Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes and genomic phenotypes

BACKGROUND AND AIMS

Although many studies revealed transcriptomic subtypes of HCC, concordance of the subtypes are not fully examined. We aim to examine a consensus of transcriptomic subtypes and correlate them with clinical outcomes.

APPROACH AND RESULTS

By integrating 16 previously established genomic signatures for HCC subtypes, we identified five clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features, but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent β-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high hepatocyte nuclear factor 4A activity. We also developed and validated a robust predictor of consensus subtype with 100 genes and demonstrated that five subtypes were well conserved in patient-derived xenograft models and cell lines. By analyzing serum proteomic data from the same patients, we further identified potential serum biomarkers that can stratify patients into subtypes.

CONCLUSIONS

Five HCC subtypes are correlated with genomic phenotypes and clinical outcomes and highly conserved in preclinical models, providing a framework for selecting the most appropriate models for preclinical studies.

Accurate somatic variant detection using weakly supervised deep learning

Identification of somatic mutations in tumor samples is commonly based on statistical methods in combination with heuristic filters. Here we develop VarNet, an end-to-end deep learning approach for identification of somatic variants from aligned tumor and matched normal DNA reads. VarNet is trained using image representations of 4.6 million high-confidence somatic variants annotated in 356 tumor whole genomes. We benchmark VarNet across a range of publicly available datasets, demonstrating performance often exceeding current state-of-the-art methods. Overall, our results demonstrate how a scalable deep learning approach could augment and potentially supplant human engineered features and heuristic filters in somatic variant calling.

Emerging Insights on Immunotherapy in Liver Cancer

Significance: Hepatocellular carcinoma (HCC) is a liver malignancy with high mortality rate, limited treatment options, and poor prognosis. Sorafenib has been the only systemic treatment option for patients with advanced HCC for more than a decade. HCC is a typical inflammation-related tumor with a distinct immunosuppressive microenvironment especially the upregulation of immune checkpoints. Recent Advances: Immunotherapy has shown persistent and powerful efficacy in HCC treatment. Several preclinical and clinical studies have prompted the application of immunotherapy in first-line, second-line, and postline treatment of HCC, which has profoundly shifted the paradigm for advanced HCC treatment in the past few years. Critical Issues and Future Directions: Major unaddressed challenges in HCC immunotherapy include the discovery and validation of biological markers that predict the efficacy, the application of immunotherapy in patients with impaired liver function and nonalcoholic steatohepatitis-associated HCC, and the exploration of immunotherapy combinations with better effectiveness. This review provides the latest advances in the research of immune microenvironment and immunotherapy in HCC. Antioxid. Redox Signal. 37, 1325-1338.

Long-term correction of hemophilia B through CRISPR/Cas9 induced homology-independent targeted integration

CRISPR/Cas9-mediated site-specific insertion of exogenous genes holds potential for clinical applications. However, it is still infeasible because homologous recombination (HR) is inefficient, especially for non-dividing cells. To overcome the challenge, we report that a homology-independent targeted integration (HITI) strategy is used for permanent integration of high-specificity-activity Factor IX variant (F9 Padua, R338L) at the albumin (Alb) locus in a novel hemophilia B (HB) rat model. The knock-in efficiency reaches 3.66%, as determined by droplet digital PCR (ddPCR). The clotting time is reduced to a normal level four weeks after treatment, and the circulating factor IX (FIX) level is gradually increased up to 52% of the normal level over nine months even after partial hepatectomy, demonstrating the amelioration of hemophilia. Through primer-extension-mediated sequencing (PEM-seq), no significant off-target effect is detected. This study not only provides a novel model for HB but also identifies a promising therapeutic approach for rare inherited diseases.

Liver tumour immune microenvironment subtypes and neutrophil heterogeneity

The heterogeneity of the tumour immune microenvironment (TIME), organized by various immune and stromal cells, is a major contributing factor of tumour metastasis, relapse and drug resistance^1-3, but how different TIME subtypes are connected to the clinical relevance in liver cancer remains unclear. Here we performed single-cell RNA-sequencing (scRNA-seq) analysis of 189 samples collected from 124 patients and 8 mice with liver cancer. With more than 1 million cells analysed, we stratified patients into five TIME subtypes, including immune activation, immune suppression mediated by myeloid or stromal cells, immune exclusion and immune residence phenotypes. Different TIME subtypes were spatially organized and associated with chemokine networks and genomic features. Notably, tumour-associated neutrophil (TAN) populations enriched in the myeloid-cell-enriched subtype were associated with an unfavourable prognosis. Through in vitro induction of TANs and ex vivo analyses of patient TANs, we showed that CCL4⁺ TANs can recruit macrophages and that PD-L1⁺ TANs can suppress T cell cytotoxicity. Furthermore, scRNA-seq analysis of mouse neutrophil subsets revealed that they are largely conserved with those of humans. In vivo neutrophil depletion in mouse models attenuated tumour progression, confirming the pro-tumour phenotypes of TANs. With this detailed cellular heterogeneity landscape of liver cancer, our study illustrates diverse TIME subtypes, highlights immunosuppressive functions of TANs and sheds light on potential immunotherapies targeting TANs.

Highly expressed FAM189B predicts poor prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most malignant tumors with persistently high morbidity and mortality. However, the expression, prognostic and clinical significance of FAM189 family genes in HCC remain largely unknown. In this study, the expression levels of FAM189 family genes in HCC were analyzed through TCGA-LIHC and ICGC-LIRI-JP cohorts, and further validated in multiple independent GEO datasets. It was found that the expression of FAM189B was significantly upregulated in HCC tumor tissues, while the expression of FAM189A1 and FAM189A2 was not significantly changed between tumor and adjacent tissues. Further analysis revealed that upregulated copy number variation contributed to increased expression of FAM189B in HCC. Survival analysis showed that highly expressed FAM189B was significantly correlated with unfavorable prognosis, including overall survival, disease-specific survival, and progression-free interval. Univariate and multivariate Cox regression analysis showed that FAM189B was a potential novel prognosis factor for HCC patients. In addition, the association between FAM189B expression and clinical and molecular characteristics was analyzed. High expression of FAM189B was associated with high AFP level, high predicted risk metastasis signature, and TP53 mutation, while there was no significant association between FAM189B expression and cancer stage or tumor grade of HCC. Gene set enrichment analysis revealed that highly expressed FAM189B was closely related with signal pathways and biological processes associated with cell proliferation and cell cycle in HCC. In conclusion, this study suggested that FAM189B was highly expressed in HCC and highly expressed FAM189B may serve as an effective prognostic indicator and a potential therapeutic target for HCC patients.

Multi-omics analysis identifies osteosarcoma subtypes with distinct prognosis indicating stratified treatment

Osteosarcoma (OS) is a primary malignant bone tumor that most commonly affects children, adolescents, and young adults. Here, we comprehensively analyze genomic, epigenomic and transcriptomic data from 121 OS patients. Somatic mutations are diverse within the cohort, and only TP53 is significantly mutated. Through unsupervised integrative clustering of the multi-omics data, we classify OS into four subtypes with distinct molecular features and clinical prognosis: (1) Immune activated (S-IA), (2) Immune suppressed (S-IS), (3) Homologous recombination deficiency dominant (S-HRD), and (4) MYC driven (S-MD). MYC amplification with HR proficiency tumors is identified with a high oxidative phosphorylation signature resulting in resistance to neoadjuvant chemotherapy. Potential therapeutic targets are identified for each subtype, including platinum-based chemotherapy, immune checkpoint inhibitors, anti-VEGFR, anti-MYC and PARPi-based synthetic lethal strategies. Our comprehensive integrated characterization provides a valuable resource that deepens our understanding of the disease, and may guide future clinical strategies for the precision treatment of OS.

Custom gene expression panel for evaluation of potential molecular markers in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. It is a highly heterogeneous disease with poor prognosis and limited treatment options, which highlights the need for reliable biomarkers. This study aims to explore molecular markers that allow stratification of HCC and may lead to better prognosis and treatment prediction.

MATERIALS AND METHODS

We studied 20 candidate genes (HCC hub genes, potential drug target genes, predominant somatic mutant genes) retrieved from literature and public databases with potential to be used as the molecular markers. We analysed expression of the genes by RT-qPCR in 30 HCC tumour and adjacent non-tumour paired samples from Vietnamese patients. Fold changes in expression were then determined using the 2-∆∆CT method, and unsupervised hierarchical clustering was generated using Cluster v3.0 software.

RESULTS

Clustering of expression data revealed two subtypes of tumours (proliferative and normal-like) and four clusters for genes. The expression profiles of the genes TOP2A, CDK1, BIRC5, GPC3, IGF2, and AFP were strongly correlated. Proliferative tumours were characterized by high expression of the c-MET, ARID1A, CTNNB1, RAF1, LGR5, and GLUL1 genes. TOP2A, CDK1, and BIRC5 HCC hub genes were highly expressed (> twofold) in 90% (27/30), 83% (25/30), and 83% (24/30) in the tissue samples, respectively. Among the drug target genes, high expression was observed in the GPC3, IGF2 and c-MET genes in 77% (23/30), 63% (19/30), and 37% (11/30), respectively. The somatic mutant Wnt/ß-catenin genes (CTNNB1, GLUL and LGR5) and TERT were highly expressed in 40% and 33% of HCCs, respectively. Among the HCC marker genes, a higher percentage of tumours showed GPC3 expression compared to AFP expression [73% (23/30) vs. 43% (13/30)].

CONCLUSION

The custom panel and molecular markers from this study may be useful for diagnosis, prognosis, biomarker-guided clinical trial design, and prediction of treatment outcomes.

Genome-wide CRISPR screen identifies synthetic lethality between DOCK1 inhibition and metformin in liver cancer

Metformin is currently a strong candidate anti-tumor agent in multiple cancers. However, its anti-tumor effectiveness varies among different cancers or subpopulations, potentially due to tumor heterogeneity. It thus remains unclear which hepatocellular carcinoma (HCC) patient subpopulation(s) can benefit from metformin treatment. Here, through a genome-wide CRISPR-Cas9-based knockout screen, we find that DOCK1 levels determine the anti-tumor effects of metformin and that DOCK1 is a synthetic lethal target of metformin in HCC. Mechanistically, metformin promotes DOCK1 phosphorylation, which activates RAC1 to facilitate cell survival, leading to metformin resistance. The DOCK1-selective inhibitor, TBOPP, potentiates anti-tumor activity by metformin in vitro in liver cancer cell lines and patient-derived HCC organoids, and in vivo in xenografted liver cancer cells and immunocompetent mouse liver cancer models. Notably, metformin improves overall survival of HCC patients with low DOCK1 levels but not among patients with high DOCK1 expression. This study shows that metformin effectiveness depends on DOCK1 levels and that combining metformin with DOCK1 inhibition may provide a promising personalized therapeutic strategy for metformin-resistant HCC patients.

Integrative transcriptomic analysis identifies a novel gene signature to predict prognosis of pancreatic cancer in different subtypes

BACKGROUND

Recent advances on pancreatic cancer molecular classifications have identified several subtypes with distinct characteristics, treatment response, and prognosis. We aim to identify the consensus gene signature that could predict the prognosis of pancreatic cancer.

METHODS

Transcriptomic data was acquired from TCGA database. Differentially expressed genes (DEGs) were identified by comparing the Basal-like, Quasi-mesenchymal and Squamous subtype to other subtypes. A new model was constructed by the least absolute shrinkage and selection operator to stratify patients into high and low-risk groups. The prognosis, transcriptomic profiles, and immune infiltration were examined between these groups.

RESULTS

We constructed a signature consisting of nine genes, and the GSEA analysis showed that the genomic profile of high-risk tumors is associated with the basal-like and squamous gene set enrichment. Patients with high-risk tumors had worse overall survival (P < 0.001) and progression free survival (P = 0.033), and are associated with a higher expression of KRAS downstream targets such as SDC1, ITGB4 and SLC2A1, which are involved in KRAS mediated macropinocytosis and tumor invasion. Meanwhile, several recurrence-associated genes increased in the high-risk tumors, including ITGA3 and TP63, which have been shown to mediate enhancer-dependent genomic reprogramming towards the squamous phenotype. The tumor immune infiltration profile analysis showed that high-risk tumors are characterized with an immune suppressive microenvironment.

CONCLUSION

The integrative transcriptomic analysis identifies a consensus gene signature that can discriminate pancreatic cancer subtypes and determine patient prognosis by evaluating the genomic reprogramming and the level of immune infiltration profile in pancreatic cancer.

Clinical value of identifying genes that inhibit hepatocellular carcinomas

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the fourth most frequent cause of cancer-related death in the world. The most common histological type of liver cancer is hepatocellular carcinoma (HCC, 75-80%).

AREAS COVERED

Based on primary literature, this review provides an updated analysis of studies of genetic characterization of HCC at the level of gene mutation profiling, copy number alterations and gene expression, with definition of molecular subgroups and identification of some molecular biomarkers and therapeutic targets.

EXPERT OPINION

A detailed and comprehensive study of the genetic abnormalities characterizing different HCC subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of these tumors may provide a fundamental contribution to improve the survival of a subset of HCC patients. Immunotherapy represents a new fundamental strategy for the treatment of HCC.

Blood-based biomarkers for immune-based therapy in advanced HCC: Promising but a long way to go

The introduction of immune checkpoint inhibitors (ICIs) represents a key shift in the management strategy for patients with hepatocellular carcinoma (HCC). However, there is a paucity of predictive biomarkers that facilitate the identification of patients that would respond to ICI therapy. Although several researchers have attempted to resolve the issue, the data is insufficient to alter daily clinical practice. The use of minimally invasive procedures to obtain patient-derived specimen, such as using blood-based samples, is increasingly preferred. Circulating tumor DNA (ctDNA) can be isolated from the blood of cancer patients, and liquid biopsies can provide sufficient material to enable ongoing monitoring of HCC. This is particularly significant for patients for whom surgery is not indicated, including those with advanced HCC. In this review, we summarize the current state of understanding of blood-based biomarkers for ICI-based therapy in advanced HCC, which is promising despite there is still a long way to go.

Proteo-genomic characterization of virus-associated liver cancers reveals potential subtypes and therapeutic targets

Primary liver cancer is a heterogeneous disease in terms of its etiology, histology, and therapeutic response. Concurrent proteomic and genomic characterization of a large set of clinical liver cancer samples can help elucidate the molecular basis of heterogeneity and thus serve as a valuable resource for personalized liver cancer treatment. In this study, we perform proteomic profiling of ~300 proteins on 259 primary liver cancer tissues with reverse-phase protein arrays, mutational analysis using whole genome sequencing and transcriptional analysis with RNA-Seq. Patients are of Japanese ethnic background and mainly HBV or HCV positive, providing insight into this important liver cancer subtype. Unsupervised classification of tumors based on protein expression profiles reveal three proteomic subclasses R1, R2, and R3. The R1 subclass is immunologically hot and demonstrated a good prognosis. R2 contains advanced proliferative tumor with TP53 mutations, high expression of VEGF receptor 2 and the worst prognosis. R3 is enriched with CTNNB1 mutations and elevated mTOR signaling pathway activity. Twenty-two proteins, including CDK1 and CDKN2A, are identified as potential prognostic markers. The proteomic classification presented in this study can help guide therapeutic decision making for liver cancer treatment.

A Novel mRNA Signature Related to Immunity to Predict Survival and Immunotherapy Response in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the incidence and mortality rates are increasing. Given the limited treatments of HCC and promising application of immunotherapy for cancer, we aimed to identify an immune-related prognostic signature that can predict overall survival (OS) rates and immunotherapy response in HCC.

METHODS

The initial signature development was conducted using a training dataset from the Cancer Genome Atlas followed by independent internal and external validations from that resource and the Gene Expression Omnibus. A signature based nomogram was generated using multivariate Cox regression analysis. The associations of signature score with tumor immune phenotype and response to immunotherapy were analyzed using single-sample gene set enrichment analysis and tumor immune dysfunction and exclusion algorithm. A cohort from Zhongshan Hospital was employed to verify the predictive robustness of the signature regarding prognostic risk and immunotherapy response.

RESULTS

The prognostic signature, IGSHCC, consisting of 22 immune-related genes, had independent prognostic ability, with training and validation cohorts. Also, IGSHCC stratified HCC patients with different outcomes in subgroups. The prognostic accuracy of IGSHCC was better than three reported prognostic signatures. The IGSHCC-based nomogram had high accuracy and significant clinical benefits in predicting 3- and 5-year OS. IGSHCC reflected distinct immunosuppressive phenotypes in low- and high-score groups. Patients with low IGSHCC scores were more likely than those with high scores to benefit from immunotherapy.

CONCLUSIONS

IGSHCC predicted HCC prognosis and response to immunotherapy, and contributed to individualized clinical management.

Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

OBJECTIVE

The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis.

METHODS

GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression.

RESULTS

We identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

Phosphogluconate dehydrogenase is a predictive biomarker for immunotherapy in hepatocellular carcinoma

Background

Phosphogluconate dehydrogenase (PGD) is involved in the regulation of various tumors. However, its role in hepatocellular carcinoma (HCC) is poorly understood. This study tried to determine the prognostic efficacy of PGD and its value for immunotherapy in HCC.

Methods

The data from the TCGA database was used to explore the predictive power of PGD expression and methylation on the overall survival (OS) of HCC through Cox regression and the Kaplan-Meier analysis. Then, we used the GEO and ICGC database to further verify the predictive power. Finally, the relationship between PGD and immune cells and the relationship between PGD and the efficacy of immunotherapy were explored through bioinformatics analysis in HCC.

Results

PGD is highly expressed in HCC tissues, which is negatively regulated by PGD methylation. Low PGD expression and PGD hypermethylation predict better OS in HCC patients. Besides, a meta-analysis based on the TCGA, GSE14520, and ICGC databases further confirms that low PGD expression is closely related to favorable OS. Then, we find significant differences of immune cell infiltrations between high and low PGD expression groups. Expressions of immune checkpoints, most HLA members and tumor mutation burden (TMB) are higher in the high PGD expression group, which indicates beneficial efficacy of immunotherapy in this group. And the potential mechanisms of PGD are exhibited.

Conclusion

PGD is an independent prognostic factor of HCC patients and plays an important role in immune cell infiltration and immunotherapy, which indicates that PGD can be used as a predictive biomarker for HCC immunotherapy.

A photo-oxidation driven proximity labeling strategy enables profiling of mitochondrial proteome dynamics in living cells

Mapping the proteomic landscape of mitochondria with spatiotemporal precision plays a pivotal role in elucidating the delicate biological functions and complex relationship with other organelles in a variety of dynamic physiological processes which necessitates efficient and controllable chemical tools. We herein report a photo-oxidation driven proximity labeling strategy to profile the mitochondrial proteome by light dependence in living cells with high spatiotemporal resolution. Taking advantage of organelle-localizable organic photoactivated probes generating reactive species and nucleophilic substrates for proximal protein oxidation and trapping, mitochondrial proteins were selectively labeled by spatially limited reactions in their native environment. Integration of photo-oxidation driven proximity labeling and quantitative proteomics facilitated the plotting of the mitochondrial proteome in which up to 310 mitochondrial proteins were identified with a specificity of 64% in HeLa cells. Furthermore, mitochondrial proteome dynamics was deciphered in drug resistant Huh7 and LPS stimulated HMC3 cells which were hard-to-transfect. A number of differential proteins were quantified which were intimately linked to critical processes and provided insights into the related molecular mechanisms of drug resistance and neuroinflammation in the perspective of mitochondria. The photo-oxidation driven proximity labeling strategy offers solid technical support to a highly precise proteomic platform in time and finer space for more knowledge of subcellular biology.

Predictive Value of the TP53 p.G245S Mutation Frequency for the Short-Term Recurrence of Hepatocellular Carcinoma as Detected by Pyrophosphate Sequencing

Aims: We explored the relationship between the mutation of the p.G245S site in TP53 and the short-term recurrence of hepatocellular carcinoma (HCC). Materials and Methods: One hundred one HCC patients were included in this study. The TP53 p.G245S mutation frequency spectrum was examined by direct sequencing of genomic DNA from tissue specimens of HCC patients. Univariate and multivariate Cox regression were used to evaluate the independent prognostic factors of tumor recurrence. Receiver operating characteristic (ROC) curve analysis was applied to determine the cutoff value of p.G245S mutation frequency and verify the predictive ability of the Cox model compared with single risk factor indices. Results: Multivariate Cox regression analysis showed that TP53 p.G245S mutation frequency (hazard ratio [HR] = 1.231, 95% CI: 1.006-1.505, p = 0.043), alpha-fetoprotein (AFP) (HR = 2.432, 95% CI: 1.297-4.561, p = 0.006), macrotrabecular-massive (MTM) (HR = 2.656, 95% CI: 0.930-7.583, p = 0.068), and portal vein tumor thrombus (PVTT) (HR = 14.297, 95% CI: 3.085-66.243, p = 0.001) were independent prognostic factors for short-term recurrence. The cutoff value of TP53 p.G245S mutation frequency (18.5%) was determined by ROC analysis. The prediction model integrating TP53 p.G245S mutation frequency, PVTT, MTM, and AFP could be a predictive indicator of short-term recurrence in HCC patients (AUC = 0.849, 95% CI: 0.748-0.950, p = 0.000001). Survival analysis indicated that the probability of short-term recurrence-free survival was significantly different among different TP53 p.G245S mutation frequency, MTM, PVTT, and AFP risk groups (p < 0.05). Conclusion: The mutation frequency of the p.G245S site was a novel prognostic risk factor for the short-term recurrence of HCC.

A Comprehensive Pan-Cancer Analysis of the Tumorigenic Effect of Leucine-Zipper-Like Transcription Regulator (LZTR1) in Human Cancer

The elucidation of the action site, mechanism of Leucine-Zipper-like Transcription Regulator-1 (LZTR1) and its relationship with RAS-MAPK signaling pathway attracts more and more scholars to focus on the researches of LZTR1 and its role in tumorigenesis. However, there was no pan-cancer analysis between LZTR1 and human tumors reported before. Therefore, we are the first to investigate the potential oncogenic roles of LZTR1 across all tumor types based on the datasets of TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus). LZTR1 plays a double-edged role in tumor development and prognosis. We found that the high expression of LZTR1 brings better outcomes in esophageal carcinoma (ESCA) and head and neck squamous cell carcinoma (HNSC) but brings worth outcomes in uveal melanoma (UVM), adrenocortical carcinoma (ACC), liver hepatocellular carcinoma (LIHC), and prostate adenocarcinoma (PRAD). Moreover, the expression of LZTR1 also strongly associated with pathological in ACC and bladder urothelial carcinoma (BLCA). We also found that the LZTR1 expression was associated with some immune cell infiltration including endothelial cells, regulatory T cells (Tregs), T cell CD8+, natural killer cells (NK cell), macrophages, neutrophil granulocyte, and cancer-associated fibroblasts in different cancers. Missense mutation in LZTR1 was detected in most cancers from TCGA datasets. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Body (GO) method was used to explain the pathogenesis of LZTR1. Our pan-cancer study provides a relatively comprehensive understanding of the carcinogenic role of LZTR1 in human tumors.

Delineation of a SMARCA4-specific competing endogenous RNA network and its function in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy worldwide, and the mortality rate continues to rise each year. SMARCA4 expression has been associated with poor prognosis in various types of cancer; however, the specific mechanism of action of SMARCA4 in HCC needs to be fully elucidated.

AIM

To explore the specific mechanism of action of SMARCA4 in HCC.

METHODS

Herein, the expression level of SMARCA4 as well as its association with HCC prognosis were evaluated using transcriptome profiling and clinical data of 18 different types of cancer collected from The Cancer Genome Atlas database. Furthermore, SMARCA4-high and -low groups were identified. Thereafter, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the function of SMARCA4, followed by construction of a SMARCA4-specific competing endogenous RNA (ceRNA) network using starBase database. The role of SMARCA4 in immunotherapy and its association with immune cells were assessed using correlation analysis.

RESULTS

It was observed that SMARCA4 was overexpressed and negatively correlated with prognosis in HCC. Further, SMARCA4 expression was positively associated with tumor mutational burden, microsatellite stability, and immunotherapy efficacy. The SNHG3/THUMP3-AS1-miR-139-5p-SMARCA4 ceRNA network was established and could be assumed to serve as a stimulatory mechanism in HCC.

CONCLUSION

The findings of this study demonstrated that SMARCA4 plays a significant role in progression and immune infiltration in HCC. Moreover, a ceRNA network was detected, which was found to be correlated with poor prognosis in HCC. The findings of this study could contribute towards the identification of predictive markers for immunotherapy and a novel mechanism of action for HCC treatment.

Hepatocellular Carcinoma in Mongolia Delineates Unique Molecular Traits and a Mutational Signature Associated with Environmental Agents

PURPOSE

Mongolia has the world's highest incidence of hepatocellular carcinoma (HCC), with ∼100 cases/100,000 inhabitants, although the reasons for this have not been thoroughly delineated.

EXPERIMENTAL DESIGN

We performed a molecular characterization of Mongolian (n = 192) compared with Western (n = 187) HCCs by RNA sequencing and whole-exome sequencing to unveil distinct genomic and transcriptomic features associated with environmental factors in this population.

RESULTS

Mongolian patients were younger, with higher female prevalence, and with predominantly HBV-HDV coinfection etiology. Mongolian HCCs presented significantly higher rates of protein-coding mutations (121 vs. 70 mutations per tumor in Western), and in specific driver HCC genes (i.e., APOB and TSC2). Four mutational signatures characterized Mongolian samples, one of which was novel (SBS Mongolia) and present in 25% of Mongolian HCC cases. This signature showed a distinct substitution profile with a high proportion of T>G substitutions and was significantly associated with a signature of exposure to the environmental agent dimethyl sulfate (71%), a 2A carcinogenic associated with coal combustion. Transcriptomic-based analysis delineated three molecular clusters, two not present in Western HCC; one with a highly inflamed profile and the other significantly associated with younger female patients.

CONCLUSIONS

Mongolian HCC has unique molecular traits with a high mutational burden and a novel mutational signature associated with genotoxic environmental factors present in this country.

Methods for the detection of tumor-specific single nucleotide somatic mutations in plasma cDNA samples

Introduction. Liquid biopsy is considered as a minimally invasive method of molecular genetic analysis that can be used for early diagnosis, prognosis of disease development, monitoring of residual disease or treatment outcomes, and selection of optimal drug therapy schemes for a patient. Along with the development of tests based on the study of panels of oncologically significant genes or their regions, for various forms of genetically heterogeneous tumors a promising approach could be the use as an object of liquid biopsy of an individual spectrum of somatic mutations of a particular patient that can be detected on the basis of high-throughput sequencing of tumor tissue.

Aim. To determine the applicability of different methods for detecting single-nucleotide somatic mutations detected in tumor tissue of a particular patient in cDNA preparations from blood plasma obtained before surgical removal of the tumor and to evaluate the possibility of quantifying the proportion of the alternative variant in the total pool of cDNA. Materials and methods. We used normal and tumor tissue, as well as blood plasma samples from patients with hepatocellular carcinoma, and various methods for detecting single-nucleotide somatic mutations: real-time polymerase chain reaction (PCR) with intercalating dye or with TaqMan probes, droplet digital PCR and high-throughput sequencing of target amplicons.

Results. Using the example of a somatic mutation in the TLN1 gene detected in tumor tissue of a patient with hepatocellular carcinoma, methods were developed and tested, each of which allows specific detection of the mutant variant in small amounts (2 ng) of cDNA from the blood plasma of the same patient. The use of droplet PCR and target amplicon sequencing methods allowed us to quantify the proportion of the mutant variant in the total cDNA pool, which was 19.7 and 23.5 %, respectively.

Conclusion. Among the methods investigated, droplet digital PCR and targeted amplicon sequencing allow not only reliable detection of mutant variants in small amounts of cDNA, but also adequate quantification, which is particularly important for the development of ways to monitor tumor growth during treatment. The close values of the proportion of mutant variants in cDNA detected by these methods indicate the accuracy of quantitative analysis and the possibility of their use for cross-validation of the results obtained.

Molecular subtypes based on Wnt-signaling gene expression predict prognosis and tumor microenvironment in hepatocellular carcinoma

Based on increasing research evidence, hepatocellular carcinoma (HCC) is heterogeneous, and genetic profiling has led to the identification of multiple subtypes of this disease. To advance our knowledge and the ability to use individualized medicine in the treatment of HCC, it is essential to perform a complete and methodical characterization of various molecular subtypes. The canonical Wnt/β-catenin pathway is an evolutionarily conserved complicated signaling mechanism that plays a role in carcinogenesis and progression of HCC. In this study, we acquired RNA sequencing, somatic mutation, and clinical data from 701 patients from The Cancer Genome Atlas and Gene Expression Omnibus databases and stratified patients into two subgroups: WNT-high and WNT-low. In general, the WNT-high subtype is associated with an immunosuppressive microenvironment, poor prognosis, cancer-related pathways, and a low response to immune checkpoint therapy. We also found that WNT3 is negatively linked to CD8⁺ T-cell infiltration using multiple immunofluorescence assays. Finally, we developed a WNT-related prognostic model to predict the survival time of patients with HCC. In summary, we developed a new classification scheme for HCC based on Wnt signaling signatures. This classification produced substantial clinical effects, both in terms of assessing patient prognosis and immunotherapy administered to patients with HCC.

Applications of molecular barcode sequencing for the detection of low-frequency variants in circulating tumour DNA from hepatocellular carcinoma

PURPOSE

Liquid biopsy has emerged as a promising tool for minimally invasive and accurate detection of various malignancies. We aimed to apply molecular barcode sequencing to circulating tumour DNA (ctDNA) from liquid biopsies of hepatocellular carcinoma (HCC).

STUDY DESIGN

Patients with HCC or benign liver disease were enrolled between 2017 and 2018. Matched tissue and serum samples were obtained from these patients. Plasma cell-free DNA was extracted and subjected to targeted sequencing with ultra-high coverage and molecular barcoding.

RESULTS

The study included 143 patients: 102 with HCC, 7 with benign liver tumours and 34 with chronic liver disease. No tier 1/2 or oncogenic mutations were detected in patients with benign liver disease. Among the HCC patients, 49 (48%) had tier 1/2 mutations in at least one gene; detection rates were higher in advanced stages (75%) than in early stages (26%-33%). TERT was the most frequently mutated gene (30%), followed by TP53 (16%), CTNNB1 (14%), ARID2 (5%), ARID1A (4%), NFE2L2 (4%), AXIN1 (3%) and KRAS (1%). Survival among patients with TP53 mutations was significantly worse (p = 0.007) than among patients without these mutations, whereas CTNNB1 and TERT mutations did not affect survival. ctDNA testing combined with α-fetoprotein and prothrombin induced by vitamin K absence-II analyses improved HCC detection, even in early stages.

CONCLUSIONS

ctDNA detection using molecular barcoding technology offers dynamic and personalized information concerning tumour biology, such information can guide clinical diagnosis and management. This detection also has the potential as a minimally invasive approach for prognostic stratification and post-therapeutic monitoring.

Clinical implications and biological features of a novel postoperative recurrent HCC classification: A multi-centre study

BACKGROUND & AIMS

The multiplicity of hepatocellular carcinoma (HCC) recurrence patterns is the most important determinant of patients' postsurgical survival. A systematic HCC recurrence classification is needed to help prevent and treat postoperative HCC recurrence in the era of precision medicine.

METHODS

A total of 1319 patients with recurrent HCC from four hospitals were enrolled and divided into a development cohort (n = 916), internal validation cohort (n = 225) and external validation cohort (n = 178). A comprehensive study of patients' clinicopathological factors and biological features was conducted.

RESULTS

Four subtypes of recurrence were identified, which integrated recurrence features, survival, effects on systemic and liver function and potential therapeutics after recurrence: type I (solitary-intrahepatic oligorecurrence); type II (multi-intrahepatic oligorecurrence); type III (progression recurrence) and type IV (hyper-progression recurrence). Type III~IV recurrence indicated exceptionally poor prognosis. Subsequently, two nomogram models were established for type III~IV recurrence prediction, and both demonstrated excellent predictive performance and applicability of pre and postoperative strategy formulation. Multiple biological analyses revealed that HCC cases with type III~IV recurrence were characterized by enrichment in p53 mutations, CCND1 amplification, high proliferation/metastasis potential, inactive metabolism and immune exhaustion features. Over-expression of high mobility group protein 2 (HMGA2) enhanced the highly malignant behaviour of HCC through multiple molecular pathways, making it a potential prognostic predictor and therapeutic target.

CONCLUSIONS

This 'recurrent HCC classification' has important potential value in identifying patients with surgical benefit, predicting postsurgical survival and guiding treatment strategies. Multidimensional biological insights also increased knowledge of factors associated with HCC recurrence.

Hepatocellular carcinoma downstaging for liver transplantation in the era of systemic combined therapy with anti-VEGF/TKI and immunotherapy

Hepatocellular carcinoma remains a global health challenge affecting close to 1 million cases yearly. Liver transplantation provides the best long-term outcomes for those meeting strict criteria. Efforts have been made to expand these criteria, whereas others have attempted downstaging approaches. Although locoregional approaches to downstaging are appealing and have demonstrated efficacy, limitations and challenges exists including poor imaging modality to assess response and appropriate endpoints along the process. Recent advances in systemic treatments including immune checkpoint inhibitors alone or in combination with tyrosine kinase inhibitors have prompted the discussion regarding their role for downstaging disease prior to transplantation. Here, we provide a review of prior locoregional approaches for downstaging, new systemic agents and their role for downstaging, and finally, key and critical considerations of the assessment, endpoints, and optimal designs in clinical trials to address this key question.

Bi-allelic hydroxymethylbilane synthase inactivation defines a homogenous clinico-molecular subtype of hepatocellular carcinoma

BACKGROUND & AIMS

Acute intermittent porphyria (AIP), caused by heterozygous germline mutations of the heme synthesis pathway enzyme HMBS (hydroxymethylbilane synthase), confers a high risk of hepatocellular carcinoma (HCC) development. Yet, the role of HMBS in liver tumorigenesis remains unclear.

METHODS

Herein, we explore HMBS alterations in a large series of 758 HCC cases, including 4 patients with AIP. We quantify the impact of HMBS mutations on heme biosynthesis pathway intermediates and we investigate the molecular and clinical features of HMBS-mutated tumors.

RESULTS

We identify recurrent bi-allelic HMBS inactivation, both in patients with AIP acquiring a second somatic HMBS mutation and in sporadic HCC with 2 somatic hits. HMBS alterations are enriched in truncating mutations, in particular in splice regions, leading to abnormal transcript structures. Bi-allelic HMBS inactivation results in a massive accumulation of its toxic substrate porphobilinogen and synergizes with CTNNB1-activating mutations, leading to the development of well-differentiated tumors with a transcriptomic signature of Wnt/β-catenin pathway activation and a DNA methylation signature related to ageing. HMBS-inactivated HCC mostly affects females, in the absence of fibrosis and classical HCC risk factors.

CONCLUSIONS

These data identify HMBS as a tumor suppressor gene whose bi-allelic inactivation defines a homogenous clinical and molecular HCC subtype.

LAY SUMMARY

Heme (the precursor to hemoglobin, which plays a key role in oxygen transport around the body) synthesis occurs in the liver and involves several enzymes including hydroxymethylbilane synthase (HMBS). HMBS mutations cause acute intermittent porphyria, a disease caused by the accumulation of toxic porphyrin precursors. Herein, we show that HMBS inactivation is also involved in the development of liver cancers with distinct clinical and molecular characteristics.

A novel four-gene signature for predicting the prognosis of hepatocellular carcinoma

OBJECTIVE

To identify and utilize gene signatures for the prognostic evaluation of postoperative patients with hepatocellular carcinoma (HCC).

METHODS

The gene mRNA expression profiles and corresponding clinicopathological data of postoperative patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Highly differentially expressed genes (DEGs) in tumor tissues compared to adjacent tissues were identified, and their associations with the overall survival (OS) of HCC patients were analyzed. The strongly associated genes were used to develop a prognostic score for the survival stratification of HCC, and the underlying mechanisms were analyzed using bioinformatics.

RESULTS

A total of 376 DEGs were identified and four DEGs (ADH4, COL15A1, RET and KCNJ16) were independently associated with OS. A prognostic score derived from the four genes could effectively stratify HCC patients with different OS outcomes, independent of clinical parameters. Patients with high scores exhibited poorer OS than patients with low scores (HR 5.526, 95% CI: 2.451-12.461, p < .001). The four genes were involved in cancer-related biological processes and were independent of each other in bioinformatics analyses.

CONCLUSION

Four genes strongly associated with the prognosis of postoperative patients with HCC were identified, and the derived prognostic score was simple and valuable for overall survival prediction.

Aristolochic acid-associated cancers: a public health risk in need of global action

Aristolochic acids (AAs) are a group of naturally occurring compounds present in many plant species of the Aristolochiaceae family. Exposure to AA is a significant risk factor for severe nephropathy, and urological and hepatobiliary cancers (among others) that are often recurrent and characterized by the prominent mutational fingerprint of AA. However, herbal medicinal products that contain AA continue to be manufactured and marketed worldwide with inadequate regulation, and possible environmental exposure routes receive little attention. As the trade of food and dietary supplements becomes increasingly globalized, we propose that further inaction on curtailing AA exposure will have far-reaching negative effects on the disease trends of AA-associated cancers. Our Review aims to systematically present the historical and current evidence for the mutagenicity and carcinogenicity of AA, and the effect of removing sources of AA exposure on cancer incidence trends. We discuss the persisting challenges of assessing the scale of AA-related carcinogenicity, and the obstacles that must be overcome in curbing AA exposure and preventing associated cancers. Overall, this Review aims to strengthen the case for the implementation of prevention measures against AA's multifaceted, detrimental and potentially fully preventable effects on human cancer development.

Hepatoblastomas with carcinoma features represent a biological spectrum of aggressive neoplasms in children and young adults

BACKGROUND & AIMS

Hepatoblastoma (HB) and hepatocellular carcinoma (HCC) are the predominant liver cancers in children, though their respective treatment options and associated outcomes differ dramatically. Risk stratification using a combination of clinical, histological, and molecular parameters can improve treatment selection, but it is particularly challenging for tumors with mixed histological features, including those in the recently created hepatocellular neoplasm not otherwise specified (HCN NOS) provisional category. We aimed to perform the first molecular characterization of clinically annotated cases of HCN NOS.

METHODS

We tested whether these histological features are associated with genetic alterations, cancer gene dysregulation, and outcomes. Namely, we compared the molecular features of HCN NOS, including copy number alterations, mutations, and gene expression profiles, with those in other pediatric hepatocellular neoplasms, including HBs and HCCs, as well as HBs demonstrating focal atypia or pleomorphism (HB FPAs), and HBs diagnosed in older children (>8).

RESULTS

Molecular profiles of HCN NOS and HB FPAs revealed common underlying biological features that were previously observed in HCCs. Consequently, we designated these tumor types collectively as HBs with HCC features (HBCs). These tumors were associated with high mutation rates (∼3 somatic mutations/Mb) and were enriched with mutations and alterations in key cancer genes and pathways. In addition, recurrent large-scale chromosomal gains, including gains of chromosomal arms 2q (80%), 6p (70%), and 20p (70%), were observed. Overall, HBCs were associated with poor clinical outcomes.

CONCLUSIONS

Our study indicates that histological features seen in HBCs are associated with combined molecular features of HB and HCC, that HBCs are associated with poor outcomes irrespective of patient age, and that transplanted patients are more likely to have good outcomes than those treated with chemotherapy and surgery alone. These findings highlight the importance of molecular testing and early therapeutic intervention for aggressive childhood hepatocellular neoplasms.

LAY SUMMARY

We molecularly characterized a class of histologically aggressive childhood liver cancers and showed that these tumors are clinically aggressive and that their observed histological features are associated with underlying recurrent molecular features. We proposed a diagnostic algorithm to identify these cancers using a combination of histological and molecular features, and our analysis suggested that these cancers may benefit from specialized treatment strategies that may differ from treatment guidelines for other childhood liver cancers.

Genome interpretation using in silico predictors of variant impact

Estimating the effects of variants found in disease driver genes opens the door to personalized therapeutic opportunities. Clinical associations and laboratory experiments can only characterize a tiny fraction of all the available variants, leaving the majority as variants of unknown significance (VUS). In silico methods bridge this gap by providing instant estimates on a large scale, most often based on the numerous genetic differences between species. Despite concerns that these methods may lack reliability in individual subjects, their numerous practical applications over cohorts suggest they are already helpful and have a role to play in genome interpretation when used at the proper scale and context. In this review, we aim to gain insights into the training and validation of these variant effect predicting methods and illustrate representative types of experimental and clinical applications. Objective performance assessments using various datasets that are not yet published indicate the strengths and limitations of each method. These show that cautious use of in silico variant impact predictors is essential for addressing genome interpretation challenges.

Therapeutic efficacy of FASN inhibition in preclinical models of HCC

BACKGROUND AND AIMS

Aberrant activation of fatty acid synthase (FASN) is a major metabolic event during the development of HCC. We evaluated the therapeutic efficacy of TVB3664, a FASN inhibitor, either alone or in combination, for HCC treatment.

APPROACH AND RESULTS

The therapeutic efficacy and the molecular pathways targeted by TVB3664, either alone or with tyrosine kinase inhibitors or the checkpoint inhibitor anti-programmed death ligand 1 antibody, were assessed in human HCC cell lines and multiple oncogene-driven HCC mouse models. RNA sequencing was performed to elucidate the effects of TVB3664 on global gene expression and tumor metabolism. TVB3664 significantly ameliorated the fatty liver phenotype in the aged mice and AKT-induced hepatic steatosis. TVB3664 monotherapy showed moderate efficacy in NASH-related murine HCCs, induced by loss of phosphatase and tensin homolog and MET proto-oncogene, receptor tyrosine kinase (c-MET) overexpression. TVB3664, in combination with cabozantinib, triggered tumor regression in this murine model but did not improve the responsiveness to immunotherapy. Global gene expression revealed that TVB3664 predominantly modulated metabolic processes, whereas TVB3664 synergized with cabozantinib to down-regulate multiple cancer-related pathways, especially the AKT/mammalian target of rapamycin pathway and cell proliferation genes. TVB3664 also improved the therapeutic efficacy of sorafenib and cabozantinib in the FASN-dependent c-MYC-driven HCC model. However, TVB3664 had no efficacy nor synergistic effects in FASN-independent murine HCC models.

CONCLUSIONS

This preclinical study suggests the limited efficacy of targeting FASN as monotherapy for HCC treatment. However, FASN inhibitors could be combined with other drugs for improved effectiveness. These combination therapies could be developed based on the driver oncogenes, supporting precision medicine approaches for HCC treatment.

Gene coexpression network analysis identifies hubs in hepatitis B virus-associated hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is among the leading causes of cancer-related death worldwide. The molecular pathogenesis of HCC involves multiple signaling pathways. This study utilizes systems and bioinformatic approaches to investigate the pathogenesis of HCC.

METHODS

Gene expression microarray data were obtained from 50 patients with chronic hepatitis B and HCC. There were 1649 differentially expressed genes inferred from tumorous and nontumorous datasets. Weighted gene coexpression network analysis (WGCNA) was performed to construct clustered coexpressed gene modules. Statistical analysis was used to study the correlation between gene coexpression networks and demographic features of patients. Functional annotation and pathway inference were explored for each coexpression network. Network analysis identified hub genes of the prognostic gene coexpression network. The hub genes were further validated with a public database.

RESULT

Five distinct gene coexpression networks were identified by WGCNA. A distinct coexpressed gene network was significantly correlated with HCC prognosis. Pathway analysis of this network revealed extensive integration with cell cycle regulation. Ten hub genes of this gene network were inferred from protein-protein interaction network analysis and further validated in an external validation dataset. Survival analysis showed that lower expression of the 10-gene signature had better overall survival and recurrence-free survival.

CONCLUSION

This study identified a crucial gene coexpression network associated with the prognosis of hepatitis B virus-related HCC. The identified hub genes may provide insights for HCC pathogenesis and may be potential prognostic markers or therapeutic targets.

Personalized quantitative models of NAD metabolism in hepatocellular carcinoma identify a subgroup with poor prognosis

Cancer cells are known to undergo metabolic adaptation to cater to their enhanced energy demand. Nicotinamide adenine dinucleotide (NAD) is an essential metabolite regulating many cellular processes within the cell. The enzymes required for NAD synthesis, starting from the base precursor - tryptophan, are expressed in the liver and the kidney, while all other tissues convert NAD from intermediate precursors. The liver, being an active metabolic organ, is a primary contributor to NAD biosynthesis. Inhibition of key enzymes in the NAD biosynthetic pathways is proposed as a strategy for designing anti-cancer drugs. On the other hand, NAD supplementation has also been reported to be beneficial in cancer in some cases. As metabolic adaptation that occurs in cancer cells can lead to perturbations to the pathways, it is important to understand the exact nature of the perturbation in each individual patient. To investigate this, we use a mathematical modelling approach integrated with transcriptomes of patient samples from the TCGA-LIHC cohort. Quantitative profiling of the NAD biosynthesis pathway helps us understand the NAD biosynthetic status and changes in the controlling steps of the pathway. Our results indicate that NAD biosynthesis is heterogeneous among liver cancer patients, and that Nicotinate phosphoribosyl transferase (NAPRT) levels are indicative of the NAD biosynthetic status. Further, we find that reduced NAPRT levels combined with reduced Nicotinamide phosphoribosyl transferase (NAMPT) levels contribute to poor prognosis. Identification of the precise subgroup who may benefit from NAD supplementation in subgroup with low levels of NAPRT and NAMPT could be explored to improve patient outcome.

Current and Emerging Molecular Markers of Liver Diseases: A Pathogenic Perspective

In the past decade, with the rapid development of molecular medicine and the application of more sophisticated methods for disease diagnosis and treatment, a number of molecular markers have become available for liver diseases. Pathogenesis-related markers are likely to be effectively discovered and rigorously validated, due to the unique biological links to diseases. The present study reviews the predominant clinical and research articles in the previous decade to provide a pathogenic perspective of current and emerging biomarkers for liver diseases, including hepatocellular neoplasms (e.g. hepatocellular carcinoma), non-neoplastic hepatocellular diseases, intrahepatic biliary diseases, and other liver diseases. Although it remains challenging to cover all markers for the diagnosis and prognosis of liver diseases, current and emerging molecular markers in clinical practice and under investigation are reviewed in a wide spectrum of liver diseases, in order to help clinicians and researchers identify liver disease markers for reference.

Mutational and transcriptional alterations and clinicopathological factors predict the prognosis of stage I hepatocellular carcinoma

Background

The prognosis of hepatocellular carcinoma (HCC) has been extensively studied. However, the impact on prognosis of stage I HCC has not been well studied at clincopathological, mutational and transcriptional levels.

Methods

Here we first characterized the influencing factors of prognosis of stage I HCC patients by downloading and analyzing the whole-exome somatic mutation data, messenger ribonucleic acid (mRNA) transcription data, along with demographic and clinical information of 163 stage I HCC patients from the TCGA database. The relationship between the influencing factors and HCC prognosis was studied in detail, and a prediction Nomogram model was established. Figures and tables were plotted using the R software.

Results

TP53, CTNNB1, TTN, MUC16 and ALB were the top mutated genes in stage I HCC. A series of co-mutations and mutually exclusive mutations were identified. Twenty-nine genes with significant stratification on prognosis were identified, including highly mutated LRP1B, ARID1A and PTPRQ. Patients with wild type (WT) genes unanimously exhibited significantly better overall survival rate than those with mutants. Patients with the top 10% tumor mutational burden (TMB) exhibited significantly worse prognosis than the rest 90%. Further characterization of transcriptional profile revealed that membrane functions, cell skeleton proteins, ion channels, receptor function and cell cycle were comprehensively altered in stage I HCC. Univariate and multivariate analyses were performed at clinicopathological, mutational and transcriptional levels. The combined analysis revealed sex, race, TMB, neoplasm histologic grade, Child–Pugh grade, MMRN1, OXT and COX6A2 transcription as independent risk factors. These factors were used to establish a Nomogram model to predict the prognosis of individual HCC patients.

Conclusions

The influencing factors of prognosis of stage I HCC have been characterized for the first time at clinicopathological, mutational and transcriptional levels. A Nomogram model has been established to predict the prognosis. Further validation is needed to confirm the effectiveness and reliability of the model.

Bioinformatic identification of differentially expressed genes associated with hepatocellular carcinoma prognosis

Hepatocellular carcinoma (HCC) is still a significant global health problem. The development of bioinformatics may provide the opportunities to identify novel therapeutic targets. This study bioinformatically identified the differentially expressed genes (DEGs) in HCC and associated them with HCC prognosis using data from published databases. The DEGs downloaded from the Gene Expression Omnibus (GEO) website were visualized using the Venn diagram software, and then subjected to the GO and KEGG analyses, while the protein-protein interaction network was analyzed using Cytoscape software with the Search Tool for the search tool for the retrieval of interacting genes and the molecular complex detection plug-in. Kaplan-Meier curves and the log rank test were used to associate the core PPI network genes with the prognosis. There were 57 upregulated and 143 downregulated genes in HCC samples. The GO and pathway analyses revealed that these DEGs are involved in the biological processes (BPs), molecular functions (MFs), and cell components (CCs). The PPI network covered 50 upregulated and 108 downregulated genes, and the core modules of this PPI network contained 34 upregulated genes. A total of 28 of these upregulated genes were associated with a poor HCC prognosis, 27 of which were highly expressed in HCC tissues. This study identified 28 DEGs to be associated with a poor HCC prognosis. Future studies will investigate their possible applications as prognostic biomarkers and potential therapeutic targets for HCC.

Molecular Classification of Hepatocellular Carcinoma Using Wnt-Hippo Signaling Pathway-Related Genes

Simple Summary

The characters of Taiwanese hepatocellular carcinoma (HCC) are different from other parts of the world. We characterized the molecular features of HCC using a newly developed classification system based on the expression of the Wnt–Hippo signaling pathway-related genes. We analyzed the data in terms of prognostic value, transcriptome features, immune infiltration, and clinical characteristics, and compared the resulting subclasses with previously published classifications. A new molecular classification method based on a 272 gene panel of Wnt–Hippo pathways that may provide a new target for the treatment.

Abstract

In Taiwan, a combination of hepatitis B and C infection, economic boom-related food and alcohol overconsumption, and Chinese medicine prescriptions has led to a high rate of hepatocellular carcinoma (HCC). However, the causative factors and underlying tumor biology for this unique HCC environment have not been identified. Wnt and Hippo signaling pathways play an important regulatory role in HCC development, and their functions are generally considered as positive and negative regulators of cell proliferation, respectively. In this study, we characterized the molecular features of HCC using a newly developed classification system based on the expression of the Wnt–Hippo signaling pathway-related genes. RNA sequencing (RNA-Seq) was performed on liver tumor tissues from 100 patients with liver cancer. RNA-Seq data for 272 previously characterized Wnt–Hippo signaling pathway-related genes were used for hierarchical clustering. We analyzed the data in terms of prognostic value, transcriptome features, immune infiltration, and clinical characteristics, and compared the resulting subclasses with previously published classifications. Four subclasses of HCC (HCCW1–4) were identified. Subclass HCCW1 displayed the highest PCDHB4 expression. Subclass HCCW2 displayed lower Edmondson–Steiner grades (I and II) and CTNNB1 mutation frequencies. Subclass HCCW3 was associated with a good prognosis, the highest PCDHGB7 expression, high CD8+ naïve T cells abundance, and relatively low TP53 mutation rates. Subclass HCCW4 was associated with a poor prognosis, the highest PCDHB2 and PCDHB6 expression, a relatively high abundance of Th1 cells, NKT and class-switched memory B cells, relatively low enrichment of cDC, iDC, and CD4+ memory T cells, and high Edmondson–Steiner grades (III and IV). We also identified Wnt–Hippo signaling pathway-related genes that may influence immune cell infiltration. We developed a panel of 272 Wnt–Hippo signaling pathway-related genes to classify HCC into four groups based on Taiwanese HCC and The Cancer Genome Atlas Liver Hepatocellular Carcinoma datasets. This novel molecular classification system may aid the treatment of HCC.

Circular RNA hsa_circ_0062682 Binds to YBX1 and Promotes Oncogenesis in Hepatocellular Carcinoma

Circular RNAs (circRNAs) have been shown to play an important role in the pathogenesis of hepatocellular carcinoma (HCC). By implementing available transcriptomic analyses of HCC patients, we identified an upregulated circRNA hsa_circ_0062682. Stable perturbations of hsa_circ_0062682 in Huh-7 and SNU-449 cell lines influenced colony formation, migration, cell proliferation, sorafenib sensitivity, and additionally induced morphological changes in cell lines, indicating an important role of hsa_circ_0062682 in oncogenesis. Pathway enrichment analysis and gene set enrichment analysis of the transcriptome data from hsa_circ_0062682 knockdown explained the observed phenotypes and exposed transcription factors E2F1, Sp1, HIF-1α, and NFκB1 as potential downstream targets. Biotinylated oligonucleotide pulldown combined with proteomic analyses identified protein interaction partners of which YBX1, a known oncogene, was confirmed by RNA immunoprecipitation. Furthermore, we discovered a complex cell-type-specific phenotype in response to the oncogenic potential of hsa_circ_0062682. This finding is in line with different classes of HCC tumours, and more studies are needed to shed a light on the molecular complexity of liver cancer.

MiR-22 Deficiency Fosters Hepatocellular Carcinoma Development in Fatty Liver

MiR-22 is mostly considered as a hepatic tumor-suppressor microRNA based on in vitro analyses. Yet, whether miR-22 exerts a tumor-suppressive function in the liver has not been investigated in vivo. Herein, in silico analyses of miR-22 expression were performed in hepatocellular carcinomas from human patient cohorts and different mouse models. Diethylnitrosamine-induced hepatocellular carcinomas were then investigated in lean and diet-induced obese miR-22-deficient mice. The proteome of liver tissues from miR-22-deficient mice prior to hepatocellular carcinoma development was further analyzed to uncover miR-22 regulated factors that impact hepatocarcinogenesis with miR-22 deficiency. MiR-22 downregulation was consistently observed in hepatocellular carcinomas from all human cohorts and mouse models investigated. The time of appearance of the first tumors was decreased and the number of tumoral foci induced by diethylnitrosamine was significantly increased by miR-22-deficiency in vivo, two features which were further drastically exacerbated with diet-induced obesity. At the molecular level, we provide evidence that the loss of miR-22 significantly affects the energetic metabolism and mitochondrial functions of hepatocytes, and the expression of tumor-promoting factors such as thrombospondin-1. Our study demonstrates that miR-22 acts as a hepatic tumor suppressor in vivo by restraining pro-carcinogenic metabolic deregulations through pleiotropic mechanisms and the overexpression of relevant oncogenes.

Long noncoding RNA LINC01132 enhances immunosuppression and therapy resistance via NRF1/DPP4 axis in hepatocellular carcinoma

Background

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in various types of cancer. Current developments in transcriptome analyses unveiled the existence of lncRNAs; however, their functional characterization remains a challenge.

Methods

A bioinformatics screen was performed by integration of multiple omics data in hepatocellular carcinoma (HCC) prioritizing a novel oncogenic lncRNA, LINC01132. Expression of LINC01132 in HCC and control tissues was validated by qRT-PCR. Cell viability and migration activity was examined by MTT and transwell assays. Finally, our results were confirmed in vivo mouse model and ex vivo patient derived tumor xenograft experiments to determine the mechanism of action and explore LINC01132-targeted immunotherapy.

Results

Systematic investigation of lncRNAs genome-wide expression patterns revealed LINC01132 as an oncogene in HCC. LINC01132 is significantly overexpressed in tumor and associated with poor overall survival of HCC patients, which is mainly driven by copy number amplification. Functionally, LINC01132 overexpression promoted cell growth, proliferation, invasion and metastasis in vitro and in vivo. Mechanistically, LINC01132 acts as an oncogenic driver by physically interacting with NRF and enhancing the expression of DPP4. Notably, LINC01132 silencing triggers CD8+ T cells infiltration, and LINC01132 knockdown combined with anti-PDL1 treatment improves antitumor immunity, which may prove a new combination therapy in HCC.

Conclusions

LINC01132 functions as an oncogenic driver that induces HCC development via the NRF1/DPP4 axis. Silencing LINC01132 may enhance the efficacy of anti-PDL1 immunotherapy in HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02478-z.

GraphBio: A shiny web app to easily perform popular visualization analysis for omics data

Background: Massive amounts of omics data are produced and usually require sophisticated visualization analysis. These analyses often require programming skills, which are difficult for experimental biologists. Thus, more user-friendly tools are urgently needed. Methods and Results: Herein, we present GraphBio, a shiny web app to easily perform visualization analysis for omics data. GraphBio provides 15 popular visualization analysis methods, including heatmap, volcano plots, MA plots, network plots, dot plots, chord plots, pie plots, four quadrant diagrams, Venn diagrams, cumulative distribution curves, principal component analysis (PCA), survival analysis, receiver operating characteristic (ROC) analysis, correlation analysis, and text cluster analysis. It enables experimental biologists without programming skills to easily perform popular visualization analysis and get publication-ready figures. Conclusion: GraphBio, as an online web application, is freely available at http://www.graphbio1.com/en/ (English version) and http://www.graphbio1.com/ (Chinese version). The source code of GraphBio is available at https://github.com/databio2022/GraphBio.

Multi-omics data integration for hepatocellular carcinoma subtyping with multi-kernel learning

Hepatocellular carcinoma (HCC) is a leading malignant liver tumor with high mortality and morbidity. Patients at the same stage can be defined as different molecular subtypes associated with specific genomic disorders and clinical features. Thus, identifying subtypes is essential to realize efficient treatment and improve survival outcomes of HCC patients. Here, we applied a regularized multiple kernel learning with locality preserving projections method to integrate mRNA, miRNA and DNA methylation data of HCC patients to identify subtypes. We identified two HCC subtypes significantly correlated with the overall survival. The patient 3-years mortality rates in the high-risk and low-risk group was 51.0% and 23.5%, respectively. The high-risk group HCC patients were 3.37 times higher in death risk compared to the low-risk group after adjusting for clinically relevant covariates. A total of 196 differentially expressed mRNAs, 2,151 differentially methylated genes and 58 differentially expressed miRNAs were identified between the two subtypes. Additionally, pathway activity analysis showed that the activities of six pathways between the two subtypes were significantly different. Immune cell infiltration analysis revealed that the abundance of nine immune cells differed significantly between the two subtypes. We further applied the weighted gene co-expression network analysis to identify gene modules that may affect patients prognosis. Among the identified modules, the key module genes significantly associated with prognosis were found to be involved in multiple biological processes and pathways, revealing the mechanism underlying the progression of HCC. Hub gene analysis showed that the expression levels of CDK1, CDCA8, TACC3, and NCAPG were significantly associated with HCC prognosis. Our findings may bring novel insights into the subtypes of HCC and promote the realization of precision medicine.

Role of genetic testing in hepatic, pancreatic, and biliary cancers

Hepatic, pancreatic, and biliary (HPB) cancers, including hepatocellular carcinoma (HCC), pancreatic ductal adenocarcinoma (PDAC), and cholangiocarcinoma (CCA) cause a disproportionate amount of the global cancer-related mortality. Despite advances in surgical technique and improved systemic therapies, overall 5-year survival remains dismal, especially for patients with pancreatic and biliary cancer. Historically, systemic therapies for patients with HPB cancers were administered in a "one-size-fits-all" approach due to limited reliable data on efficacy for specific patient populations. However, recent advances in genetic testing techniques have greatly improved our understanding of HPB oncogenesis, shedding light on specific genetic mutations responsible for progression from physiologic cellular regulation to uninhibited cellular replication and invasive cancer. Investigations into the oncogenesis of HPB cancers have revealed multiple actionable genetic variants, as well as increased susceptibilities to currently available systemic therapies. For example, patients with PDAC and a known BRCA mutation are more likely to benefit from FOLFIRINOX or gemcitabine plus cisplatin. While patients with CCA and a IDH1 mutation may benefit from ivosidenib. As a result, many national and societal guidelines now recommend some form of genetic testing in the workup of patients with HPB cancers. We herein review the role of genetic testing in these aggressive cancers including DNA sequencing techniques, clinically relevant mutations, therapeutic implications, and current clinical recommendations.

Transcriptome sequencing of hepatocellular carcinoma uncovers multiple types of dysregulated ncRNAs

Transcriptome profiling of hepatocellular carcinoma (HCC) by next-generation sequencing (NGS) technology has been broadly performed by previous studies, which facilitate our understanding of the molecular mechanisms of HCC formation, progression, and metastasis. However, few studies jointly analyze multiple types of noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and micro-RNAs (miRNAs), and further uncover their implications in HCC. In this study, we observed that the circRNA cZRANB1 and lncRNA DUXAP10 were not only significantly upregulated in tumor tissues, but also higher expressed in blood exosomes of HCC as compared with healthy donors. From the analysis of subclass-associated dysregulated ncRNAs, we observed that DLX6-AS1, an antisense RNA of DLX6, and the sense gene DLX6 were highly expressed in S1, a subclass with a more invasive/disseminative phenotype. High correlation between DLX6-AS1 and DLX6 suggested that DLX6-AS1 may function via promoting the transcription of DLX6. Integrative analysis uncovers circRNA–miRNA, lncRNA–miRNA, and competing endogenous RNA networks (ceRNAs). Specifically, cZRANB1, LINC00501, CTD-2008L17.2, and SLC7A11-AS1 may function as ceRNAs that regulate mRNAs by competing the shared miRNAs. Further prognostic analysis demonstrated that the dysregulated ncRNAs had the potential to predict HCC patients’ overall survival. In summary, we identified some novel circRNAs and miRNAs, and dysregulated ncRNAs that could participate in HCC tumorigenesis and progression by inducing transcription of their neighboring genes, increasing their derived miRNAs, or acting as miRNA sponges. Moreover, our systematic analysis provides not only rich data resources for related researchers, but also new insights into the molecular basis of how different ncRNAs coordinately or antagonistically participate in the pathogenesis process of diseases.

Identification of novel lactate metabolism signatures and molecular subtypes for prognosis in hepatocellular carcinoma

Background: Evidence has shown that lactate, an immune signaling molecule, is associated with hepatocellular carcinoma (HCC) progression and immune suppression. Therefore, identifying lactate metabolism-related molecules is a promising therapeutic strategy to inhibit the development of HCC and overcome chemotherapy resistance. Long noncoding RNAs (lncRNAs) are related to tumorigenesis and metastasis. Hence, verifying the molecular subtypes of lncRNAs related to lactate metabolism will play a critical role in managing HCC.

Methods: Based on HCC data in The Cancer Genome Atlas (TCGA), lactate metabolic pathway-related genes were enriched by gene collection and enrichment analysis (GSEA). Lactate metabolism-related lncRNAs (LM_lncRNAs) were identified by correlation analysis, HCC molecular subtypes were determined using nonnegative matrix factorization (NMF) clustering, and the response of the three subtypes to chemotherapeutics was further evaluated using the Genomic Tumor Sensitive Cell Line (GDSC) dataset. LM_lncRNAs were examined via Lasso-Cox regression analysis to determine prognosis for patients. A Nomagram plot was used to predict patient survival time.

Results: Three molecular subtypes of HCC were identified. The survival rate of patients with C1 subtype was higher than that of those with C2 and C3. Additionally, patients with C3 subtype have higher levels of immune cell infiltration and high expression of genes related to immune checkpoints. The GDSC results indicated that patients with C3 subtypes were more sensitive to chemotherapy drugs such as sorafenib and sunitinib. The prognostic risk assessment model consisted of six risk factors (AC034229.4, AC131009.1, MYOSLID, AC008667.1, AC012073.1, AC068025.1) and two protective factors (LINC00402 and AC103858.1). Based on Kaplan-Meier analysis, low-risk HCC patients had a high survival rate, and the receiver operating characteristic curve (ROC), calibration curve, and C-index confirmed good prediction ability.

Conclusion: In this study, the molecular subtyping method and prediction model of lactate metabolism-related lncRNAs (LM_lncRNAs) were constructed for the prognosis of HCC patients. This work demonstrated the potential targets of LM_lncRNAs and provided a novel perspective and therapeutic paradigm for future clinical translation.

Knockdown of NDUFC1 inhibits cell proliferation, migration, and invasion of hepatocellular carcinoma

Background

NADH: ubiquinone oxidoreductase subunit C1(NDUFC1) encodes a subunit of the Complex I, which may support the structural stability of Complex I and assist in its biogenesis. The expression and functional roles of NDUFC1 in hepatocellular carcinoma (HCC) remain unknown.

Result

We knocked down the expression of NDUFC1 in HCC cell lines to explore the effects of NDUFC1 downregulation on HCC in vitro. MTT assay determined that downregulation of NDUFC1 significantly inhibited cell proliferation. Flow cytometry with (propidium iodide) PI staining indicated silencing of NDUFC1 arrested cell cycle of BEL-7404 cells at G2 phase and SK-HEP-1 cells at S/G2 phase. Annexin V-PI double staining and flow cytometric analysis showed that the downregulation of NDUFC1 significantly increased the population of apoptotic cells. Wound-healing assay and transwell assay indicated that the downregulation of NDUFC1 suppressed the migration and invasion of HCC cells. According to the detection of complex1 activity, we found that the activity of NDUFC1 silenced group decreased, whereas the content of ROS increased. Furthermore, combined with bioinformatics analysis of senescence-related genes, we found that the silence of NDUFC1 in HCC could induce senescence and inhibit autophagy. In addition, NDUFC1 could correlate positively with cancer-related pathways, among which the p53 pathways and the PI3K/Akt/mTOR pathways. Finally, NDUFC1 is high expression in HCC specimens. High NDUFC1 expression was associated with poor prognosis and was an independent risk factor for reduced overall survival (OS).

Conclusions

Our study indicated, for the first time, that NDUFC1 is an independent risk factor for the poor prognosis of HCC patients. NDUFC1 may promote tumor progression by inhibiting mitochondrial Complex I and up-regulating ROS through multiple cancer-related and senescence-related pathways of HCC, including p53 pathways and PI3K/Akt/mTOR pathways. We suppose that NDUFC1 might be a potential target for the mitochondrial metabolism therapy of HCC.

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

Simple Summary

DNA repair pathways have been implicated in hepatocellular carcinoma outcomes. We found that hepatocellular carcinomas (HCC) could be separated into two groups (high and low) based on the overall expression of genes involved in DNA repair. Among the low repair group, there were three subgroups, one of which shared features of the high repair group. Given the important role of liver in metabolism and detoxification and its regenerative capacity, proliferation and DNA damage responses are critical in subdividing major biological categories of liver tumors. High repair samples showed more proliferative and regenerative signatures and had poorer outcomes versus the low repair that were more associated with the genes involved in normal liver biology. These biological groups suggest that dysregulation in endogenous liver processes promotes a pro-tumorigenic microenvironment that may facilitate tumor progression or identify tumors that require more substantial clinical intervention.

Abstract

DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.