Genomic and transcriptional heterogeneity of multifocal hepatocellular carcinoma

A novel MYC-ZNF706-SLC7A11 regulatory circuit contributes to cancer progression and redox balance in human hepatocellular carcinoma

The oncogenic potential of chromosome 8q22 copy number gain in liver cancer remains to be depicted. Here, we report that ZNF706, encoded by a gene mapped to chromosome 8q22, is a C2H2-type zinc finger protein. However, the biological function and mechanism of ZNF706 have been poorly investigated. Clinically, ZNF706 expression was elevated in hepatocellular carcinoma (HCC), and high ZNF706 expression was associated with unfavorable survival in HCC patients. Functional experiments revealed that ZNF706 knockdown inhibited HCC progression both in vitro and in vivo. RNA sequencing (RNA-seq) and chromatin immunoprecipitation-based deep sequencing (ChIP-seq) revealed that mechanistically, ZNF706 is a crucial ferroptosis regulator and that SLC7A11 is a critical target of ZNF706. In addition, ZNF706 knockdown inhibited SLC7A11 expression, increased lipid peroxidation, and promoted ferroptosis. Further analysis revealed that ZNF706 is a novel direct target transcriptionally activated by MYC in HCC cells. Importantly, MYC depletion reduced SLC7A11-mediated redox homeostasis, and this effect was reversed by ZNF706 reexpression. Collectively, our data demonstrate that ZNF706 is a potential oncogene in liver cancer and functions as a ferroptosis regulator by modulating SLC7A11 expression, constituting a potential therapeutic target for HCC.

Combination of bulk RNA and single-cell sequencing unveils PANoptosis-related immunological ecology hallmarks and classification for clinical decision-making in hepatocellular carcinoma

PANoptosis is engaged in the program of immune response and carcinogenicity. Nonetheless, the actual impacts of PANoptosis on clinical management and oncology immunity in hepatocellular carcinoma (HCC) are not fully grasped. RNA-seq-derived computations were conducted to sort out the molecular subtypes and elucidate the disparities based on PANoptosis molecules. Single-cell sequencing (scRNA-seq) tools including Cytotrace and Addmodulescore were extracted to characterize diversification potency and quantify the PANoptosis motion. Transcriptional factors were inferred by the pySCENIC package and Cellchat program scrutinized the intercellular exchange across cell compartments. The PANoptosis score system originated by incorporating 10 machine learning algorithms and 101 compositions to project clinical results and deteriorate tendencies. Circulatory PANoptosis-associated protein HSP90AA1 was determined by enzyme-linked immunosorbent assay (ELISA). HCC individuals could be categorized into low- and high-PANoptosis groups with diverse biogenic and pharmacotherapy heterogeneity. Individuals in the elevated PANoptosis subtype were characterized as "hot tumor" conveying the increased presence of immunogenicity while reiterating an explicit negative connection with tumor stemness. Compared to immune and stromal cells, cancerous cells showcased decreased PANoptosis and heightened PANoptosis malignant cell subgroups might be tied to a substantial level of genomic expression of SREBF2, JUND, GATAD1, ZBTB20, SMAD5 and implied a more aggressive potential. The PANoptosis index, derived from machine learning, has been established to provide succinct frameworks for predicting outcomes and clarified the noteworthy utility of conventional regimens, as the differentiated power of HCC occurred together with vascular invasion and hepatocellular adenoma (HCA). The experiment confirmed that the circulating HSP90AA1 was aberrantly augmented in HCC patients, thus demonstrating its potential as a discriminatory biomarker. We systematically deciphered the molecular and immune ecosystem traits of PANoptosis in bulk and scRNA-seq degrees, which may deliver advantageous insights for customized treatment, awareness of the pathological process and prognosis scrutiny for HCC patients.

Increases in 4-Acetaminobutyric Acid Generated by Phosphomevalonate Kinase Suppress CD8+ T Cell Activation and Allow Tumor Immune Escape

Certain metabolites in the tumor microenvironment (TME) can alter innate immunity. Here, it is shown how phosphomevalonate kinase (PMVK) allows hepatocellular carcinoma (HCC) cells to overcome the anti-tumor immunity mediated by CD8+ T cells. In HCCs, depletion of PMVK is required to facilitate CD8+ T cell activation and their subsequent suppression of tumor growth. Mechanistically, PMVK phosphorylates and stabilizes glutamate decarboxylase 1 (GAD1), thus increasing the synthesis of γ-aminobutyric acid (GABA), which normally functions as a neurotransmitter. However, PMVK also recruits acetyl-CoA acetyltransferase 1 (ACAT1) and allows it to convert GABA, to 4-acetaminobutyric acid (4-Ac-GABA), which is released into the TME. There, 4-Ac-GABA activates the GABAA receptor (GABAAR) on CD8+ T cells, which inhibits AKT1 signaling. This in turn suppresses CD8+ T cell activation, intratumoral infiltration, and the anti-tumor response. Inhibiting PMVK or GABAAR in HCC mouse models overcomes resistance to anti-PD-1 immune checkpoint therapy. These findings reveal non-canonical and cooperative functions among the key metabolic enzymes PMVK, GAD1, and ACAT1 that reprogram glutamine metabolism to synthesize a potent CD8+ T cell inhibitor 4-Ac-GABA. Blocking 4-Ac-GABA signaling in CD8+ T cells, particularly when combined with immune checkpoint inhibition, potentially represents a new and potent form of immunotherapy.

HOXA9 promotes proliferation, metastasis and prevents apoptosis in hepatocellular carcinoma

PURPOSE

This research aimed to evaluate the expression level of Homeobox A9 (HOXA9) and its role in tumorigenesis of hepatocellular carcinoma (HCC).

METHODS

Bioinformatic analysis, qPCR and Western blot analysis of clinical samples were employed to evaluate mRNA and protein levels of HOXA9 in HCC patients and cell lines. In vitro cell proliferation, migration and invasion, cloning formation, xenograft tumor model, wound healing and apoptosis assays, RNA sequencing analysis of RPL38-silenced HCC-LM3 cells and qPCR, Western blot analysis were performed for validation. Analysis of HOXA9-related genes were conducted to identify their relationships between HOXA9.

RESULTS

HOXA9 is dramatically upregulated in HCC. Upregulation of HOXA9 in HCC predicts poor survival of patients. Besides, HOXA9 promotes proliferation, metastasis and prevents apoptosis in HCC in vitro. In addition, HOXA9 controlled by Ribosomal protein RPL38 is upregulated in HCC. Bioinformatic analysis also indicated that HOXA9 is involved in the regulation of DNA methylation and immune infiltration in HCC.

CONCLUSION

HOXA9 is dramatically upregulated in hepatocellular carcinoma and predicts poor prognosis. Besides, HOXA9 promoted proliferation and metastasis and prevented apoptosis in vitro, which is regulated by Ribosomal protein RPL38 in HCC.

Early identification of hepatocellular carcinoma patients at high-risk of recurrence using the ADV score: a multicenter retrospective study

BACKGROUND

Postoperative recurrence is a vital reason for poor 5-year overall survival in hepatocellular carcinoma (HCC) patients. The ADV score is considered a parameter that can quantify HCC aggressiveness. This study aimed to identify HCC patients at high-risk of recurrence early using the ADV score.

METHODS

The medical data of consecutive HCC patients undergoing hepatectomy from The First Affiliated Hospital of Nanjing Medical University (TFAHNJMU) and Nanjing Drum Tower Hospital (NJDTH) were retrospectively reviewed. Based on the status of microvascular invasion and the Edmondson-Steiner grade, HCC patients were divided into three groups: low-risk group (group 1: no risk factor exists), medium-risk group (group 2: one risk factor exists), and high-risk group (group 3: coexistence of two risk factors). In the training cohort (TFAHNJMU), the R package nnet was used to establish a multi-categorical unordered logistic regression model based on the ADV score to predict three risk groups. The Welch's T-test was used to compare differences in clinical variables in three predicted risk groups. NJDTH served as an external validation center. At last, the confusion matrix was developed using the R package caret to evaluate the diagnostic performance of the model.

RESULTS

350 and 405 patients from TFAHNJMU and NJDTH were included. HCC patients in different risk groups had significantly different liver function and inflammation levels. Density maps demonstrated that the ADV score could best differentiate between the three risk groups. The probability curve was plotted according to the predicted results of the multi-categorical unordered logistic regression model, and the best cut-off values of the ADV score were as follows: low-risk ≤ 3.4 log, 3.4 log < medium-risk ≤ 5.7 log, and high-risk > 5.7 log. The sensitivities of the ADV score predicting the high-risk group (group 3) were 70.2% (99/141) and 78.8% (63/80) in the training and external validation cohort, respectively.

CONCLUSION

The ADV score might become a valuable marker for screening patients at high-risk of HCC recurrence with a cut-off value of 5.7 log, which might help surgeons, pathologists, and HCC patients make appropriate clinical decisions.

Comprehensive analysis of POLH-AS1 as a prognostic biomarker in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC), a prevalent primary malignant tumor, is notorious for its high mortality rate. Despite advancements in HCC treatment, patient outcomes remain suboptimal. This study endeavors to assess the potential prognostic significance of POLH-AS1 in HCC.

METHODS

In this research, we gathered RNA-Seq information from individuals with HCC in The Cancer Genome Atlas (TCGA). We analyzed the levels of POLH-AS1 expression in both HCC cells and tissues using statistical tests. Additionally, we examined various prognostic factors in HCC using advanced methodologies. Furthermore, we employed Spearman's rank correlation analysis to examine the association between POLH-AS1 expression and the tumor's immune microenvironment. Finally, the functional roles of POLH-AS1 in HCC were validated in two HCC cell lines (HEP3B and HEPG2).

RESULTS

Our analysis revealed elevated POLH-AS1 expression across various cancers, including HCC, with heightened expression correlating with HCC progression. Notably, POLH-AS1 expression emerged as a potential biomarker for HCC patient survival and prognosis. Mechanistically, we identified the involvement of POLH-AS1 in tumorigenesis pathways such as herpes simplex virus 1 infection, interactions with neuroactive receptors, and the cAMP signaling pathway. Lastly, inhibition of POLH-AS1 was discovered to hinder the proliferation, invasion and migration of HEP3B and HEPG2 HCC cells.

CONCLUSIONS

POLH-AS1 emerges as a promising prognostic biomarker and therapeutic target for HCC, offering potential avenues for enhanced patient management and treatment strategies.

Recent developments in molecular targeted therapies for hepatocellular carcinoma in the genomic era

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the third 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 the definition of molecular subgroups and the identification of some molecular biomarkers and therapeutic targets. Recent therapeutic developments are also highlighted.

EXPERT OPINION

Deepening the understanding of the molecular complexity of HCC is progressively paving the way for the development of more personalized treatment approaches. Two important strategies involve the definition and validation of molecularly defined therapeutic targets in a subset of HCC patients and the identification of suitable biomarkers for approved systematic therapies (multikinase inhibitors and immunotherapies). The extensive molecular characterization of patients at the genomic and transcriptomic levels and the inclusion of detailed and relevant translational studies in clinical trials will represent a fundamental tool for improving the benefit of systemic therapies in HCC.

miR-19a-3p promotes the growth of hepatocellular carcinoma by regulating p53/SOX4

Objective

This study aims to investigate the potential functions of miR-19a-3p in HCC.

Method

We collected serum samples to analyze miR-19a-3p expression. We utilized CCK8 and Transwell assays to access miR-19a-3p's influence on HCC cells malignancy. We used dual-luciferase reporter and western blotting to validate the impact of p53/miR-19 on miR-19/SOX4.

Results

The results demonstrated that miR-19a-3p was highly expressed in pre-operative serum samples and HCC cells, which can promote cell proliferation, migration and invasion in HCC under in vitro conditions. Additionally, there was a p53 binding site on the upstream of miR-19a-3p, which was inhibited by p53. SOX4 was the direct gene targeted by miR-19a-3p. The imbalance of p53-miR-19-SOX4 loop was one reason for the progress of HCC.

Conclusion

Our findings validate the mechanisms of miR-19a-3p and highlight its potential as a therapeutic target in HCC.

Prognostic implications of preoperative, postoperative, and dynamic changes of alpha-fetoprotein and des-gamma (γ)-carboxy prothrombin expression pattern for hepatocellular carcinoma after hepatic resection: a multicenter observational study

Background

The utility of pre- and post-operative alpha-fetoprotein (AFP) and des-gamma (γ)-carboxy prothrombin (DCP) expression patterns and their dynamic changes as predictors of the outcome of hepatic resection for hepatocellular carcinoma (HCC) has yet to be well elucidated.

Methods

From a multicenter database, AFP and DCP data during the week prior to surgery and the first post-discharge outpatient visit (within 1-2 months after surgery) were collected from patients with HCC who underwent hepatectomy. AFP-DCP expression patterns were categorized according to the number of positive tumor markers (AFP ≥ 20ng/mL, DCP ≥ 40mAU/mL), including double-negative, single-positive, and double-positive. Changes in the AFP-DCP expression patterns were delineated based on variations in the number of positive tumor markers when comparing pre- and post-operative patterns.

Results

Preoperatively, 53 patients (8.3%), 337 patients (52.8%), and 248 patients (38.9%) exhibited double-negative, single-positive, and double-positive AFP-DCP expression patterns, respectively. Postoperatively, 463 patients (72.6%), 130 patients (20.4%), and 45 patients (7.0%) showed double-negative, single-positive, and double-positive AFP-DCP expression patterns, respectively. Survival analysis showed a progressive decrease in recurrence-free (RFS) and overall survival (OS) as the number of postoperative positive tumor markers increased (both P < 0.001). Multivariate analysis showed that postoperative AFP-DCP expression pattern, but not preoperative AFP-DCP expression pattern, was an independent risk factor for RFS and OS. Further analysis showed that for patients with positive preoperative markers, prognosis gradually improves as positive markers decrease postoperatively. In particular, when all postoperative markers turned negative, the prognosis was consistent with that of preoperative double-negative patients, regardless of the initial number of positive markers.

Conclusions

AFP-DCP expression patterns, particularly postoperative patterns, serve as vital sources of information for prognostic evaluation following hepatectomy for HCC. Moreover, changes in AFP-DCP expression patterns from pre- to post-operation enable dynamic prognostic risk stratification postoperatively, aiding the development of individualized follow-up strategies.

Machine learning-based model for predicting tumor recurrence after interventional therapy in HBV-related hepatocellular carcinoma patients with low preoperative platelet-albumin-bilirubin score

Introduction

This study aimed to develop a prognostic nomogram for predicting the recurrence-free survival (RFS) of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients with low preoperative platelet-albumin-bilirubin (PALBI) scores after transarterial chemoembolization (TACE) combined with local ablation treatment.

Methods

We gathered clinical data from 632 HBV-related HCC patients who received the combination treatment at Beijing You'an Hospital, affiliated with Capital Medical University, from January 2014 to January 2020. The patients were divided into two groups based on their PALBI scores: low PALBI group (n=247) and high PALBI group (n=385). The low PALBI group was then divided into two cohorts: training cohort (n=172) and validation cohort (n=75). We utilized eXtreme Gradient Boosting (XGBoost), random survival forest (RSF), and multivariate Cox analysis to pinpoint the risk factors for RFS. Then, we developed a nomogram based on the screened factors and assessed its risk stratification capabilities and predictive performance.

Results

The study finally identified age, aspartate aminotransferase (AST), and prothrombin time activity (PTA) as key predictors. The three variables were included to develop the nomogram for predicting the 1-, 3-, and 5-year RFS of HCC patients. We confirmed the nomogram's ability to effectively discern high and low risk patients, as evidenced by Kaplan-Meier curves. We further corroborated the excellent discrimination, consistency, and clinical utility of the nomogram through assessments using the C-index, area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

Conclusion

Our study successfully constructed a robust nomogram, effectively predicting 1-, 3-, and 5-year RFS for HBV-related HCC patients with low preoperative PALBI scores after TACE combined with local ablation therapy.

Th17 Cells Secrete TWEAK to Trigger Epithelial-Mesenchymal Transition and Promote Colorectal Cancer Liver Metastasis

Liver metastasis is the leading cause of mortality in patients with colorectal cancer. Given the significance of both epithelial-mesenchymal transition (EMT) of tumor cells and the immune microenvironment in colorectal cancer liver metastasis (CRLM), the interplay between them could hold the key for developing improved treatment options. We employed multiomics analysis of 130 samples from 18 patients with synchronous CRLM integrated with external datasets to comprehensively evaluate the interaction between immune cells and EMT of tumor cells in liver metastasis. Single-cell RNA sequencing analysis revealed distinct distributions of nonmalignant cells between primary tumors from patients with metastatic colorectal cancer (mCRC) and non-metastatic colorectal cancer, showing that Th17 cells were predominantly enriched in the primary lesion of mCRC. TWEAK, a cytokine secreted by Th17 cells, promoted EMT by binding to receptor Fn14 on tumor cells, and the TWEAK-Fn14 interaction enhanced tumor migration and invasion. In mouse models, targeting Fn14 using CRISPR-induced knockout or lipid nanoparticle-encapsulated siRNA alleviated metastasis and prolonged survival. Mice lacking Il17a or Tnfsf12 (encoding TWEAK) exhibited fewer metastases compared with wild-type mice, while cotransfer of Th17 with tumor cells promoted liver metastasis. Higher TWEAK expression was associated with a worse prognosis in patients with colorectal cancer. In addition, CD163L1+ macrophages interacted with Th17 cells, recruiting Th17 via the CCL4-CCR5 axis. Collectively, this study unveils the role of immune cells in the EMT process and identifies TWEAK secreted by Th17 as a driver of CRLM.

SIGNIFICANCE

TWEAK secreted by Th17 cells promotes EMT by binding to Fn14 on colorectal cancer cells, suggesting that blocking the TWEAK-Fn14 interaction may be a promising therapeutic approach to inhibit liver metastasis.

Cuproptosis-related molecular classification and gene signature of hepatocellular carcinoma and experimental verification

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor overall prognosis. Cuproptosis, a recently proposed mode of copper-dependent cell death, plays a critical role in the malignant progression of various tumors; however, the expression and prognostic value of cuproptosis-related regulatory genes in HCC remain unclear.

Methods

Genomic, genetic, and expression profiles of ten key cuproptosis-related regulatory genes were analyzed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset and protein expression data from the Human Protein Atlas (HPA) database. Unsupervised clustering of HCC patients based on these ten key cuproptosis-related regulatory genes was used to identify different HCC subtypes and analyze the differences in clinical and immune characteristics among subtypes. Subsequently, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox analyses were used to establish a cuproptosis-related prognostic signature, and the accuracy of prognostic signature prediction was internally validated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curve in TCGA training and testing cohorts. The prognostic signature was externally validated using TCGA-LIHC entire cohort and International Cancer Genome Consortium Liver Cancer (ICGC-LIRI) cohorts. Finally, the expression landscape of cuproptosis-related regulatory genes in prognostic signature was explored by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry (IHC) experiments.

Results

Ten cuproptosis-related genes were differentially expressed in normal and HCC tissues. Unsupervised clustering identified two subtypes and HCC patients with these two subtypes had different clinical prognoses and immune characteristics, as well as different degrees of response to immunotherapy. Lipoyltransferase 1 (LIPT1), dihydrolipoamide s-acetyltransferase (DLAT), and cyclin dependent kinase inhibitor 2A (CDKN2A) were selected to construct a prognostic signature, which significantly distinguished HCC patients with different survival periods in the TCGA training and testing cohorts and was well validated in both the TCGA-LIHC entire cohort and ICGC-LIRI cohort. The risk score of the prognostic signature was confirmed to be an independent prognostic factor, and nomograms were generated to effectively predict the probability of HCC patient survival. The qRT-PCR, western blotting and IHC results also revealed a significant imbalance in the expression of these cuproptosis-related genes in HCC.

Conclusions

The classification and prognostic signature based on cuproptosis-related regulatory genes helps to explain the heterogeneity of HCC, which may contribute to the individualized treatment of patients with the disease.

Risk Models for Predicting the Recurrence and Survival in Patients With Hepatocellular Carcinoma Undergoing Radio-Frequency Ablation

Background

Hepatocellular carcinoma (HCC) patients have a poor prognosis after radio-frequency ablation (RFA), and investigating the risk factors affecting RFA and establishing predictive models are important for improving the prognosis of HCC patients.

Methods

Patients with HCC undergoing RFA in Shenzhen People's Hospital between January 2011 and December 2021 were included in this study. Using the screened independent influences on recurrence and survival, predictive models were constructed and validated, and the predictive models were then used to classify patients into different risk categories and assess the prognosis of different categories.

Results

Cox regression model indicated that cirrhosis (hazard ratio [HR] = 1.65), alpha-fetoprotein (AFP) ⩾400 ng/mL (HR = 2.03), tumor number (multiple) (HR = 2.11), tumor diameter ⩾20 mm (HR = 2.30), and platelets (PLT) ⩾ 244 (109/L) (HR = 2.37) were independent influences for recurrence of patients after RFA. On the contrary, AFP ⩾400 ng/mL (HR = 2.48), tumor number (multiple) (HR = 2.52), tumor diameter ⩾20 mm (HR = 2.25), PLT ⩾244 (109/L) (HR = 2.36), and hemoglobin (HGB) ⩾120 (g/L) (HR = 0.34) were regarded as independent influences for survival. The concordance index (C-index) of the nomograms for predicting disease-free survival (DFS) and overall survival (OS) was 0.727 (95% confidence interval [CI] = 0.770-0.684) and 0.770 (95% CI = 0.821-7.190), respectively. The prognostic performance of the nomograms was significantly better than other staging systems by analysis of the time-dependent C-index and decision curves. Each patient was scored using nomograms and influencing factors, and patients were categorized into low-, intermediate-, and high-risk groups based on their scores. In the Kaplan-Meier survival curve, DFS and OS were significantly better in the low-risk group than in the intermediate- and high-risk groups.

Conclusions

The 2 prediction models created in this work can effectively predict the recurrence and survival rates of HCC patients following RFA.

Roles of PPAR activation in cancer therapeutic resistance: Implications for combination therapy and drug development

Therapeutic resistance is a major obstacle to successful treatment or effective containment of cancer. Peroxisome proliferator-activated receptors (PPARs) play an essential role in regulating energy homeostasis and determining cell fate. Despite of the pleiotropic roles of PPARs in cancer, numerous studies have suggested their intricate relationship with therapeutic resistance in cancer. In this review, we provided an overview of the roles of excessively activated PPARs in promoting resistance to modern anti-cancer treatments, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy. The mechanisms through which activated PPARs contribute to therapeutic resistance in most cases include metabolic reprogramming, anti-oxidant defense, anti-apoptosis signaling, proliferation-promoting pathways, and induction of an immunosuppressive tumor microenvironment. In addition, we discussed the mechanisms through which activated PPARs lead to multidrug resistance in cancer, including drug efflux, epithelial-to-mesenchymal transition, and acquisition and maintenance of the cancer stem cell phenotype. Preliminary studies investigating the effect of combination therapies with PPAR antagonists have suggested the potential of these antagonists in reversing resistance and facilitating sustained cancer management. These findings will provide a valuable reference for further research on and clinical translation of PPAR-targeting treatment strategies.

Preclinical liver cancer models in the context of immunoprecision therapy: Application and perspectives

Hepatocellular carcinoma (HCC), ranking as the third leading cause of cancer-related mortality globally, continues to pose challenges in achieving optimal treatment outcomes. The complex nature of HCC, characterized by high spatiotemporal heterogeneity, invasive potential, and drug resistance, presents difficulties in its research. Consequently, an in-depth understanding and accurate simulation of the immune microenvironment of HCC are of paramount importance. This article comprehensively explores the application of preclinical models in HCC research, encompassing cell line models, patient-derived xenograft mouse models, genetically engineered mouse models, chemically induced models, humanized mouse models, organoid models, and microfluidic chip-based patient derived organotypic spheroids models. Each model possesses its distinct advantages and limitations in replicating the biological behavior and immune microenvironment of HCC. By scrutinizing the limitations of existing models, this paper aims to propel the development of next-generation cancer models, enabling more precise emulation of HCC characteristics. This will, in turn, facilitate the optimization of treatment strategies, drug efficacy prediction, and safety assessments, ultimately contributing to the realization of personalized and precision therapies. Additionally, this article also provides insights into future trends and challenges in the fields of tumor biology and preclinical research.

Susceptibility Genes Associated with Multiple Primary Cancers

With advancements in treatment and screening techniques, we have been witnessing an era where more cancer survivors harbor multiple primary cancers (MPCs), affecting approximately one in six patients. Identifying MPCs is crucial for tumor staging and subsequent treatment choices. However, the current clinicopathological criteria for clinical application are limited and insufficient, making it challenging to differentiate them from recurrences or metastases. The emergence of next-generation sequencing (NGS) technology has provided a genetic perspective for defining multiple primary cancers. Researchers have found that, when considering multiple tumor pairs, it is crucial not only to examine well-known essential mutations like MLH1/MSH2, EGFR, PTEN, BRCA1/2, CHEK2, and TP53 mutations but also to explore certain pleiotropic loci. Moreover, specific deleterious mutations may serve as regulatory factors in second cancer development following treatment. This review aims to discuss these susceptibility genes and provide an explanation of their functions based on the signaling pathway background. Additionally, the association network between genetic signatures and different tumor pairs will be summarized.

Molecular evolution in different subtypes of multifocal hepatocellular carcinoma

BACKGROUND

Multifocal hepatocellular carcinoma (MF-HCC) accounts for > 40% of HCCs, exhibiting a poor prognosis than single primary HCCs. Characterizing molecular features including dynamic changes of mutational signature along with clonal evolution, intrahepatic metastatic timing, and genetic footprint in the preneoplastic stage underlying different subtypes of MF-HCC are important for understanding their molecular evolution and developing a precision management strategy.

METHODS

We conducted whole-exome sequencing in 74 tumor samples from spatially distinct regions in 35 resected lesions and adjacent noncancerous tissues from 11 patients, 15 histologically confirmed preneoplastic lesions, and six samples from peripheral blood mononuclear cells. A previously published MF-HCC cohort (n = 9) was included as an independent validation dataset. We combined well-established approaches to investigate tumor heterogeneity, intrahepatic metastatic timing, and molecular footprints in different subtypes of MF-HCCs.

RESULTS

We classified MF-HCCs patients into three subtypes, including intrahepatic metastasis, multicentric occurrence, and mixed intrahepatic metastasis and multicentric occurrence. The dynamic changes in mutational signatures between tumor subclonal expansions demonstrated varied etiologies (e.g., aristolochic acid exposure) underlying the clonal progression in different MF-HCC subtypes. Furthermore, the clonal evolution in intrahepatic metastasis exhibited an early metastatic seeding at 10-4-0.01 cm3 in primary tumor volume (below the limits of clinical detection), further validated in an independent cohort. In addition, mutational footprints in the preneoplastic lesions for multicentric occurrence patients revealed common preneoplastic arising clones, evidently being ancestors of different tumor lesions.

CONCLUSION

Our study comprehensively characterized the varied tumor clonal evolutionary history underlying different subtypes of MF-HCC and provided important implications for optimizing personalized clinical management for MF-HCC.

Personalized drug screening in patient-derived organoids of biliary tract cancer and its clinical application

Patients with biliary tract cancer (BTC) show different responses to chemotherapy, and there is no effective way to predict chemotherapeutic response. We have generated 61 BTC patient-derived organoids (PDOs) from 82 tumors (74.4%) that show similar histological and genetic characteristics to the corresponding primary BTC tissues. BTC tumor tissues with enhanced stemness- and proliferation-related gene expression by RNA sequencing can more easily form organoids. As expected, BTC PDOs show different responses to the chemotherapies of gemcitabine, cisplatin, 5-fluoruracil, oxaliplatin, etc. The drug screening results in PDOs are further validated in PDO-based xenografts and confirmed in 92.3% (12/13) of BTC patients with actual clinical response. Moreover, we have identified gene expression signatures of BTC PDOs with different drug responses and established gene expression panels to predict chemotherapy response in BTC patients. In conclusion, BTC PDO is a promising precision medicine tool for anti-cancer therapy in BTC patients.

Galectin-14 promotes hepatocellular carcinoma tumor growth via enhancing heparan sulfate proteoglycan modification

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy and lacks effective treatment. Bulk-sequencing of different gene transcripts by comparing HCC tissues and adjacent normal tissues provides some clues for investigating the mechanisms or identifying potential targets for tumor progression. However, genes that are exclusively expressed in a subpopulation of HCC may not be enriched or detected through such a screening. In the current study, we performed a single cell-clone-based screening and identified galectin-14 as an essential molecule in the regulation of tumor growth. The aberrant expression of galectin-14 was significantly associated with a poor overall survival of liver cancer patients with database analysis. Knocking down galectin-14 inhibited the proliferation of tumor growth, whereas overexpressing galectin-14 promoted tumor growth in vivo. Non-targeted metabolomics analysis indicated that knocking down galectin-14 decreased glycometabolism; specifically that glycoside synthesis was significantly changed. Further study found that galectin-14 promoted the expression of cell surface heparan sulfate proteoglycans (HSPGs) that functioned as co-receptors, thereby increasing the responsiveness of HCC cells to growth factors, such as epidermal growth factor and transforming growth factor-alpha. In conclusion, the current study identifies a novel HCC-specific molecule galectin-14, which increases the expression of cell surface HSPGs and the uptake of growth factors to promote HCC cell proliferation.

Targeting VPS72 inhibits ACTL6A/MYC axis activity in HCC progression

BACKGROUND AND AIMS

HCC is a highly heterogeneous disease that is caused largely by genomic copy number variations. Herein, the mechanistic and therapeutically targeted role of vacuolar protein sorting 72 homologue (VPS72), a novel copy number variation cis-driven gained gene identified by genome-wide copy number variation and transcriptome analyses in HCC, is not well understood.

APPROACH AND RESULTS

First, overexpression of VPS72 enhanced the initiation and progression of HCC in vitro and in vivo . Mechanistically, VPS72 interacted with the oncoproteins MYC and actin-like 6A (ACTL6A) and promoted the formation of the ACTL6A/MYC complex. Furthermore, ACTL6A regulated VPS72 protein stability by weakening the interaction between tripartite motif containing 21 (TRIM21) and VPS72. Thus, the interaction between VPS72 and ACTL6A enhanced the affinity of MYC for its target gene promoters and promoted their transcription, thereby contributing to HCC progression, which was inhibited by adeno-associated virus serotype 8 (AAV8)-mediated short hairpin RNA (shRNA) against VPS72.

CONCLUSIONS

This study reveals the molecular mechanism of ACTL6A/VPS72/MYC in HCC, providing a theoretical basis and therapeutic target for this malignancy.

Dose Consideration of Lenvatinib's Anti-Cancer Effect on Hepatocellular Carcinoma and the Potential Benefit of Combined Colchicine Therapy

PURPOSE

The dose-dependent anti-cancer effect of lenvatinib on hepatocellular carcinoma (HCC) cells and the potential benefit of combined colchicine therapy were investigated.

METHODS

Four primary cultured HCC (S103, S143, S160, S176) cell lines were investigated by differential expressions of genes (11 lenvatinib target genes and NANOG) and anti-proliferative effect using clinically achievable plasma lenvatinib (250, 350 ng/mL) and colchicine (4 ng/mL) concentrations.

RESULTS

Colchicine showed an anti-proliferative effect on all cell lines. Lenvatinib at 250 ng/mL inhibited proliferation in all cell lines, but 350 ng/mL inhibited only three cell lines. For lenvatinib target genes, colchicine down-regulated more genes and up-regulated less genes than lenvatinib did in three cell lines. Lenvatinib up-regulated NANOG in all cell lines. Colchicine down-regulated NANOG in three cell lines but up-regulated NANOG with less magnitude than lenvatinib did in S103. Overall, combined colchicine and 250 ng/mL lenvatinib had the best anti-cancer effects in S143, with similar effects with combined colchicine and 350 ng/mL lenvatinib in S176 but less effects than combined colchicine and 350 ng/mL lenvatinib in S103 and S160.

CONCLUSIONS

Lenvatinib does not show a dose-dependent anti-cancer effect on HCC. Combined colchicine and lenvatinib can promote the total anti-cancer effects on HCC.

Prediction model of no-response before the first transarterial chemoembolization for hepatocellular carcinoma: TACF score

Previous clinic models for patients with hepatocellular carcinoma (HCC) receiving transarterial chemoembolization (TACE) mainly focused on the overall survival, whereas a simple-to-use tool for predicting the response to the first TACE and the management of risk classification before TACE are lacking. Our aim was to develop a scoring system calculated manually for these patients. A total of 437 patients with hepatocellular carcinoma (HCC) who underwent TACE treatment were carefully selected for analysis. They were then randomly divided into two groups: a training group comprising 350 patients and a validation group comprising 77 patients. Furthermore, 45 HCC patients who had recently undergone TACE treatment been included in the study to validate the model's efficacy and applicability. The factors selected for the predictive model were comprehensively based on the results of the LASSO, univariate and multivariate logistic regression analyses. The discrimination, calibration ability and clinic utility of models were evaluated in both the training and validation groups. A prediction model incorporated 3 objective imaging characteristics and 2 indicators of liver function. The model showed good discrimination, with AUROCs of 0.735, 0.706 and 0.884 and in the training group and validation groups, and good calibration. The model classified the patients into three groups based on the calculated score, including low risk, median risk and high-risk groups, with rates of no response to TACE of 26.3%, 40.2% and 76.8%, respectively. We derived and validated a model for predicting the response of patients with HCC before receiving the first TACE that had adequate performance and utility. This model may be a useful and layered management tool for patients with HCC undergoing TACE.

Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma

Cuproptosis has been recently used to indicate unique biological processes triggered by Cu action as a new term. This study aimed to explore the relationship between cuproptosis-related lncRNA and hepatocellular carcinoma (HCC) with regard to immunity and prognosis. RNA sequencing and the clinical data were downloaded from the TCGA database. The cuproptosis-related genes were sorted out through literature study. The cuproptosis-related IncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The K-M survival analysis, receiver operating characteristic analysis, and C-index analysis were adopted to evaluate the prognostic prediction performance of the signature. The functional enrichment, immune infiltration and tumor mutation analysis were further analyzed. Subsequently, we predicted the differences in chemosensitivity from tumor gene expression levels for some chemotherapy drugs. The prognostic signature consisting of 5 overall survival-related CUPlncRNAs. It showed an extraordinary ability to predict the prognoses of patients with HCC. The signature can predict the abundance of immune cell infiltration, immune functions, expression of immune checkpoint inhibitors, m6A genes, which was supported by the GO biological process and KEGG analysis. And it may also have a guiding effect in the sensitivity of different chemotherapeutic drugs and tumor mutation burden. We constructed a new cuproptosis-related lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on NK cell marker genes to predict prognosis and immunotherapy response in hepatocellular carcinoma

BACKGROUND

Prognostic modeling of NK cell marker genes in patients with hepatocellular carcinoma based on single cell sequencing and transcriptome data analysis.

METHODS

Marker genes of NK cells were analyzed according to single cell sequencing data of hepatocellular carcinoma. Univariate Cox regression, lasso regression analysis, and multivariate Cox regression were performed to estimate the prognostic value of NK cell marker genes. TCGA, GEO and ICGC transcriptomic data were applied to build and validate the model. Patients were divided into high and low risk groups based on the median risk score. XCELL, timer, quantitative sequences, MCP counter, EPIC, CIBERSORT and CIBERSORT-abs were performed to explore the relationship between risk score and tumor microenvironment in hepatocellular carcinoma. Finally the sensitivity of the model to chemotherapeutic agents was predicted.

RESULTS

Single-cell sequencing identified 207 marker genes for NK cells in hepatocellular carcinoma. Enrichment analysis suggested that NK cell marker genes were mainly involved in cellular immune function. Eight genes were selected for prognostic modeling after multifactorial COX regression analysis. The model was validated in GEO and ICGC data. Immune cell infiltration and function were higher in the low-risk group than in the high-risk group. The low-risk group was more suitable for ICI and PD-1 therapy. Half-maximal inhibitory concentrations of Sorafenib, Lapatinib, Dabrafenib, and Axitinib were significantly different on the two risk groups.

CONCLUSION

A new signature of hepatocyte NK cell marker genes possesses a powerful ability to predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma.

From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies

Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.

Hepatocellular Carcinoma: Past and Present Challenges and Progress in Molecular Classification and Precision Oncology

Hepatocellular carcinoma (HCC) is one of the most common solid tumor malignancies in the world and represents roughly 90% of all primary malignancies of the liver. The most common risk factors for HCC include hepatitis B virus, hepatitis C virus, alcohol, and increasingly, fatty liver. Most HCC is diagnosed at advanced stages, excluding the possibility of curative resection, which leaves systemic therapy as the only treatment option. However, given the extreme mutational diversity and heterogenous nature of HCC, efforts to develop new targeted systemic therapies were largely unsuccessful until recently. HCC pathogenesis is thought to be a multistage process driven by a wide array of nonmutually exclusive driver mutations accompanied by many passenger mutations, with the average tumor possessing approximately 40 genomic aberrations. Over the past two decades, several efforts to categorize HCC prognostically and therapeutically according to different molecular subclassifications with the intent to guide treatment and identify drug targets have emerged, though, no single consensus has been reached. Recent breakthroughs in drug development have greatly expanded treatment options, but the ideal of uniting each patient's unique HCC with a targeted systemic therapy remains elusive.

A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients

Background

Edmondson-Steiner (E-S) grade is a pathological indicator of the degree of hepatocellular carcinoma (HCC) differentiation, and E-S grade III-IV is a poor prognostic factor for HCC patients. Predicting poorly differentiated HCC has essential significance for clinical decision-making. Although some studies have developed predictive models based on magnetic resonance imaging (MRI) and radiomics, radiomic features that require specific software for analysis are impractical for clinical work. This study aims to develop a novel and user-friendly nomogram model to predict E-S grade III-IV.

Patients and Methods

Medical data on patients meeting the inclusion criteria were obtained from the Nanjing Drum Tower Hospital HCC database (January 2020 to December 2022). Univariate analysis was used to screen for risk factors associated with E-S grade III-IV. A novel nomogram was established based on the subsequent multivariate logistic regression analysis. The performance of the established model was evaluated through diagnostic ability, calibration, and clinical benefits.

Results

Overall, 240 HCC patients were included in this study. Among them, 103 were highly differentiated (E-S grade I-II) HCC and 137 were poorly differentiated (E-S grade III-IV) HCC. A nomogram model that integrated alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibodies (HCVAb), aspartate aminotransferase to lymphocyte ratio index (ALRI), and macrovascular invasion was established. The novel model had a good diagnostic performance with an area under the curve (AUC) value of 0.763. Meanwhile, the model had a diagnostic accuracy of 72.5%, a sensitivity of 78.1%, and a specificity of 65.1%. The calibration curve showed good calibration of the nomogram model (mean absolute error = 0.043), and the decision curve analysis (DCA) demonstrated that the clinical benefit was provided.

Conclusion

Our developed nomogram model could successfully predict E-S grade III-IV in HCC patients, which may be helpful in clinical decision-making.

Integrated analysis revealing a novel stemness-metabolism-related gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant lethal tumor and both cancer stem cells (CSCs) and metabolism reprogramming have been proven to play indispensable roles in HCC. This study aimed to reveal the connection between metabolism reprogramming and the stemness characteristics of HCC, established a new gene signature related to stemness and metabolism and utilized it to assess HCC prognosis and immunotherapy response. The clinical information and gene expression profiles (GEPs) of 478 HCC patients came from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). The one-class logistic regression (OCLR) algorithm was employed to calculate the messenger ribonucleic acid expression-based stemness index (mRNAsi), a new stemness index quantifying stemness features. Differentially expressed analyses were done between high- and low-mRNAsi groups and 74 differentially expressed metabolism-related genes (DEMRGs) were identified with the help of metabolism-related gene sets from Molecular Signatures Database (MSigDB). After integrated analysis, a risk score model based on the three most efficient prognostic DEMRGs, including Recombinant Phosphofructokinase Platelet (PFKP), phosphodiesterase 2A (PDE2A) and UDP-glucuronosyltransferase 1A5 (UGT1A5) was constructed and HCC patients were divided into high-risk and low-risk groups. Significant differences were found in pathway enrichment, immune cell infiltration patterns, and gene alterations between the two groups. High-risk group patients tended to have worse clinical outcomes and were more likely to respond to immunotherapy. A stemness-metabolism-related model composed of gender, age, the risk score model and tumor-node-metastasis (TNM) staging was generated and showed great discrimination and strong ability in predicting HCC prognosis and immunotherapy response.

Estimating Microvascular Invasion in Patients with Resectable Multinodular Hepatocellular Carcinoma by Using Preoperative Contrast-Enhanced MRI: Establishment and Validation of a Risk Score

Objective

To determine the preoperative clinicoradiological factors to predict microvascular invasion (MVI) in patients with resectable multinodular hepatocellular carcinoma (mHCC), and further to establish and validate a stratified risk scoring system.

Methods

Two hundred and seventy-three patients with pathologically confirmed mHCC (≥2 lesions) without major vascular invasion and biliary tract tumor thrombosis, who underwent preoperative contrast-enhanced MRI and hepatectomy, were consecutively enrolled (training/validation cohort=193/80). Preoperative clinicoradiological variables were collected and analyzed. The multivariable logistic regression was performed to determine the independent predictors of MVI and create a risk score system. The C-index, calibration curve and decision curve were used to evaluate the performance of the risk score. A risk score-based prognostic stratification system was performed in mHCC patients. The risk score system was further verified in the validation cohort.

Results

AFP > 400 ng/mL, presence of satellite nodule, mosaic architecture and increased total tumor diameter were independent predictors of MVI while fat in mass was an independent protective factor of MVI. The risk score yielded satisfactory C-index values (training/validation cohort: 0.777/0.758) and fitted well in calibration curves. Decision curve analysis further confirmed its clinical utility. Based on the risk score, mHCC patients were stratified into high-/low-MVI-risk subgroups with significantly different recurrence-free survival (both P < 0.001).

Conclusion

The presented risk score incorporating clinicoradiological parameters could stratify mHCC patients into high-risk and low-risk subgroups and predict prognosis in patients with resectable mHCC.

Case Report: A case of hepatocellular carcinoma with aberrant right hepatic artery treated with transarterial chemoembolization and infusion chemotherapy separately to bilobar lesion combining with systemic therapies and sequential hepatectomy

Background

Hepatocellular carcinoma (HCC) with a dismal prognosis is the second most deadly malignancy globally. Surgery is believed to be a curative approach. Nevertheless, there is still a considerable probability of postoperative recurrence. Most patients present in advanced stages with a surgically and oncologically unresectable disease. Systemic medicines are increasingly important to downstage the disease and further improve survival.

Case summary

A 67-year-old Chinese man with uncontrolled hepatitis B was discovered to have liver masses with abnormal serum vitamin K absence or antagonist-II (PIVKA-II) level during checkup for upper abdominal discomfort. Abdominal multiphase computerized tomography (CT) and gadoxetate disodium-enhanced magnetic resonance imaging (MRI) showed the bulky bilobar HCCs of Barcelona Clinic Liver Cancer stage B and China Liver Cancer Staging stage IIa. Furthermore, the aberrant right hepatic artery (RHA) originates from the superior mesenteric artery. Due to the location being adjacent to important vasculatures and massive size of the right-sided lesion, curative resection appears to be challenging. To achieve a favorable surgical margin, repeated hepatic arterial infusion chemotherapy (HAIC) was adopted through the variant RHA, while transarterial chemoembolization (TACE) was delivered to the left lobe to arrest tumor growth. Furthermore, sintilimab plus lenvatinib served as the sequential systemic therapy. After 5 months of conversion treatment, the partial response with a decreased serum PIVKA-II level was attained. The R0 hepatectomy was then performed without postoperative complications. The immunohistochemistry and next-generation sequencing results suggested that the two-side HCCs existing tumor heterogeneity were not completely consistent. The patient continues to be without evidence of disease.

Conclusion

Our case highlights a favorable outcome in a man with bilobar bulky HCC after undergoing the comprehensive therapeutic schedule that includes personalized intervention and systemic drug therapy. In terms of conversion therapy, our case provides a secure and practical reference for managing unresectable bilobar HCC coexisting with the aberrant hepatic artery.

Whole genome and RNA sequencing analyses for 254 Taiwanese hepatocellular carcinomas

BACKGROUND

Comprehensive and integrative analysis of hepatocellular carcinoma (HCC) is important. In this study, we explored Taiwanese HCCs using multi-omics analyses.

METHODS

We analyzed 254 HCCs by whole genome sequencing and total RNA sequencing, and then used bioinformatic tools to analyze genomic and transcriptomic alterations in coding and non-coding sequences to explore the clinical importance of each sequence.

RESULTS

The frequencies of the five most commonly mutated cancer-related genes were TERT, TP53, CTNNB1, RB1, and ARID1A. Genetic alteration frequencies influenced the etiology of HCC; some alterations were also correlated with clinicopathological conditions. Many cancer-related genes had copy number alterations (CNAs) and structure variants (SVs) that changed according to etiology and exhibited potential associations with survival. We also identified several alterations in histone-related genes, HCC-related long non-coding RNAs, and non-coding driver genes that may contribute to the onset and progression of HCC. Transcriptomic analysis revealed that 229 differentially expressed and 148 novel alternative splicing (AS) genes, as well as the presence of fusion genes, were associated with patient survival. Moreover, somatic mutations, CNAs, and SVs were associated with immune checkpoint gene expression and tumor microenvironment. Finally, we identified relationships among AS, immune checkpoint gene expression and tumor microenvironment.

CONCLUSIONS

This study shows that genomic alterations are associated with survival, including DNA-based and RNA-based data. Moreover, genomic alterations and their associations with immune checkpoint genes and the tumor microenvironment may provide novel insights for the diagnosis and treatment of HCC.

Inhibition of TRPV4 remodels single cell polarity and suppresses the metastasis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor, frequently causing both intrahepatic and extrahepatic metastases. The overall prognosis of patients with metastatic HCC is poor. Recently, single-cell (sc) polarity is proved to be an innate feature of some tumor cells in liquid phase, and directly involved in the cell adhesion to blood vessel and tumor metastasis. Here, we characterize the maintained sc polarity of HCC cells in a suspension culture, and investigate its roles and regulatory mechanisms during metastasis. We demonstrate that transient receptor potential vanilloid 4 (TRPV4) is a promoting regulator of sc polarity via activating Ca²⁺-dependent AMPK/MLC/ERM pathway. This attenuates the adhesion of metastatic HCC cells to vascular endothelial cells. The reduction of cancer metastases can result from TRPV4 inhibition, which not only impacts the migration and invasion of tumor cells, but also prevents the adhesion to vascular endothelial cells. Additionally, we discover a brand-new TRPV4 inhibitor called GL-V9 that modifies the degree of sc polarization and significantly decreases the metastatic capacity of HCC cells. Taken together, our data shows that TRPV4 and calcium signal are significant sc polarity regulators in metastatic HCC, and that the pharmacological intervention that results in HCC cells becoming depolarized suggests a promising treatment for cancer metastasis.

Advancements in Focal Amplification Detection in Tumor/Liquid Biopsies and Emerging Clinical Applications

Focal amplifications (FAs) are crucial in cancer research due to their significant diagnostic, prognostic, and therapeutic implications. FAs manifest in various forms, such as episomes, double minute chromosomes, and homogeneously staining regions, arising through different mechanisms and mainly contributing to cancer cell heterogeneity, the leading cause of drug resistance in therapy. Numerous wet-lab, mainly FISH, PCR-based assays, next-generation sequencing, and bioinformatics approaches have been set up to detect FAs, unravel the internal structure of amplicons, assess their chromatin compaction status, and investigate the transcriptional landscape associated with their occurrence in cancer cells. Most of them are tailored for tumor samples, even at the single-cell level. Conversely, very limited approaches have been set up to detect FAs in liquid biopsies. This evidence suggests the need to improve these non-invasive investigations for early tumor detection, monitoring disease progression, and evaluating treatment response. Despite the potential therapeutic implications of FAs, such as, for example, the use of HER2-specific compounds for patients with ERBB2 amplification, challenges remain, including developing selective and effective FA-targeting agents and understanding the molecular mechanisms underlying FA maintenance and replication. This review details a state-of-the-art of FA investigation, with a particular focus on liquid biopsies and single-cell approaches in tumor samples, emphasizing their potential to revolutionize the future diagnosis, prognosis, and treatment of cancer patients.

MiR-21-5p promotes sorafenib resistance and hepatocellular carcinoma progression by regulating SIRT7 ubiquitination through USP24

OBJECTIVE

To validate the mechanism by which miR-21-5p mediates autophagy in drug-resistant cells in hepatocellular carcinoma (HCC), aggravating sorafenib resistance and progression of HCC.

METHODS

HCC cells were treated with sorafenib to establish sorafenib-resistant cells, and nude mice were subcutaneously injected with hepatoma cells to establish animal models. RT-qPCR was used to determine the level of miR-21-5p, and Western blotting was used to determine the level of related proteins. Cell apoptosis, cell migration, the level of LC3 were accessed. Immunohistochemical staining was used for detection of Ki-67 and LC3. A dual-luciferase reporter assay certified that miR-21-5p targets USP42, and a co-immunoprecipitation assay validated the mutual effect between USP24 and SIRT7.

RESULTS

miR-21-5p and USP42 were highly expressed in HCC tissue and cells. Inhibition of miR-21-5p or knockdown of USP42 inhibited cell proliferation and cell migration, upregulated the level of E-cadherin, and downregulated the level of vimentin, fibronectin and N-cadherin. Overexpression of miR-21-5p reversed the knockdown of USP42. Inhibition of miR-21-5p downregulated the ubiquitination level of SIRT7, downregulated the levels of LC3II/I ratio and Beclin1, and upregulated the expression of p62. The tumor size in the miR-21-5p inhibitor group was smaller, and Ki-67 and LC3 in tumor tissue were reduced, while the overexpression of USP42 reversed the effect of the miR-21-5p inhibitor.

CONCLUSION

miR-21-5p promotes deterioration and sorafenib resistance in hepatocellular carcinoma by upregulating autophagy levels. Knockdown of miR-21-5p inhibits the development of sorafenib-resistant tumors by USP24-mediated SIRT7 ubiquitination.

Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has one of the highest mortality rates among solid cancers. Late diagnosis and a lack of efficacious treatment options contribute to the dismal prognosis of HCC. Immune checkpoint inhibitor (ICI)-based immunotherapy has presented a new milestone in the treatment of cancer. Immunotherapy has yielded remarkable treatment responses in a range of cancer types including HCC. Based on the therapeutic effect of ICI alone (programmed cell death (PD)-1/programmed death-ligand1 (PD-L)1 antibody), investigators have developed combined ICI therapies including ICI + ICI, ICI + tyrosine kinase inhibitor (TKI), and ICI + locoregional treatment or novel immunotherapy. Although these regimens have demonstrated increasing treatment efficacy with the addition of novel drugs, the development of biomarkers to predict toxicity and treatment response in patients receiving ICI is in urgent need. PD-L1 expression in tumor cells received the most attention in early studies among various predictive biomarkers. However, PD-L1 expression alone has limited utility as a predictive biomarker in HCC. Accordingly, subsequent studies have evaluated the utility of tumor mutational burden (TMB), gene signatures, and multiplex immunohistochemistry (IHC) as predictive biomarkers. In this review, we aim to discuss the current state of immunotherapy for HCC, the results of the predictive biomarker studies, and future direction.

CircTNPO3 promotes hepatocellular carcinoma progression by sponging miR-199b-5p and regulating STRN expression

Hepatocellular carcinoma (HCC) is the most common primary liver tumor, which seriously threatens human health. CircTNPO3 was up-regulated in HCC tissues. However, the regulatory mechanism of circTNPO3 in HCC was still unclear. We aimed to investigate the circTNPO3 function in the development of HCC. qRT-PCR and Western blot examined gene and protein levels. CCK8, EdU, flow cytometry, and Transwell assays were used to detect cell viability, proliferation, apoptosis, and invasion abilities. Dual-luciferase reporter and RIP assays determined the relationship between circTNPO3, miR-199b-5p, and striatin (STRN). The effect of CircTNPO3 on HCC progress was investigated in vivo. CircTNPO3 and STRN were significantly increased, while miR-199b-5p was repressed in HCC tissues or cells. Afterward, miR-199b-5p was negatively correlated with STRN. circTNPO3 was positively correlated with STRN. Knockdown of circTNPO3 inhibited cell viability, proliferation, invasion, and promoted apoptosis, while circTNPO3 overexpression had the opposite results. Furthermore, miR-199b-5p inhibition could eliminate the regulatory effect of sh-circTNPO3 on the proliferation and apoptosis in HCC cells. CircTNPO3 positively regulated STRN expression by targeting miR-199b-5p. MiR-199b-5p suppressed HCC progression by inhibiting STRN expression. Tumor formation in nude mice showed that knockdown of circTNPO3 significantly inhibited tumor growth and suppressed ki-67 levels. CircTNPO3 promoted HCC progression through regulating STRN expression by sponging miR-199b-5p, which provided a strategy for HCC treatment.

A novel fatty acid metabolism-related gene prognostic signature and candidate drugs for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. Fatty acid metabolism (FAM) is associated with the development and treatment of HCC. This study aimed to build a FAM-related gene model to assess the prognosis of HCC and provide guidance for individual treatment. RNA-sequencing data of patients with HCC from The Cancer Genome Atlas and Gene Expression Omnibus database (GSE14520) were extracted as the training and validation sets, respectively. A FAM-related gene predictive signature was built, and the performance of prognostic model was assessed. The immune infiltration and drug sensitivity were also evaluated. Quantitative real-time polymerase chain reaction and western blot were performed to evaluate the levels of the model genes. A 12-gene FAM-related risk signature was constructed; patients with a higher risk score had poorer prognosis than those with a lower risk score. Risk score was shown as an independent risk factor for overall survival of HCC, and the signature was further confirmed as an effective and accurate model. A nomogram was constructed, and it exhibited the good performance in the prognostic prediction. In addition, the immune cell infiltration and sensitivity to chemotherapy drugs were correlated with different risk levels. Finally, quantitative real-time polymerase chain reaction and western blot proved the changes of above genes. Differential expression of FAM-related genes can be used to predict response to immunotherapy and chemotherapy, and improve the clinical prognosis evaluation of patients with HCC, which provides new clues for further experimental exploration and verification on FAM-related genes in HCC.

Vessels That Encapsulate Tumor Clusters (VETC) Predict cTACE Response in Hepatocellular Carcinoma

Background

To investigate the correlation between hepatocellular carcinoma (HCC) pathological types and conventional transarterial chemoembolization (cTACE), and to evaluate the predictive value of the pathological types for efficacy of cTACE.

Methods

We investigated 186 naive HCC patients from 2 hospitals, including 63 patients with recurrence after surgical resection, and 123 unresectable cases, who underwent at least one cTACE procedure as the first treatment. All patients were histologically diagnosed with HCC by surgical resection and/or liver biopsy. Lipiodol deposition rate, ORR (objective response rate), PFS (progression-free survival), OS (overall survival) were compared among different HCC pathological types.

Results

This study evaluated 186 naive HCC patients and 189 tumor nodules. Vessels that encapsulate tumor clusters (VETC), macrotrabecular-massive (MTM), CK19-positive types were identified in 38% (72/189), 40% (76/189), and 28% (53/189) of the whole cohort, respectively. VETC, MTM and CK19-negative HCCs derived significantly better lipiodol deposition rate and ORR. cTACE prolonged the PFS of VETC and CK19-negative HCCs compared with non-VETC and CK19-positive HCCs in the recurrence, liver biopsy and combining whole cohorts, whereas the OSs of different pathological types were not significantly different. Multivariate analysis showed that VETC (OR, 4.671, 95% CI [1.954, 11.166], P<0.001) and CK19-positive type (OR, 0.127, 95% CI [0.044, 0.362], P<0.001) were independent predictive factors for the first cTACE response. However, only VETC type was significantly associated with the second cTACE response in multivariate analysis (OR, 3.31, 95% CI [1.24, 8.83], P=0.017), suggesting that VETC might be a more useful predictor of cTACE response.

Conclusion

Our study suggests that VETC is an effective predictor of cTACE response in patients with HCC.

Molecular characteristics of multifocal esophageal squamous cell carcinomas to discriminate multicentric origin from intramural metastasis

Multifocal esophageal squamous cell carcinomas (ESCCs) can be diagnosed as of multicentric origin (MO) or intramural metastasis (IMM). We aimed here to accurately discriminate MO from IMM and explore the tumor immune microenvironment of multifocal ESCCs. Multifocal ESCCs were identified in 333 ESCC patients, and in 145 patients discrimination between MO and IMM was not possible by histopathological examination. Of the 145 patients, tissues of 14 were analyzed by whole-exome sequencing (WES) of 71 different tumor regions, and MO, IMM, and MO/IMM mixed groups were identified in three, ten, and one cases, respectively, based on the similarity of genomic architecture between or among different tumors from one patient. Further phylogenetic analyses revealed complex clonal evolution patterns in IMM cases, and tumor cells disseminated from the primary tumors to IMM tumors were independent of lymph node metastasis. The NanoString-based assay showed that immune cell infiltrates were significantly enriched, and that the immune and proliferation pathways were more activated, in large tumors than in small ones in MO but not IMM cases. Similarly, PD-L1 expression and the density of paratumoral CD8⁺ T cells were higher in large tumors than in small tumors in MO. Taken together, through analysis of the genomic and immune landscapes, our study has comprehensively characterized the heterogeneity and clonal relationship of multifocal ESCCs, which may be helpful in distinguishing MO from IMM, and for interpreting the immunotherapy responses for multifocal ESCC patients. © 2022 The Pathological Society of Great Britain and Ireland.

Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. RAS-related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important roles in the progression and prognosis of LIHC. However, the clinical role, prognostic significance, and immune regulation of RAS-related lncRNAs in LIHC remains unclear. Our study aims to construct and validate a RAS-related lncRNA prognostic risk signature that can estimate the prognosis and response to immunotherapy in LIHC.

Methods

The clinical information and corresponding messenger RNA (mRNA)/lncRNA expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and 502 RAS-related lncRNAs were identified by Pearson correlation analysis. A prognostic risk signature with 5 RAS-related lncRNAs was then developed based on the Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm analyses. Subsequently, Kaplan-Meier survival curve, receiver operating characteristic (ROC) curve, and the nomogram were established to evaluate the predictive accuracy of the signature. In addition, the immune microenvironment, tumor mutation burden, and drug sensitivity associated with the signature were also analyzed in LIHC.

Results

Compared with the low-risk groups, the high-risk groups had an unfavorable outcome. Multivariate regression analysis revealed that the risk score signature was the independent prognostic factor superior to the other clinical variables. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses demonstrated that the risk score was highly associated with the nuclear division, DNA replication, and immune response. The group with high risk tended to hold a lower immune escape rate and better immunotherapy efficacy, while the group with low risk was more sensitive to some small molecular targeted drugs.

Conclusions

We developed a RAS-related lncRNA risk signature that was highly associated with the prognosis and response to immunotherapy and targeted drugs and which provided novel mechanistic insights into the personalized treatment and potential drug selection for patients with LIHC.

Development and experimental verification of a prognosis model for cuproptosis-related subtypes in HCC

BACKGROUND

Cuproptosis is a recently discovered mechanism of programmed cell death caused by intracellular aggregation of mitochondrial lipoylated proteins and destabilization of iron-sulfur proteins triggered by copper. Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to predict the survival of patients with HCC using the cuproptosis-related gene (CRG) expression.

METHODS

We analyzed the expression, methylation, and mutation status of CRGs in 538 HCC patients and correlated the date with clinical prognosis. HCC patients were divided into two clusters based on their CRG expression. The relationship between CRGs, risk genes, and the immune microenvironment was analyzed using the CIBERSORT algorithm and the single-cell data analysis method. A cuproptosis risk model was constructed according to the five risk genes using the LASSO COX method. To facilitate the clinical applicability of the proposed risk model, we constructed a nomogram and conducted an antineoplastic drug sensitivity analysis.

RESULTS

Our results suggest that the expression levels of CRGs in HCC are regulated by methylation. The prognoses were significantly different between the patients of the two clusters. The prognostic risk score positively correlated with memory T cell activation and negatively correlated with natural killer (NK) and regulatory T cell activation.

CONCLUSION

Our findings indicate the involvement of CRG regulation in HCC and provide new insights into prognosis assessment. Drug sensitivity analysis predicted drug candidates for the treatment of patients with different HCC subtypes.

Genetic dominance of transforming growth factor-β1 polymorphisms in chronic liver disease

Chronic liver disease (CLD) is an extremely common clinical condition accompanied by sustained inflammatory response leading to tissue damage. Transforming growth factor-β1 (TGF-β1) is known as a master immune regulator in CLDs, but the association between TGF-β1 polymorphisms and CLD risk is controversial and inconclusive, and the genetic dominance of CLDs remains unknown. In this study, the relationship between TGF-β1 polymorphisms and CLD susceptibility is systematically analyzed based on 35 eligible studies. Individuals with the TGF-β1-509 allele (TT or CT) or codon 10 allele (Pro/Pro) show an increased risk of CLDs. Subgroup analyses indicate TGF-β1-509C/T has a significant correlation with cirrhosis and chronic hepatitis C, codon 10 is associated with chronic hepatitis B occurrence, and codon 25 exhibits a relationship with autoimmune hepatitis risk. Missense mutations in G29E, A105S, D191N, and F321L of TGF-β1 are the genetic factors of HCC susceptibility. Furthermore, the TGF-β1 gene expression is significantly elevated in CLD patients, and the TGF-β1 codon 263 is located close to the region where the TGF-β1 dimerization interacts, indicating the TGF-β1 codon 263 variant may affect the secretion of TGF-β1 by altering its dimerization. Together, our findings provide new insights into the immune regulator gene TGF-β1 polymorphisms as susceptibility factors for CLD occurrence and regulators for TGF-β1 expression, which have implications for the regulation of immune factors during CLD development.

Liquid biopsy for children with central nervous system tumours: Clinical integration and technical considerations

Circulating cell-free DNA (cfDNA) analysis has the potential to revolutionise the care of patients with cancer and is already moving towards standard of care in some adult malignancies. Evidence for the utility of cfDNA analysis in paediatric cancer patients is also accumulating. In this review we discuss the limitations of blood-based assays in patients with brain tumours and describe the evidence supporting cerebrospinal fluid (CSF) cfDNA analysis. We make recommendations for CSF cfDNA processing to aid the standardisation and technical validation of future assays. We discuss the considerations for interpretation of cfDNA analysis and highlight promising future directions. Overall, cfDNA profiling shows great potential as an adjunct to the analysis of biopsy tissue in paediatric cancer patients, with the potential to provide a genetic molecular profile of the tumour when tissue biopsy is not feasible. However, to fully realise the potential of cfDNA analysis for children with brain tumours larger prospective studies incorporating serial CSF sampling are required.

Chemokine clouding and liver cancer heterogeneity: Does it impact clinical outcomes?

Tumor heterogeneity is a predominant feature of hepatocellular carcinoma (HCC) that plays a crucial role in chemoresistance and limits the efficacy of available chemo/immunotherapy regimens. Thus, a better understanding regarding the molecular determinants of tumor heterogeneity will help in developing newer strategies for effective HCC management. Chemokines, a sub-family of cytokines are one of the key molecular determinants of tumor heterogeneity in HCC and are involved in cell survival, growth, migration, and angiogenesis. Herein, we provide a panoramic insight into the role of chemokines in HCC heterogeneity at genetic, epigenetic, metabolic, immune cell composition, and tumor microenvironment levels and its impact on clinical outcomes. Interestingly, our in-silico analysis data showed that expression of chemokine receptors impacts infiltration of various immune cell populations into the liver tumor and leads to heterogeneity. Thus, it is evident that aberrant chemokines clouding impacts HCC tumor heterogeneity and understanding this phenomenon in depth could be harnessed for the development of personalized medicine strategies in future.

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.

The lncRNA KIF9-AS1 Accelerates Hepatocellular Carcinoma Growth by Recruiting DNMT1 to Promote RAI2 DNA Methylation

Background

Hepatocellular carcinoma (HCC) is a very common malignant tumor. Long noncoding RNAs (lncRNAs) enable discoveries of new therapeutic tumor targets. We aimed to study the role and potential regulatory mechanisms of the lncRNA KIF9-AS1 in HCC.

Methods

CCK-8, scratch assay, and flow cytometry were used to detect cell proliferation, migration, and apoptosis, respectively. Bax, Bcl-2, ERK, and pERK expression were measured by western blotting. StarBase predicted KIF9-AS1 expression in HCC and paracancerous tissues. RPISeq predicted the interaction score of KIF9-AS1 and DNMT1, and MethyPrimer revealed the CpG island distribution in the RAI2 promoter. MSP was performed to measure RAI2 methylation. RIP and ChIP were performed to examine lncRNA KIF9-AS1, DNMT1, and RAI2 interactions. Finally, the effect of KIF9-AS1 knockdown on HCC was verified with nude mice.

Results

We found that KIF9-AS1 expression was increased in HCC tissues. KIF9-AS1 knockdown inhibited the proliferation and migration, and facilitated the apoptosis of HCC cells. lncRNA KIF9-AS1-mediated RAI2 expression led to DNMT1 recruitment and regulated RAI2 DNA methylation. RAI2 overexpression inhibited the proliferation and migration and promoted the apoptosis of HCC cells. KIF9-AS1 knockdown inhibited subcutaneous tumor formation in vivo.

Conclusion

This study shows that KIF9-AS1 accelerates HCC growth by inducing DNMT1 promotion of RAI2 DNA methylation.

Metabolomics-based classification reveals subtypes of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death, and the prognosis varies due to its high heterogeneity, systematic evaluation of HCC is mainly based on genomic and transcriptomic features, metabolomics-based classification has yet to be reported. Here we performed RNA-seq on 50 paired samples and metabolomics analysis on 72 paired samples of both normal and tumor tissues from HCC patients. Through unsupervised hierarchical cluster analysis with train and test data sets, metabolic and gene expression signatures were identified. We found that most fluxes related to glutamate are attenuated, except for the glutamate-proline pathway. Three subgroups were identified with distinct survival, clinical observations, and metabolic/gene signatures. S1 is characterized by a relatively poor prognosis, a low concentration of the degradation products of phosphatidylcholine and phosphatidylethanolamine, an enrichment of specific genes related to focal adhesion, and an upregulation of genes on chromosome 6q27. Beyond commonly downregulated metabolites, S2 tumors are largely characterized by few alterations in metabolites and genes, as well as low incidence of mutations/loss of heterozygosity, the metabolite signature of this group consists of hexoses and their phosphates, and the prognosis is the best, with a 5-year survival rate of greater than 80%. S3 is characterized by the worst survival (an approximately 20% 5-year survival rate), unsaturated fatty acid metabolites, an upregulation of specific genes involved in metastasis, and an upregulation of genes on chromosome 1q21. The metabolite-based classifications are more stable and reproducible, with each subgroup characterized by a distinct molecular signature and disease prognosis.

Clinical features and prognostic factors in patients with microvascular infiltration of hepatocellular carcinoma: Development and validation of a nomogram and risk stratification based on the SEER database

Background

The goal is to establish and validate an innovative prognostic risk stratification and nomogram in patients of hepatocellular carcinoma (HCC) with microvascular invasion (MVI) for predicting the cancer-specific survival (CSS).

Methods

1487 qualified patients were selected from the Surveillance, Epidemiology and End Results (SEER) database and randomly assigned to the training cohort and validation cohort in a ratio of 7:3. Concordance index (C-index), area under curve (AUC) and calibration plots were adopted to evaluate the discrimination and calibration of the nomogram. Decision curve analysis (DCA) was used to quantify the net benefit of the nomogram at different threshold probabilities and compare it to the American Joint Committee on Cancer (AJCC) tumor staging system. C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to evaluate the improvement of the new model over the AJCC tumor staging system. The new risk stratifications based on the nomogram and the AJCC tumor staging system were compared.

Results

Eight prognostic factors were used to construct the nomogram for HCC patients with MVI. The C-index for the training and validation cohorts was 0.785 and 0.776 respectively. The AUC values were higher than 0.7 both in the training cohort and validation cohort. The calibration plots showed good consistency between the actual observation and the nomogram prediction. The IDI values of 1-, 3-, 5-year CSS in the training cohort were 0.17, 0.16, 0.15, and in the validation cohort were 0.17, 0.17, 0.17 (P<0.05). The NRI values of the training cohort were 0.75 at 1-year, 0.68 at 3-year and 0.67 at 5-year. The DCA curves indicated that the new model more accurately predicted 1-year, 3-year, and 5-year CSS in both training and validation cohort, because it added more net benefit than the AJCC staging system. Furthermore, the risk stratification system showed the CSS in different groups had a good regional division.

Conclusions

A comprehensive risk stratification system and nomogram were established to forecast CSS for patients of HCC with MVI.

The clonal expression genes associated with poor prognosis of liver cancer

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