Biomarkers in Hepatocellular Carcinoma: Diagnosis, Prognosis and Treatment Response Assessment

The novel circular RNA HIPK3 accelerates the proliferation and invasion of hepatocellular carcinoma cells by sponging the micro RNA-124 or micro RNA-506/pyruvate dehydrogenase kinase 2 axis

Circular RNAs (circRNAs) have been confirmed to be associated with the progression of various cancers, including hepatocellular carcinoma (HCC). However, the role and mechanism of circHIPK3 in HCC are still unclear. To investigate its function, circHIPK3 expression was first determined by RT–qPCR in HCC tissues or cells. Functionally, cell proliferation and invasion were investigated by CCK-8, EdU, or Transwell assays. In terms of understanding the mechanism, the interaction of the circRNA HIPK3/micro RNA 124 (miRNA 124) or micro RNA 506 (miRNA506) /PDK2 regulatory loop was verified by dual-luciferase reporter gene assay. In addition, a xenograft tumor model was established to confirm the impact of circHIPK3 on the growth of HCC cells in vivo. We found that circHIPK3 was upregulated in HCC patients and associated with clinical characteristics, while miR-124 and miR-506 were downregulated in HCC patients. Additionally, we proved that knock down of circHIPK3 remarkably suppressed the proliferation and invasion of HCC cells. Mechanistically, circHIPK3 directly bound to miR-124 or miR-506 and inhibited their expression, and PDK2 was a target gene of miR-124 or miR-506. Moreover, circHIPK3 overexpression reversed the inhibitory effect of miR-124 or miR-506 on HCC progression. miR-124 or miR-506 could also suppress tumorigenesis of HCC cells by PDK2. Furthermore, in vivo evidence confirmed that knock down of circHIPK3 inhibited tumor formation. We suggest that circHIPK3 can accelerate the proliferation and invasion of HCC cells by sponging miR-124 or miR-506 to upregulate PDK2, which is the underlying mechanism of circHIPK3-induced HCC progression.

Role of SLC39A6 in the development and progression of liver cancer

Liver cancer is one of the most common malignant solid tumor types worldwide. The solute carrier (SLC)39A family is a main member of the SLC group of membrane transport proteins, which transfer zinc to the cytoplasm when cells are depleted of zinc; thus, it may provide a novel therapeutic target for human cancer. However, the prognostic value of SLC39A genes in patients with liver cancer has remained elusive. Therefore, the present study aimed to explore whether SLC39A family genes are associated with the survival rate of patients with liver cancer and to investigate the role of key genes of the SLC39A family in liver cancer. The mRNA expression of the SLC39A family in liver cancer was obtained from the UALCAN database. Survival curve analysis was performed to investigate the prognostic value of SLC39A family genes in the overall survival of patients with liver cancer. In addition to the bioinformatics analysis, SLC39A6 was knocked down in HepG2 and Hep3B cells to examine the effect on the proliferation, migration and invasion of liver cancer cells. The results suggested that SLC39A6 was significantly upregulated in liver cancer tissues compared with normal liver tissues. High expression of SLC39A6 was significantly associated with poor overall survival of patients with liver cancer. Furthermore, knockdown of SLC39A6 inhibited the proliferation, migration and invasion of liver cancer cells in vitro and in vivo. Collectively, the results of the present study suggested that SLC39A6 may be a promising prognostic biomarker for liver cancer and is associated with the proliferation, migration and invasion of liver cancer.

Molecular and genetic markers in hepatocellular carcinoma: In silico analysis to clinical validation (current limitations and future promises)

Hepatocellular carcinoma (HCC) is the second cause of cancer-related mortality. The diagnosis of HCC depends mainly on α-fetoprotein, which is limited in its diagnostic and screening capabilities. There is an urgent need for a biomarker that detects early HCC to give the patients a chance for curative treatment. New targets of therapy could enhance survival and create future alternative curative methods. In silico analysis provides both; discovery of biomarkers, and understanding of the molecular pathways, to pave the way for treatment development. This review discusses the role of in silico analysis in the discovery of biomarkers, molecular pathways, and the role the author has contributed to this area of research. It also discusses future aspirations and current limitations. A literature review was conducted on the topic using various databases (PubMed, Science Direct, and Wiley Online Library), searching in various reviews, and editorials on the topic, with overviewing the author’s own published and unpublished work. This review discussed the steps of the validation process from in silico analysis to in vivo validation, to incorporation into clinical practice guidelines. In addition, reviewing the recent lines of research of bioinformatic studies related to HCC. In conclusion, the genetic, molecular and epigenetic markers discoveries are hot areas for HCC research. Bioinformatics will enhance our ability to accomplish this understanding in the near future. We face certain limitations that we need to overcome.

Mechanism of miR-424-5p promoter methylation in promoting epithelial-mesenchymal transition of hepatocellular carcinoma cells

The current study set out to clarify the role of miR-424-5p promoter methylation in epithelial mesenchymal transition (EMT) of hepatocellular carcinoma (HCC) cells. The findings of quantitative real-time-polymerase chain reaction and methylation-sensitive high-resolution melting assays elicited that miR-424-5p was poorly expressed in HCC tissues and cells while highly methylated. Meanwhile, upon demethylation, miR-424-5p expression levels were partly recovered in HCC cells. In addition, miR-424-5p upregulation reduced cell viability and elevated apoptosis of HCC cells, in parallel with increased N-cadherin and decreased E-cadherin levels. Dual-luciferase reporter assay further validated that miR-424-5p bound to the kinesin family member 2A (KIF2A), and miR-424-5p overexpression downregulated KIF2A. In addition, KIF2A overexpression reversed the miR-424-5p-driven changes in terms of cell viability, apoptosis and EMT-related protein levels. Furthermore, xenograft tumors were established via injection of Huh7 cells, followed by miR-424-5p overexpression in vivo, which inhabited KIF2A downregulation and attenuated tumor growth along with decreased Ki67 positive expression, diminished N-cadherin and elevated E-cadherin levels. Overall, our findings supported the conclusion that miR-424-5p promoter methylation reduced miR-424-5p expression and upregulated KIF2A, thereby promoting HCC EMT.

Network-based prioritization of cancer biomarkers by phenotype-driven module detection and ranking

This paper describes an ensemble method with supervised module detection and further module prioritization for reliable network-based biomarker discovery. We design a module detection and ranking method called mRank to discover reliable network modules as cancer diagnostic biomarkers, with two procedures: (1) an iterative supervised module detection guided by phenotypic states in a specific network, (2) a block-based module ranking locally and globally via network topological centrality. We validate its effectiveness and efficiency by identifying hepatocellular carcinoma (HCC) network modules on a comprehensive gene regulatory network with specifying gene interactions by HCC RNA-seq data from the Cancer Genome Atlas (TCGA). These top-ranked modules by mRank get a mean AUC of 0.995 on TCGA HCC dataset with 371 tumor samples and 50 controls by cross-validation SVM. Based on the prior knowledge of cancer dysfunctions enriched in top-ranked modules, 69 genes are identified as HCC candidate biomarkers. They are further validated in independent cohorts with a classifier trained on TCGA HCC dataset. A mean AUC of 0.846 is achieved in distinguishing 976 disease samples from 827 controls. Moreover, some known HCC signatures such as AFP and SPP1 are also included in our identified biomarkers. mRank enables us to find more reliable network modules for cancer diagnosis. For a proof-of-concept study, we validate it in identifying HCC network biomarkers and it is generalizable to other cancers or complex disease. The overall results have demonstrated that mRank can find effective network biomarkers for cancer diagnosis which result in less false positives.

CircCCNB1 silencing acting as a miR-106b-5p sponge inhibited GPM6A expression to promote HCC progression by enhancing DYNC1I1 expression and activating the AKT/ERK signaling pathway

Background: Circular RNAs (circRNAs), which generally act as microRNA (miRNA) sponges to competitively regulate the downstream target genes of miRNA, play an essential role in cancer biology. However, few studies have been reported on the role of circRNA based competitive endogenous RNA (ceRNA) network in hepatocellular carcinoma (HCC). Herein, we aimed to screen and establish the circRNA/miRNA/mRNA networks related to the prognosis and progression of HCC and further explore the underlying mechanisms of tumorigenesis. Methods: GEO datasets GSE97332, GSE108724, and GSE101728 were utilized to screen the differentially expressed circRNAs (DE-circRNAs), DE-miRNAs, and DEmRNAs between HCC and matched para-carcinoma tissues. After six RNA-RNA predictions and five intersections between DE-RNAs and predicted RNAs, the survival-related RNAs were screened by the ENCORI analysis tool. The ceRNA networks were constructed using Cytoscape software, based on two models of up-regulated circRNA/down-regulated miRNA/up-regulated mRNA and down-regulated circRNA/up-regulated miRNA/down-regulated mRNA. The qRT-PCR assay was utilized for detecting the RNA expression levels in HCC cells and tissues. The apoptosis, Edu, wound healing, and transwell assays were performed to evaluate the effect of miR-106b-5p productions on the proliferation, invasion, and metastasis of HCC cells. In addition, the clone formation, cell cycle, and nude mice xenograft tumor assays were used to investigate the influence of hsa_circ_0001495 (circCCNB1) silencing and overexpression on the proliferation of HCC cells in vitro and in vivo. Furthermore, the mechanism of downstream gene DYNC1I1 and AKT/ERK signaling pathway via the circCCNB1/miR-106b-5p/GPM6A network in regulating the cell cycle was also explored. Results: Twenty DE-circRNAs with a genomic length less than 2000bp, 11 survival-related DE-miRNAs, and 61 survival-related DE-mRNAs were screened out and used to construct five HCC related ceRNA networks. Then, the circCCNB1/miR-106b-5p/GPM6A network was randomly selected for subsequent experimental verification and mechanism exploration at in vitro and in vivo levels. The expression of circCCNB1 and GPM6A were significantly down-regulated in HCC cells and cancer tissues, while miR-106b-5p expression was up-regulated. After transfections, miR-106b-5p mimics notably enhanced the proliferation, invasion, and metastasis of HCC cells, while the opposite was seen with miR-105b-5p inhibitor. In addition, circCCNB1 silencing promoted the clone formation ability, the cell cycle G1-S transition, and the growth of xenograft tumors of HCC cells via GPM6A downregulation. Subsequently, under-expression of GPM6A increased DYNC1I1 expression and activated the phosphorylation of the AKT/ERK pathway to regulate the HCC cell cycle. Conclusions: We demonstrated that circCCNB1 silencing promoted cell proliferation and metastasis of HCC cells by weakening sponging of oncogenic miR-106b-5p to induce GPM6A underexpression. DYNC1I1 gene expression was up-regulated and further led to activation of the AKT/ERK signaling pathway.

Metabolic Reprogramming and Risk Stratification of Hepatocellular Carcinoma Studied by Using Gas Chromatography-Mass Spectrometry-Based Metabolomics

Hepatocellular carcinoma (HCC) displays a high degree of metabolic and phenotypic heterogeneity and has dismal prognosis in most patients. Here, a gas chromatography-mass spectrometry (GC-MS)-based nontargeted metabolomics method was applied to analyze the metabolic profiling of 130 pairs of hepatocellular tumor tissues and matched adjacent noncancerous tissues from HCC patients. A total of 81 differential metabolites were identified by paired nonparametric test with false discovery rate correction to compare tumor tissues with adjacent noncancerous tissues. Results demonstrated that the metabolic reprogramming of HCC was mainly characterized by highly active glycolysis, enhanced fatty acid metabolism and inhibited tricarboxylic acid cycle, which satisfied the energy and biomass demands for tumor initiation and progression, meanwhile reducing apoptosis by counteracting oxidative stress. Risk stratification was performed based on the differential metabolites between tumor and adjacent noncancerous tissues by using nonnegative matrix factorization clustering. Three metabolic clusters displaying different characteristics were identified, and the cluster with higher levels of free fatty acids (FFAs) in tumors showed a worse prognosis. Finally, a metabolite classifier composed of six FFAs was further verified in a dependent sample set to have potential to define the patients with poor prognosis. Together, our results offered insights into the molecular pathological characteristics of HCC.

The Influence of ICAM1 3'UTR Gene Polymorphism on the Occurrence and Metastasis of Primary Liver Cancer

Objective

In this study, we explored the influence of single nucleotide polymorphism (SNP) in the noncoding region of intercellular adhesion molecule 1 (ICAM1) gene on the occurrence and metastasis of primary hepatocellular carcinoma (PHC).

Methods

Sanger sequencing was used to analyze the genotypes of rs3093032, rs923366, and rs281437 locus in the 3′untranslated region (UTR) of the ICAM1 gene. The level of plasma ICAM1 was analyzed by enzyme-linked immunosorbent assay (ELISA).

Results

After adjusting for risk factors such as BMI, smoking, drinking, family history of tumors, and hepatitis B virus test results, the CT genotype at rs3093032 of the ICAM1 gene (OR = 0.19, 95% CI: 0.08-0.44, P < 0.01), dominance model (OR = 0.23, 95% CI: 0.11-0.48, P < 0.01), and T allele (OR = 0.27, 95% CI: 0.14-0.53, P < 0.01) were related to the reduced risk of PHC susceptibility. rs923366 locus CT genotype (OR = 0.63, 95% CI: 0.44-0.90, P = 0.01), TT genotype (OR = 0.23, 95% CI: 0.10-0.53, P < 0.01), dominant model (OR = 0.55, 95% CI: 0.39-0.77, P < 0.01), recessive model (OR = 0.28, 95% CI: 0.12-0.62, P < 0.01), and T allele (OR = 0.55, 95% CI: 0.42-0.73, P < 0.01) were related to a reduction in the risk of PHC susceptibility. rs281437 locus CT genotype (OR = 2.08, 95% CI: 1.40-3.09, P < 0.01), TT genotype (OR = 5.20, 95% CI: 2.22-12.17, P < 0.01), dominant model (OR = 2.45, 95% CI: 1.69-3.54, P < 0.01), recessive model (OR = 4.32, 95% CI: 1.86-10.06, P < 0.01), and T allele (OR = 2.46, 95% CI: 1.79-3.38, P < 0.01) were significantly related to the increased risk of PHC susceptibility. SNPs at rs3093032, rs923366, and rs281437 of the ICAM1 gene were significantly correlated with TNM stage and tumor metastasis of PHC patients (P < 0.05).

Conclusion

SNPs at rs3093032, rs923366, and rs281437 in the 3′UTR region of the ICAM1 gene are related to the occurrence and metastasis of PHC.

The Use of Machine Learning to Create a Risk Score to Predict Survival in Patients with Hepatocellular Carcinoma: A TCGA Cohort Analysis

INTRODUCTION

Hepatocellular carcinoma (HCC) accounts for approximately 90% of primary liver malignancies and is currently the fourth most common cause of cancer-related death worldwide. Due to varying underlying etiologies, the prognosis of HCC differs greatly among patients. It is important to develop ways to help stratify patients upon initial diagnosis to provide optimal treatment modalities and follow-up plans. The current study uses Artificial Neural Network (ANN) and Classification Tree Analysis (CTA) to create a gene signature score that can help predict survival in patients with HCC.

METHODS

The Cancer Genome Atlas (TCGA-LIHC) was analyzed for differentially expressed genes. Clinicopathological data were obtained from cBioPortal. ANN analysis of the 75 most significant genes predicting disease-free survival (DFS) was performed. Next, CTA results were used for creation of the scoring system. Cox regression was performed to identify the prognostic value of the scoring system.

RESULTS

363 patients diagnosed with HCC were analyzed in this study. ANN provided 15 genes with normalized importance >50%. CTA resulted in a set of three genes (NRM, STAG3, and SNHG20). Patients were then divided in to 4 groups based on the CTA tree cutoff values. The Kaplan-Meier analysis showed significantly reduced DFS in groups 1, 2, and 3 (median DFS: 29.7 months, 16.1 months, and 11.7 months, p < 0.01) compared to group 0 (median not reached). Similar results were observed when overall survival (OS) was analyzed. On multivariate Cox regression, higher scores were associated with significantly shorter DFS (1 point: HR 2.57 (1.38-4.80), 2 points: 3.91 (2.11-7.24), and 3 points: 5.09 (2.70-9.58), p < 0.01).

CONCLUSION

Long-term outcomes of patients with HCC can be predicted using a simplified scoring system based on tumor mRNA gene expression levels. This tool could assist clinicians and researchers in identifying patients at increased risks for recurrence to tailor specific treatment and follow-up strategies for individual patients.

Hepatocellular carcinoma biomarkers, an imminent need

Hepatocellular carcinoma (HCC) is the most common malignant neoplasm of the liver and one of the deadliest cancers worldwide. The identification of novel, highly specific and more sensitive biomarkers for HCC is crucial because existing ones are deficient and non-confirmatory without histological biopsy or imaging techniques.

Dynamic Changes in Neutrophil-to-Lymphocyte Ratio are Associated with Survival and Liver Toxicity Following Stereotactic Body Radiotherapy for Hepatocellular Carcinoma

Purpose

Immune response to antitumor therapies has been correlated with oncologic outcomes. This study aimed to determine whether dynamic changes in immune parameters could predict survival outcomes and assess their relationship with liver toxicity in hepatocellular carcinoma (HCC) patients treated with stereotactic body radiation therapy (SBRT).

Methods

Data on pre- and post-SBRT (within 3 months) peripheral blood cell counts, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were retrospectively collected. Kinetic changes in these immune parameters and delta-NLR (dNLR) and delta-PLR (dPLR) in response to SBRT were evaluated. Overall survival (OS) and progression-free survival (PFS) were compared based on baseline NLR/PLR and dNLR/dPLR. Additionally, the association of these dynamic measures with liver toxicity was determined.

Results

The study included 93 patients with a median 10.7-month follow-up. Significant increases in NLR (p<0.001) and PLR (p=0.003) were observed after SBRT. In the multivariable analysis, elevated pre-SBRT NLR (p<0.001) and dNLR (p=0.011) were predictive of worse OS. dNLR was not associated with PFS. Neither PLR nor dPLR was predictive of survival outcomes. Patients with Child-Turcotte-Pugh class B had higher dNLR and greater risk of liver toxicity than class A counterparts. Receiver operating characteristic curve analysis found that dNLR ≥1.9 was an optimal cut-off value for determining liver toxicity risk (35.1% vs 7.5%, p=0.002).

Conclusion

Baseline NLR and dNLR can complementarily predict OS in HCC patients treated with SBRT. Elevated dNLR is associated with worse OS and development of liver toxicity, possibly through their relationship with baseline liver function. Dynamic changes in NLR should be monitored in HCC care.

Identification of ABCC5 Among ATP-Binding Cassette Transporter Family as a New Biomarker for Hepatocellular Carcinoma Based on Bioinformatics Analysis

Purpose

Liver cancer is the fifth most common type of cancer worldwide, and the ATP-binding cassette (ABC) transporter family has been widely accepted as a cause of multidrug resistance. This study was conducted to explore the potential value and mechanisms of the ABC transporter gene family in the liver hepatocellular carcinoma (LIHC).

Materials and Methods

Data were collected from different public databases. UALCAN, ONCOMINE, and GEPIA were used to retrieve a selection of differently expressed and pathological stage-related genes among the ABC family. Principal component analysis (PCA) was utilized for grouping, and its prognostic value was evaluated by univariate and multivariate Cox analyses. The co-expression pattern was constructed with UALCAN, and the functional analyses were carried out with DAVID. The correlation between the biomarker and immune infiltration, genetic alteration frequency, and drug sensitivity were explored with TIMER, cBioPortal, GDSC and CTRP, respectively. Finally, tSNE algorithm was used to explore the distribution of ABCC5 expressed cells.

Results

Among the ABC transporter family members, ABCC5 was differently expressed and strongly related to the pathological stage of LIHC. PCA divided patients of LIHC into two groups, and Cox analyses demonstrated that ABCC5 was an independent risk factor of LIHC. Functional analyses indicated that the genes were enriched in the pathways of transmembrane transporter, ATPase activity, and bile secretion. ABCC5 is also associated with immune infiltration of cells like macrophages, neutrophils, and dendritic cells. The genetic alteration frequency of ABCC5 confirmed its potential value in LIHC. In addition, several drugs were explored and found to be relevant to LIHC. The t-SNE showed that expression of ABCC5 was most concentrated in macrophages, followed by hepatocytes.

Conclusion

ABCC5 may facilitate LIHC progression through different mechanisms and be a potential biomarker and target for diagnosis, prognosis, and therapy of LIHC.

SPRY4-AS1, A Novel Enhancer RNA, Is a Potential Novel Prognostic Biomarker and Therapeutic Target for Hepatocellular Carcinoma

A growing number of evidence have demonstrated the involvement of enhancer RNAs (eRNAs) in tumor progression. However, the possible functions of eRNAs in hepatocellular carcinoma (HCC) remain largely unclear. Our present research aimed to screen critical eRNAs and to further delve into the clinical significance of eRNAs in HCC patients. In this study, we identified 124 prognosis-related eRNAs by analyzing The Cancer Genome Atlas (TCGA) datasets. Among them, SPRY4 antisense RNA 1 (SPRY4-AS1) may be a key eRNA involved in HCC progression. SPRY4 was a regulatory target of SPRY4-AS1. High SPRY4-AS1 expression was associated with poor prognosis of HCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) assays revealed that the mainly enriched biological process included Human papillomavirus infection, Hippo signaling pathway, and Proteoglycans in cancer. Besides, RT-PCR and immunohistochemical staining confirmed SPRY4-AS1 as an overexpressed eRNA in HCC specimens. The pan-cancer assays revealed that SPRY4-AS1 was associated with glioblastoma multiforme (GBM), adrenocortical carcinoma (ACC), brain lower grade glioma (LGG) and mesothelioma(MESO). Positive associations were observed between SPRY4-AS1 and SPRY4 (its target gene) in 16 tumor types. Collectively, our findings reveal a novel eRNA SPRY4-AS1 for HCC progression and suggest that SPRY4-AS1 may be a potential biomarker and therapeutic target for HCC.

Development of a Toll-Like Receptor-Based Gene Signature That Can Predict Prognosis, Tumor Microenvironment, and Chemotherapy Response for Hepatocellular Carcinoma

Objective: Emerging evidence highlights the implications of the toll-like receptor (TLR) signaling pathway in the pathogenesis and therapeutic regimens of hepatocellular carcinoma (HCC). Herein, a prognostic TLR-based gene signature was conducted for HCC.

Methods: HCC-specific TLRs were screened in the TCGA cohort. A LASSO model was constructed based on prognosis-related HCC-specific TLRs. The predictive efficacy, sensitivity, and independency of this signature was then evaluated and externally verified in the ICGC, GSE14520, and GSE76427 cohorts. The associations between this signature and tumor microenvironment (stromal/immune score, immune checkpoint expression, and immune cell infiltrations) and chemotherapy response were assessed in HCC specimens. The expression of TLRs in this signature was verified in HCC and normal liver tissues by Western blot. Following si-MAP2K2 transfection, colony formation and apoptosis of Huh7 and HepG2 cells were examined.

Results: Herein, we identified 60 HCC-specific TLRs. A TLR-based gene signature (MAP2K2, IRAK1, RAC1, TRAF3, MAP3K7, and SPP1) was conducted for HCC prognosis. High-risk patients exhibited undesirable outcomes. ROC curves confirmed the well prediction performance of this signature. Multivariate Cox regression analysis demonstrated that the signature was an independent prognostic indicator. Also, high-risk HCC was characterized by an increased immune score, immune checkpoint expression, and immune cell infiltration. Meanwhile, high-risk patients displayed higher sensitivity to gemcitabine and cisplatin. The dysregulation of TLRs in the signature was confirmed in HCC. MAP2K2 knockdown weakened colony formation and elevated apoptosis of Huh7 and HepG2 cells.

Conclusion: Collectively, this TLR-based gene signature might assist clinicians to select personalized therapy programs for HCC patients.

Atezolizumab and bevacizumab as first line therapy in advanced hepatocellular carcinoma: Practical considerations in routine clinical practice

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. For advanced HCC, sorafenib was considered the standard of care for more than ten years. Recently the atezolizumab and bevacizumab combination has become standard of care for these patients without contraindications to either immune checkpoint inhibitors or antiangiogenic therapy. We now review the practical aspects of the atezolizumab and bevacizumab combination, including current evidence, indications, contraindications, management of adverse events, sequencing of this combination, areas of current knowledge gaps and future areas of active clinical research of this combination for busy clinicians in clinical practice.

Pan-cancer analysis and single-cell analysis revealed the role of ABCC5 transporter in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer. Many patients with hepatocellular carcinoma are diagnosed at an advanced stage because the early symptoms are not obvious. For advanced hepatocellular carcinoma, immunotherapy and targeted therapy seem to be a promising direction. Finding a new prognostic marker for hepatocellular carcinoma and exploring its role in the immune microenvironment is of great value. ABCC transporters have previously been associated with drug resistance in hepatocellular tumors, but the exact mechanism remains unclear. Here, we conducted a study on ABCC5 in HCC and found that the expression of ABCC5 was up-regulated in HCC and was associated with poor prognosis. Further exploration revealed that ABCC5 was associated with immune infiltration of hepatocellular carcinoma. Single-cell analysis revealed a potential relationship between ABCC5 and immune cell differentiation. Therefore, it is significant to continue to explore the role of ABCC5 in hepatocellular carcinoma.

Silica-Based Nanoframeworks Involved Hepatocellular Carcinoma Theranostic

Silica-based nanoframeworks have been extensively studied for diagnosing and treating hepatocellular carcinoma (HCC). Several reviews have summarized the advantages and disadvantages of these nanoframeworks and their use as drug-delivery carriers. Encouragingly, these nanoframeworks, especially those with metal elements or small molecular drugs doping into the skeleton structure or modifying onto the surface of nanoparticles, could be multifunctional components participating in HCC diagnosis and treatment rather than functioning only as drug-delivery carriers. Therefore, in this work, we described the research progress of silica-based nanoframeworks involved in HCC diagnosis (plasma biomarker detection, magnetic resonance imaging, positron emission tomography, photoacoustic imaging, fluorescent imaging, ultrasonography, etc.) and treatment (chemotherapy, ferroptotic therapy, radiotherapy, phototherapy, sonodynamic therapy, immunotherapy, etc.) to clarify their roles in HCC theranostics. Further, the future expectations and challenges associated with silica-based nanoframeworks were highlighted. We believe that this review will provide a comprehensive understanding for researchers to design novel, functional silica-based nanoframeworks that can effectively overcome HCC.

Laparoscopic Surgery for a Patient With Multiple Liver Metastases of Unknown Origin Concomitant With Gallbladder Tumor

BACKGROUND

The liver is the digestive organ where metastatic adenocarcinoma of unknown primary site is most often observed.

CASE REPORT

A 74-year-old man was diagnosed with a growing gallbladder tumor and multiple liver tumors limited to the left lateral sector. Liver tumors were suggested to be primary or secondary adenocarcinoma with no relation to the gallbladder tumor. Also for diagnostic purposes, laparoscopic full-thickness resection of the gallbladder, laparoscopic lateral sectionectomy and lymph node sampling were performed. The final histopathological diagnosis was hyperplastic polyp of the gallbladder and metastatic poorly differentiated adenocarcinoma of the liver. Liver tumors were suspected to originate from the stomach, duodenum, or small intestine; however, the primary sites could not be identified. The patient has been closely followed up without any chemotherapy 3 months after surgery.

CONCLUSION

Laparoscopic surgery can be strongly recommended for patients with multiple liver tumors of unknown origin concomitant with a gallbladder tumor.

N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m⁶A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m⁶A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear.

Case presentation

The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy.

Conclusion

SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.

Telocytes promote hepatocellular carcinoma by activating the ERK signaling pathway and miR-942-3p/MMP9 axis

In China, hepatocellular carcinoma (HCC) is considered a malignant tumor with poor prognosis, frequent metastasis, and a high relapse rate. Telocytes (TCs) participate in tumorigenic, invasive, and migratory processes by secreting functional proteins and transmitting cell-to-cell information, but their functions in HCC are still unknown. TC counts and MMP9 expression in liver cancer tissues were measured using immunohistochemistry, western blotting, and RT-PCR. Primary TCs from liver para-cancer tissues were cultured in vitro. To verify the role of TCs in HCC, a metastatic cancer animal model was established using three types of liver cancer cell lines in vivo. TCs promoted HCC cell metastasis by MMP9 expression in vitro and in vivo. Platelet-derived growth factor-alpha (PDGF-α), secreted by HCC cells, activated the Ras/ERK signaling pathway in TCs, thereby increasing MMP9 expression; Moreover, miR-942-3p suppressed MMP9 expression in TCs. Our results reveal the role of TCs in HCC and the mechanisms by which they elicit their effects, and they may serve as novel prognostic markers for HCC.

Non-Coding RNA-Based Biosensors for Early Detection of Liver Cancer

Primary liver cancer is an aggressive, lethal malignancy that ranks as the fourth leading cause of cancer-related death worldwide. Its 5-year mortality rate is estimated to be more than 95%. This significant low survival rate is due to poor diagnosis, which can be referred to as the lack of sufficient and early-stage detection methods. Many liver cancer-associated non-coding RNAs (ncRNAs) have been extensively examined to serve as promising biomarkers for precise diagnostics, prognostics, and the evaluation of the therapeutic progress. For the simple, rapid, and selective ncRNA detection, various nanomaterial-enhanced biosensors have been developed based on electrochemical, optical, and electromechanical detection methods. This review presents ncRNAs as the potential biomarkers for the early-stage diagnosis of liver cancer. Moreover, a comprehensive overview of recent developments in nanobiosensors for liver cancer-related ncRNA detection is provided.

Serum Cartilage Oligomeric Matrix Protein and Golgi Protein-73: New Diagnostic and Predictive Tools for Liver Fibrosis and Hepatocellular Cancer?

Simple Summary

Hepatocellular carcinoma (HCC) ranks as the sixth most common malignancy and represents the fourth leading cause of cancer-related deaths. However, most HCC cases are insidious in the early stages leading to a delay in diagnosis with limited treatment options. In patients with chronic liver diseases, advanced liver fibrosis and cirrhosis are the leading risk factors for the development of HCC. Cartilage oligomeric matrix protein (COMP) and Golgi protein-73 (GP73) are two biomarkers that have been associated with the progression of chronic liver disease, including inflammation, fibrosis, and HCC. The aim of our study was to assess the performance of the combination of these biomarkers. We confirmed, in a large cohort of 288 patients with chronic liver diseases, that the combination of GP73 and COMP had a high discriminative ability to detect severe fibrosis/cirrhosis and is efficient in predicting the development of HCC.

Abstract

The cartilage oligomeric matrix protein (COMP) and Golgi-protein-73 (GP73) have been proposed as markers of liver fibrosis and hepatocellular carcinoma (HCC). Our aim was to assess the performance of the combination of these markers in diagnosing cirrhosis and predicting HCC development. Sera from 288 consecutive patients with chronic liver diseases were investigated by using COMP and GP73-ELISAs. Dual positivity for COMP (>15 U/L) and GP73 (>20 units) was observed in 24 (8.3%) patients, while 30 (10.4%) were GP73(+)/COMP(−), 37/288 (12.8%) GP73(−)/COMP(+), and 197 (68.5%) GP73(−)/COMP(−). Positivity for both markers was associated with cirrhosis [23/24 (95.8%) for GP73(+)/COMP(+) vs. 22/30 (73.3%) for GP73(+)/COMP(−) vs. 25/37 (67.6%) for GP73(−)/COMP(+) vs. 46/197 (23.4%) for GP73(−)/COMP(−); P < 0.001]. The combination of GP73, COMP, the aspartate aminotransferase/platelets ratio index, and the Fibrosis-4 score had even higher diagnostic accuracy to detect the presence of cirrhosis [AUC (95% CI): 0.916 (0.878–0.946)] or significant liver fibrosis (METAVIR ≥ F2) [AUC (95% CI): 0.832 (0.768–0.883)] than each marker alone. Kaplan-Meier analysis showed that positivity for both GP73 and COMP was associated with higher rates of HCC development (P < 0.001) and liver-related deaths (P < 0.001) during follow-up. In conclusion, the combination of GP73 and COMP seems efficient to detect cirrhosis and predict worse outcomes and the development of HCC in patients with chronic liver diseases.

Biomarkers in Hepatobiliary Cancers: What is Useful in Clinical Practice?

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.

Genomic Landscape of Liquid Biopsy for Hepatocellular Carcinoma Personalized Medicine

Hepatocellular carcinoma (HCC) is the sixth most frequently diagnosed cancer and the third leading cause of cancer-related deaths worldwide. Advanced-stage HCC patients have poor survival rates and this requires the discovery of novel clear biomarkers for HCC early diagnosis and prognosis, identifying risk factors, distinguishing HCC from non-HCC liver diseases, and assessment of treatment response. Liquid biopsy has emerged as a novel minimally invasive approach to enable monitoring tumor progression, metastasis, and recurrence. Since the liquid biopsy analysis has relatively high specificity and low sensitivity in cancer early detection, there is a risk of bias. Next-generation sequencing (NGS) technologies provide accurate and comprehensive gene expression and mutational profiling of liquid biopsies including cell-free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and genomic components of extracellular vesicles (EVs) including micro-RNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). Since HCC is a highly heterogeneous cancer, HCC patients can display various genomic, epigenomic, and transcriptomic patterns and exhibit varying sensitivity to treatment options. Identification of individual variabilities in genomic signatures in liquid biopsy has the potential to greatly enhance precision oncology capabilities. In this review, we highlight and critically discuss the latest progress in characterizing the genomic landscape of liquid biopsy, which can advance HCC personalized medicine.

Biomarkers of Oncogenesis, Adipose Tissue Dysfunction and Systemic Inflammation for the Detection of Hepatocellular Carcinoma in Patients with Nonalcoholic Fatty Liver Disease

Simple Summary

Circulating biomarkers for the detection of hepatocellular carcinoma in patients with dysmetabolic liver disease are an unmet need. In the present study, we observed that serum values of five biomarkers (namely, AFP, PIVKA-II, GPC-3, adiponectin and IL-6) were significantly different between patients with and without hepatocellular carcinoma; the best accuracy for the detection of tumor was achieved by PIVKA-II. Furthermore, we developed a model combining age, gender, PIVKA-II, GPC-3 and adiponectin that showed an excellent performance for the identification of patients with hepatocellular carcinoma. This model may be useful for the surveillance of patients with dysmetabolic liver disease at risk of hepatocellular carcinoma development.

Abstract

Current surveillance strategy for patients with nonalcoholic fatty liver disease (NAFLD) at risk of hepatocellular carcinoma (HCC) development is unsatisfactory. We aimed to investigate the diagnostic accuracy of alpha-fetoprotein (AFP), protein induced by vitamin K absence or antagonist-II (PIVKA-II), glypican-3 (GPC-3), adiponectin, leptin and interleukin-6 (IL-6), alone or in combination, for the discrimination between NAFLD patients with or without HCC. The biomarkers were investigated in a cohort of 191 NAFLD patients (median age 62, 54–68 years; 121 males and 70 females) with advanced fibrosis/cirrhosis, 72 of whom had a diagnosis of HCC. PIVKA-II showed the best performance for the detection of HCC with an area under the curve (AUC) of 0.853, followed by adiponectin (AUC = 0.770), AFP (AUC = 0.763), GPC-3 (AUC = 0.759) and by IL-6 (AUC = 0.731), while the leptin values were not different between patients with and without HCC. The accuracy of the biomarkers’ combination was assessed by a stratified cross-validation approach. The combination of age, gender, PIVKA-II, GPC-3 and adiponectin further improved the diagnostic accuracy (AUC = 0.948); the model correctly identified the 87% of the patients. In conclusion, we developed a model with excellent accuracy for the detection of HCC that may be useful to improve the surveillance of NAFLD patients at risk of tumor development.

Predictive effects of preoperative serum CA125 and AFP levels on post-hepatectomy survival in patients with hepatitis B-related hepatocellular carcinoma

The association between the serum levels of cancer antigen 125 (CA125; also termed MUC16) and the prognosis of patients with hepatocellular carcinoma (HCC) has not been widely reported to date. The aim of the present study was to determine the association between preoperative serum CA125 levels and prognosis of patients with hepatitis B virus (HBV)-related HCC after hepatectomy. The study included 306 patients with HBV-related HCC who underwent liver resection and were classified into four subgroups based on their baseline CA125 and α-fetoprotein (AFP) levels. The perioperative clinical data were compared and analyzed. Kaplan-Meier and Cox regression analyses were performed to determine the associations between patient clinicopathological characteristics and survival. The results revealed that the median follow-up time was 35 months. Patients with low preoperative serum CA125 levels presented with improved 3-year disease-free survival (DFS) (79.3 vs. 75.7%; P=0.278) and overall survival (OS) (84.4 vs. 77.1%; P=0.001) rates compared with those among patients with high preoperative serum CA125 levels. High preoperative serum CA125 levels were a risk factor associated with short DFS and OS rates in all patients. In patients with baseline AFP levels >100 ng/ml, low preoperative serum CA125 levels were significantly associated with prolonged DFS and OS rates (log-rank test P=0.002 and P=0.005, respectively). In patients with AFP levels ≤100 ng/ml, no significant differences were observed in DFS or OS rates between the high and low preoperative serum CA125 groups. Patients with high preoperative serum CA125 and AFP levels exhibited the worst prognosis (low DFS and OS rates). In conclusion, high baseline CA125 levels may be associated with a poor prognosis in patients with HBV-related HCC.

A Novel Epigenetic Machine Learning Model to Define Risk of Progression for Hepatocellular Carcinoma Patients

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.

The Angiopoietin/Tie2 Pathway in Hepatocellular Carcinoma

Due to the usually late diagnosis and lack of effective therapies, hepatocellular carcinoma (HCC), which poses a growing global health problem, is characterized by a poor prognosis. Angiogenesis plays an important role in HCC progression, and vascular endothelial growth factor (VEGF) and angiopoietins (Angs) are key drivers of HCC angiogenesis. VEGF-targeting strategies already represent an important component of today’s systemic treatment landscape of HCC, whereas targeting the Ang/Tie2 signaling pathway may harbor future potential in this context due to reported beneficial anticancer effects when targeting this pathway. In addition, a better understanding of the relation between Angs and HCC angiogenesis and progression may reveal their potential as predictive factors for post-treatment disease progression and prognosis. In this review, we give a comprehensive overview of the complex role of Ang/Tie2 signaling in HCC, pinpointing its potential value as biomarker and target for HCC treatments, aiding HCC diagnosis and therapy.