Emerging biomarkers in HCC patients: Current status

Integrating network pharmacology, bioinformatics, and experimental validation to unveil the molecular targets and mechanisms of galangin for treating hepatocellular carcinoma

BACKGROUND

Galangin, a flavonoid compound, is derived from Alpinia officinarum Hance. Previous studies have shown that galangin can inhibit the proliferation of hepatocellular carcinoma (HCC), but its mechanism is still unclear. This study aims to investigate the potential targets and molecular mechanisms of galangin on HCC through network pharmacology, bioinformatics, molecular docking, and experimental in vitro validation.

METHODS

In this study, network pharmacology was used to investigate the targets and mechanisms of galangin in the treatment of HCC. AutoDockTools software was used to simulate and calculate the binding of galangin to its core targets. GO and KEGG enrichment analyses were conducted in the DAVID database to explore the main biological functions and signaling pathways impacted by galangin intervention. In addition, bioinformatics was applied to examine the correlation between the differential expressions of the anti-HCC core targets of galangin and the survival of patients with HCC. Finally, the findings obtained from network pharmacology and bioinformatics were verified in cell experiments.

RESULTS

A total of 67 overlapping target genes of galangin and HCC were identified. Through the analysis of the protein-protein interaction (PPI) network, 10 hub genes with the highest degree of freedom were identified, including SRC, ESR1, MMP9, CDK4, CCNB1, MMP2, CDK2, CDK1, CHK1, and PLK1. These genes were found to be closely related to the degradation of the extracellular matrix, signal transduction, and the cell cycle. GO and KEGG enrichment analyses revealed that galangin exerts an anti-HCC role by affecting various signaling pathways, including the cell cycle, pathways in cancer, and the PI3K-Akt signaling pathway. The results of molecular docking indicated a significant interaction between galangin and CCNB1, CDK4, CDK1, and PLK1. Bioinformatics analysis revealed that CCNB1, CDK4, CDK1, and PLK1 were upregulated in the liver of patients with HCC at both the mRNA and protein levels. Flow cytometry analysis showed that galangin induced G0/G1 phase arrest and cell apoptosis in HepG2 and Huh7 cells. Additionally, galangin suppressed the expression of key proteins and mRNAs involved in the cell cycle pathway.

CONCLUSIONS

These results suggest that galangin inhibits the growth of HCC cells by arresting the cell cycle at the G0/G1 phase.

The regulation of hypoxia-related lncRNAs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is still a public health disease with its high prevalence and morbidity. Short of early diagnosis biomarkers and effective therapy, the treatment of HCC patients hasn't achieved ideal effect. Hypoxia is a hallmark of HCC, which is mainly induced by imbalance of tumor cell proliferation and insufficient supply of oxygen. Recently, amounting evidence suggested lncRNAs, especially hypoxia-related lncRNAs play a pivotal role in regulating HCC. Hypoxia-related lncRNAs are involved in altering glucose metabolism, maintaining of cancer stem cell-like properties (CSCs), cell apotosis, proliferation and immune escape, which all contribute to the poor prognosis of HCC patients. The novel identified hypoxia-related lncRNAs could be the potential target or biomarkers of HCC, which are beneficial to the clinical treatment. Herein, we summarized currently reported hypoxia-related lncRNAs and their related mechanisms, providing potential application and future perspective of hypoxia-related lncRNAs as a potential therapeutic target.

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

Artificial Intelligence-Driven Platform: Unveiling Critical Hepatic Molecular Alterations in Hepatocellular Carcinoma Development

Since most Hepatocellular Carcinoma (HCC) typically arises as a consequence of long-term liver damage, the hepatic molecular characteristics are closely related to the occurrence of HCC. Gaining comprehensive information about the location, morphology, and hepatic molecular alterations related to HCC is essential for accurate diagnosis. However, there is a dearth of technological advancements capable of concurrently providing precise HCC diagnosis and discerning the accompanying hepatic molecular alterations. In this study, an integrated information system is developed for the pathological-level diagnosis of HCC and the revelation of critical molecular alterations in the liver. This system utilizes computed tomography/Surface-enhanced Raman scattering combined with an artificial intelligence strategy to establish connections between the occurrence of HCC and alterations in hepatic biomolecules. Employing artificial intelligence techniques, the SERS spectra from both healthy and HCC groups are successfully classified into two distinct categories with a remarkable accuracy rate of 91.38%. Based on molecular profiling, it is identified that the nucleotide-to-lipid signal ratio holds significant potential as a reliable indicator for the occurrence of HCC, thereby serving as a promising tool for prevention and therapeutic surveillance.

The chemokine CCL20 can assist AFP in serological diagnosis of hepatocellular carcinoma

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P < 0.05); The AUC of ROC curve to distinguish HCC patients from healthy controls was 0.859, the sensitivity was 73.42%, and the specificity was 86.84%. After combination with AFP, the AUC increased to 0.968, the sensitivity was 88.16%, and the specificity was 97.37%. Although CCL20 was increased in the serum of patients with benign liver diseases, combined with AFP, the AUC to distinguish HCC patients from non-HCC cohorts (benign liver disease group and healthy control group) was 0.902, with a sensitivity of 91.67% and a specificity of 75.26%. Collectively, serum CCL20 is closely related to the occurrence of HCC, and detection of serum CCL20 can assist AFP in improving the diagnostic sensitivity of HCC.

PGK1 is a potential biomarker for early diagnosis and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a common type of liver cancer, is increasing in incidence worldwide. An early diagnosis of hepatocellular carcinoma (HCC) is still challenging: Currently, few biomarkers are available to diagnose the early stage of HCC, therefore, additional prognostic biomarkers are required to identify potential risk factors. The present study analyzed gene expression levels of HCC tissue samples and the protein expression levels obtained from the GSE46408 HCC dataset using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The metabolically associated differentially expressed genes (DEGs), including DEGs involved in the glucose metabolism pathway, were selected for further analysis. Phosphoglycerate kinase 1 (PGK1), a glycolytic enzyme, was determined as a potential prognostic biomarker through Kaplan-Meier curve and clinical association variable analyses. This was also verified based on the expression levels of PGK1 in tumor tissue and protein expression levels in several liver cancer cell lines. PGK1 mRNA demonstrated a high level of expression in HCC tissue and was significantly associated with a poor prognosis, showing a negative association with survival time. In addition, as an independent risk factor, PGK1 may potentially be a valuable prognostic biomarker for patients with HCC. Furthermore, expression of PGK1 was associated with the early stages (stage I and T1) of HCC. Moreover, PGK1 mRNA expression levels demonstrated a positive association with progression of liver cancer. The results suggested that PGK1 mRNA may be involved in the degree of HCC malignancy and may be a future potential prognostic biomarker for HCC progression.

SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer

BACKGROUND

The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution.

METHODS

We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers).

RESULTS

We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies.

CONCLUSIONS

Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

Insights into the history and tendency of liver transplantation for liver cancer: a bibliometric-based visual analysis

Research on liver transplantation (LT) for liver cancer has gained increasing attention. This paper has comprehensively described the current status, hotspots and trends in this field. A total of 2991 relevant articles from 1 January 1963 to 28 February 2023 were obtained from the Web of Science Core Collection. VOSviewer and CiteSpace software were utilized as bibliometric tools to analyze and visualize knowledge mapping. Between 1963 and 2023, the number of papers in the area of LT for liver cancer increased continuously. A total of 70 countries/regions, 2303 institutions and 14 840 researchers have published research articles, with the United States and China being the two most productive countries. Our bibliometric-based visual analysis revealed the expansion of LT indications for liver cancer and the prevention/treatment of cancer recurrence as ongoing research hotspots over the past decades. Meanwhile, emerging studies also focus on downstaging/bridging treatments before LT and the long-term survival of LT recipient, in particular the precise application of immunosuppressants.

Identifying the programmed cell death index of hepatocellular carcinoma for prognosis and therapy response improvement by machine learning: a bioinformatics analysis and experimental validation

Background

Despite advancements in hepatocellular carcinoma (HCC) treatments, the prognosis for patients remains suboptimal. Cumulative evidence suggests that programmed cell death (PCD) exerts crucial functions in HCC. PCD-related genes are potential predictors for prognosis and therapeutic responses.

Methods

A systematic analysis of 14 PCD modes was conducted to determine the correlation between PCD and HCC. A novel machine learning-based integrative framework was utilized to construct the PCD Index (PCDI) for prognosis and therapeutic response prediction. A comprehensive analysis of PCDI genes was performed, leveraging data including single-cell sequencing and proteomics. GBA was selected, and its functions were investigated in HCC cell lines by in vitro experiments.

Results

Two PCD clusters with different clinical and biological characteristics were identified in HCC. With the computational framework, the PCDI was constructed, demonstrating superior prognostic predictive efficacy and surpassing previously published prognostic models. An efficient clinical nomogram based on PCDI and clinicopathological factors was then developed. PCDI was intimately associated with immunological attributes, and PCDI could efficaciously predict immunotherapy response. Additionally, the PCDI could predict the chemotherapy sensitivity of HCC patients. A multilevel panorama of PCDI genes confirmed its stability and credibility. Finally, the knockdown of GBA could suppress both the proliferative and invasive capacities of HCC cells.

Conclusion

This study systematically elucidated the association between PCD and HCC. A robust PCDI was constructed for prognosis and therapy response prediction, which would facilitate clinical management and personalized therapy for HCC.

P53 and VEGF are promising biomarkers for sorafenib efficacy in an experimental model of NASH-related HCC

The efficacy of systemic therapy for hepatocellular carcinoma (HCC) related to non-alcoholic steatohepatitis (NASH) is poorly understood. In this study we evaluated the effects of sorafenib based on the expression of molecular markers related to major hepatocarcinogenesis pathways and angiogenesis in a NASH-related HCC model. Forty male rats were submitted to NASH-HCC induction through the combination of a high-fat and choline deficient diet and diethylnitrosamine (100 mg/L) administration in the drinking water for 13 and 16 weeks. After the induction period, the rats received daily gavage administration of saline solution (control) or Sorafenib (5 mg/kg/day) for 3 weeks. Thereafter, the animals were euthanized and samples from liver nodules were collected for histopathological analysis and immunohistochemical assessment of HEP-PAR-1, glutamine-synthetase, VEGF, survivin, β-catenin and p53. A semi-quantitative score was used for VEGF, survivin and β-catenin analysis. For p53, the percentage of positive cells was determined. Results were processed by Wilcoxon's test or Student's t-test. Both protocols efficiently induced HCC, most of them being moderately to poorly differentiated. Sorafenib-treated animals showed a decreased expression of VEGF and p53 in HCCs generated at 13 weeks when compared to control animals (p = 0.03; p = 0.04, respectively). No significant difference in β-catenin and survivin were observed. There was a significant decrease in VEGF and p53 expression when comparing the two control groups (13 vs. 16 weeks, p < 0.01). p53 and VEGF are promising biomarkers for assessment of efficacy of Sorafenib, whereas survivin and β-catenin were not found useful. Decreased immunohistochemical expression of p53 and VEGF in the 16 week control group may indicate a different metabolic status of HCC.

IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer-related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)-assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC.

CCNB1 is involved in bladder cancer pathogenesis and silencing CCNB1 decelerates tumor growth and improves prognosis of bladder cancer

In search of an effective therapeutic target for bladder urothelial carcinoma (BLCA), the present study aimed to investigate the expression of cyclin B1 (CCNB1) and its putative mechanism in BLCA. BLCA sequencing data from Gene Expression Omnibus and The Cancer Genome Atlas were used to analyze expression of CCNB1 mRNA and high CCNB1 expression had a poorer prognosis compared with those with low expression. Immunohistochemistry (IHC) samples collected from the Human Protein Atlas database were analyzed for CCNB1 protein expression. Short hairpin (sh) CCNB1-transfected BLCA T24 and 5637 cells were used to investigate the effects of CCNB1 and inhibit the proliferation, migration and invasion of BLCA cells, affect the cell cycle distribution and promote apoptosis of 5637 cells. A sh-CCNB1 BLCA chicken embryo chorioallantoic membrane (CAM) transplantation model was established to observe the impacts of sh-CCNB1 on the tumorigenesis of BLCA in vivo. Analysis of sequencing data showed that CCNB1 mRNA was significantly elevated in tumor and BLCA compared with normal tissues [standardized mean difference (SMD)=1.21; 95% CI: 0.26-2.15; I²=95.9%]. IHC indicated that CCNB1 protein was localized in the nucleus and cytoplasm and was significantly increased in BLCA tumor tissues. The in vitro tests demonstrated that proliferation of T24 and 5637 cells transfected with sh-CCNB1 was significantly inhibited and cell migration and invasion ability were significantly decreased. sh-CCNB1 decreased the percentage of T24 cells in G0/G1, 5637 cells in the G0/G1 phase and S phase and increased percentage of 5637 cells in the G2/M phase and increased early apoptosis of 5637 cells. The in vivo experiments demonstrated that the mass of transplanted tumors was significantly decreased compared with the control group following silencing of CCNB1. The present results suggested that CCNB1 was involve in the development and prognosis of BLCA and silencing of CCNB1 may be a promising targeted therapy for BLCA.

Identification and Validation of Ferroptosis-Related Subtypes and a Predictive Signature in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with an immunosuppressive Tumor microenvironment (TME). Ferroptosis plays an essential role in tumor proliferation, invasion, and metastasis. However, the relationship between ferroptosis and TME of HCC has remained elusive.

Methods

Differentially expressed ferroptosis-related genes (DE FRGs) between normal liver tissues and HCC tissues were obtained from The Cancer Genome Atlas (TCGA). On this basis, we identified the molecular subtypes mediated by DE FRGs and TME cell infiltration. Next, a predictive signature was established to quantity the ferroptosis-related characteristics by performing the least absolute shrinkage and selection operator Cox regression analyses. Univariate and multivariate COX analyses determined the independent prognostic factors. Finally, the expression stability of 3 ferroptosis-related signature genes was verified in cancer and paracancerous normal tissues of HCC.

Results

We identified three different molecular subtypes and found that the subtype with the better prognosis was associated with high enrichment of immune- and metabolic-related hallmark signaling pathways and high infiltration of immune cells in TME. The signature was considered to be an independent prognostic factor. We also found that the signature can reflect the infiltration characteristics of different immune cells in TME. Immunosuppressive cells such as myeloid-derived suppressor cells (MDSCs), regulatory T cells, and type 17 T helper cells were significantly enriched in the high-risk group. The analysis data of immune checkpoints and tumor mutation load indicated that the signature had great potential in predicting Immunotherapy response and chemotherapeutic sensitivity. In addition, the overexpression of 3 ferroptosis-related signature genes was confirmed in HCC tissues and HCC cell lines. Ferroptosis inducer RSL3 inhibited the proliferation of HCC cells and was a potential cancer immunotherapy agent.

Conclusion

These findings enhanced our understanding of the regulatory mechanism of ferroptosis in HCC and provided new insights into evaluating prognosis and developing more effective Immunotherapy and chemotherapy strategies.

UBE2K promotes the malignant progression of hepatocellular carcinoma by regulating c-Myc

Hepatocellular carcinoma (HCC) is a serious threat to human health and life due to its high morbidity and mortality. Ubiquitin-conjugating enzymes are players in the ubiquitin proteasome system and are responsible for a great number of physiological activities in cells. The action of ubiquitin-conjugating enzyme UBE2K in HCC has not been reported. Therefore, we studied the function and role of UBE2K in the malignant progression of HCC. An analysis of UBE2K expression in HCC cells was performed using RT-qPCR and protein immunoblotting. CCK-8, Transwell and sphere formation assays were used to identify the potential effects of UBE2K in HCC cell proliferation, migration and stemness property. RT-qPCR, and protein immunoblotting experiments was taken to explore the regulation between UBE2K and c-Myc. Here, we discovered that UBE2K expression was elevated in HCC cells, and elevated UBE2K predicts worse prognosis for HCC patients. Functionally, UBE2K promote, while UBE2K knockdown suppressed cell proliferation, migration and stemness property of HCC cells. Furthermore, c-Myc was identified as a downstream target of UBE2K. Moreover, functional rescue experiments finally proved that UBE2K facilitates the malignant progression of HCC cells by upregulating c-Myc. We clarified through in vivo experiments that UBE2K expression promotes tumor growth in HCC. Taken together, our study results proved the molecular regulation of UBE2K and c-Myc in HCC and the oncogenic role of UBE2K/c-Myc axis in HCC progression, thus it provides a promising molecular target for the diagnosis and treatment of HCC.

Downregulation of ST6GAL1 Promotes Liver Inflammation and Predicts Adverse Prognosis in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most malignant tumors worldwide. The ST6 β-galactoside α-2, 6-sialyltransferase 1 (ST6GAL1) has been found aberrantly expressed in a variety of cancers including HCC, but its function and mechanism in regulating liver inflammation remain to be investigated. This study aimed to explore the role of ST6GAL1 in HCC. The data of ST6GAL1 expression, prognosis, and clinical parameters were collected and further analyzed from the public databases including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Gene Expression Omnibus (GEO). The HCC rat model was constructed by intraperitoneal injection of diethylnitrosamine. The mRNA and protein expression levels of ST6GAL1 in rat liver tissues were detected by real-time quantitative polymerase chain reaction, capillary electrophoresis, and Western blot.

Results

The ST6GAL1 mRNA and protein expression levels were both lower in HCC tissues compared with normal liver tissues in the public databases and HCC rat model. The survival analysis showed that upregulation of ST6GAL1 was an independent prognostic factor for good prognosis in HCC patients. The ST6GAL1 mRNA expression showed a negative correlation with ST6GAL1 methylation levels. Enrichment analysis showed that ST6GAL1 expression was most associated with metabolic, cancer, estrogen, axon guidance, cAMP, and PI3K-AKT signaling pathways. The ST6GAL1 mRNA expression negatively correlated with liver inflammation status and proportion of NK CD56bright, NK CD56dim, pDC, and CD8+ T cells in liver.

Conclusion

Compared with normal tissues, ST6GAL1 was lower expressed in HCC tumor tissues, and the downregulation of ST6GAL1 was associated with a poor prognosis in HCC patients. ST6GAL1 could further affect the infiltration of immune cells to exert anti-inflammation function in liver. Our study indicated that ST6GAL1 could be a potential biomarker and therapeutic target to assess the prognosis and regulate the immune cells infiltration level of HCC.

Case Report: Combining liver partition and portal vein ligation after thrombectomy for tumor isolation (CLAPT) to treat advanced hepatocellular carcinoma with portal vein tumor thrombosis

Background

Primary liver cancer is the third leading cause of cancer-related deaths worldwide in 2020, and hepatocellular carcinoma (HCC) is the major pathological type. Patients with HCC complicated with portal vein tumor thrombosis (PVTT) have a poor prognosis, and controversies regarding treatment options exist among international scholars. Patients with VP4 or Cheng’s type III classification are generally considered ineligible for surgical treatment.

Methods

We retrospectively analyzed three cases of HCC with PVTT who underwent a novel modified surgical procedure. The procedure included portal vein thrombectomy and portal vein ligation with liver parenchymal separation for the resection of the tumor thrombus involving the main portal vein trunk and for the isolation of the giant tumor. The three cases were then treated with targeted drugs postoperatively.

Results

One case developed acute renal failure in the perioperative period, and the renal function gradually recovered after the treatment. The two remaining cases recovered uneventfully postoperatively. The prognosis of the three patients was encouraging. Only one patient died of lung metastasis after 13 months, and the remaining patients were still alive after 41 and 21 months, respectively.

Conclusions

We provide a new possible surgical option for patients with advanced HCC with PVTT. The surgical procedure was inspired by associating liver partition with portal vein ligation for staged hepatectomy and portal vein thrombectomy. The survival time was significantly prolonged after the patients underwent thrombectomy, tumor isolation, and postoperative nonsurgical treatment. Hence, the combination of liver partition and portal vein ligation after thrombectomy for tumor isolation has the potential for the treatment of advanced HCC with PVTT.

The clonal expression genes associated with poor prognosis of liver cancer

The extensive spatial genomic intratumor heterogeneity (ITH) in liver cancer hindered treatment development and limited biomarker design. Early events that drive tumor malignant transformation in tumor founder cells are clonally present in all tumor cell populations, which provide stable biomarkers for the localization of tumor cells and patients’ prognosis. In the present study, we identified the recurrently clonal somatic mutations and copy number alterations (CNAs) (893 clonal somatic mutations and 6,617 clonal CNAs) in 353 liver cancer patients from The Cancer Genome Atlas (TCGA) and evaluated their prognosis potential. We showed that prognosis-related clonal alterations might play essential roles in tumor evolution. We identified 32 prognosis related clonal alterations differentially expressed between paired normal and tumor samples, that their expression was cross-validated by three independent cohorts (50 paired samples in TCGA, 149 paired samples in GSE76297, and 9 paired samples in SUB6779164). These clonal expression alterations were also significantly correlated with clinical phenotypes. Using stepwise regression, we identified five (UCK2, EFNA4, KPAN2, UBE2T, and KIF14) and six (MCM10, UCK2, IQGAP3, EFNA4, UBE2T, and KPNA2) clonal expression alterations for recurrence and survival model construction, respectively. Furthermore, in 10 random repetitions, we showed strong applicability of the multivariate Cox regression models constructed based on the clonal expression genes, which significantly predicted the outcomes of the patients in all the training and validation sets. Taken together, our work may provide a new avenue to overcome spatial ITH and refine biomarker design across cancer types.

GENES EXPRESSION AND SERUM BIOMARKERS FOR DIAGNOSIS OF HEPATOCELLULAR CARCINOMA, CIRRHOSIS AND HEPATITIS C

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Risk factors for HCC include hepatitis C (HCV) and B (HBV) virus infection, alcoholic cirrhosis and genetic alterations that can affect several cellular pathways.

OBJECTIVE

This study purposed to analyze the gene and serum protein expression of vascular endothelial growth factor (VEGF), angiogenesis, alpha fetoprotein, cystatin B (CSTB), β-catenin and glypican-3 (GPC3) in groups with HCC, cirrhosis or HCV and controls, and their relation with clinical staging in the HCC and cirrhosis groups, as well its sensitivity and specificity values.

METHODS

A total of 230 individuals were distributed in Group 1 (G1) - 80 patients with HCC; Group 2 (G2) - 76 patients with cirrhosis due to any etiology; Group 3 (G3) - 33 patients with HCV; Group 4 (G4 - controls) - 41 individuals without clinical or biochemical signs of any liver disease. Gene expression was analyzed by qRT-PCR and serum proteins were performed using the ELISA method.

RESULTS

Increased VEGF and angiogenesis, alpha fetoprotein expression could be observed in BCLC stage-D patients compared to stage-B patients, and stage-C patients showed higher expression of β-catenin, compared to stage-B patients (P<0.05). For VEGF and GPC3, discriminatory power was observed between HCC patients and controls (AUC =0.71; 0.82, respectively). CSTB showed discriminatory power in the comparison between patients with HCV and controls (AUC =0.74).

CONCLUSION

The present study confirms the sensitivity of serum CSTB in the diagnosis of hepatitis C, and gene expression of VEGF and serum GPC3, confer both sensitivity and specificity for the diagnosis of HCC.

Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma

BACKGROUND

At present, the diagnostic ability of hepatocellular carcinoma (HCC) based on serum alpha-fetoprotein level is limited. Finding markers that can effectively distinguish cancer and non-cancerous tissues is important for improving the diagnostic efficiency of HCC.

RESULTS

In this study, we developed a predictive model for HCC diagnosis using personalized biological pathways combined with a machine learning algorithm based on regularized regression and carry out relevant examinations. In two training sets, the overall cross-study-validated area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve and the Brier score of the diagnostic model were 0.987 [95%confidence interval (CI): 0.979-0.996], 0.981 and 0.091, respectively. Besides, the model showed good transferability in external validation set. In TCGA-LIHC cohort, the AUROC, AURPC and Brier score were 0.992 (95%CI: 0.985-0.998), 0.967 and 0.112, respectively. The diagnostic model has accomplished very impressive performance in distinguishing HCC from non-cancerous liver tissues. Moreover, we further analyzed the extracted biological pathways to explore molecular features and prognostic factors. The risk score generated from a 12-gene signature extracted from the characteristic pathways was correlated with some immune related pathways and served as an independent prognostic factor for HCC.

CONCLUSION

We used personalized biological pathways analysis and machine learning algorithm to construct a highly accurate HCC diagnostic model. The excellent interpretable performance and good transferability of this model enables it with great potential for personalized medicine, which can assist clinicians in diagnosis for HCC patients.

EIF4A3-induced circTOLLIP promotes the progression of hepatocellular carcinoma via the miR-516a-5p/PBX3/EMT pathway

BACKGROUND

Circular RNAs (circRNAs) function as crucial regulators in multiple cancers, including hepatocellular carcinoma (HCC). However, the roles of circRNAs in HCC remains largely unknown.

METHODS

circTOLLIP was identified in HCC by screening of two public circRNA microarray datasets and detected in HCC cells and tissues through quantitative real-time PCR (qRT-PCR) and in situ hybridization (ISH). Gain- and loss-of-function assays were performed to confirm the biological effects of circTOLLIP on HCC in vitro and in vivo. Mechanistically, bioinformatics analysis of online databases, MS2-RNA pulldown, biotin-labeled circTOLLIP/miR-516a-5p RNA pulldown, RNA immunoprecipitation (RIP), luciferase reporter assay, fluorescence in situ hybridization assay (FISH) and RNA sequencing were used to confirm the regulation of Eukaryotic initiation factor 4A3 (EIF4A3) on circTOLLIP and the interaction among circTOLLIP, miR-516a-5p and PBX homeobox 3 (PBX3).

RESULTS

circTOLLIP was significantly upregulated in HCC cells and tissues. High circTOLLIP expression was correlated with poor overall survival (OS) and disease-free survival (DFS) in patients. circTOLLIP promoted the proliferation and metastasis of HCC cells in vitro and in vivo. Mechanistically, EIF4A3 promoted the biogenesis of circTOLLIP without affecting its stability. Moreover, circTOLLIP sponged miR-516a-5p to elevate the expression of PBX3, thereby activating the epithelial-to-mesenchymal transition (EMT) pathway and facilitating tumor progression in HCC.

CONCLUSIONS

Our findings indicate that EIF4A3-induced circTOLLIP promotes the progression of HCC through the circTOLLIP/miR-516a-5p/PBX3/EMT axis.

The Combined Signatures of Hypoxia and Cellular Landscape Provides a Prognostic and Therapeutic Biomarker in HBV-Related Hepatocellular Carcinoma

Prognosis and treatment options of hepatitis B virus‐related hepatocellular carcinoma (HBV‐HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV‐HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia‐related genes and 64 TME cells was performed in 452 HBV‐HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta‐analysis for generating the Hypoxia‐TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia‐TME defined subgroups were analyzed. Patients in the Hypoxia^low/TME^high subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune‐related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early‐ and late‐HCC stages. In addition, the Hypoxia‐TME classifier was validated in another independent HBV‐HCC cohort (n = 144) and several pan‐cancer cohorts. Overall, the Hypoxia‐TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies.

Bioluminescent RAPPID Sensors for the Single-Step Detection of Soluble Axl and Multiplex Analysis of Cell Surface Cancer Biomarkers

Early diagnosis of cancer is essential for the efficacy of treatment. Our group recently developed RAPPID, a bioluminescent immunoassay platform capable of measuring a wide panel of biomarkers directly in solution. Here, we developed and systematically screened different RAPPID sensors for sensitive detection of the soluble fraction of Axl (sAxl), a cell surface receptor that is overexpressed in several types of cancer. The best-performing RAPPID sensor, with a limit of detection of 8 pM and a >9-fold maximal change in emission ratio, was applied to measure Axl in three different contexts: clinically relevant sAxl levels (∼0.5 and ∼1 nM) in diluted blood plasma, proteolytically cleaved Axl in the cell culture medium of A431 and HeLa cancer cells, and Axl on the membrane of A431 cells. We further extended the sensor toolbox by developing dual-color RAPPID for simultaneous detection of Axl and EGFR on A431 and HeLa cells, as well as an AND-gate RAPPID that measures the concurrent presence of these two cell surface receptors on the same cell. These new RAPPID sensors provide attractive alternatives for more laborious protein detection and quantification methods such as FACS and immunostainings, due to their simple practical implantation and low intrinsic background signal.

Identification of an EMT-related lncRNA signature and LINC01116 as an immune-related oncogene in hepatocellular carcinoma

Background: Epithelial–mesenchymal transition (EMT) plays a critical role in the recurrence and metastasis of hepatocellular carcinoma (HCC). Some long noncoding (lnc)RNAs are involved in this process through the regulation of EMT-related transcription factors.

Methods: In this study, we established a novel EMT-related lncRNA signature in HCC and identified hub lncRNAs that can serve as potential therapeutic targets. Differentially expressed lncRNAs were identified by screening HCC patient data from The Cancer Genome Atlas, and a correlation analysis was performed to identify those associated with EMT. The EMT-related lncRNA signature was established by univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. After verifying the prognostic accuracy of the signature, its relationships to immune cell infiltration and immune checkpoint targets were explored. LINC01116 was identified as a hub lncRNA and its role in HCC was investigated in vitro and in vivo.

Results: A 5-lncRNA signature was developed for HCC and its prognostic accuracy was assessed by survival, time-dependent receiver operating characteristic curve, clinical correlation, and Cox regression analyses. The correlation analysis showed that the lncRNA signature was closely related to immune cell infiltration and 10 immune checkpoint targets and also predicted the prognosis of HCC patients with high accuracy. In vitro and in vivo experiments revealed that LINC01116 stimulated cell proliferation, cell cycle progression, and tumor metastasis. We also found that LINC01116 was closely related to immune regulation.

Conclusions: These results demonstrate that LINC01116 is an immune-related oncogene that is associated with both EMT and immune regulation in HCC. Moreover, the EMT-related lncRNA signature that includes LINC01116 can guide risk stratification and clinical decision-making in HCC management.

DEP domain containing 1B (DEPDC1B) exerts the tumor promoter in hepatocellular carcinoma through activating p53 signaling pathway via kinesin family member 23 (KIF23)

Hepatocellular carcinoma (HCC) is closely associated with chronic liver disease and possesses a high incidence. DEP domain containing 1B (DEPDC1B) expression has been found to be upregulated in HCC according to bioinformatics analysis. This paper sought to study the specific role of DEPDC1B in HCC. The data of DEPDC1B expression and individual overall survival in HCC and normal liver tissues were acquired from UALCAN database. The association between DEPDC1B and the downstream signal, kinesin family member 23 (KIF23), was determined using LinkedOmics and STRING database, and subsequently confirmed by co-immunoprecipitation assay. The expression levels of DEPDC1B and KIF23 in normal hepatic epithelial cells and HCC cell lines were assessed by RT-qPCR and Western blotting, respectively. Following transfection with small interference RNA-DEPDC1B, the influences of DEPDC1B knockdown on cell proliferation, colony formation, cell cycle, cell invasion, migration, and KIF23 expression were evaluated. In addition, the effects of KIF23 overexpression on the above aspects of HCC cells were also determined, as well as the expression level of p53 signaling-related proteins. The results indicated that DEPDC1B was highly expressed in HCC cells. DEPDC1B knockdown inhibited the proliferation, migration, invasion, cycle, and KIF23 expression in HCC cells. Moreover, KIF23 overexpression reversed the inhibitory effect of DEPDC1B knockdown in HCC cells and the activation of the p53 signaling. In conclusion, DEPDC1B knockdown exerts anti-cancer role in HCC by activating the p53 signaling through KIF23.

ETS Proto-Oncogene 1-activated muskelin 1 antisense RNA drives the malignant progression of hepatocellular carcinoma by targeting miR-22-3p to upregulate ETS Proto-Oncogene 1

Long noncoding RNA muskelin 1 antisense RNA (MKLN1-AS) acted as an oncogenic regulator in hepatocellular carcinoma (HCC). This study was performed to investigate the functional mechanism of MKLN1-AS. MKLN1-AS, microRNA-22-3p (miR-22-3p) and ETS Proto-Oncogene 1 (ETS1) levels were examined using reverse transcription-quantitative polymerase-chain reaction. Protein expression was detected by Western blot. The target relation was analyzed by dual-luciferase reporter assay, RNA immunoprecipitation assay and RNA pull-down assay. Cell proliferation ability was determined through cell counting kit-8 assay, colony formation assay and ethylenediurea assay. Angiogenesis was examined by tube formation assay. Cell migration and invasion were assessed via transwell assay. In vivo research was conducted by xenograft tumor model in nude mice. MKLN1-AS was upregulated in HCC tissues and cells. ETS1 promoted the ETS1 expression by binding to the 582–596 sites. Silence of MKLN1-AS suppressed cell growth, angiogenesis, migration, and invasion. MKLN1-AS interacted with miR-22-3p in HCC cells. The function of MKLN1-AS downregulation was relieved by miR-22-3p inhibition in HCC cells. ETS1 was validated as a target of miR-22-3p, and MKLN1-AS upregulated the ETS1 expression by sponging miR-22-3p. Overexpression of miR-22-3p retarded HCC progression by downregulating the level of ETS1. Tumor growth in vivo was also enhanced by MKLN1-AS through the regulation of miR-22-3p/ETS1 axis. These data demonstrated that ETS1-mediated MKLN1-AS contributed to the malignant phenotypes of HCC cells via depending on the miR-22-3p/ETS1 regulatory axis.

Elevated DNA Polymerase Delta 1 Expression Correlates With Tumor Progression and Immunosuppressive Tumor Microenvironment in Hepatocellular Carcinoma

Background and Objective

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and the DNA polymerase delta (POLD) family is significantly related to cancer prognosis. This study aimed to explore the significance of the POLD family in HCC via the DNA damage repair (DDR) pathway.

Methods

Data mining was conducted using bioinformatics methods. RNA sequencing and clinicopathological data were collected from The Cancer Genome Atlas, GTEx database and the Gumz Renal cohort. Statistical analyses were also performed in cancer samples (n>12,000) and the Affiliated Hospital of Youjiang Medical University for Nationalities (AHYMUN, n=107) cohort.

Results

The POLD family (POLD1-4) was identified as the most important functional component of the DDR pathway. Based on the analysis of independent cohorts, we found significantly elevated POLD expression in HCC compared with normal tissues. Second, we investigated the prognostic implication of elevated POLD1 expression in HCC and pan-cancers, revealing that increased POLD1 levels were correlated to worse prognoses for HCC patients. Additionally, we identified 11 hub proteins interacting closely with POLD proteins in base excision repair, protein-DNA complex and mismatch repair signaling pathways. Moreover, POLD1 mutation functioned as an independent biomarker to predict the benefit of targeted treatment. Importantly, POLD1 expression was associated with immune checkpoint molecules, including CD274, CD80, CD86, CTLA4, PDCD1 and TCGIT, and facilitated an immune-excluded tumor microenvironment. Additionally, we confirmed that elevated POLD1 expression was closely correlated with the aggressive progression and poor prognosis of HCC in the real-world AHYMUN cohort.

Conclusion

We identified a significant association between elevated POLD1 expression and poor patient survival and immune-excluded tumor microenvironment of HCC. Together, these findings indicate that POLD1 provides a valuable biomarker to guide the molecular diagnosis and development of novel targeted therapeutic strategies for HCC patients.

Low APOA-1 Expression in Hepatocellular Carcinoma Patients Is Associated With DNA Methylation and Poor Overall Survival

Background: Hepatocellular carcinoma (HCC) is the most frequent fatal malignancy, and it has a poor prognosis. Apolipoprotein 1 (APOA-1), the main protein component of high-density lipoproteins, is involved in numerous biological processes. Thus, this study was performed to detect the clinical significance of APOA-1 mRNA, APOA-1 expression, and APOA-1DNA methylation in patients with HCC.

Methods: Data mining was performed using clinical and survival data from the Cancer Genome Atlas (TCGA) and Oncomine databases. The serum concentration of APOA-1 was measured in 316 patients with HCC and 100 healthy individuals at Renmin Hospital of Wuhan University, and the intact clinical information was reviewed and determined using univariate and multivariate Cox hazard models.

Results: Bioinformatic analysis revealed that APOA-1 mRNA was present at lower levels in the serum of patients with HCC than in that of healthy individuals, and there was a strong negative correlation between levels of APOA-1 mRNA and APOA-1 DNA methylation. High expression of APOA-1 transcription correlated with better overall survival (p = 0.003), and APOA-1 hypermethylation correlated with progress-free survival (p = 0.045) in HCC sufferers. Next, the clinical data analysis demonstrated that APOA-1 protein levels in the serum were significantly lower in patients with HCC than in healthy controls. Furthermore, the expression of APOA-1 was significantly associated with some significant clinical indexes, and elevated APOA-1 expression was significantly associated with favorable (OS; HR:1.693, 95% CI: 1.194–2.401, p = 0.003) and better progression-free survival (PFS; HR = 1.33, 95% CI = 1.194–2.401, p = 0.045). Finally, enrichment analysis suggested that co-expressed genes of APOA-1 were involved in lipoprotein metabolism and FOXA2/3 transcription factor networks.

Conclusion: APOA-1 mRNA expression is negatively regulated by DNA methylation in HCC. Low expression of APOA-1 might be a potential risk biomarker to predict survival in patients with HCC.

Cabozantinib for HCC Treatment, From Clinical Back to Experimental Models

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality worldwide. Patients with early-stage HCC can be treated successfully with surgical resection or liver transplantation. However, the usual late diagnosis of HCC precludes curative treatments, and systemic therapies are the only viable option for inoperable patients. Sorafenib, an orally available multikinase inhibitor, is a systemic therapy approved for treating patients with advanced HCC yet providing limited benefits. Consequently, new drugs have been developed to overcome sorafenib resistance and improve patients' prognoses. A new promising strategy is using c-MET inhibitors, such as cabozantinib, as activation of c-MET occurs in up to 40% of HCC patients. In particular, cabozantinib, in combination with the checkpoint inhibitor atezolizumab, is currently in phase 3 clinical trial for HCC, and the results are eagerly awaited. Herein, we summarize and review the drugs approved for the treatment of advanced HCC, mainly focusing on the clinical and preclinical efficacy evaluation of cabozantinib. Also, we report the available preclinical data on cabozantinib-based combination therapies for HCC, current obstacles for cabozantinib therapy, and the future directions for cabozantinib-based treatment for HCC.

AFP-L3 for the diagnosis of early hepatocellular carcinoma: A meta-analysis

BACKGROUND

The present study aimed to systematically evaluate the diagnostic value of an isoform of alpha-fetoprotein (AFP), AFP-L3, for early hepatocellular carcinoma (HCC) by a meta-analysis.

METHODS

Diagnostic reports of AFP-L3% in early HCC were searched in the PubMed, Web of Science, Cochrane Library, and Embase databases up to December 2019. The retrieved literature was reviewed, and eligible articles were selected. Data were extracted from the eligible articles, and the risk of bias was evaluated according to the Quality Assessment of Diagnostic Accuracy Studies scale. Statistical analyses were conducted by MetaDiSc1.4 and RevMan5.3 software. The sensitivities, specificities, and diagnostic odds ratios were pooled. The summary receiver operating characteristic curve was drawn, and the area under the curve was calculated.

RESULTS

Six studies with acceptable quality were included in the meta-analysis involving 2447 patients. No threshold effect was observed among the 6 studies, but there was obvious heterogeneity. The pooled sensitivity, specificity, and positive and negative likelihood ratios of AFP-L3% for the diagnosis of early HCC were 0.34 (95% CI 0.30-0.39, P < .0001), 0.92 (95% CI 0.91-0.93, P < .0001), 4.46 (95% CI 2.94-6.77, P = .0033), and 0.71 (95% CI 0.61-0.82, P = .0004), respectively. The diagnostic odds ratio was 6.78 (95% CI 4.02-11.44, P = .0074). The the area under the curve of the summary receiver operating characteristic was 0.755 (95% CI 0.57-0.94).

CONCLUSION

AFP-L3% has high specificity but low sensitivity for diagnose early HCC, suggesting that AFP-L3% is more valuable for excluding HCC in conditions with elevated AFP than for diagnosing early HCC. In addition, a hypersensitive detection method can improve the diagnostic accuracy of AFP-L3% for early HCC.

Cyclin-dependent kinase 19 upregulation correlates with an unfavorable prognosis in hepatocellular carcinoma

Objectives

Cyclin-dependent kinase 19 (CDK19) is a component of the mediator coactivator complex, which is required for transcriptional activation. In this study, we utilized public databases and wet-bench hepatic cell line experiments to elucidate the potential roles of CDK19 in hepatocellular cancer (HCC).

Materials and methods

We studied the relationships between CDK19 expression and several clinical features related to HCC via the Oncomine and UALCAN databases. The prognostic value of CDK19 was tested using the Kaplan–Meier Plotter database. We presented the mutations of CDK19 and addressed the relation of CDK19 expression with immune cell infiltration by means of the cBioPortal, Catalogue of Somatic Mutations in Cancer (COSMIC) and Tumor IMmune Estimation Resource (TIMER) databases. Hub genes were obtained and further analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. To test the in silico findings, we knocked down CDK19 with short hairpin RNA (shRNA) technology in two hepatic cell lines and conducted several functional characterization experiments.

Results

Marked CDK19 upregulation was found in HCC tissues versus normal liver tissues, and CDK19 mRNA expression had high diagnostic value in HCC patients. Subgroup analysis showed that CDK19 overexpression was associated with sex, tumor stage and TP53 mutation status. The prognostic value of CDK19 upregulation for overall survival (OS) was significant in patients with stage 2–3, stage 3–4, and grade 2 disease. One percent of the patients had CDK19 mutations, but no relationship between CDK19 mutation and prognosis was observed. CDK19 was positively correlated with the abundances of CD4 + T cells, macrophages and dendritic cells. We identified 10 genes correlated with CDK19, 8 of which presented excellent prognostic value in HCC. These hub genes were directly involved in cell division and regulation of the G2/M cell cycle transition. Protein–protein interaction (PPI) and pathway predictions indicated that CDK19 is highly likely to be involved in several cellular functions, such as proliferation, migration, and invasion. These functions were strongly interfered from two independent hepatic cell lines after CDK19 knockdown.

Conclusions

CDK19 could be a prognostic marker in HCC, and its therapeutic potential in HCC needs further study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01962-8.

An Autophagy-Related Gene-Based Prognostic Risk Signature for Hepatocellular Carcinoma: Construction and Validation

BACKGROUND

Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer. Treatment is dramatically difficult due to its high complexity and poor prognosis. Due to the disclosed dual functions of autophagy in cancer development, understanding autophagy-related genes devotes into novel biomarkers for HCC.

METHODS

Differential expression of genes in normal and tumor groups was analyzed to acquire autophagy-related genes in HCC. These genes were subjected to GO and KEGG pathway analyses. Genes were then screened by univariate regression analysis. The screened genes were subjected to multivariate Cox regression analysis to build a prognostic model. The model was validated by the ICGC validation set.

RESULTS

To sum up, 42 differential genes relevant to autophagy were screened by differential expression analysis. Enrichment analysis showed that they were mainly enriched in pathways including regulation of autophagy and cell apoptosis. Genes were screened by univariate analysis and multivariate Cox regression analysis to build a prognostic model. The model constituted 6 feature genes: EIF2S1, BIRC5, SQSTM1, ATG7, HDAC1, and FKBP1A. Validation confirmed the accuracy and independence of this model in predicting the HCC patient's prognosis.

CONCLUSION

A total of 6 feature genes were identified to build a prognostic risk model. This model is conducive to investigating interplay between autophagy-related genes and HCC prognosis.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

Liquid Biopsy in Hepatocellular Carcinoma: Opportunities and Challenges for Immunotherapy

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types worldwide. HCC is often diagnosed at a late stage when the therapeutic options are very limited. However, even at the earlier stages, the best treatment is liver transplantation, surgical resection or ablation. Surgical resection and ablation may carry a high risk of tumor recurrence. The recent introduction of immunotherapies resulted in clinical responses for a subgroup of patients, but there were still no effective predictive markers for response to immunotherapy or for recurrence after surgical therapy. The identification of biomarkers that could correlate and predict response or recurrence would require close monitoring of the patients throughout and after the completion of treatment. However, this would not be performed efficiently by repeated and invasive tissue biopsies. A better approach would be to use liquid biopsies including circulating tumor DNA (ctDNA), circulating RNA (e.g., microRNAs), circulating tumor cells (CTC) and extracellular vesicles (EVs) (e.g., exosomes) for disease monitoring in a non-invasive manner. In this review, we discuss the currently available technology that can enable the use of liquid biopsy as a diagnostic and prognostic tool. Moreover, we discuss the opportunities and challenges of the clinical application of liquid biopsy for immunotherapy of HCC.

PDLIM2 prevents the malignant phenotype of hepatocellular carcinoma cells by negatively regulating β-catenin

Hepatocellular carcinoma (HCC) is one of the most common malignancies and leading causes of cancer-related deaths globally. Despite significant advances in therapy, the molecular mechanisms underlying HCC development and progression remain unclear. Here, we aimed to explore the potential role of PDLIM2 in the development and epithelial-mesenchymal transition (EMT) of HCC via a possible modulation of β-catenin. We first confirmed that PDLIM2 was downregulated in HCC tissues and cells and found lower PDLIM2 expression was associated with worse prognosis in HCC patients. Loss- and gain- of function experiments were performed to evaluate the roles of PDLIM2 and β-catenin in HCC cell proliferation, migration, invasion, EMT, and colony formation. EMT was determined based on the levels of E-cadherin, zonula occludens-1, N-cadherin, and vimentin expression. In vivo, the roles of PDLIM2 and β-catenin in HCC were investigated by using a nude mouse xenograft model. It should be noted that PDLIM2 led to the inhibition of β-catenin activity and its downstream gene expression. Importantly, ectopic PDLIM2 expression inhibited the proliferation, migration, invasion, and EMT of HCC cells by reducing β-catenin expression both in vitro and in vivo, thereby suppressing the occurrence and progression of HCC. Taken together, our results demonstrated that overexpressed PDLIM2 exerts a tumor-suppressive role in HCC by regulating β-catenin. This study suggests that the PDLIM2 may be a promising target for the treatment of HCC.