Copy Number Aberrations of Multiple Genes Identified as Prognostic Markers for Extrahepatic Metastasis-free Survival of Patients with Hepatocellular Carcinoma

Molecular and immune landscape of hepatocellular carcinoma for therapeutic development

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with an estimated 750,000 deaths in 2022. Recent emergence of molecular targeted agents and immune checkpoint inhibitors and their combination therapies have been transforming HCC care, but their prognostic impact in advanced-stage disease remains unsatisfactory. In addition, their application to early-stage disease is still an unmet need. Omics profiling studies have elucidated recurrent and heterogeneously present molecular aberrations involved in pro-cancer tumor (immune) microenvironment that may guide therapeutic strategies. Recurrent aberrations such somatic mutations in TERT promoter and TP53 have been regarded undruggable, but recent studies have suggested that these may serve as new classes of therapeutic targets. HCC markers such as alpha-fetoprotein, glypican-3, and epithelial cell adhesion molecule have also been explored as therapeutic targets. These molecular features may be utilized as biomarkers to guide the application of new approaches as companion biomarkers to maximize therapeutic benefits in patients who are likely to benefit from the therapies, while minimizing unnecessary harm in patients who will not respond. The explosive number of new agents in the pipelines have posed challenges in their clinical testing. Novel clinical trial designs guided by predictive biomarkers have been proposed to enable their efficient and cost-effective evaluation. These new developments collectively facilitate clinical translation of personalized molecular-targeted therapies in HCC and substantially improve prognosis of HCC patients.

Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

Construction of a radiogenomic signature based on endoplasmic reticulum stress for predicting prognosis and systemic combination therapy response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. Various factors in the tumor environment (TME) can lead to the activation of endoplasmic reticulum stress (ERS), thereby affecting the occurrence and development of tumors. The objective of our study was to develop and validate a radiogenomic signature based on ERS to predict prognosis and systemic combination therapy response.

METHODS

Using data from The Cancer Genome Atlas Program (TCGA) as a training cohort and data from International cancer genome consortium (ICGC) as a testing cohort. Univariate Cox regression and multivariate Cox regression analysis were used to identify prognostic-related genes and construct a model. HCC single-cell data obtained from Gene Expression Omnibus (GEO) were used to map gene signatures and explore inter-cellular signaling communications. Finally, a radiogenomic signature was used to predict the objective response rate (ORR) and overall survival (OS).

RESULTS

A total of four gene signatures related to ERS, including Stanniocalcin-2 (STC2), Melanoma-Associated Antigen 3 (MAGEA3), BR Serine/Threonine-Protein Kinase 2 (BRSK2), DEAD/H-Box Helicase 11 (DDX11) were identified. Macrophages were significantly different between high-risk and low-risk groups. The high-risk group showed higher targeting programmed cell death-1 (PD-1) and mutated tumor protein p53 (TP53) scores. Drug sensitivity analysis found that most sensitive drugs target the phosphatidylinositol 3-kinase/ mechanistic target of rapamycin (PI3K/mTOR) signaling pathway. Further research revealed the expression of STC2 in the endothelial cells (ECs), particularly plasmalemma vesicle associated protein (PLVAP) + ECs, and may regulate the reprogramming and function of macrophages. Furthermore, we identified nine radiomic features and established a radiogenomic signature based on ERS that can predict prognosis and response to systemic combination therapy. This signature can guide systemic combination therapy for patients with unresectable HCC.

CONCLUSIONS

We established an ERS prognostic model that can predict patient prognosis. We also found that ERS is closely related to the TME and is mainly manifested in the interaction between tumor-associated endothelial cells (TAEs) and tumor-associated macrophages (TAMs). Moreover, we constructed a radiogenomic signature based on the ERS. This signature can guide subsequent combination therapy for patients with unresectable HCC.

Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression.

APOM Modulates the Glycolysis Process in Liver Cancer Cells by Controlling the Expression and Activity of HK2 via the Notch Pathway

The metabolic pathway of aerobic glycolysis in tumor cells has garnered significant attention in tumor research because of its high activation in cancer cells. Previous research conducted by our team has demonstrated that Apolipoprotein M (APOM) exhibits potential as a factor against liver cancer. However, further investigations are needed to elucidate the precise approach and mechanism that are involved in this process. The findings of this study demonstrated that the inhibition of APOM gene expression led to a notable increase in glucose uptake within liver cancer cells, along with increased levels of lactate dehydrogenase A (LDHA) mRNA and protein expression, as well as increased lactate and adenosine triphosphate (ATP) levels (P < 0.05). These alterations in the cellular microenvironment may be associated with a significant increase in the expression level and enzyme activity of the pivotal enzyme hexokinase 2 (HK2) (P < 0.05). Subsequent investigations revealed notable enrichment of the Notch pathway in liver cancer samples exhibiting low expression of the APOM gene. Western blot experiments demonstrated that the inhibition of APOM gene expression triggers the activation of the Notch pathway in liver cancer cells. Furthermore, the administration of a γ-secretase inhibitor (DAPT) successfully mitigated the increase in HK2 levels, glucose uptake, lactate production, and proliferation of liver cancer cells induced by the downregulation of the APOM gene (P < 0.05). In conclusion, diminished APOM expression may facilitate the progression of liver cancer by stimulating the aerobic glycolysis pathway, which is mediated by the Notch signaling pathway.

Comprehensive assessment of regulatory T-cells-related scoring system for predicting the prognosis, immune microenvironment and therapeutic response in hepatocellular carcinoma

INTRODUCTION

Regulatory T cells (Tregs) play important roles in tumor immunosuppression and immune escape. The aim of the present study was to construct a novel Tregs-associated biomarker for the prediction of tumour immune microenvironment (TIME), clinical outcomes, and individualised treatment in hepatocellular carcinoma (HCC).

METHODS

Single-cell sequencing data were obtained from the three independent cohorts. Cox and LASSO regression were utilised to develop the Tregs Related Scoring System (TRSSys). GSE140520, ICGC-LIRI and CHCC cohorts were used for the validation of TRSSys. Kaplan-Meier, ROC, and Cox regression were utilised for the evaluation of TRSSys. The ESTIMATE, TIMER 2.0, and ssGSEA algorithm were utilised to determine the value of TRSSys in predicting the TIME. GSVA, GO, KEGG, and TMB analyses were used for mechanistic exploration. Finally, the value of TRSSys in predicting drug sensitivity was evaluated based on the oncoPredict algorithm.

RESULTS

Comprehensive validation showed that TRSSys had good prognostic predictive efficacy and applicability. Additionally, ssGSEA, TIMER and ESTIMATE algorithm suggested that TRSSys could help to distinguish different TIME subtypes and determine the beneficiary population of immunotherapy. Finally, the oncoPredict algorithm suggests that TRSSys provides a basis for individualised treatment.

CONCLUSIONS

TRSSys constructed in the current study is a novel HCC prognostic prediction biomarker with good predictive efficacy and stability. Additionally, risk stratification based on TRSSys can help to identify the TIME landscape subtypes and provide a basis for individualized treatment options.

Differential Response to Sorafenib Administration for Advanced Hepatocellular Carcinoma

Sorafenib has been used to treat advanced hepatocellular carcinoma (aHCC). However, there is no evidence for a response of different target lesions to sorafenib administration. Therefore, we aimed to evaluate the effect of sorafenib on various aHCC target lesions. The outcomes of sorafenib treatment on aHCC, i.e., treatment response for all Child A status patients receiving the drug, were analyzed. Of 377 aHCC patients, 73 (19.3%) had complete/partial response to sorafenib, while 134 (35.4%) and 171 (45.2) had a stable or progressive disease, respectively, in the first six months. Of the evaluated metastatic lesions, 149 (39.4%), 48 (12.7%), 123 (32.5%), 98 (25.9%), 83 (22.0%), and 45 (11.9%) were present in liver, bone, lung, portal/hepatic vein thrombus, lymph nodes, and peritoneum, respectively. The overall survival and duration of treatment were 16.9 ± 18.3 and 8.1 ± 10.5 months (with median times of 11.4 and 4.6, respectively). Our analysis showed poor outcomes in macroscopic venous thrombus and bone, higher AFP, and multiple target lesions. ALBI grade A had a better outcome. Sorafenib administration showed good treatment outcomes in selected situations. PD patients with thrombus or multiple metastases should be considered for sorafenib second-line treatment. The ALBI liver function test should be selected as a treatment criterion.

Correlating genomic copy number alterations with clinicopathologic findings in 75 cases of hepatocellular carcinoma

BACKGROUND

Oligonucleotide array comparative genomic hybridization (aCGH) analysis has been used for detecting somatic copy number alterations (CNAs) in various types of tumors. This study aimed to assess the clinical utility of aCGH for cases of hepatocellular carcinoma (HCC) and to evaluate the correlation between CNAs and clinicopathologic findings.

METHODS

aCGH was performed on 75 HCC cases with paired DNA samples from tumor and adjacent nontumor tissues. Survival outcomes from these cases were analyzed based on Barcelona-Clinic Liver Cancer Stage (BCLC), Edmondson-Steiner grade (E-S), and recurrence status. Correlation of CNAs with clinicopathologic findings was analyzed by Wilcoxon rank test and clustering vs. K means.

RESULTS

The survival outcomes indicated that BCLC stages and recurrence status could be predictors and E-S grades could be a modifier for HCC. The most common CNAs involved gains of 1q and 8q and a loss of 16q (50%), losses of 4q and 17p and a gain of 5p (40%), and losses of 8p and 13q (30%). Analyses of genomic profiles and clusters identified that losses of 4q13.2q35.2 and 10q22.3q26.13 seen in cases of stage A, grade III and nonrecurrence were likely correlated with good survival, while loss of 1p36.31p22.1 and gains of 2q11.2q21.2 and 20p13p11.1 seen in cases of stage C, grade III and recurrence were possibly correlated with worst prognosis.

CONCLUSIONS

These results indicated that aCGH analysis could be used to detect recurrent CNAs and involved key genes and pathways in patients with HCC. Further analysis on a large case series to validate the correlation of CNAs with clinicopathologic findings of HCC could provide information to interpret CNAs and predict prognosis.

Genomic Landscape of HCC

INTRODUCTION

Hepatocellular carcinoma (HCC) is a leading cause of cancer related mortality in the world and it has limited treatment options. Understanding the molecular drivers of HCC is important to develop novel biomarkers and therapeutics.

PURPOSE OF REVIEW

HCC arises in a complex background of chronic hepatitis, fibrosis and liver regeneration which lead to genomic changes. Here, we summarize studies that have expanded our understanding of the molecular landscape of HCC.

RECENT FINDINGS

Recent technological advances in next generation sequencing (NGS) have elucidated specific genetic and molecular programs involved in hepatocarcinogenesis. We summarize the major somatic mutations and epigenetic changes have been identified in NGS-based studies. We also describe promising molecular therapies and immunotherapies which target specific genetic and epigenetic molecular events.

SUMMARY

The genomic landscape of HCC is incredibly complex and heterogeneous. Promising new developments are helping us decipher the molecular drivers of HCC and leading to new therapies.

Relationship between Methylation of FHIT and CDH13 Gene Promoter Region and Liver Cancer

In order to demonstrate the relationship between methylation of fragile histidine triad (FHIT) and T-cadherin/H-cadherin (CDH13) genes and liver cancer, the methylation status of FHIT and CDH13 was detected in healthy individuals and in Mongolian and Han patients with liver cancer. The phenol-chloroform method was used to extract genomic DNA. The methylation specific polymerase chain reaction method was applied to detect the methylation status of FHIT and CDH13. The relationship between smoking and alcohol consumption and gene (FHIT and CDH13) methylation was analyzed. There was significant difference in methylation rate of FHIT (72.67%, 34.67%) and CDH13 (72.0%, 28.0%) between liver cancer patients and healthy individuals of Mongolian descent (P<0.05), as well as that of FHIT (68%, 30.67%) and CDH13 (64%, 26%) between liver cancer patients and healthy individuals of Han individuals (P<0.05). There was also a relationship between smoking and drinking and the methylation of FHIT and CDH13 (P<0.05). Thus, the methylation of FHIT and CDH13 had a relationship with liver cancer incidence. Smoking and alcohol ingestion may promote the methylation of FHIT and CDH13.