis in patients with various types of solid cancer. The present study analyzed the mRNA expression levels of BGN in various types of solid cancer when compared with that in normal tissues via the Oncomine database. The UALCAN, OncoLnc and Kaplan-Meier Plotter databases were additionally used to evaluate the prognostic values of BGN in patients with solid cancer and co-expression gene analysis was conducted using the protein-protein interaction networks of BGN. The present study observed that the mRNA expression levels of BGN were increased in bladder, brain and central nervous system, breast, colorectal, esophageal, gastric, head and neck, lung, ovarian and 28 subtypes of cancer compared with normal tissues. The increased expression of BGN was identified to be associated with a poor outcome in ovarian and gastric cancer. Based on the co-expression network, BGN was identified as the key gene in a 43-gene network. The present findings of increased expression of BGN in solid tumors and its positive association with poor outcome on patient survival indicate that BGN may serve as a prognostic marker and as a target for novel therapeutics for multiple types of cancer.

Genome-wide screening diagnostic biomarkers and the construction of prognostic model of hepatocellular carcinoma

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in decades, the overall survival (OS) of HCC remains dissatisfactory, so it is particularly important to find better diagnostic and prognostic biomarkers. In this study, we found a more reliable potential diagnostic biomarkers and constructed a more accurate prognostic evaluation model based on integrated transcriptome sequencing analysis of multiple independent data sets. First, we performed quality evaluation and differential analysis on seven Gene Expression Omnibus (GEO) data sets, and then comprehensively analyzed the differentially expressed genes with a robust rank aggregation algorithm. Next, Least absolute shrinkage and selection operator (LASSO) regression was used to establish an 8-gene prognostic risk score (RS) model. Finally, the prognostic model was further validated in the GEO data set. Also, RS has independence on other clinicopathological characteristics but has similarities in prognostic assessment compared with the T stage. Moreover, the combination of T stage and prognostic RS model based on the 8-gene had a better prognostic evaluation effect. In brief, our research suggest that the prognostic risk model of 8 genes has important clinical significance in HCC patients, and can further enrich the prognostic guidance value of the traditional T stage.

Integrative module analysis of HCC gene expression landscapes

Despite hepatocellular carcinoma (HCC) being a common cancer globally, its initiation and progression are not well understood. The present study was designed to investigate the hub genes and biological processes of HCC, which change substantially during its progression. Three gene expression profiles of 480 patients with HCC were obtained from the Gene Expression Omnibus database. Subsequent to performing functional annotations and constructing protein-protein interaction (PPI) networks, 657 differentially expressed genes were identified, which were subsequently used to screen candidate hub genes. PPI networks were modularized using the weighted gene correlation network analysis algorithm, the topological overlapping matrix and the hierarchical cluster tree, which were utilized via STRING. Clinical data obtained from The Cancer Genome Atlas were then analyzed to validate the experiments performed using six hub genes. Additionally, a transcription factor and microRNA-mRNA network were constructed to determine the potential regulatory mechanisms of six hub genes. The results revealed that the oxidation-reduction process and cell cycle associated processes were markedly involved in HCC progression. Six highly expressed genes, including cyclin B2, cell division cycle 20, mitotic arrest deficient 2 like 1, minichromosome maintenance complex component 2, centromere protein F and BUB mitotic checkpoint serine/threonine kinase B, were confirmed as hub genes and validated via experiments associated with cell division. These hub genes are necessary for confirmatory experiments and may be used in clinical gene therapy as biomarkers or drug targets.

Downregulation of orosomucoid 2 acts as a prognostic factor associated with cancer-promoting pathways in liver cancer

BACKGROUND

Liver cancer has a high mortality and morbidity rate throughout the world. In clinical practice, the prognosis of liver cancer patients is poor, and the complex reasons contribute to treatment failures, including fibrosis, hepatitis viral infection, drug resistance and metastasis. Thus, screening novel prognostic biomarkers is of great importance for guiding liver cancer therapy. Orosomucoid genes (ORMs) encode acute phase plasma proteins, including orosomucoid 1 (ORM1) and ORM2. Previous studies showed their upregulation upon inflammation, but the specific function of ORMs has not yet been determined, especially in the development of liver cancer.

AIM

To determine the expression of ORMs and their potential function in liver cancer.

METHODS

Analysis of the expression of ORMs in different human tissues was performed on data from the HPA RNA-seq normal tissues project. The expression ratio of ORMs was determined using the HCCDB database, including the ratio between liver cancer and other cancers, normal liver and other normal tissues, liver cancer and adjacent normal liver tissues. Analysis of ORM expression in different cancer types was performed using The Cancer Genome Atlas and TIMER database. The expression of ORMs in liver tumor tissues and adjacent normal tissues were further confirmed using Gene Expression Omnibus data, including GSE36376 and GSE14520. The 10-year overall survival (OS), progression-free survival (PFS) and relapse-free survival (RFS) rates between high and low ORM expression groups in liver cancer patients were determined using the Kaplan-Meier plotter tool. Gene Set Enrichment Analysis (GSEA) was employed to explore the ORM2-associated signaling network. Correlations between ORM2 expression and tumor purity or the infiltration level of macrophages in liver tumor tissues were determined using the TIMER database. The correlation between ORM2 gene levels, tumor-associated macrophage (TAM) markers (including CD68 and TGFβ1) and T cell immunosuppression (including CTLA4 and PD-1) in liver tumor tissues and liver GTEx was determined using the GEPIA database.

RESULTS

ORM1 and ORM2 were highly expressed in normal liver and liver tumor tissues. ORM1 and ORM2 expression was significantly decreased in liver tumor tissues compared with adjacent normal tissues, and similar results were also noted in cholangiocarcinoma, esophageal carcinoma, and lung squamous cell carcinoma. Further analysis of the Gene Expression Omnibus Database also confirmed the downregulation of ORM1 and ORM2 in liver tumors. Survival analysis showed that the high ORM2 group had better survival rates in OS, PFS and RFS. ORM1 only represented better performance in PFS, but not in OS or RFS. GSEA analysis of ORM2 from The Cancer Genome Atlas liver cancer data identified that ORM2 positively associated with the G2/M checkpoint, E2F target signaling, as well as Wnt/β-catenin and Hedgehog signaling. Moreover, apoptosis, IFN-α responses, IFN-γ responses and humoral immune responses were upregulated in the ORM2 high group. ORM2 expression was negatively correlated with the macrophage infiltration level, CD68, TGFβ1, CTLA4 and PD-1 levels.

CONCLUSION

The results showed that ORM1 and ORM2 were highly expressed specifically in liver tissues, whereas ORM1 and ORM2 were downregulated in liver tumor tissues. ORM2 is a better prognostic factor for liver cancer. Furthermore, ORM2 is closely associated with cancer-promoting pathways.

Angiogenic Factor with G Patch and FHA Domains 1 (AGGF1) Acts as Diagnostic Biomarker and Adverse Prognostic Factor of Hepatocellular Carcinoma (HCC): Evidence from Bioinformatic Analysis

Background

Angiogenic factor with G patch and FHA domains 1 (AGGF1) is a novel identified initiator of angiogenesis through promoting the proliferation of endothelial cells. The continuous angiogenesis plays a key role in the growth, invasion, and metastasis of hepatocellular carcinoma (HCC), while the diagnostic and prognostic roles of AGGF1 for HCC need to be further studied.

Material/Methods

The mRNA sequencing datasets and clinical features of HCC patients were extracted from The Cancer Genome Atlas database. The relationship between clinical features and AGGF1 expression was analyzed by Wilcoxon test. Further validation explorations were carried out using online database Oncomine. The diagnostic receiver operating characteristic curves of AGGF1 and alpha-fetoprotein were compared to examine the diagnostic efficacy of AGGF1. Survival analysis and Gene Set Enrichment Analysis were performed to explore the prediction value and potential mechanism of AGGF1 dysregulation in HCC.

Results

Comprehensive overexpression of AGGF1 was observed in HCC, correlating with poor overall survival. Upregulated level of AGGF1 was statistically associated with poor differentiated histological grade, advanced cancer stage and T classification. AGGF1 was a more effective diagnostic marker than alpha-fetoprotein in HCC. Several important pathways related to HCC including pathway in cancer and P53 signaling pathway were differentially enriched in the high AGGF1 expression phenotype.

Conclusions

AGGF1 was a potential diagnostic and prognostic marker for poor clinical outcomes in HCC patients. Moreover, vital pathways regulated by AGGF1 in HCC may include regulation of autophagy, Wnt signaling pathway, pathway in cancer, cell cycle, and P53 signaling pathway.

Development and validation of a prognostic classifier based on HIF-1 signaling for hepatocellular carcinoma

HIF-1 (hypoxia-inducible factor 1) signaling played a vital role in HCC (hepatocellular carcinoma) prognosis. We aimed to establish an accurate risk scoring system for HCC prognosis prediction and treatment guidance. 424 samples from TCGA (The Cancer Genome Atlas) and 445 samples from GSE14520 dataset were included as the derivation and validation cohort, respectively. In the derivation cohort, prognostic relevant signatures were selected from sixteen HIF-1 related genes and LASSO regression was adopted for model construction. Tumor-infiltrating immune cells were calculated using CIBERSORT algorithm. HIF-1 signaling significantly increased in HCC samples compared with normal tissues. Scoring system based on SLC2A1, ENO1, LDHA and GAPDH exhibited a continuous predictive ability for OS (overall survival) in HCC patients. PCA and t-SNE analysis confirmed a reliable clustering ability of risk score in both cohorts. Patients were classified into high-risk and low-risk groups and the survival outcomes between the two groups showed significant differences. In the derivation cohort, Cox regression indicated the scoring system was an independent predictor for OS, which was validated in the validation cohort. Different infiltrating immune cells fraction and immune scores were also observed in different groups. Herein, a novel integrated scoring system was developed based on HIF-1 related genes, which would be conducive to the precise treatment of patients.

Cancer stem cell-specific expression profiles reveal emerging bladder cancer biomarkers and identify circRNA_103809 as an important regulator in bladder cancer

Bladder cancer stem cells (BCSCs), exhibiting self-renewal and differentiation capacities, may contribute to the tumor initiation, metastasis, recurrence and drug resistance of bladder cancer. However, the underlying functional mechanisms of BCSCs remain to be clarified. In this study, we describe the differentially-expressed mRNAs, lncRNAs, and circRNAs in BCSCs compared with that in bladder cancer non-stem cells (BCNSCs) through the transcriptome microarray data analysis using bladder cancer patients’ specimens. CircRNA_103809, the top one among the highly expressed circRNA identified in BCSCs, promotes the self-renewal, migration and invasion capabilities of bladder cancer by acting as a miR-511 sponge. Additionally, GO and KEGG pathway analysis suggest the differentially expressed genes identified may be involved in the cellular metabolism, differentiation and metastasis regulation of the cancer cells. Co-expression networks of lncRNAs/mRNAs and circRNAs/mRNAs constructed by WGCNA give a picture of the non-coding/coding RNAs regulating patterns in BCSCs. Notably, as core genes in the networks, AHCY, C6orf136 and LRIG1 show high potential to be prognosticators for bladder cancer. Therefore, further studies of non-coding RNA functional mechanisms in BCSCs is valuable for detecting the pathogenic mechanisms and discovering novel biomarkers in bladder cancer.

Oncogene PLCE1 may be a diagnostic biomarker and prognostic biomarker by influencing cell cycle, proliferation, migration, and invasion ability in hepatocellular carcinoma cell lines

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide. HCC has traits of late diagnosis and high recurrence. This study explored potential diagnosis and prognosis significance of phospholipase C epsilon 1 (PLCE1) in HCC. The messenger RNA (mRNA) levels and diagnostic value of PLCE1 were determined by real-time polymerase chain reaction and online databases GEPIA, oncomine, and GSE14520 data set. Survival analysis used the Kaplan-Meier Plotter website. Cell cycle, proliferation, migration, and invasion assays were performed with downregulated PLCE1 expression in HCC-M and HepG2 cell lines. PLCE1 was differentially expressed and highly expressed in tumors and had low expression in nontumor tissues (all p < .05). The diagnostic value of PLCE1 was validated with the datasets (all p < .01, all areas under curves > 0.7). PLCE1 mRNA expression was associated with the overall and relapse-free survival (both p < .05). Functional experiments indicated that downregulation of PLCE1 expression led to increased G1 stage in cell cycle and decreased cell proliferation, migration, and invasion compared with a negative control group (all p ≤ .05). The oncogene PLCE1 was differentially expressed in HCC and non-HCC tissues. It is a candidate for diagnosis and serves as prognosis biomarker. PLCE1 influenced survival by affecting the cell cycle, proliferation, migration, and invasion ability.

Transmembrane protein 106C promotes the development of hepatocellular carcinoma

Several protein-coding genes have been identified to play essential roles in cancer biology, and they are dysregulated in many tumors. Transmembrane protein 106C (TMEM106C) is differentially expressed in several human and porcine diseases; however, the expression and biological functions of TMEM106C in hepatocellular carcinoma (HCC) are not clear. In our study, we obtained paired tissue samples from patients undergoing resection for HCC and public databases, which were analyzed for TMEM106C expression using quantitative real-time polymerase chain reaction (qRT-PCR). We further conducted in vitro and in vivo experiments in HCC cell lines and nude mice, respectively, in which TMEM106C was overexpressed or knocked down. Cell-Counting Kit-8 and colony formation experiments were used to determine the influence of TMEM106C on cell proliferation, flow cytometric assays were used to detect the influence on cell cycle distribution and apoptosis, and transwell assays were used for detecting changes in cell migration and invasion. TMEM106C levels were significantly elevated in HCC tissues and cell lines from public databases and our collected specimens from patients. Moreover, higher TMEM106C expression levels predicted a poor prognosis in HCC patients in survival analysis. Overexpression of TMEM106C in HCC cells accelerated cell growth, migration, and invasion, but it inhibited cell apoptosis by targeting forkhead box O-1 (FOXO1) and FOXO3. Conversely, TMEM106C knockdown impeded cell proliferation and metastasis, whereas it enhanced the rate of apoptosis. More important, knockdown of the expression of TMEM106C in HCC cells inhibited the growth of xenograft tumors in vivo. Collectively, these results suggest that TMEM106C acts as an oncogene and can serve as a potential therapeutic target for HCC in the future.

Expression, immune infiltration and clinical significance of SPAG5 in hepatocellular carcinoma: A gene expression-based study

BACKGROUND

Overexpression of sperm-associated antigen 5 (SPAG5) is a marker of poor prognosis in numerous tumors and is recognized as an index of tumor proliferation; however, its expression in liver cancer remains unclear.

METHODS

The Oncomine (https://www.oncomine.org) and Timer (https://cistrome.shinyapps.io/timer) databases were used to analyze the expression of SPAG5 in liver hepatocellular carcinoma (HCC) and normal liver tissues. The relationship between the expression of SPAG5 and immune infiltration of HCC was investigated using the Timer and GEPIA (http://gepia.cancer-pku.cn) databases, and the mechanism was analyzed using Gene Set Enrichment Analysis. A Kaplan-Meier Plotter (http://kmplot.com/analysis) was used to evaluate the effect of SPAG5 on the prognosis of patients with HCC.

RESULTS

The results revealed that the SPAG5 expression level was positively correlated with the infiltration levels of CD8⁺ T cells, macrophages, neutrophils, and especially B cells and dendritic cells. In addition, SPAG5 expression was significantly associated with T cell exhaustion. The overall survival time, progression-free survival time, recurrence-free survival time and disease-specific survival time were significantly reduced for HCC patients with high SPAG5 expression (p < 0.01) and high expression of SPAG5 was significantly associated with a poor overall survival time and progression-free survival time of grade and stage II-III HCC (p < 0.05) but not with stage I HCC (p > 0.05). Additionally, the expression of SPAG5 is related to the p53 and cell cycle signal pathways.

CONCLUSIONS

In conclusion, SPAG5 is not only a marker of immune infiltration and poor prognosis, but also a potential therapeutic target for liver cancer.

TUG1 Is a Regulator of AFP and Serves as Prognostic Marker in Non-Hepatitis B Non-Hepatitis C Hepatocellular Carcinoma

Thyroid hormone (T₃) and its receptor (TR) are involved in cell metabolism and cancer progression. Hypothyroidism is associated with significantly elevated risk of hepatocellular carcinoma (HCC). Levels of the glycoprotein alpha-fetoprotein (AFP) are increased in the majority of patients with HCC and may be useful in diagnosis and follow-up. However, the relationship between T₃/TR and AFP levels in HCC is currently unclear. The expression profiles of long non-coding RNAs (lncRNAs) were compared in microarrays of HepG2-TRα1 cells treated with/without T₃ and HCC specimens. The effects of T₃ on taurine upregulated gene 1 (TUG1) and AFP expression were validated using qRT-PCR. A correlation between TUG1 and AFP was confirmed via RNAi and clustered regularly interspaced short palindromic repeats (CRISPR) strategies. Finally, overall and recurrence-free survival rates were analyzed using the Kaplan–Meier method and confirmed in online datasets. T₃/TR treatment reduced TUG1 expression in vitro, resulting in the downregulation of AFP mRNA. Knockdown of TUG1 suppressed cell cycle progression and soft agar colony formation and induced cellular senescence. Our data support the involvement of TUG1 in the T₃/TR-mediated suppression of cell growth. AFP mRNA levels showed strong positive correlations with TUG1 and unfavorable prognosis in patients with non-hepatitis B/non-hepatitis C HCC (NBNC-HCC). T₃/TR, TUG1, and AFP may potentially serve as effective prognostic markers for NBNC-HCC.

Novel candidate biomarkers of origin recognition complex 1, 5 and 6 for survival surveillance in patients with hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) has high morbidity and mortality and lacks effective biomarkers for early diagnosis and survival surveillance. Origin recognition complex (ORC), consisting of ORC1-6 isoforms, was examined to assess the potential significance of ORC isoforms for HCC prognosis. Methods: Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases were used to examine differential isoform expression, stage-specific expression, calculate Pearson correlations and perform survival analysis. A human protein atlas database was utilized to evaluate the protein expression of ORCs in liver tissue. The cBioPortal database was used to assess isoform mutations and the survival significance of ORCs in HCC. Cytoscape software was employed to construct gene ontologies, metabolic pathways and gene-gene interaction networks. Results: Differential expression analysis indicated that ORC1 and ORC3-6 were highly expressed in tumor tissues in the Oncomine and GEPIA databases, while ORC2 was not. All the ORCs were showed positive and statistically significant correlations with each other (all P<0.001). ORC1-2 and ORC4-6 expressions were associated with disease stages I-IV (all P<0.05), but ORC3 was not. Survival analysis found that ORC1 and ORC4-6 expressions were associated with overall survival (OS), and ORC1-3 and ORC5-6 expression were associated with recurrence-free survival (RFS; all P<0.05). In addition, low expression of these ORC genes consistently indicated better prognosis compared with high expression. Protein expression analysis revealed that ORC1 and ORC3-6 were expressed in normal liver tissues, whereas ORC2 was not. Enrichment analysis indicated that ORCs were associated with DNA metabolic process, sequence-specific DNA binding and were involved in DNA replication, cell cycle, E2F-enabled inhibition of pre-replication complex formation and G1/S transition. Conclusions: Differentially expressed ORC1, 5 and 6 are candidate biomarkers for survival prediction and recurrence surveillance in HCC.

An Integrated Model Based on a Six-Gene Signature Predicts Overall Survival in Patients With Hepatocellular Carcinoma

Background: Nowadays, clinical treatment outcomes of patients with hepatocellular carcinoma (HCC) have been improved. However, due to the complexity of the molecular mechanisms, the recurrence rate and mortality in HCC inpatients are still at a high level. Therefore, there is an urgent need in screening biomarkers of HCC to show therapeutic effects and improve the prognosis. Methods: In this study, we aim to establish a gene signature that can predict the prognosis of HCC patients by downloading and analyzing RNA sequencing data and clinical information from three independent public databases. Firstly, we applied the limma R package to analyze biomarkers by the genetic data and clinical information downloaded from the Gene Expression Omnibus database (GEO), and then used the least absolute shrinkage and selection operator (LASSO) Cox regression and survival analysis to establish a gene signature and a prediction model by data from the Cancer Genome Atlas (TCGA). Besides, messenger RNA (mRNA) and protein expressions of the six-gene signature were explored using Oncomine, Human Protein Atlas (HPA) and the International Cancer Genome Consortium (ICGC). Results: A total of 8,306 differentially expressed genes (DEGs) were obtained between HCC (n = 115) and normal tissues (n = 52). Top 5,000 significant genes were selected and subjected to the weighted correlation network analysis (WGCNA), which constructed nine gene co-expression modules that assign these genes to different modules by cluster dendrogram trees. By analyzing the most significant module (red module), six genes (SQSTM1, AHSA1, VNN2, SMG5, SRXN1, and GLS) were screened by univariate, LASSO, and multivariate Cox regression analysis. By a survival analysis with the HCC data in TCGA, we established a nomogram based on the six-gene signature and multiple clinicopathological features. The six-gene signature was then validated as an independent prognostic factor in independent HCC cohort from ICGC. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the six-gene signature and nomogram. Besides, overexpression of the six genes at the mRNA and protein levels was validated using Oncomine and HPA, respectively. Conclusion: The predictive six-gene signature and nomograms established in this study can assist clinicians in selecting personalized treatment for patients with HCC.

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Sorafenib Inhibits Ribonucleotide Reductase Regulatory Subunit M2 (RRM2) in Hepatocellular Carcinoma Cells

The main curative treatments for hepatocellular carcinoma (HCC) are surgical resection and liver transplantation, which only benefits 15% to 25% of patients. In addition, HCC is highly refractory and resistant to cytotoxic chemotherapy. Although several multi-kinase inhibitors, such as sorafenib, regorafenib, and lenvatinib, have been approved for treating advanced HCC, only a short increase of median overall survival in HCC patients was achieved. Therefore, there is an urgent need to design more effective strategies for advanced HCC patients. Human ribonucleotide reductase is responsible for the conversion of ribonucleoside diphosphate to 2′-deoxyribonucleoside diphosphate to maintain the homeostasis of nucleotide pools. In this study, mining the cancer genomics and proteomics data revealed that ribonucleotide reductase regulatory subunit M2 (RRM2) serves as a prognosis biomarker and a therapeutic target for HCC. The RNA sequencing (RNA-Seq) analysis and public microarray data mining found that RRM2 was a novel molecular target of sorafenib in HCC cells. In vitro experiments validated that sorafenib inhibits RRM2 expression in HCC cells, which is positively associated with the anticancer activity of sorafenib. Although both RRM2 knockdown and sorafenib induced autophagy in HCC cells, restoration of RRM2 expression did not rescue HCC cells from sorafenib-induced autophagy and growth inhibition. However, long-term colony formation assay indicated that RRM2 overexpression partially rescues HCC cells from the cytotoxicity of sorafenib. Therefore, this study identifies that RRM2 is a novel target of sorafenib, partially contributing to its anticancer activity in HCC cells.

TAZ target gene ITGAV regulates invasion and feeds back positively on YAP and TAZ in liver cancer cells

The Hippo pathway effectors yes-associated protein (YAP) and WW domain containing transcription regulator 1 (TAZ/WWTR1) support tumor initiation and progression in various cancer entities including hepatocellular carcinoma (HCC). However, to which extent YAP and TAZ contribute to liver tumorigenesis via common and exclusive molecular mechanisms is poorly understood. RNAinterference (RNAi) experiments illustrate that YAP and TAZ individually support HCC cell viability and migration, while for invasion additive effects were observed. Comprehensive expression profiling revealed partly overlapping YAP/TAZ target genes as well as exclusively regulated genes. Integrin-αV (ITGAV) is a novel TAZ-specific target gene, whose overexpression in human HCC patients correlates with poor clinical outcome, TAZ expression in HCCs, and the abundance of YAP/TAZ target genes. Functionally, ITGAV contributes to actin stress fiber assembly, tumor cell migration and invasion. Perturbation of ITGAV diminishes actin fiber formation and nuclear YAP/TAZ protein levels. We describe a novel Hippo downstream mechanism in HCC cells, which is regulated by TAZ and ITGAV and that feedbacks on YAP/TAZ activity. This mechanism may represent a therapeutic target structure since it contributes to signal amplification of oncogenic YAP/TAZ in hepatocarcinogenesis.

Comprehensive analysis of biological networks and the eukaryotic initiation factor 4A-3 gene as pivotal in hepatocellular carcinoma

Eukaryotic initiation factor 4A-3 (EIF4A3) is a core component of the exon junction complex (EJC). Abnormalities in EIF4A3 are associated with carcinogenesis. The present study aimed to determine the biological role of EIF4A3 in hepatocellular carcinoma (HCC). Our study is based on the analysis of HCC sequencing data from public databases. We first used the Gene Expression Profiling Interactive Analysis tool and ONCOMINE to analyze the EIF4A3 expression, and the results were validated in human clinical tissues by a quantitative real-time polymerase chain reaction, Western blot, and immunohistochemical. Then, we used cBioPortal to identify EIF4A3 alterations and function networks. Finally, we created a network of genes that were positively correlated with EIF4A3 using LinkedOmics, and analyzed this network using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. For the genes identified, we also analyzed the relevant kinase and transcription factor target networks as well as the protein-protein interaction networks. Our results show that EIF4A3 was overexpressed in HCC tissues in comparison with normal tissues, and high EIF4A3 expression was significantly associated with poor prognosis. Analysis of the functional networks of genes that were co-occurring with EIF4A3 amplification revealed connections with several chemokine signaling pathways. Furthermore, genes that positively correlated with EIF4A3 were mainly related to cell cycle and spliceosome pathways, several cell cycle regulatory kinases, and tumor-associated transcription factors. Finally, crosslinking-immunoprecipitation and high-throughput sequencing (CLIP-seq) data showed that EIF4A3 protein binds to multiple exon regions of the cell cycle regulatory genes cyclin-dependent kinases 1 and 2 and transcription factor E2F1. Our study unveils potential biological networks in HCC and the pivotal role of EIF4A3 as a bridging protein, highlighting the need for an in-depth study of EIF4A3 in carcinogenesis.

Decreased DC-SIGNR expression in hepatocellular carcinoma predicts poor patient prognosis

Dendritic cell-specific intercellular adhesion molecule-grabbing non-integrin-related protein (DC-SIGNR) is a transmembrane receptor primarily involved in pathogen recognition by the innate immune system, with particular importance for viral recognition. DC-SIGNR may also be associated with tumorigenesis. The aim of the present study was to investigate the association between DC-SIGNR expression, development of hepatocellular carcinoma (HCC), and clinicopathological features. Immunohistochemistry was used to assess DC-SIGNR protein expression in HCC and paired non-cancerous tissue samples. DC-SIGNR expression was lower in HCC tissues compared with adjacent non-tumor tissue samples. The expression of DC-SIGNR was associated with small tumor size, low Edmondson grade and high patient long term survival rates. Bioinformatics analyses were performed on several datasets to assess the potential function of DC-SIGNR and related genes; the data revealed that DC-SIGNR mRNA expression was lower in HCC tissues compared with non-cancerous controls, and analyses of ten-year survival rates indicated patients with low DC-SIGNR expression exhibited shorter average survival times. In conclusion, decreased DC-SIGNR expression in HCC tissues may be a relevant predictive biomarker of clinical prognosis, in addition to being a viable therapeutic target for HCC treatment.