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Xiao MY, Pei WJ, Li S, Li FF, Xie P, Luo HT, Hyun Yoo H, Piao XL. Gypenoside L inhibits hepatocellular carcinoma by targeting the SREBP2-HMGCS1 axis and enhancing immune response. Bioorg Chem 2024; 150:107539. [PMID: 38861912 DOI: 10.1016/j.bioorg.2024.107539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/30/2024] [Accepted: 06/06/2024] [Indexed: 06/13/2024]
Abstract
Hepatocellular carcinoma (HCC) is a malignant tumor that occurs in the liver, with a high degree of malignancy and relatively poor prognosis. Gypenoside L has inhibitory effects on liver cancer cells. However, its mechanism of action is still unclear. This study aims to investigate the inhibitory effects of gypenoside L on HCC in vitro and in vivo, and explore its potential mechanisms. The results showed that gypenoside L reduced the cholesterol and triglyceride content in HepG2 and Huh-7 cells, inhibited cell proliferation, invasion and metastasis, arrested cell cycle at G0/G1 phase, promoted cell apoptosis. Mechanistically, it targeted the transcription factor SREPB2 to inhibit the expression of HMGCS1 protein and inhibited the downstream proteins HMGCR and MVK, thereby regulating the mevalonate (MVA) pathway. Overexpression HMGCS1 led to significant alterations in the cholesterol metabolism pathway of HCC, which mediated HCC cell proliferation and conferred resistance to the therapeutic effect of gypenoside L. In vivo, gypenoside L effectively suppressed HCC growth in tumor-bearing mice by reducing cholesterol production, exhibiting favorable safety profiles and minimal toxic side effects. Gypenoside L modulated cholesterol homeostasis, enhanced expression of inflammatory factors by regulating MHC I pathway-related proteins to augment anticancer immune responses. Clinical samples from HCC patients also exhibited high expression levels of MVA pathway-related genes in tumor tissues. These findings highlight gypenoside L as a promising agent for targeting cholesterol metabolism in HCC while emphasizing the effectiveness of regulating the SREBP2-HMGCS1 axis as a therapeutic strategy.
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MESH Headings
- Humans
- Carcinoma, Hepatocellular/drug therapy
- Carcinoma, Hepatocellular/pathology
- Carcinoma, Hepatocellular/metabolism
- Gynostemma/chemistry
- Liver Neoplasms/drug therapy
- Liver Neoplasms/pathology
- Liver Neoplasms/metabolism
- Sterol Regulatory Element Binding Protein 2/metabolism
- Sterol Regulatory Element Binding Protein 2/antagonists & inhibitors
- Cell Proliferation/drug effects
- Animals
- Mice
- Dose-Response Relationship, Drug
- Molecular Structure
- Drug Screening Assays, Antitumor
- Apoptosis/drug effects
- Structure-Activity Relationship
- Antineoplastic Agents, Phytogenic/pharmacology
- Antineoplastic Agents, Phytogenic/chemistry
- Mice, Inbred BALB C
- Mice, Nude
- Liver Neoplasms, Experimental/drug therapy
- Liver Neoplasms, Experimental/pathology
- Liver Neoplasms, Experimental/metabolism
- Plant Extracts
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Affiliation(s)
- Man-Yu Xiao
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Wen-Jing Pei
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Si Li
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Fang-Fang Li
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Peng Xie
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Hao-Tian Luo
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Hye Hyun Yoo
- Pharmacomicrobiomics Research Center, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do 15588, Republic of Korea.
| | - Xiang-Lan Piao
- Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing 100081, China; School of Pharmacy, Minzu University of China, Beijing 100081, China.
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2
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Wang G, Zou X, Chen Q, Nong W, Miao W, Luo H, Qu S. The relationship and clinical significance of lactylation modification in digestive system tumors. Cancer Cell Int 2024; 24:246. [PMID: 39010066 PMCID: PMC11251390 DOI: 10.1186/s12935-024-03429-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 07/02/2024] [Indexed: 07/17/2024] Open
Abstract
Lactylation, an emerging post-translational modification, plays a pivotal role in the initiation and progression of digestive system tumors. This study presents a comprehensive review of lactylation in digestive system tumors, underscoring its critical involvement in tumor development and progression. By focusing on metabolic reprogramming, modulation of the tumor microenvironment, and the molecular mechanisms regulating tumor progression, the potential of targeting lactylation as a therapeutic strategy is highlighted. The research reveals that lactylation participates in gene expression regulation and cell signaling by affecting the post-translational states of histones and non-histone proteins, thereby influencing metabolic pathways and immune evasion mechanisms in tumor cells. Furthermore, this study assesses the feasibility of lactylation as a therapeutic target, providing insights for clinical treatment of gastrointestinal cancers. Future research should concentrate on elucidating the mechanisms of lactylation, developing efficient lactylation inhibitors, and validating their therapeutic efficacy in clinical trials, which could transform current cancer treatment and immunotherapy approaches. In summary, this review emphasizes the crucial role of lactylation in tumorigenesis and progression through a detailed analysis of its molecular mechanisms and clinical significance.
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Affiliation(s)
- Gang Wang
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China
| | - Xiaosu Zou
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China
| | - Qicong Chen
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China
| | - Wenqian Nong
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China
| | - Weiwei Miao
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China
| | - Honglin Luo
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China.
| | - Shenhong Qu
- Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, 530021, Guangxi, China.
- Department of Otolaryngology & Head and Neck, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, Guangxi, China.
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3
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Hu Y, Xing Y, Fan G, Xie H, Zhao Q, Liu L. L-arginine combination with 5-fluorouracil inhibit hepatocellular carcinoma cells through suppressing iNOS/NO/AKT-mediated glycolysis. Front Pharmacol 2024; 15:1391636. [PMID: 38841361 PMCID: PMC11150577 DOI: 10.3389/fphar.2024.1391636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/06/2024] [Indexed: 06/07/2024] Open
Abstract
L-arginine can produce nitric oxide (NO) under the action of inducible nitric oxide synthase (iNOS), while 5-fluorouracil (5-FU) can induce the increase of iNOS expression. The present study was to investigate the mechanism of L-arginine combined with 5-FU regulating glucose metabolism of hepatocellular carcinoma (HCC) through iNOS/NO/AKT pathway. The combination of L-arginine and 5-FU resulted in decreased cell survival and exhibited synergistic cytotoxic effects in HepG2 and SMMC7721 cells. Meanwhile, L-arginine increased 5-FU inhibitory effect on HepG2 and SMMC7721 cells by increasing NO production. Co-treatment with L-arginine and 5-FU resulted in a significant decrease in both G6PDH and LDH enzymatic activities, as well as reduced levels of ATP and LD compared to treatment with L-arginine or 5-FU alone. Moreover, the combination of L-arginine and 5-FU resulted in a decrease in the expression of GLUT1, PKM2, LDHA, p-PI3K and p-AKT. Furthermore, the combination demonstrated a synergistic effect in downregulating the expression of HIF-1α and β-catenin, which were further diminished upon the addition of shikonin, a specific inhibitor of PKM2. LY294002 treatment further reduced the expression of GLUT1, PKM2, and LDHA proteins induced by combined L-arginine and 5-FU treatment compared to the combined group. However, the reduction in p-PI3K, p-AKT, and GLUT1 expression caused by L-arginine and 5-FU combination was also reversed in HepG2 and SMMC7721 cells with iNOS knockdown, respectively. Additionally, the combination of L-arginine and 5-FU led to a greater reduction in the enzymatic activity of ALT, AST, G6PDH and LDH, as well as a significant reduction in hepatic index, AFP, AFP-L3, ATP and LD levels in a rat model of HCC. Moreover, the simultaneous administration of L-arginine and 5-FU significantly improved the gross morphology of the liver, reduced nuclear atypia, inhibited the proliferation of cancer cells, and decreased the expression levels of p-PI3K, p-AKT, GLUT1, PKM2, and LDHA, while iNOS expression was increased in the combination group. Taking together, L-arginine and 5-FU combination resulted in the inhibition of enzymes in aerobic glycolysis via the iNOS/NO/AKT pathway, which led to the suppression of glucose metabolism and downregulation of nuclear transcription factors, thereby impeding the proliferation of hepatocellular carcinoma cells.
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Affiliation(s)
- Yile Hu
- College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China
| | - Yihao Xing
- College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China
| | - Gaolu Fan
- Department of Pharmacy, Luoyang Third People’ Hospital, Luoyang, China
| | - Huaxia Xie
- College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China
| | - Qingzan Zhao
- School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Ling Liu
- College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China
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4
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Liu F, Liao Z, Zhang Z. MYC in liver cancer: mechanisms and targeted therapy opportunities. Oncogene 2023; 42:3303-3318. [PMID: 37833558 DOI: 10.1038/s41388-023-02861-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/28/2023] [Accepted: 10/03/2023] [Indexed: 10/15/2023]
Abstract
MYC, a major oncogenic transcription factor, regulates target genes involved in various pathways such as cell proliferation, metabolism and immune evasion, playing a critical role in the tumor initiation and development in multiple types of cancer. In liver cancer, MYC and its signaling pathways undergo significant changes, exerting a profound impact on liver cancer progression, including tumor proliferation, metastasis, dedifferentiation, metabolism, immune microenvironment, and resistance to comprehensive therapies. This makes MYC an appealing target, despite it being previously considered an undruggable protein. In this review, we discuss the role and mechanisms of MYC in liver physiology, chronic liver diseases, hepatocarcinogenesis, and liver cancer progression, providing a theoretical basis for targeting MYC as an ideal therapeutic target for liver cancer. We also summarize and prospect the strategies for targeting MYC, including direct and indirect approaches to abolish the oncogenic function of MYC in liver cancer.
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Affiliation(s)
- Furong Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education; NHC Key Laboratory of Organ Transplantation; Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, China
| | - Zhibin Liao
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education; NHC Key Laboratory of Organ Transplantation; Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, China
| | - Zhanguo Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Wuhan, Hubei, 430030, China.
- Key Laboratory of Organ Transplantation, Ministry of Education; NHC Key Laboratory of Organ Transplantation; Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, China.
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5
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Jin J, Zhao Q, Wei Z, Chen K, Su Y, Hu X, Peng X. Glycolysis-cholesterol metabolic axis in immuno-oncology microenvironment: emerging role in immune cells and immunosuppressive signaling. Cell Biosci 2023; 13:189. [PMID: 37828561 PMCID: PMC10571292 DOI: 10.1186/s13578-023-01138-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023] Open
Abstract
Cell proliferation and function require nutrients, energy, and biosynthesis activity to duplicate repertoires for each daughter. It is therefore not surprising that tumor microenvironment (TME) metabolic reprogramming primarily orchestrates the interaction between tumor and immune cells. Tumor metabolic reprogramming affords bioenergetic, signaling intermediates, and biosynthesis requirements for both malignant and immune cells. Different immune cell subsets are recruited into the TME, and these manifestations have distinct effects on tumor progression and therapeutic outcomes, especially the mutual contribution of glycolysis and cholesterol metabolism. In particularly, glycolysis-cholesterol metabolic axis interconnection plays a critical role in the TME modulation, and their changes in tumor metabolism appear to be a double-edged sword in regulating various immune cell responses and immunotherapy efficacy. Hence, we discussed the signature manifestation of the glycolysis-cholesterol metabolic axis and its pivotal role in tumor immune regulation. We also highlight how hypothetical combinations of immunotherapy and glycolysis/cholesterol-related metabolic interventions unleash the potential of anti-tumor immunotherapies, as well as developing more effective personalized treatment strategies.
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Affiliation(s)
- Jing Jin
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, People's Republic of China
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Qijie Zhao
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Zhigong Wei
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Keliang Chen
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Yonglin Su
- Department of Rehabilitation, Cancer Center, West China Hospital, Sichuan University, Sichuan, People's Republic of China.
| | - Xiaolin Hu
- Department of Nursing, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
| | - Xingchen Peng
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
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6
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Li Z, Jin C, Lu X, Zhang Y, Zhang Y, Wen J, Liu Y, Liu X, Li J. Studying the mechanism underlying lipid metabolism in osteosarcoma based on transcriptomic RNA sequencing and single-cell data. J Gene Med 2023:e3491. [PMID: 36847293 DOI: 10.1002/jgm.3491] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/03/2023] [Accepted: 02/16/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND We aimed to provide a new typing method for osteosarcoma (OS) based on single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the perspective of lipid metabolism and examine its potential mechanisms in the onset and progression of OS. METHODS Scores for six lipid metabolic pathways were calculated by single-sample gene set enrichment analysis (ssGSEA) based on a scRNA-seq dataset and three microarray expression profiles. Subsequently, cluster typing was conducted using unsupervised consistency clustering. Furthermore, single-cell clustering and dimensionality-reduction analyses identified cell subtypes. Finally, an analysis of cellular receptors was performed using CellphoneDB to identify cellular communication. RESULTS OS was classified into three subtypes based on lipid metabolic pathways. Among them, patients in clust3 showed poor prognoses, whereas those in clust1 and clust2 exhibited good prognoses. In addition, ssGSEA analysis showed that patients in clust3 had lower immune cell scores. Moreover, the Th17 cell differentiation pathway was significantly differentially enriched between clust2 and clust3, with lower enrichment scores for metabolic pathways in the former relative to clust1 and clust2. In total, 24 genes were upregulated between clust1 and clust2, whereas 20 were downregulated in clust3. These observations were validated by single-cell data analysis. Finally, through scRNA-seq data analysis, we identified nine ligand-receptor pairs particularly critical for communication between normal and malignant cells. CONCLUSIONS Three clusters were identified and the single-cell analysis revealed that malignant cells dominated lipid metabolism patterns in tumors, thereby influencing the tumor microenvironment.
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Affiliation(s)
- Zhe Li
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Chi Jin
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xinchang Lu
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yan Zhang
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhang
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jia Wen
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yongkui Liu
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaoting Liu
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jiazhen Li
- Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
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7
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Jung J, Park S, Jang Y, Lee SH, Jeong YS, Yim SY, Lee JS. Clinical Significance of Glycolytic Metabolic Activity in Hepatocellular Carcinoma. Cancers (Basel) 2022; 15:186. [PMID: 36612182 PMCID: PMC9818850 DOI: 10.3390/cancers15010186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/17/2022] [Accepted: 12/23/2022] [Indexed: 12/31/2022] Open
Abstract
High metabolic activity is a hallmark of cancers, including hepatocellular carcinoma (HCC). However, the molecular features of HCC with high metabolic activity contributing to clinical outcomes and the therapeutic implications of these characteristics are poorly understood. We aimed to define the features of HCC with high metabolic activity and uncover its association with response to current therapies. By integrating gene expression data from mouse liver tissues and tumor tissues from HCC patients (n = 1038), we uncovered three metabolically distinct HCC subtypes that differ in clinical outcomes and underlying molecular biology. The high metabolic subtype is characterized by poor survival, the strongest stem cell signature, high genomic instability, activation of EPCAM and SALL4, and low potential for benefitting from immunotherapy. Interestingly, immune cell analysis showed that regulatory T cells (Tregs) are highly enriched in high metabolic HCC tumors, suggesting that high metabolic activity of cancer cells may trigger activation or infiltration of Tregs, leading to cancer cells' evasion of anti-cancer immune cells. In summary, we identified clinically and metabolically distinct subtypes of HCC, potential biomarkers associated with these subtypes, and a potential mechanism of metabolism-mediated immune evasion by HCC cells.
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Affiliation(s)
- Joann Jung
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sowon Park
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yeonwoo Jang
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sung-Hwan Lee
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Yonsei University College of Medicine, Yonsei 03722, Republic of Korea
- Division of Hepatobiliary and Pancreas, Department of Surgery, CHA Bundang Medical Center, CHA University, Seongnam 46371, Republic of Korea
| | - Yun Seong Jeong
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sun Young Yim
- Division of Hepatobiliary and Pancreas, Department of Surgery, CHA Bundang Medical Center, CHA University, Seongnam 46371, Republic of Korea
- Department of Internal Medicine, Korea University College of Medicine, Seoul 02841, Republic of Korea
| | - Ju-Seog Lee
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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8
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Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma. Biomolecules 2022; 12:biom12111700. [DOI: 10.3390/biom12111700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/12/2022] [Accepted: 11/13/2022] [Indexed: 11/18/2022] Open
Abstract
Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes. We screened differentially expressed proteins between tumorous and adjacent nontumorous tissues of hepatitis B virus (HBV)-related HCC patients using a Nanoscale Liquid Chromatography–Tandem Mass Spectrometry platform and combined it with transcriptomic data of lipid-metabolism-related genes from the GEO and HPA databases to identify dysregulated genes that may be involved in lipid metabolic processes. The potential clinical values of these genes were explored by bioinformatics online analysis tools (GEPIA, cBioPortal, SurvivalMeth, and TIMER). The expression levels of the secreted protein (angiopoietin-like protein 6, ANGPTL6) in serum were analyzed by ELISA. The ability of serum ANGPTL6 to diagnose early HCC was assessed by ROC curves. The results showed that serum ANGPTL6 could effectively differentiate between HBV-related early HCC patients with normal serum alpha-fetoprotein (AFP) levels and the noncancer group (healthy participants and chronic hepatitis B patients) (AUC = 0.717, 95% CI: from 0.614 to 0.805). Serum ANGPTL6 can be used as a potential second-line biomarker to supplement serum AFP in the early diagnosis of HBV-related HCC.
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9
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Tang L, Wei R, Chen R, Fan G, Zhou J, Qi Z, Wang K, Wei Q, Wei X, Xu X. Establishment and validation of a cholesterol metabolism-related prognostic signature for hepatocellular carcinoma. Comput Struct Biotechnol J 2022; 20:4402-4414. [PMID: 36051877 PMCID: PMC9420502 DOI: 10.1016/j.csbj.2022.07.030] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 07/16/2022] [Indexed: 12/16/2022] Open
Abstract
Hepatocellular carcinoma (HCC) represents the most important type of liver cancer, the 5-year survival rate for advanced HCC is 2%. The heterogeneity of HCC makes previous models fail to achieve satisfactory results. The role of Cholesterol-based metabolic reprogramming in cancer has attracted more and more attention. In this study, we screened cholesterol metabolism-related genes (CMRGs) based on a systematical analysis from TCGA and GEO database. Then, we constructed a prognostic signature based on the screened 5 CMRGs: FDPS, FABP5, ANXA2, ACADL and HMGCS2. The clinical value of the five CMRGs was validated by TCGA database and HPA database. HCC patients were assigned to the high-risk and low-risk groups on the basis of median risk score calculated by the five CMRGs. We evaluated the signature in TCGA database and validated in ICGC database. The results revealed that the prognostic signature had good prognostic performance, even among different clinicopathological subgroups. The function analysis linked CMRGs with KEGG pathway, such as cell adhesion molecules, drug metabolism-cytochrome P450 and other related pathways. In addition, patients in the high-risk group exhibited characteristics of high TP53 mutation, high immune checkpoints expression and high immune cell infiltration. Furthermore, based on the prognostic signature, we identified 25 most significant small molecule drugs as potential drugs for HCC patients. Finally, a nomogram combined risk score and TNM stage was constructed. These results indicated our prognostic signature has an excellent prediction performance. This study is expected to provide a potential diagnostic and therapeutic strategies for HCC.
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Affiliation(s)
- Linsong Tang
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Rongli Wei
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Ronggao Chen
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Guanghan Fan
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Junbin Zhou
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Zhetuo Qi
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Kai Wang
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Qiang Wei
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Xuyong Wei
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
| | - Xiao Xu
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou 310003, China
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10
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Zhang J, Xiao X, Guo Q, Wei Z, Hua W. Identification of Four Metabolic Subtypes of Glioma Based on Glycolysis-Cholesterol Synthesis Genes. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:9448144. [PMID: 35242216 PMCID: PMC8886743 DOI: 10.1155/2022/9448144] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 01/06/2022] [Accepted: 01/17/2022] [Indexed: 12/21/2022]
Abstract
Based on alterations in gene expression associated with the production of glycolysis and cholesterol, this research classified glioma into prognostic metabolic subgroups. In this study, data from the CGGA325 and The Cancer Genome Atlas (TCGA) datasets were utilized to extract single nucleotide variants (SNVs), RNA-seq expression data, copy number variation data, short insertions and deletions (InDel) mutation data, and clinical follow-up information from glioma patients. Glioma metabolic subtypes were classified using the ConsensusClusterPlus algorithm. This study determined four metabolic subgroups (glycolytic, cholesterogenic, quiescent, and mixed). Cholesterogenic patients had a higher survival chance. Genome-wide investigation revealed that inappropriate amplification of MYC and TERT was associated with improper cholesterol anabolic metabolism. In glioma metabolic subtypes, the mRNA levels of mitochondrial pyruvate carriers 1 and 2 (MPC1/2) presented deletion and amplification, respectively. Differentially upregulated genes in the glycolysis group were related to pathways, including IL-17, HIF-1, and TNF signaling pathways and carbon metabolism. Downregulated genes in the glycolysis group were enriched in terpenoid backbone biosynthesis, nitrogen metabolism, butanoate metabolism, and fatty acid metabolism pathway. Cox analysis of univariate and multivariate survival showed that risks of glycolysis subtypes were significantly higher than other subtypes. Those results were validated in the CGGA325 dataset. The current findings greatly contribute to a comprehensive understanding of glioma and personalized treatment.
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Affiliation(s)
- Jinsen Zhang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
| | - Xing Xiao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
| | - Qinglong Guo
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
| | - Zixuan Wei
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Wei Hua
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
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11
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Chen Y, Lee K, Liang Y, Qin S, Zhu Y, Liu J, Yao S. A Cholesterol Homeostasis-Related Gene Signature Predicts Prognosis of Endometrial Cancer and Correlates With Immune Infiltration. Front Genet 2021; 12:763537. [PMID: 34790227 PMCID: PMC8591263 DOI: 10.3389/fgene.2021.763537] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 10/13/2021] [Indexed: 12/24/2022] Open
Abstract
Background: Endometrial cancer (EC) is one of the most common gynecological malignancies in women. Cholesterol metabolism has been confirmed to be closely related to tumor proliferation, invasion and metastasis. However, the correlation between cholesterol homeostasis-related genes and prognosis of EC remains unclear. Methods: EC patients from the Cancer Genome Atlas (TCGA) database were randomly divided into training cohort and test cohort. Transcriptome analysis, univariate survival analysis and LASSO Cox regression analysis were adopted to construct a cholesterol homeostasis-related gene signature from the training cohort. Subsequently, Kaplan-Meier (KM) plot, receiver operating characteristic (ROC) curve and principal component analysis (PCA) were utilized to verify the predictive performance of the gene signature in two cohorts. Additionally, enrichment analysis and immune infiltration analysis were performed on differentially expressed genes (DEGs) between two risk groups. Results: Seven cholesterol homeostasis-related genes were selected to establish a gene signature. KM plot, ROC curve and PCA in two cohorts demonstrated that the gene signature was an efficient independent prognostic indicator. The enrichment analysis and immune infiltration analysis indicated that the high-risk group generally had lower immune infiltrating cells and immune function. Conclusion: We constructed and validated a cholesterol homeostasis-related gene signature to predict the prognosis of EC, which correlated to immune infiltration and expected to help the diagnosis and precision treatment of EC.
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Affiliation(s)
- Yili Chen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Kaping Lee
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yanchun Liang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shuhang Qin
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yuan Zhu
- Department of Obstetrics and Gynecology, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Junxiu Liu
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shuzhong Yao
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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12
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Zhu Z, Qin J, Dong C, Yang J, Yang M, Tian J, Zhong X. Identification of four gastric cancer subtypes based on genetic analysis of cholesterogenic and glycolytic pathways. Bioengineered 2021; 12:4780-4793. [PMID: 34346836 PMCID: PMC8806458 DOI: 10.1080/21655979.2021.1956247] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Warburg phenomenon refers to the development of unique metabolic patterns during the growth of tumor cells. This study stratified gastric cancer into prognostic metabolic subgroups according to changes in gene expressions related to glycolysis and cholesterol synthesis. The RNA-seq expression data, single nucleotide variants (SNV), short insertions and deletions (InDel) mutation data, copy number variation (CNV) data and clinical follow-up information data of gastric cancer tissues were downloaded from The Cancer Genome Atlas (TCGA) database. ConsensusClusterPlus was used to stratify the metabolic subtypes of gastric cancer. Four metabolic subtypes (Cholesterogenic, Glycolytic, Mixed and Quiescent) of gastric cancer were identified, and patients with cholesterogenic tumors had the longest disease-specific survival (DSS). Genome-wide analysis showed that aberrant amplification of TP53 and MYC in gastric cancer was associated with abnormal cholesterol anabolic metabolism. The mRNA levels of mitochondrial pyruvate carriers 1 and 2 (MPC1/2) differed among the four subtypes. Tumors in the glycolytic group showed a higher PDCD1. A genomic signature based on tumor metabolism of different cancer types was established. This study showed that genes related to glucose and lipid metabolism play an important role in gastric cancer and facilitate a personalized treatment of gastric cancer.
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Affiliation(s)
- Zhou Zhu
- Department of Gastrointestinal Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Jian Qin
- Department of Radiation Oncology of Clinical Cancer Center, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Chencheng Dong
- Department of Gastrointestinal Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Jin Yang
- Strategic Operations Department, YuceBio Technology Co., Ltd, Guangzhou, China
| | - Maughan Yang
- Strategy DevelopmentDepartment, Meta Health Sector of Yuanzhi Technology Group, Beijing, China
| | - Jana Tian
- Strategy DevelopmentDepartment, Meta Health Sector of Yuanzhi Technology Group, Beijing, China
| | - Xiaogang Zhong
- Department of Gastrointestinal Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
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13
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Zheng Q, Yang Q, Zhou J, Gu X, Zhou H, Dong X, Zhu H, Chen Z. Immune signature-based hepatocellular carcinoma subtypes may provide novel insights into therapy and prognosis predictions. Cancer Cell Int 2021; 21:330. [PMID: 34193146 PMCID: PMC8243542 DOI: 10.1186/s12935-021-02033-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 06/19/2021] [Indexed: 02/07/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) has a poor prognosis and has become the sixth most common malignancy worldwide due to its high incidence. Advanced approaches to therapy, including immunotherapeutic strategies, have played crucial roles in decreasing recurrence rates and improving clinical outcomes. The HCC microenvironment is important for both tumour carcinogenesis and immunogenicity, but a classification system based on immune signatures has not yet been comprehensively described. Methods HCC datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) were used in this study. Gene set enrichment analysis (GSEA) and the ConsensusClusterPlus algorithm were used for clustering assessments. We scored immune cell infiltration and used linear discriminant analysis (LDA) to improve HCC classification accuracy. Pearson's correlation analyses were performed to assess relationships between immune signature indices and immunotherapies. In addition, weighted gene co-expression network analysis (WGCNA) was applied to identify candidate modules closely associated with immune signature indices. Results Based on 152 immune signatures from HCC samples, we identified four distinct immune subtypes (IS1, IS2, IS3, and IS4). Subtypes IS1 and IS4 had more favourable prognoses than subtypes IS2 and IS3. These four subtypes also had different immune system characteristics. The IS1 subtype had the highest scores for IFNγ, cytolysis, angiogenesis, and immune cell infiltration among all subtypes. We also identified 11 potential genes, namely, TSPAN15, TSPO, METTL9, CD276, TP53I11, SPINT1, TSPO, TRABD2B, WARS2, C9ORF116, and LBH, that may represent potential immunological biomarkers for HCC. Furthermore, real-time PCR revealed that SPINT1, CD276, TSPO, TSPAN15, METTL9, and WARS2 expression was increased in HCC cells. Conclusions The present gene-based immune signature classification and indexing may provide novel perspectives for both HCC immunotherapy management and prognosis prediction. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-02033-4.
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Affiliation(s)
- Qiuxian Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Qin Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Jiaming Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Xinyu Gu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Haibo Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Xuejun Dong
- Department of Clinical Laboratory Center, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | - Haihong Zhu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China.
| | - Zhi Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China.
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14
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Down-regulation of RBP4 indicates a poor prognosis and correlates with immune cell infiltration in hepatocellular carcinoma. Biosci Rep 2021; 41:228242. [PMID: 33834191 PMCID: PMC8055798 DOI: 10.1042/bsr20210328] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/01/2021] [Accepted: 04/08/2021] [Indexed: 02/06/2023] Open
Abstract
Recent research has indicated that metabolically related genes play crucial roles in the pathogenesis of hepatocellular carcinoma (HCC). We evaluated the associations between novel biomarkers and retinol-binding protein 4 (RBP4) for predicting clinical HCC outcomes, hub-related genes, pathway regulation, and immune cells infiltration. Bioinformatic analyses based on data from The Cancer Genome Atlas were performed using online analysis tools. RBP4 expression was low in HCC and was also down-regulated in pan-cancers compared with normal tissues. RBP4 expression was also significantly different based on age (41–60 years old versus 61–80 years old), and low RBP4 expression levels were associated with advanced tumor stages and grades. Higher RBP4 expression was associated with better overall survival time in HCC patients, and we identified a deletion-mutation rate of 1.4% in RBP4. We also identified ten co-expressed genes most related to RBP4 and explored the relationships between six hub genes (APOB, FGA, FGG, SERPINC1, APOA1, and F2) involved in RBP4 regulation. A pathway enrichment analysis for RBP4 indicated complement and coagulation cascades, metabolic pathways, antibiotic biosynthesis pathways, peroxisome proliferator-activated receptor signaling pathways, and pyruvate metabolism pathways. These results suggest that RBP4 may be a novel biomarker for HCC prognosis, and an indicator of low immune response to the disease.
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15
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Chen Z, Chen L, Sun B, Liu D, He Y, Qi L, Li G, Han Z, Zhan L, Zhang S, Zhu K, Luo Y, Chen L, Zhang N, Guo H. LDLR inhibition promotes hepatocellular carcinoma proliferation and metastasis by elevating intracellular cholesterol synthesis through the MEK/ERK signaling pathway. Mol Metab 2021; 51:101230. [PMID: 33823318 PMCID: PMC8102998 DOI: 10.1016/j.molmet.2021.101230] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/23/2021] [Accepted: 03/30/2021] [Indexed: 12/14/2022] Open
Abstract
Objective Adaptive rewiring of cancer energy metabolism has received increasing attention. By binding with LDLs, LDLRs make most of the circulating cholesterol available for cells to utilize. However, it remains unclear how LDLR works in HCC development by affecting cholesterol metabolism. Methods Database analyses and immunohistochemical staining were used to identify the clinical significance of LDLR in HCC. A transcriptome analysis was used to reveal the mechanism of LDLR aberration in HCC progression. A liver orthotopic transplantation model was used to evaluate the role of LDLR in HCC progression in vivo. Results Downregulation of LDLR was identified as a negative prognostic factor in human HCC. Reduced expression of LDLR in HCC cell lines impaired LDL uptake but promoted proliferation and metastasis in vitro and in vivo. Mechanistically, increasing intracellular de novo cholesterol biosynthesis was the chief contributor to malignant behaviors caused by LDLR inhibition, which could be rescued by simvastatin. Activation of the MEK/ERK pathway by LDLR downregulation partially contributed to intracellular cholesterol synthesis in HCC. Conclusions Downregulation of LDLR may elevate intracellular cholesterol synthesis to accelerate proliferation and motility through a mechanism partially attributed to stimulation of the MEK/ERK signaling pathway. Repression of intracellular cholesterol synthesis with statins may constitute a targetable liability in the context of lower LDLR expression in HCC. Downregulation of LDLR is identified as a negative prognostic factor in human HCC. LDLR inhibition facilitates the proliferation and metastasis of HCC cells. Increased cholesterol synthesis chiefly contributes to the malignant behaviors caused by LDLR reduction. Blockade of cholesterol synthesis by simvastatin attenuates HCC progression under lower LDLR. Activation of the MEK/ERK pathway by LDLR downregulation promotes cholesterol synthesis in HCC.
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Affiliation(s)
- Ziye Chen
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Lu Chen
- Department of Hepatobiliary Cancer, Liver Cancer Research Center, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Bo Sun
- The Second Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Dongming Liu
- Department of Hepatobiliary Cancer, Liver Cancer Research Center, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Yuchao He
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Lisha Qi
- Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Guangtao Li
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Zhiqiang Han
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Linlin Zhan
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Su Zhang
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Keyun Zhu
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Yi Luo
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Liwei Chen
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Ning Zhang
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China; Translational Cancer Research Center, Peking University First Hospital, Beijing 100034, China.
| | - Hua Guo
- Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
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16
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Xia R, Tang H, Shen J, Xu S, Liang Y, Zhang Y, Gong X, Min Y, Zhang D, Tao C, Wang S, Zhang Y, Yang J, Wang C. Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population. Cancer Cell Int 2021; 21:154. [PMID: 33663535 PMCID: PMC7934443 DOI: 10.1186/s12935-021-01857-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 02/24/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. However, studies have not established glycolysis-related gene signatures that can be used to construct accurate prognostic models for GI cancers in the Asian population. Herein, we aimed at establishing a novel glycolysis-related gene expression signature to predict the prognosis of GI cancers. METHODS First, we evaluated the mRNA expression profiles and the corresponding clinical data of 296 Asian GI cancer patients in The Cancer Genome Atlas (TCGA) database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL and TCGA-READ). Differentially expressed mRNAs between GI tumors and normal tissues were investigated. Gene Set Enrichment Analysis (GSEA) was performed to identify glycolysis-related genes. Then, univariate, LASSO regression and multivariate Cox regression analyses were performed to establish a key prognostic glycolysis-related gene expression signature. The Kaplan-Meier and receiver operating characteristic (ROC) curves were used to evaluate the efficiency and accuracy of survival prediction. Finally, a risk score to predict the prognosis of GI cancers was calculated and validated using the TCGA data sets. Furthermore, this risk score was verified in two Gene Expression Omnibus (GEO) data sets (GSE116174 and GSE84433) and in 28 pairs of tissue samples. RESULTS Prognosis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1) among the differentially expressed glycolysis-related genes were screened and identified. The five-gene expression signature was used to assign patients into high- and low-risk groups (p < 0.05) and it showed a satisfactory prognostic value for overall survival (OS, p = 6.383 × 10-6). The ROC curve analysis revealed that this model has a high sensitivity and specificity (0.757 at 5 years). Besides, stratification analysis showed that the prognostic value of the five-gene signature was independent of other clinical characteristics, and it could markedly discriminate between GI tumor tissues and normal tissues. Finally, the expression levels of the five prognosis-related genes in the clinical tissue samples were consistent with the results from the TCGA data sets. CONCLUSIONS Based on the five glycolysis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1), and in combination with clinical characteristics, this model can independently predict the OS of GI cancers in Asian patients.
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Affiliation(s)
- Rong Xia
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Hua Tang
- Department of General Surgery, Tongling People's Hospital, 468 Bijiashan Road, Tongling, Anhui Province, 244000, People's Republic of China
| | - Jiemiao Shen
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Shuyu Xu
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Yinyin Liang
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Yuxin Zhang
- The First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, People's Republic of China
| | - Xing Gong
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Yue Min
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Di Zhang
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Chenzhe Tao
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Shoulin Wang
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China
| | - Yi Zhang
- Department of Colorectal Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China.
| | - Jinyou Yang
- Department of Clinical Medicine and Rehabilitation, Jiangsu College of Nursing, 9 Keji Road, Huai'an, 223005, People's Republic of China.
| | - Chao Wang
- Key Lab of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China. .,State Key Lab of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, People's Republic of China.
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