Discovery of a Carbamoyl Phosphate Synthetase 1-Deficient HCC Subtype With Therapeutic Potential Through Integrative Genomic and Experimental Analysis

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Loss of lncRNA LINC01056 leads to sorafenib resistance in HCC

BACKGROUND AND AIMS

Sorafenib is a major nonsurgical option for patients with advanced hepatocellular carcinoma (HCC); however, its clinical efficacy is largely undermined by the acquisition of resistance. The aim of this study was to identify the key lncRNA involved in the regulation of the sorafenib response in HCC.

MATERIALS AND METHODS

A clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) single-guide RNA (sgRNA) synergistic activation mediator (SAM)-pooled lncRNA library was applied to screen for the key lncRNA regulated by sorafenib treatment. The role of the identified lncRNA in mediating the sorafenib response in HCC was examined in vitro and in vivo. The underlying mechanism was delineated by proteomic analysis. The clinical significance of the expression of the identified lncRNA was evaluated by multiplex immunostaining on a human HCC microtissue array.

RESULTS

CRISPR/Cas9 lncRNA library screening revealed that Linc01056 was among the most downregulated lncRNAs in sorafenib-resistant HCC cells. Knockdown of Linc01056 reduced the sensitivity of HCC cells to sorafenib, suppressing apoptosis in vitro and promoting tumour growth in mice in vivo. Proteomic analysis revealed that Linc01056 knockdown in sorafenib-treated HCC cells induced genes related to fatty acid oxidation (FAO) while repressing glycolysis-associated genes, leading to a metabolic switch favouring higher intracellular energy production. FAO inhibition in HCC cells with Linc01056 knockdown significantly restored sensitivity to sorafenib. Mechanistically, we determined that PPARα is the critical molecule governing the metabolic switch upon Linc01056 knockdown in HCC cells and indeed, PPARα inhibition restored the sorafenib response in HCC cells in vitro and HCC tumours in vivo. Clinically, Linc01056 expression predicted optimal overall and progression-free survival outcomes in HCC patients and predicted a better sorafenib response. Linc01056 expression indicated a low FAO level in HCC.

CONCLUSION

Our study identified Linc01056 as a critical epigenetic regulator and potential therapeutic target in the regulation of the sorafenib response in HCC.

Lipid Metabolism as a Potential Target of Liver Cancer

Hepatocellular carcinoma (HCC) stands as a severe malignant tumor with a profound impact on overall health, often accompanied by an unfavorable prognosis. Despite some advancements in the diagnosis and treatment of this disease, improving the prognosis of HCC remains a formidable challenge. It is noteworthy that lipid metabolism plays a pivotal role in the onset, development, and progression of tumor cells. Existing research indicates the potential application of targeting lipid metabolism in the treatment of HCC. This review aims to thoroughly explore the alterations in lipid metabolism in HCC, offering a detailed account of the potential advantages associated with innovative therapeutic strategies targeting lipid metabolism. Targeting lipid metabolism holds promise for potentially enhancing the prognosis of HCC.

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.

Deficiency in SLC25A15, a hypoxia-responsive gene, promotes hepatocellular carcinoma by reprogramming glutamine metabolism

BACKGROUND & AIMS

The role of solute carrier family 25 member 15 (SLC25A15), a critical component of the urea cycle, in hepatocellular carcinoma (HCC) progression remains poorly understood. This study investigated the impact of SLC25A15 on HCC progression and its mechanisms.

METHODS

We systematically investigated the function of SLC25A15 in HCC progression using large-scale data mining and cell, animal, and organoid models. Furthermore, we analyzed its involvement in reprogramming glutamine metabolism.

RESULTS

SLC25A15 expression was significantly decreased in HCC tissues, and patients with low SLC25A15 levels had a poorer prognosis. Hypoxia-exposed HCC cells or tissues had lower SLC25A15 expression. A positive correlation between HNF4A, a transcription factor suppressed by hypoxia, and SLC25A15 was observed in both HCC tissues and cells. Modulating HNF4A levels altered SLC25A15 mRNA levels. SLC25A15 upregulated SLC1A5, increasing glutamine uptake. The reactive metabolic pathway of glutamine was increased in SLC25A15-deficient HCC cells, providing energy for HCC progression through additional lipid synthesis. Ammonia accumulation due to low SLC25A15 levels suppressed the expression of OGDHL (oxoglutarate dehydrogenase L), a switch gene that mediates SLC25A15 deficiency-induced reprogramming of glutamine metabolism. SLC25A15-deficient HCC cells were more susceptible to glutamine deprivation and glutaminase inhibitors. Intervening in glutamine metabolism increased SLC25A15-deficient HCC cells' response to anti-PD-L1 treatment.

CONCLUSION

SLC25A15 is hypoxia-responsive in HCC, and low SLC25A15 levels result in glutamine reprogramming through SLC1A5 and OGDHL regulation, promoting HCC progression and regulating cell sensitivity to anti-PD-L1. Interrupting the glutamine-derived energy supply is a potential therapeutic strategy for treating SLC25A15-deficient HCC.

IMPACT AND IMPLICATIONS

We first demonstrated the tumor suppressor role of solute carrier family 25 member 15 (SLC25A15) in hepatocellular carcinoma (HCC) and showed that its deficiency leads to reprogramming of glutamine metabolism to promote HCC development. SLC25A15 can serve as a potential biomarker to guide the development of precision therapeutic strategies aimed at targeting glutamine deprivation. Furthermore, we highlight that the use of an inhibitor of glutamine utilization can enhance the sensitivity of low SLC25A15 HCC to anti-PD-L1 therapy.

Endoplasmic Reticulum Stress and Metabolism in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, accounting for 85% to 90% of all liver cancer cases. It is a hepatocyte-derived primary tumor, causing 550,000 deaths per year, ranking it as one of the most common cancers worldwide. The liver is a highly metabolic organ with multiple functions, including digestion, detoxification, breakdown of fats, and production of bile and cholesterol, in addition to storage of vitamins, glycogen, and minerals, and synthesizing plasma proteins and clotting factors. Due to these fundamental and diverse functions, the malignant transformation of hepatic cells can have a severe impact on the liver's metabolism. Furthermore, tumorigenesis is often accompanied by activation of the endoplasmic reticulum (ER) stress pathways, which are known to be highly intertwined with several metabolic pathways. Because HCC is characterized by changes in the metabolome and by an aberrant activation of the ER stress pathways, the aim of this review was to summarize the current knowledge that links ER stress and metabolism in HCC, thereby focusing on potential therapeutic targets.

Non-alcoholic fatty liver disease and diabetes mellitus as growing aetiologies of hepatocellular carcinoma

Obesity-related complications such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D) are well-established risk factors for the development of hepatocellular carcinoma (HCC). This review provides insights into the molecular mechanisms that underlie the role of steatosis, hyperinsulinemia and hepatic inflammation in HCC development and progression. We focus on recent findings linking intracellular pathways and transcription factors that can trigger the reprogramming of hepatic cells. In addition, we highlight the role of enzymes in dysregulated metabolic activity and consequent dysfunctional signalling. Finally, we discuss the potential uses and challenges of novel therapeutic strategies to prevent and treat NAFLD/T2D-associated HCC.

IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer-related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)-assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC.

Underexpression of Carbamoyl Phosphate Synthetase I as Independent Unfavorable Prognostic Factor in Intrahepatic Cholangiocarcinoma: A Potential Theranostic Biomarker

Intrahepatic cholangiocarcinoma (IHCC) is the second most common malignant neoplasm of the liver. In spite of the increasing incidence worldwide, it is relatively rare in Western countries. IHCC is relatively common in Eastern and Southeastern Asia. Patients with IHCC are usually diagnosed at an advanced stage, therefore, the clinical outcome is dismal. Dysregulation of urea cycle metabolic enzyme expression is found in different types of cancers. Nevertheless, a comprehensive evaluation of genes related to the urea cycle (i.e., GO:0000050) has not been conducted in IHCC. By performing a comparative analysis of gene expression profiles, we specifically examined genes associated with the urea cycle (GO:0000050) in a publicly accessible transcriptomic dataset (GSE26566). Interestingly, CPS1 was identified as the second most prominently down-regulated gene in this context. Tumor tissues of 182 IHCC patients who underwent curative-intent hepatectomy were enrolled. The expression level of CPS1 protein in our IHCC cohort was assessed by immunohistochemical study. Subsequent to that, statistical analyses were carried out to examine the expression of CPS1 in relation to various clinicopathological factors, as well as to assess its impact on survival outcomes. We noticed that lower immunoreactivity of CPS1 in IHCC was associated with tumor progression (pT status) with statistical significance (p = 0.003). CPS1 underexpression was not only negatively correlated to overall survival (OS), disease-free survival (DFS), local recurrence-free survival (LRFS) and metastasis-free survival (MeFS) in univariate analysis but also an independent prognosticator to forecast poorer clinical outcome for all prognostic indices (OS, DFS, LRFS and MeFs) in patients with IHCC (all p ≤ 0.001). These results support that CPS1 may play a crucial role in IHCC oncogenesis and tumor progression and serve as a novel prognostic factor and a potential diagnostic and theranostic biomarker.

Deficiency of Carbamoyl Phosphate Synthetase 1 Engenders Radioresistance in Hepatocellular Carcinoma via Deubiquitinating c-Myc

PURPOSE

Tumor radiation resistance is the main obstacle to effective radiation therapy for patients with hepatocellular carcinoma (HCC). We identified the role of urea cycle key enzyme carbamoyl phosphate synthetase 1 (CPS1) in radioresistance of HCC and explored its mechanism, aiming to provide a novel radiosensitization strategy for the CPS1-deficiency HCC subtype.

METHODS AND MATERIALS

The expression of CPS1 was measured by western blot and immunohistochemistry. Cell growth assay, EdU assay, cell apoptosis assay, cell cycle assay, clone formation assay, and subcutaneous tumor assay were performed to explore the relationship between CPS1 and radioresistance of HCC cells. Lipid metabonomic analysis was used for investigating the effects of CPS1 on lipid synthesis of HCC cells. RNA sequencing and coimmunoprecipitation assay were carried out to reveal the mechanism of CPS1 participating in the regulation of HCC radiation therapy resistance. Furthermore, 10074-G5, the specific inhibitor of c-Myc, was administered to HCC cells to investigate the role of c-Myc in CPS1-deficiency HCC cells.

RESULTS

We found that urea cycle key enzyme CPS1 was frequently lower in human HCC samples and positively associated with the patient's prognosis. Functionally, the present study proved that CPS1 depletion could accelerate the development of HCC and induce radiation resistance of HCC in vitro and in vivo, and deficiency of CPS1 promoted the synthesis of some lipid molecules. Regarding the mechanism, we uncovered that inhibition of CPS1 upregulated CyclinA2 and CyclinD1 by stabilizing oncoprotein c-Myc at the posttranscriptional level and generated radioresistance of HCC cells. Moreover, inactivation of c-Myc using 10074-G5, a specific c-Myc inhibitor, could partially attenuate the proliferation and radioresistance induced by depletion of CPS1.

CONCLUSIONS

Our results recapitulated that silencing CPS1 could promote HCC progression and radioresistance via c-Myc stability mediated by the ubiquitin-proteasome system, suggesting that targeting c-Myc in CPS1-deficiency HCC subtype may be a valuable radiosensitization strategy in the treatment of HCC.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma

Introduction

Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC.

Methods

Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC. The proteomics (n=159) and cell-line transcriptome data (n=1019) were collected to screen the implication of sensitive drugs. A novel multi-step machine-learning framework was then performed to construct a classification predictor, including recognizing stable reversed gene pairs, establishing a robust prediction model, and validating the robustness of the predictor in five independent cohorts (n=900).

Results

Two heterogeneous mutation signature clusters were identified, and a high-risk prognosis cluster was recognized for further analysis. Notably, mutation signature cluster 1 (MSC1) was featured by activated anti-tumor immune and metabolism dysfunctional states, higher genomic instability (high TMB, SNV neoantigen, indel neoantigens, and total neoantigens), and a dismal prognosis. Notably, MSC performed as an independent risk factor than clinical traits (eg, stage, vascular invasion). Additionally, afatinib and canertinib were recognized which might have potential therapeutic implications in MSC1, and the targets of these drugs presented a higher expression in both gene and protein levels in HCC.

Discussion

Our studies may provide a promising platform for improving prognosis and tailoring therapy in HCC.

A High-Throughput Sequencing Data-Based Classifier Reveals the Metabolic Heterogeneity of Hepatocellular Carcinoma

Metabolic heterogeneity plays a key role in poor outcomes in malignant tumors, but its role in hepatocellular carcinoma (HCC) remains largely unknown. In the present study, we aim to disentangle the metabolic heterogeneity features of HCC by developing a classification system based on metabolism pathway activities in high-throughput sequencing datasets. As a result, HCC samples were classified into two distinct clusters: cluster 1 showed high levels of glycolysis and pentose phosphate pathway activity, while cluster 2 exhibited high fatty acid oxidation and glutaminolysis status. This metabolic reprogramming-based classifier was found to be highly correlated with several clinical variables, including overall survival, prognosis, TNM stage, and 𝛼-fetoprotein (AFP) expression. Of note, activated oncogenic pathways, a higher TP53 mutation rate, and increased stemness were also observed in cluster 1, indicating a causal relationship between metabolic reprogramming and carcinogenesis. Subsequently, distinct metabolism-targeted therapeutic strategies were proven in human HCC cell lines, which exhibit the same metabolic properties as corresponding patient samples based on this classification system. Furthermore, the metabolic patterns and effects of different types of cells in the tumor immune microenvironment were explored by referring to both bulk and single-cell data. It was found that malignant cells had the highest overall metabolic activities, which may impair the anti-tumor capacity of CD8+ T cells through metabolic competition, and this provided a potential explanation for why immunosuppressive cells had higher overall metabolic activities than those with anti-tumor functions. Collectively, this study established an HCC classification system based on the gene expression of energy metabolism pathways. Its prognostic and therapeutic value may provide novel insights into personalized clinical practice in patients with metabolic heterogeneity.

Lactylome analysis suggests lactylation-dependent mechanisms of metabolic adaptation in hepatocellular carcinoma

Enhanced glycolysis and accumulation of lactate is a common feature in various types of cancer. Intracellular lactate drives a recently described type of posttranslational modification, lysine lactylation (Kla), on core histones. However, the impact of lactylation on biological processes of tumour cells remains largely unknown. Here we show a global lactylome profiling on a prospectively collected hepatitis B virus-related hepatocellular carcinoma (HCC) cohort. Integrative lactylome and proteome analysis of the tumours and adjacent livers identifies 9,275 Kla sites, with 9,256 sites on non-histone proteins, indicating that Kla is a prevalent modification beyond histone proteins and transcriptional regulation. Notably, Kla preferentially affects enzymes involved in metabolic pathways, including the tricarboxylic acid cycle, and carbohydrate, amino acid, fatty acid and nucleotide metabolism. We further verify that lactylation at K28 inhibits the function of adenylate kinase 2, facilitating the proliferation and metastasis of HCC cells. Our study therefore reveals that Kla plays an important role in regulating cellular metabolism and may contribute to HCC progression.

Glutamine synthetase limits β-catenin-mutated liver cancer growth by maintaining nitrogen homeostasis and suppressing mTORC1

Glutamine synthetase (GS) catalyzes de novo synthesis of glutamine that facilitates cancer cell growth. In the liver, GS functions next to the urea cycle to remove ammonia waste. As a dysregulated urea cycle is implicated in cancer development, the impact of GS's ammonia clearance function has not been explored in cancer. Here, we show that oncogenic activation of β-catenin (encoded by CTNNB1) led to a decreased urea cycle and elevated ammonia waste burden. While β-catenin induced the expression of GS, which is thought to be cancer promoting, surprisingly, genetic ablation of hepatic GS accelerated the onset of liver tumors in several mouse models that involved β-catenin activation. Mechanistically, GS ablation exacerbated hyperammonemia and facilitated the production of glutamate-derived nonessential amino acids, which subsequently stimulated mechanistic target of rapamycin complex 1 (mTORC1). Pharmacological and genetic inhibition of mTORC1 and glutamic transaminases suppressed tumorigenesis facilitated by GS ablation. While patients with hepatocellular carcinoma, especially those with CTNNB1 mutations, have an overall defective urea cycle and increased expression of GS, there exists a subset of patients with low GS expression that is associated with mTORC1 hyperactivation. Therefore, GS-mediated ammonia clearance serves as a tumor-suppressing mechanism in livers that harbor β-catenin activation mutations and a compromised urea cycle.

The pivotal application of patient-derived organoid biobanks for personalized treatment of gastrointestinal cancers

Gastrointestinal cancers (GICs) occupy more than 30% of the cancer-related incidence and mortality around the world. Despite advances in the treatment strategies, the long-term overall survival has not been improved for patients with GICs. Recently, the novel patient-derived organoid (PDO) culture technology has become a powerful tool for GICs in a manner that recapitulates the morphology, pathology, genetic, phenotypic, and behavior traits of the original tumors. Excitingly, a number of evidences suggest that the versatile technology has great potential for personalized treatment, suppling the clinical application of molecularly guided personalized treatment. In the paper, we summarize the literature on the topics of establishing organoid biobanks of PDOs, and their application in the personalized treatment allowing for radiotherapy, chemotherapy, targeted therapy, and immunotherapy selection for GICs. Despite the limitations of current organoid models, high-throughput drug screening of GIC PDO combined with next-generation sequencing technology represents a novel and pivotal preclinical model for precision medicine of tumors and has a great value in promoting the transformation from basic cancer research to clinical application.

Identification and validation in a novel quantification system of the glutamine metabolism patterns for the prediction of prognosis and therapy response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) has one of the highest mortality rates worldwide. Abnormal glutamine metabolism (GM) has been reported to be involved in HCC progression. The current study sought to examine the predictive value of GM in HCC patient's prognosis and therapy response.

METHODS

The RNA-sequencing data and clinical information of HCC samples were obtained from The Cancer Genome Atlas (TCGA) database (N=377) and Gene Expression Omnibus (GEO) database (N=242). By analyzing a data set from TCGA, we showed that the GM landscape of HCC patients was developed based on the non-negative matrix factorization (NMF) algorithm. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analyses were used to construct a risk model. The accuracy of the model, which was based on the GM-related genes (GMRGs), was verified by Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves. We also verified the reliability of the model based on GEO data. Finally, the immune infiltration analysis, pathway enrichment analysis, and treatment response prediction results were compared to each other in the 2 risk groups.

RESULTS

In our study, the HCC samples were divided into 2 GM-related patterns; that is, C1 and C2. The multi-analysis revealed that the GM-related patterns were associated with the pathologic stage, T stages, N stages, histologic grade, and the tumor immune microenvironment (TIME). Next, the prognostic model containing 5 GMRGs (i.e., aldehyde dehydrogenase 5 family member A1, ASNSD1, carbamoyl-phosphate synthetase 1, GMPS, and PPAT) was constructed to calculate the risk score. The high-risk group of HCC patients had significantly worse overall survival (OS) than the low-risk group in both datasets (P<0.001). Multivariate Cox regression uncover the riskScores may serve as an independent prognostic marker for HCC patients [TCGA: hazard ratio (HR) =2.909 (1.940-4.362), P<0.001; GEO: HR =2.911 (1.753-5.848), P=0.043]. Finally, we found that the prognostic model was significantly correlated with the pathologic stage and TIME of the HCC patients in both databases. Moreover, the prognostic model may guide the immunotherapy, chemotherapy, and targeted drugs choice.

CONCLUSIONS

In summary, we developed a GM-related 5-gene risk-score model, which may be a useful tool for predicting prognosis and guiding the treatment of HCC patients.

Ornithine aminotransferase and carbamoyl phosphate synthetase 1 involved in ammonia metabolism serve as novel targets for early stages of gastric cancer

Objective

The sensitivity and specificity of current biomarkers for gastric cancer were insufficient. The aim of the present study was to screen novel biomarkers and determine the diagnostic values of ornithine aminotransferase (OAT) and carbamoyl phosphate synthetase 1 (CPS1) for detecting gastric cancer.

Methods

With stable isotope tags, we labelled an initial discovery group of four paired gastric cancer tissue samples and identified with LC‐ESI‐MS/MS. A validation group of 159 gastric cancer samples and 30 healthy controls were used to validate the candidate targets. GSEA was used to explore the pathways activated in gastric cancer.

Results

Four hundred and thirty one proteins were found differentially expressed in gastric cancer tissues. Of these proteins, OAT and CPS1 were found over‐expressed in gastric cancer patients, with sensitivity of 70.4% (95% CI: 63.3%–77.6%) and specificity of 80.5% (95% CI: 74.3%–86.7%) for ornithine aminotransferase, and with sensitivity of 68.6% (95% CI: 61.3%–75.8%) and specificity of 73% (95% CI: 66%–79.9%) for carbamoyl phosphate synthetase 1. The co‐expression of OAT and CPS1 in gastric cancer tissues has a sensitivity of 81% (95% CI: 73.2%–88.8%) and specificity of 89% (95% CI: 83%–95%). Furthermore, both OAT and CPS1 were overexpressed in patients with local invasion T3 and T4 stages than those in patients with T1 and T2 stages. The co‐expression of OAT and CPS1 was strongly correlated with histological grade I 68% (95% CI: 58.7%–77.3%) and TNM stage I/II 52% (95% CI: 42%–62%). The areas under ROC curves were up to 0.758 for the co‐expression of OAT and CPS1 in gastric cancer. GSEA results showed that two gene sets and 30 gene sets were activated in OAT high‐ and CPS1 high‐expression patients with gastric cancer, respectively.

Conclusions

The present findings indicated a tight correlation between the co‐expression of OAT and CPS1 and the histological grade, local invasion, and TNM stages of gastric cancer. Therefore, OAT and CPS1 might be predictors for gastric cancer invasion and potential targets for anticancer drug design for gastric cancer.

Identification and Validation of Genomic Subtypes and a Prognostic Model Based on Antigen-Presenting Cells and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

Currently, the prognosis of hepatocellular carcinoma (HCC) is poor, and there is a lack of effective targeted therapy. As key mediators of the immune response, the prognostic value of antigen-presenting cells (APCs) in HCC still remains unclear. In this study, we aimed to identify APC-related genomic subtypes and develop a novel prognostic model in HCC. Our results indicated that overall survival (OS) and the level of immune infiltration significantly differed between different APC clusters. By analyzing the gene expression profile between APC clusters, APC-related genomic subtypes were identified. There was a significant difference in OS and tumor microenvironment infiltration in HCC patients with different genomic subtypes. With the aid of genomic subtypes, significantly differentially expressed genes were screened to generate a novel prognostic model. The risk score of the model had a significant positive correlation with APCs and was associated with immune checkpoint expressions. Through the clinical cohort collected from the First Affiliated Hospital of Wenzhou Medical University, the prognostic value of the risk score was further validated. Moreover, after the risk score and clinical characteristics were combined, a nomogram was constructed to evaluate the prognosis for HCC patients. In conclusion, we mainly identified the APC-related genomic subtypes and generated a novel prognostic model to improve the prognostic prediction and targeted therapy for HCC patients.

Hepatocyte-Specific Knock-Out of Nfib Aggravates Hepatocellular Tumorigenesis via Enhancing Urea Cycle

Nuclear Factor I B (NFIB) has been reported to promote tumor growth, metastasis, and liver regeneration, but its mechanism in liver cancer is not fully elucidated. The present study aims to reveal the role of NFIB in hepatocellular carcinogenesis. In our study, we constructed hepatocyte-specific NFIB gene knockout mice with CRISPR/Cas9 technology (Nfib^-/-; Alb-cre), and induced liver cancer mouse model by intraperitoneal injection of DEN/CCl₄. First, we found that Nfib^-/- mice developed more tumor nodules and had heavier livers than wild-type mice. H&E staining indicated that the liver histological severity of Nfib^-/- group was more serious than that of WT group. Then we found that the differentially expressed genes in the tumor tissue between Nfib^-/- mice and wild type mice were enriched in urea cycle. Furthermore, ASS1 and CPS1, the core enzymes of the urea cycle, were significantly upregulated in Nfib^-/- tumors. Subsequently, we validated that the expression of ASS1 and CPS1 increased after knockdown of NFIB by lentivirus in normal hepatocytes and also promoted cell proliferation in vitro. In addition, ChIP assay confirmed that NFIB can bind with promoter region of both ASS1 and CPS1 gene. Our study reveals for the first time that hepatocyte-specific knock-out of Nfib aggravates hepatocellular tumor development by enhancing the urea cycle.

DNAJC24 is a potential therapeutic target in hepatocellular carcinoma through affecting ammonia metabolism

Evolutionarily conserved heat shock proteins are involved in the heat shock response of cells in response to changes in the external environment. In normal tissues, heat shock proteins can help cells survive in a rapidly changing environment. Likewise, in malignant tumors heat shock proteins may help tumor cells cope with external stresses as well as the stress of treatment. In this way they become accomplices of malignant tumors. Here we demonstrated for the first time that high expression of DNAJC24 (a heat shock protein) shortens survival in patients with HCC by immunohistochemical staining of 167 paired hepatocellular carcinomas and paraneoplastic tissues as well as data from public databases. In vitro experiments demonstrated that stimuli such as hypoxia, starvation and heat could upregulate DNAJC24 expression in HCC cells through transcriptional regulation of HSF2, and high expression of DNAJC24 in HCC cells could promote the proliferation and motility of HCC cells. In addition, we also verified that targeting DNAJC24 under normal culture conditions can affect the proliferation and autophagy of HCC cells by interfering with ammonia metabolism, thereby inhibiting the malignant progression of HCC. Overall, we suggested that DNAJC24 may become a new target for the treatment of HCC.

Metabolic Reprogramming and Its Relationship to Survival in Hepatocellular Carcinoma

Hepatocarcinogenesis is frequently accompanied by substantial metabolic reprogramming to maximize the growth and proliferation of cancer cells. In this study, we carried out a comprehensive study of metabolomics and lipidomics profiles combined with gene expression analysis to characterize the metabolic reprogramming in hepatocellular carcinoma (HCC). Compared with adjacent noncancerous liver tissue, the enhanced aerobic glycolysis and de novo lipogenesis (DNL) and the repressed urea cycle were underscored in HCC tissue. Furthermore, multiscale embedded correlation analysis was performed to construct differential correlation networks and reveal pathologically relevant molecule modules. The obtained hub nodes were further screened according to the maximum biochemical diversity and the least intraclass correlation. Finally, a panel of ornithine, FFA 18:1, PC O-32:1 and TG (18:1_17:1_18:2) was generated to achieve the prognostic risk stratification of HCC patients (p < 0.001 by log-rank test). Altogether, our findings suggest that the metabolic dysfunctions of HCC detected via metabolomics and lipidomics would contribute to a better understanding of clinical relevance of hepatic metabolic reprogramming and provide potential sources for the identification of therapeutic targets and the discovery of biomarkers.

Implications of Stemness Features in 1059 Hepatocellular Carcinoma Patients from Five Cohorts: Prognosis, Treatment Response, and Identification of Potential Compounds

Simple Summary

Cancer stemness has been reported to drive hepatocellular carcinoma (HCC) tumorigenesis and treatment resistance. However, comprehensive interpretations of transcriptomic stemness features in HCC patients have not been conducted in multiple cohorts. Our aim was to interpret clinical and therapeutic implications of transcriptional stemness features and explore potential compounds for HCC treatment. We found that transcriptional stemness indexes (mRNAsi) were independently associated with worse HCC prognosis. The HCC stemness risk model (HSRM) developed in this study significantly predicted prognosis and treatment response in various HCC cohorts. Analysis of two stemness subtypes suggested several liver-specific metabolic pathways, and mutations of TP53 and RB1 were associated with HCC transcriptional stemness. Moreover, we also identified potential compounds that target HCC transcriptional stemness. Our findings comprehensively characterized transcriptional stemness as a risk factor in HCC progression and treatment.

Abstract

Cancer stemness has been reported to drive hepatocellular carcinoma (HCC) tumorigenesis and treatment resistance. In this study, five HCC cohorts with 1059 patients were collected to calculate transcriptional stemness indexes (mRNAsi) by the one-class logistic regression machine learning algorithm. In the TCGA-LIHC cohort, we found mRNAsi was an independent prognostic factor, and 626 mRNAsi-related genes were identified by Spearman correlation analysis. The HCC stemness risk model (HSRM) was trained in the TCGA-LIHC cohort and significantly discriminated overall survival in four independent cohorts. HSRM was also significantly associated with transarterial chemoembolization treatment response and rapid tumor growth in HCC patients. Consensus clustering was conducted based on mRNAsi-related genes to divide 1059 patients into two stemness subtypes. On gene set variation analysis, samples of subtype I were found enriched with pathways such as DNA replication and cell cycle, while several liver-specific metabolic pathways were inhibited in these samples. Somatic mutation analysis revealed more frequent mutations of TP53 and RB1 in the subtype I samples. In silico analysis suggested topoisomerase, cyclin-dependent kinase, and histone deacetylase as potential targets to inhibit HCC stemness. In vitro assay showed two predicted compounds, Aminopurvalanol-a and NCH-51, effectively suppressed oncosphere formation and impaired viability of HCC cell lines, which may shed new light on HCC treatment.

Organoids as research models for hepatocellular carcinoma

Organoid culture is an emerging research tool that has proved tremendously useful in a multitude of aspects, one of which is cancer research. They largely overcome the limitations of previous cancer models by their faithful recapitulation of the in vivo biology, while still remaining amenable to perturbations. Using a cocktail of biologicals that mimic the stem cell niche signaling, hepatocellular carcinoma (HCC) organoids could be generated from tissue samples of both human and murine origin. Existing reports show that HCC organoids retain key characteristics of their parental tumor tissue, including the histological architecture, genomic landscape, expression profile and intra-tumor heterogeneity. There is ongoing effort to establish living biobanks of patient-derived cancer organoids, annotated with multi-omics data and clinical data, and they can be particularly valuable in stratification of HCC subtypes, pre-clinical drug discovery and personalized medicine. In the future, efforts in the standardization of procedures and nomenclature, refinement of protocols, as well as engineering of the culture systems will enable scientists to unleash the full potential of organoid technology.