Genetic Biomarkers For Hepatocellular Carcinoma In The Era Of Precision Medicine

TFAIP6 facilitates hepatocellular carcinoma cell glycolysis through upregulating c-myc/PKM2 axis

Background

Hepatocellular carcinoma (HCC) is the most prevalent liver cancer. Despite of the improvement of therapies, the durable response rate and survival benefit are still limited for HCC patients. It's urgent to clarify the molecular mechanisms and find therapeutic strategies to improve the clinical outcome. TNFα-stimulated gene-6 (TNFAIP6) plays a critical role in the prognosis of various tumors, but its roles in HCC are still unclear.

Methods

Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) analysis were employed to evaluate the clinical relevance of TNFAIP6 expressions in HCC patients. Cell counting kit-8 (CCK-8), Edu assay, and transwell assay were performed to evaluate the malignancy of HCC cells. Glucose uptake, lactate production, ATP production, extracellular acidification rate (ECAR) by Seahorse XF analyzer were employed to evaluate the role of TNFAIP6 in the regulation of aerobic glycolysis. The expressions of key proteins involved in glycolysis were examined by Western blot. Co-immunoprecipitation (Co-IP) and chromatin immunoprecipitation (ChIP) were used for protein-protein interactions or protein-RNA interactions respectively. Knockdown and overexpression of TNFAIP6 in HCC cells were employed for analyzing the functions of TNFAIP6 in HCC.

Results

TNFAIP6 was significantly upregulated in HCC and predicted a poor clinical prognosis. Knockdown of TNFAIP6 inhibited in vitro cell proliferation, invasion, migration, as well as glycolysis in HCC cells. Mechanistically, we clarified that TNFAIP6 interacted with heterogeneous nuclear ribonucleoprotein C (HNRNPC), stabilized c-Myc mRNA and upregulated pyruvate kinase M2 (PKM2) to promote glycolysis.

Conclusions

Our study reveals a molecular mechanism by which TNFAIP6 promotes aerobic glycolysis, which is beneficial for malignance of HCC and provides a potential clinical therapy for disease management.

Genetic screening of liver cancer: State of the art

Liver cancer, primarily hepatocellular carcinoma, remains a global health challenge with rising incidence and limited therapeutic options. Genetic factors play a pivotal role in the development and progression of liver cancer. This state-of-the-art paper provides a comprehensive review of the current landscape of genetic screening strategies for liver cancer. We discuss the genetic underpinnings of liver cancer, emphasizing the critical role of risk-associated genetic variants, somatic mutations, and epigenetic alterations. We also explore the intricate interplay between environmental factors and genetics, highlighting how genetic screening can aid in risk stratification and early detection via using liquid biopsy, and advancements in high-throughput sequencing technologies. By synthesizing the latest research findings, we aim to provide a comprehensive overview of the state-of-the-art genetic screening methods for liver cancer, shedding light on their potential to revolutionize early detection, risk assessment, and targeted therapies in the fight against this devastating disease.

An immune-related signature for optimizing prognosis prediction and treatment decision of hepatocellular carcinoma

BACKGROUND

An immune-related gene signature (IGS) was established for discriminating prognosis, predicting benefit of immunotherapy, and exploring therapeutic options in hepatocellular carcinoma (HCC).

METHODS

Based on Immune-related hub genes and The Cancer Genome Atlas (TCGA) LIHC dataset (n = 363), an immune-related gene signature (IGS) was established by least absolute shrinkage and selection operator (LASSO) analysis. The prognostic significance and clinical implications of IGS were verified in International Cancer Genome Consortium (ICGC) and Chinese HCC (CHCC) cohorts. The molecular and immune characteristics and the benefit of immune checkpoint inhibitor (ICI) therapy in IGS-defined subgroups were analyzed. In addition, by leveraging the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing datasets, we determined the potential therapeutic agents for high IGS-risk patients.

RESULTS

The IGS was constructed based on 8 immune-related hub genes with individual coefficients. The IGS risk model could robustly predict the survival of HCC patients in TCGA, ICGC, and CHCC cohorts. Compared with 4 previous established immune genes-based signatures, IGS exhibited superior performance in survival prediction. Additionally, for immunological characteristics and enriched pathways, a low-IGS score was correlated with IL-6/JAK/STAT3 signaling, inflammatory response and interferon α/γ response pathways, low TP53 mutation rate, high infiltration level, and more benefit from ICI therapy. In contrast, high IGS score manifested an immunosuppressive microenvironment and activated aggressive pathways. Finally, by in silico screening potential compounds, vindesine, ispinesib and dasatinib were identified as potential therapeutic agents for high-IGS risk patients.

CONCLUSIONS

This study developed a robust IGS model for survival prediction of HCC patients, providing new insights into integrating tailored risk stratification with precise immunotherapy and screening potentially targeted agents.

Association between serum midkine levels and tumor size in Indonesian hepatocellular carcinoma patients: a cross-sectional study

Background: The incidence of liver cancer is increased worldwide with 75%–85% are diagnosed as hepatocellular carcinoma (HCC). Current practice has low sensitivity limitations to diagnose the early stages of HCC, thus urging the need for a biomarker with higher sensitivity to detect HCC, specifically in the early stage. This study aimed to determine the association between Midkine levels and progressiveness of hepatocellular carcinoma (HCC), according to tumor size, Barcelona Clinic Liver Cancer (BCLC), and presence of portal venous thrombosis.

Methods: This cross-sectional study involved 100 patients in Adam Malik General Hospital diagnosed with HCC, collected with a consecutive sampling method, whose diagnosis were confirmed by findings of hypervascular on arterial phase imaging and portal vein or delayed phase washout triple-phase CT Scan. Samples are later categorized according to Barcelona Clinic Liver Cancer (BCLC) stages, tumor size, and presence of portal venous thrombosis. Blood samples were drawn to measure serum Midkine using ELISA. Kruskal-Wallis and Mann-Whitney U tests were conducted to determine the difference of Midkine levels based on tumor size, BCLC staging, and presence of portal venous thrombosis.

Results: Serum Midkine level shows a significant difference over tumor size (p=0.014), no significant difference found compared to BCLC stages and presence of portal venous thrombosis.

Conclusion: Serum Midkine levels are associated with the tumor size of HCC, thus helping physicians determine treatment plans.

Efficacy and safety of immune checkpoint inhibitors-combined antiangiogenic drugs in the treatment of hepatocellular carcinoma: A systematic review and meta analysis

Background

Hepatocellular carcinoma is a pathological type of liver cancer and accounts for the majority of primary liver cancers. We conducted a meta-analysis to evaluate the efficacy and safety of immune checkpoint inhibitors in combination with antiangiogenic drugs in the treatment of hepatocellular carcinoma.

Methods

We searched scientific literature databases and clinical trials databases through May 2022 for required studies. Progression-free survival was taken as the main outcome, and overall survival, response rate and adverse events as secondary outcomes. These data were extracted, combined and used for meta-analysis to compare the treatment effect and safety of immune checkpoint inhibitors combined with antiangiogenic drugs in patients with advanced/unresectable/metastatic hepatocellular carcinoma.

Results

This study included 3 randomized controlled trials and 6 single-arm trials of immune checkpoint inhibitors in combination with antiangiogenic drugs in hepatocellular carcinoma. Meta-analysis showed that compared with single use, combination of the two can significantly improve PFS (HR=5.93, 95% CI=5.41, 6.45) and OS (HR=15.84, 95% CI=15.39, 16.28). The ORR and DOR of patients with combination therapy were HR=19.11, 95% CI=15.99, 22.22 and HR=12.26, 95% CI=10.32, 14.21, respectively. Common adverse reactions to combination therapy included hypertension (26.8%), diarrhea (23.6%), fatigue (23.8%), decreased appetite (22.8%), hypothyroidism (9.9%), and rash (14.5%).

Conclusion

In the treatment of advanced/unresectable/metastatic hepatocellular carcinoma, immune checkpoint inhibitors combined with antiangiogenic drugs achieved better survival benefits than alone. In addition, the combination therapy has tolerable safety.

Identification of chromatin organization-related gene signature for hepatocellular carcinoma prognosis and predicting immunotherapy response

BACKGROUND

Chromatin organization is associated with tumorigenesis; however, information on its role in hepatocellular carcinoma (HCC) is limited. Moreover, although immune checkpoint inhibitors (ICIs) have proven effective against HCC, the optimal index remains unknown. In this study, we aimed to construct a chromatin organization-related gene signature (CORGS) for prognosis and predicting response to ICIs in HCC.

METHODS

HCC-related data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Construction (ICGC). Chromatin organization-related genes (CORGs) were retrieved from Gene Set Enrichment Analysis. Differentially expressed genes (DEGs) and prognostic genes were then applied to select candidate genes using advanced statistical methods, including learning vector quantization, random forest, and lasso regression. Subsequently, the CORGS was established based on chromatin organization-related hub genes using multivariate Cox regression analysis, evaluated with Kaplan-Meier survival curves, and verified in 64 samples of HCC patients from Fujian Provincial Hospital (FPH) via quantitative PCR. Subsequently, functional enrichment analysis, tumor somatic mutation analysis, and tumor immune analysis were performed to evaluate the potential value of the CORGS.

RESULTS

Three hundred and thirty-nine CORGs were identified as DEGs, and 186 were associated with HCC prognosis (all P < 0.05). Four intersection genes were selected to establish the CORGS using TCGA cohort, which was found to serve as an independent risk factor for HCC patients. CORGS was then validated in an ICGC cohort. In addition, CORGS reliability was verified in 64 samples from HCC patients and 26 adjacent non-tumorous tissues, collected from the FPH. The CORGS was also associated with tumor immune microenvironment characteristics and ICI response. Moreover, data from "IMvigor 210" revealed that more patients in the low CORGS group responded to atezolizumab compared to high CORGS patients (P < 0.05). Finally, a nomogram of tumor characteristics and the CORGS was established, exhibiting superior discrimination and calibration compared to the current staging system and published models.

CONCLUSIONS

CORGS may serve as an effective predictive biomarker for HCC as well as a potential index of the tumor immune microenvironment and ICI response.

The Identification and Analysis of MicroRNAs Combined Biomarkers for Hepatocellular Carcinoma Diagnosis

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor with high morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs) were novel biomarkers with higher accuracy.

OBJECTIVE

We aimed to identify combinatorial biomarkers of miRNAs to construct a classification model for the diagnosis of HCC.

METHOD

The mature miRNAs expression profile data of six cancers (liver, lung, gastric, breast, prostate and colon) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database with accession number GSE36915, GSE29250, GSE99417, GSE41970, GSE64333 and GSE35982. The messenger RNA (mRNA) expression profile data of these six cancers were obtained from TCGA. Three R software packages, student's t-test and a normalized fold-change method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs). Using all combinations of obtained HCC- specific DEMs as input features, we construct a classification model by support vector machine searching for the optimal combination. Furthermore, target genes prediction was conducted on the miRWalk 2.0 website to obtain differentially expressed mRNAs (DEmRNAs), and KEGG pathway enrichment was analyzed on the DAVID website.

RESULTS

The optimal combination consisted of four miRNAs (hsa-miR-130a-3p, hsa-miR-450b-5p, hsa-miR-136-5p and hsa-miR-24-1-5p), of which the last one has not been currently reported to be relevant to HCC. The target genes of hsa-miR-24-1-5p (CDC7, ACACA, CTNNA1, and NF2) were involved in the cell cycle, AMPK signaling pathway, Hippo signaling pathway and insulin signaling pathway, which affect the proliferation, metastasis, and apoptosis of cancer cells. Moreover, the area under the receiver operating characteristic curves of the four miRNAs were all higher than 0.85.

CONCLUSION

These results suggest that the miRNAs combined biomarkers were reliable for the diagnosis of HCC. Hsa-miR-24-1-5p was a novel biomarker for HCC diagnosis identified in this study.

Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma

Background

The initiation and progression of tumors were due to variations of gene sets rather than individual genes. This study aimed to identify novel biomarkers based on gene set variation analysis (GSVA) in hepatocellular carcinoma.

Methods

The activities of 50 hallmark pathways were scored in three microarray datasets with paired samples with GSVA, and differential analysis was performed with the limma R package. Unsupervised clustering was conducted to determine subtypes with the ConsensusClusterPlus R package in the TCGA-LIHC (n = 329) and LIRI-JP (n = 232) cohorts. Differentially expressed genes among subtypes were identified as initial variables. Then, we used TCGA-LIHC as the training set and LIRI-JP as the validation set. A six-gene model calculating the risk scores of patients was integrated with the least absolute shrinkage and selection operator (LASSO) and stepwise regression analyses. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were performed to assess predictive performances. Multivariate Cox regression analyses were implemented to select independent prognostic factors, and a prognostic nomogram was integrated. Moreover, the diagnostic values of six genes were explored with the ROC curves and immunohistochemistry.

Results

Patients could be separated into two subtypes with different prognoses in both cohorts based on the identified differential hallmark pathways. Six prognostic genes (ASF1A, CENPA, LDHA, PSMB2, SRPRB, UCK2) were included in the risk score signature, which was demonstrated to be an independent prognostic factor. A nomogram including 540 patients was further integrated and well-calibrated. ROC analyses in the five cohorts and immunohistochemistry experiments in solid tissues indicated that CENPA and UCK2 exhibited high and robust diagnostic values.

Conclusions

Our study explored a promising prognostic nomogram and diagnostic biomarkers in hepatocellular carcinoma.

Patient stratification in hepatocellular carcinoma: impact on choice of therapy

INTRODUCTION

HCC comprises around 60 to 80% of all primary liver cancers and exhibits wide geographical variability. Appropriate treatment allocation needs to include both patient and tumor characteristics.

AREAS COVERED

Current HCC classification systems to guide therapy are either liver function-centric and evaluate physiologic liver function to guide therapy or prognostic stratification classification systems broadly based on tumor morphologic parameters, patient performance status, and liver reserve assessment. This review focuses on different classification systems for HCC, their strengths, and weaknesses as well as the use of artificial intelligence in improving prognostication in HCC.

EXPERT OPINION

Future HCC classification systems will need to incorporate clinic-pathologic data from a multitude of sources and emerging therapies to develop patient-specific treatment plans targeting a patient's unique tumor profile.

Precision Medicine for Hepatocellular Carcinoma: Clinical Perspective

Hepatocellular carcinoma (HCC) is one of the major malignant diseases worldwide, characterized by growing incidence and high mortality rates despite apparent improvements in surveillance programs, diagnostic and treatment procedures, molecular therapies, and numerous research initiatives. Most HCCs occur in patients with liver cirrhosis, and the competing mortality risks from the tumor and the cirrhosis should be considered. Presently, previously identified risk factors, such as hepatitis virus infection, hepatic inflammation and fibrosis, and metabolic syndrome, may be used as chemoprevention targets. The application of precision medicine for HCC management challenges the one-size-fits-all concept; moreover, patients should no longer be treated entirely according to the histology of their tumor but based on molecular targets specific to their tumor biology. Next-generation sequencing emphasizes HCC molecular heterogeneity and aids our comprehension of possible vulnerabilities that can be exploited. Moreover, genetic sequencing as part of a precision medicine concept may work as a promising tool for postoperative cancer monitoring. The use of genetic and epigenetic markers to identify therapeutic vulnerability could change the diagnosis and treatment of HCC, which so far was based on Barcelona clinic liver cancer (BCLC) staging. In daily clinical practice, the shift from a stage-oriented to a therapeutic-oriented approach is needed to direct the choice of HCC treatment toward the potentially most effective option on an individual basis. The important factor in precision medicine is the promotion of patient management based on the individual approach, knowing that the final decision must be approved by a multidisciplinary expert team.

The prominence of potential biomarkers in the diagnosis and management of hepatocellular carcinoma: Current scenario and future anticipation

Hepatocellular carcinoma (HCC) is one of the most aggressive and truculent types of cancer. Early detection of HCC is a massive concern that can boost the overall survival rates of HCC patients. As a result, there is a continual quest for advancements in screening, diagnosis, and treatment strategies to enhance the prognosis at its early stages. However, the confluence of inflammation and cirrhosis hampers the early detection of HCC. The analysis of different types of biomarkers such as tissue biomarkers, serum biomarkers, protein biomarkers, autoantibody markers, and improved imaging techniques has played a vital role in ameliorating HCC monitoring responses. Therefore biomarkers that can identify HCC early with a high degree of sensitivity and specificity might be prodigiously serviceable in the diagnosis and treatment of this notorious disorder. This study offers an overview of the contemporary understanding of several types of biomarkers implicated in hepatocarcinogenesis and their applications in monitoring, diagnosis, and prognosis presage. In additament, we address the role of image techniques associated with HCC diagnosis.

Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer

Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

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.

Long Non-coding RNA DANCR in Cancer: Roles, Mechanisms, and Implications

Long non-coding RNA (lncRNA) DANCR (also known as ANCR)—differentiation antagonizing non-protein coding RNA, was first reported in 2012 to suppress differentiation of epithelial cells. Emerging evidence demonstrates that DANCR is a cancer-associated lncRNA abnormally expressed in many cancers (e.g., lung cancer, gastric cancer, breast cancer, hepatocellular carcinoma). Increasing studies suggest that the dysregulation of DANCR plays critical roles in cancer cell proliferation, apoptosis, migration, invasion, and chemoresistance in vitro and tumor growth and metastasis in vivo. Mechanistic analyses show that DANCR can serve as miRNA sponges, stabilize mRNAs, and interact with proteins. Recent research reveals that DANCR can be detected in many body fluids such as serum, plasma, and exosomes, providing a quick and convenient method for cancer monitor. Thus DANCR can be used as a promising diagnostic and prognostic biomarker and therapeutic target for various types of cancer. This review focuses on the role and mechanism of DANCR in cancer progression with an emphasis on the clinical significance of DANCR in human cancers.

Characterization of metabolic landscape in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, accounting for approximately 75%-85% of primary liver cancers. Metabolic alterations have been labeled as an emerging hallmark of tumors. Specially, the last decades have registered a significant improvement in our understanding of the role of metabolism in driving the carcinogenesis and progression of HCC. In this paper, we provide a review of recent studies that investigated the metabolic traits of HCC with a specific focus on three common metabolic alterations involving glycolysis, lipid metabolism, and glutamine addiction which have been gaining much attention in the field of HCC. Next, we describe some representative diagnostic markers or tools, and promising treatment agents that are proposed on the basis of the aforementioned metabolic alterations for HCC. Finally, we present some challenges and directions that may promisingly speed up the process of developing objective diagnostic markers and therapeutic options underlying HCC. Specifically, we recommend future investigations to carefully take into account the influence of heterogeneity, control for study-specific confounds, and invite the validation of existing biomarkers.

The human melanoma proteome atlas-Defining the molecular pathology

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

Peripheral Blood Genetic Biomarkers for the Early Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and has high mortality. Biomarkers related to HCC, such as alpha-fetoprotein, and imaging technology, such as ultrasound and computed tomography, have been used to screen and monitor HCC, but HCC is still difficult to diagnose effectively in the early stage due to the low sensitivity of the above mentioned traditional methods. There is an urgent need for noninvasive biomarkers to facilitate the screening and early diagnosis of HCC. With the advancement of next-generation sequencing, genetic biomarkers are becoming the core of cancer diagnosis. Genetic biomarkers such as peripheral blood circulating tumor DNA, microRNAs, long noncoding RNAs, circular RNAs, and exosomes have become the focus of early HCC diagnostics. HCC genetic biomarkers have been implemented in clinical practice. In this review, we describe the available literature on peripheral blood genetic biomarkers in the diagnosis of early HCC.

Selecting the first line treatment in non-metastatic hepatocellular carcinoma - comparing clinical practice guidelines

Primary malignancy of the liver or hepatocellular carcinoma (HCC) is unique in its presentation, disease process, and management. Unlike breast or colon cancer, the staging of HCC depends on performance status and baseline liver function along with pathological characteristics. Apart from traditional options like surgery and systemic therapy, effective management can be achieved in selected cases with liver transplant and locoregional therapy (LRT) like transarterial chemoembolization (TACE), transarterial radioembolization (TARE), and ablation. Liver study societies and cancer groups across the globe proposed guidelines to aid the treating physicians in choosing first-line treatment for liver cancer. It is tough to compare these guidelines as they differ not only in treatment recommendations but also in risk assessment (and staging). The approach to the same patient may be different in the country he or she is managed. In clinical practice, decisions are usually taken on the consensus of multidisciplinary tumor boards and do not necessarily adhere to any guidelines. In the early (and very early) stage HCC, curative options like surgery, transplant, and ablation are recommended. In intermediate stage HCC, LRT (TACE and TARE) is preferred in the first line and systemic therapy for treatment failure or residual disease. Systemic therapy, including the atezolizumab/bevacizumab combination and tyrosine kinase inhibitors (TKI) like sorafenib and lenvatinib, is used for advanced stages. Supportive care is advised for terminal stage HCC.

Biomarkers in Hepatocellular Carcinoma: Current Status and Future Perspectives

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and one of the leading causes of cancer-related death worldwide. HCC is highly heterogeneous, both within the tumor and among individuals, which is closely related to the HCC surveillance, diagnosis, prognosis, and treatment response. With the advances of next-generation sequencing, the genomic landscape of HCC has been identified which vastly improves our understanding of genetic and epigenetic changes and their interaction during HCC development. In particular, gene mutations, epigenetic modifications, aberrant expression of coding and non-coding RNAs have been extensively explored and many of them are considered as biomarkers for HCC. Most recently, the gut microbiome has been proposed as potential non-invasive biomarkers for HCC diagnosis. In this review, we summarize the current development of HCC biomarkers studies and provide insights on further steps towards precision medicine of HCC.

Lenvatinib for hepatocellular carcinoma: From preclinical mechanisms to anti-cancer therapy

Lenvatinib, a multi-target tyrosine kinase inhibitor (TKI), is an emerging first-line therapy for hepatocellular carcinoma (HCC). Its application has changed the status of sorafenib as the only first-line TKI treatment for HCC for more than a decade. Evidence has shown that lenvatinib possesses antitumor proliferation and immunomodulatory activity in preclinical studies. In comparison, lenvatinib was non-inferior to sorafenib in overall survival (OS), and even shows superiority with regard to all the secondary efficacy endpoints. Immune-checkpoint inhibitors(ICIs)are now being incorporated into HCC treatment. Positive outcomes have been achieved in the combination of lenvatinib plus ICIs, bringing broader prospects for HCC. This review presents an overview on the therapeutic mechanisms and clinical efficacy of lenvatinib in HCC, and we discuss the future perspectives of lenvatinib in HCC management with focus on biomarker-guided precision medicine.

Emerging roles and the regulation of aerobic glycolysis in hepatocellular carcinoma

Liver cancer has become the sixth most diagnosed cancer and the fourth leading cause of cancer death worldwide. Hepatocellular carcinoma (HCC) is responsible for up to 75–85% of primary liver cancers, and sorafenib is the first targeted drug for advanced HCC treatment. However, sorafenib resistance is common because of the resultant enhancement of aerobic glycolysis and other molecular mechanisms. Aerobic glycolysis was firstly found in HCC, acts as a hallmark of liver cancer and is responsible for the regulation of proliferation, immune evasion, invasion, metastasis, angiogenesis, and drug resistance in HCC. The three rate-limiting enzymes in the glycolytic pathway, including hexokinase 2 (HK2), phosphofructokinase 1 (PFK1), and pyruvate kinases type M2 (PKM2) play an important role in the regulation of aerobic glycolysis in HCC and can be regulated by many mechanisms, such as the AMPK, PI3K/Akt pathway, HIF-1α, c-Myc and noncoding RNAs. Because of the importance of aerobic glycolysis in the progression of HCC, targeting key factors in its pathway such as the inhibition of HK2, PFK or PKM2, represent potential new therapeutic approaches for the treatment of HCC.