1
|
Li M, Gao X, Su Y, Shan S, Qian W, Zhang Z, Zhu D. FOXM1 transcriptional regulation. Biol Cell 2024:e2400012. [PMID: 38963053 DOI: 10.1111/boc.202400012] [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: 01/30/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 07/05/2024]
Abstract
FOXM1 is a key transcriptional regulator involved in various biological processes in mammals, including carbohydrate and lipid metabolism, aging, immune regulation, development, and disease. Early studies have shown that FOXM1 acts as an oncogene by regulating cell proliferation, cell cycle, migration, metastasis, and apoptosis, as well as genes related to diagnosis, treatment, chemotherapy resistance, and prognosis. Researchers are increasingly focusing on FOXM1 functions in tumor microenvironment, epigenetics, and immune infiltration. However, researchers have not comprehensively described FOXM1's involvement in tumor microenvironment shaping, epigenetics, and immune cell infiltration. Here we review the role of FOXM1 in the formation and development of malignant tumors, and we will provide a comprehensive summary of the role of FOXM1 in transcriptional regulation, interacting proteins, tumor microenvironment, epigenetics, and immune infiltration, and suggest areas for further research.
Collapse
Affiliation(s)
- Mengxi Li
- Hubei Key Laboratory of Diabetes and Angiopathy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
- School of Nuclear Technology and Chemistry & Biology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Xuzheng Gao
- Hubei Key Laboratory of Diabetes and Angiopathy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Yanting Su
- School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Shigang Shan
- School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Wenbin Qian
- School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Zhenwang Zhang
- Hubei Key Laboratory of Diabetes and Angiopathy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
- School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| | - Dan Zhu
- Hubei Key Laboratory of Diabetes and Angiopathy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
- School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Hubei University of Science and Technology, Xianning, Hubei Province, P. R. China
| |
Collapse
|
2
|
Zhang ZH, Du Y, Wei S, Pei W. Multilayered insights: a machine learning approach for personalized prognostic assessment in hepatocellular carcinoma. Front Oncol 2024; 13:1327147. [PMID: 38486931 PMCID: PMC10937467 DOI: 10.3389/fonc.2023.1327147] [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: 10/24/2023] [Accepted: 12/08/2023] [Indexed: 03/17/2024] Open
Abstract
Background Hepatocellular carcinoma (HCC) is a complex malignancy, and precise prognosis assessment is vital for personalized treatment decisions. Objective This study aimed to develop a multi-level prognostic risk model for HCC, offering individualized prognosis assessment and treatment guidance. Methods By utilizing data from The Cancer Genome Atlas (TCGA) and the Surveillance, Epidemiology, and End Results (SEER) database, we performed differential gene expression analysis to identify genes associated with survival in HCC patients. The HCC Differential Gene Prognostic Model (HCC-DGPM) was developed through multivariate Cox regression. Clinical indicators were incorporated into the HCC-DGPM using Cox regression, leading to the creation of the HCC Multilevel Prognostic Model (HCC-MLPM). Immune function was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and immune cell infiltration was assessed. Patient responsiveness to immunotherapy was evaluated using the Immunophenoscore (IPS). Clinical drug responsiveness was investigated using drug-related information from the TCGA database. Cox regression, Kaplan-Meier analysis, and trend association tests were conducted. Results Seven differentially expressed genes from the TCGA database were used to construct the HCC-DGPM. Additionally, four clinical indicators associated with survival were identified from the SEER database for model adjustment. The adjusted HCC-MLPM showed significantly improved discriminative capacity (AUC=0.819 vs. 0.724). External validation involving 153 HCC patients from the International Cancer Genome Consortium (ICGC) database verified the performance of the HCC-MLPM (AUC=0.776). Significantly, the HCC-MLPM exhibited predictive capacity for patient response to immunotherapy and clinical drug efficacy (P < 0.05). Conclusion This study offers comprehensive insights into HCC prognosis and develops predictive models to enhance patient outcomes. The evaluation of immune function, immune cell infiltration, and clinical drug responsiveness enhances our comprehension and management of HCC.
Collapse
Affiliation(s)
| | - Yunxiang Du
- Department of Oncology, Huai’an 82 Hospital, China RongTong Medical Healthcare Group Co., Ltd., Chengdu, China
| | - Shuzhen Wei
- Department of Oncology, Huai’an 82 Hospital, China RongTong Medical Healthcare Group Co., Ltd., Chengdu, China
| | - Weidong Pei
- Department of Discipline Development, China RongTong Medical Healthcare Group Co., Ltd., Chengdu, China
| |
Collapse
|
3
|
Chen J, Chen C, Tao L, Cai Y, Wang C. A comprehensive analysis of the potential role of necroptosis in hepatocellular carcinoma using single-cell RNA Seq and bulk RNA Seq. J Cancer Res Clin Oncol 2023; 149:13841-13853. [PMID: 37535163 DOI: 10.1007/s00432-023-05208-w] [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: 06/13/2023] [Accepted: 07/25/2023] [Indexed: 08/04/2023]
Abstract
PURPOSE Necroptosis plays an essential role in oncogenesis and tumor progression in hepatocellular carcinoma (HCC). This study aimed to investigate the role of necroptosis in the development and progression of HCC. Specifically, we constructed a prognostic prediction model using necroptosis-associated genes (NAGs) to predict patient outcomes. METHODS Using data from The Cancer Genome Atlas (TCGA) database, we analyzed gene expression and clinical data. We identified a 5-gene model associated with NAGs and explored genetic features and immune cell infiltration using the CIBERSORT algorithm. In addition, we conducted single-cell RNA sequencing to investigate the potential role of necroptosis in HCC. RESULTS We constructed a 5-gene prognostic model based on NAGs that demonstrated excellent predictive accuracy in both training and validation sets. Using multifactorial cox regression analysis, we confirmed the risk score derived from the model as an independent predictor of prognosis, surpassing other clinical characteristics. Patients with high risk scores had significantly worse prognosis than those with low risk scores. To enhance the clinical utility of the necroptosis score, we constructed an accurate nomogram. Additionally, we compared metabolic pathway and immune microenvironment differences between HCC tumors with high and low risk scores. Our single-cell RNA sequencing analyses revealed that necroptosis in HCC was primarily associated with a specific subset of macrophages. CONCLUSIONS Our study revealed the presence of two distinct necroptosis subtypes in HCC and developed a robust prognostic model with exceptional predictive accuracy. We observed significantly higher infiltration of M0 macrophages in the high-risk group. We propose that rescuing cytochrome c metabolism in HCC could serve as a potential therapeutic strategy. Furthermore, at a single-cell resolution, our analysis identified myeloid cells as the primary cells exhibiting necroptosis. Specifically, macrophages expressing CD5L, CETP, and MARCO, which may belong to a subset of tissue-resident macrophages, were found to be highly susceptible to necroptosis. These findings suggest the involvement of this specific macrophage subset in potential antitumor therapies. Our study provides novel insights into predicting patient prognosis and developing personalized therapeutic approaches for HCC.
Collapse
Affiliation(s)
- Jiakang Chen
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Cuimin Chen
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Lili Tao
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Yusi Cai
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Chun Wang
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, China.
| |
Collapse
|
4
|
Mao H, Wang R, Shao F, Zhao M, Tian D, Xia H, Zhao Y. HMGCS2 serves as a potential biomarker for inhibition of renal clear cell carcinoma growth. Sci Rep 2023; 13:14629. [PMID: 37670031 PMCID: PMC10480187 DOI: 10.1038/s41598-023-41343-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 08/24/2023] [Indexed: 09/07/2023] Open
Abstract
3-Hydroxymethylglutaryl-CoA synthase 2 (HMGCS2) is the rate-limiting enzyme for ketone body synthesis, and most current studies focus on mitochondrial maturation and metabolic reprogramming. The role of HMGCS2 was evaluated in a pan-cancer multi-database using R language, and HMGCS2 was lowly expressed or not differentially expressed in all tumor tissues compared with normal tissues. Correlation analysis of clinical case characteristics, genomic heterogeneity, tumor stemness, and overall survival revealed that HMGCS2 is closely related to clear cell renal cell carcinoma (KIRC). Single-cell sequencing data from normal human kidneys revealed that HMGCS2 is specifically expressed in proximal tubular cells of normal adults. In addition, HMGCS2 is associated with tumor immune infiltration and microenvironment, and KIRC patients with low expression of HMGCS2 have worse prognosis. Finally, the results of cell counting kit 8 assays, colony formation assays, flow cytometry, and Western blot analysis suggested that upregulation of HMGCS2 increased the expression of key tumor suppressor proteins, inhibited the proliferation of clear cell renal cell carcinoma cells and promoted cell apoptosis. In conclusion, HMGCS2 is abnormally expressed in pan-cancer, may play an important role in anti-tumor immunity, and is expected to be a potential tumor prognostic marker, especially in clear cell renal cell carcinoma.
Collapse
Affiliation(s)
- Huajie Mao
- Department of Laboratory Medicine, The First Affiliated Hospital of Northwest University, Xi'an No.1 Hospital, Xi'an, 710002, China
| | - Runzhi Wang
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, the College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Fengling Shao
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, the College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Ming Zhao
- Department of Science and Education, The First Affiliated Hospital of Northwest University, Xi'an No.1 Hospital, Xi'an, 710002, China
| | - Dayu Tian
- Department of Laboratory Medicine, The First Affiliated Hospital of Northwest University, Xi'an No.1 Hospital, Xi'an, 710002, China
| | - Hua Xia
- Department of Laboratory Medicine, The First Affiliated Hospital of Northwest University, Xi'an No.1 Hospital, Xi'an, 710002, China
| | - Ya Zhao
- Department of Laboratory Medicine, The First Affiliated Hospital of Northwest University, Xi'an No.1 Hospital, Xi'an, 710002, China.
| |
Collapse
|
5
|
Wang D, Zhang Y, Wang X, Zhang L, Xu S. Construction and validation of an aging-related gene signature predicting the prognosis of pancreatic cancer. Front Genet 2023; 14:1022265. [PMID: 36741321 PMCID: PMC9889561 DOI: 10.3389/fgene.2023.1022265] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/10/2023] [Indexed: 01/20/2023] Open
Abstract
Background: Pancreatic cancer is a malignancy with a high mortality rate and worse prognosis. Recently, public databases and bioinformatics tools make it easy to develop the prognostic risk model of pancreatic cancer, but the aging-related risk signature has not been reported. The present study aimed to identify an aging-related risk signature with potential prognostic value for pancreatic cancer patients. Method: Gene expression profiling and human clinical information of pancreatic cancer were derived from The Cancer Genome Atlas database (TCGA). Aging-related gene sets were downloaded from The Molecular Signatures Database and aging-related genes were obtained from the Human Ageing Genomic Resources database. Firstly, Gene set enrichment analysis was carried out to investigate the role of aging process in pancreatic cancer. Secondly, differentially expressed genes and aging-related prognostic genes were screened on the basis of the overall survival information. Then, univariate COX and LASSO analysis were performed to establish an aging-related risk signature of pancreatic cancer patients. To facilitate clinical application, a nomogram was established to predict the survival rates of PCa patients. The correlations of risk score with clinical features and immune status were evaluated. Finally, potential therapeutic drugs were screened based on the connectivity map (Cmap) database and verified by molecular docking. For further validation, the protein levels of aging-related genes in normal and tumor tissues were detected in the Human Protein Atlas (HPA) database. Result: The genes of pancreatic cancer were markedly enriched in several aging-associated signaling pathways. We identified 14 key aging-related genes related to prognosis from 9,020 differentially expressed genes and establish an aging-related risk signature. This risk model indicated a strong prognostic capability both in the training set of TCGA cohort and the validation set of PACA-CA cohort and GSE62452 cohort. A nomogram combining risk score and clinical variables was built, and calibration curve and Decision curve analysis (DCA) have proved that it has a good predictive value. Additionally, the risk score was tightly linked with tumor immune microenvironment, immune checkpoints and proinflammatory factors. Moreover, a candidate drug, BRD-A47144777, was screened and verified by molecular docking, indicating this drug has the potential to treat PCa. The protein expression levels of GSK3B, SERPINE1, TOP2A, FEN1 and HIC1 were consistent with our predicted results. Conclusion: In conclusion, we identified an aging-related signature and nomogram with high prediction performance of survival and immune cell infiltration for pancreatic cancer. This signature might potentially help in providing personalized immunotherapy for patients with pancreatic cancer.
Collapse
Affiliation(s)
- Dengchuan Wang
- Office of Medical Ethics, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
| | - Yonggang Zhang
- Department of Clinical Laboratory, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
| | - Xiaokang Wang
- Department of Pharmacy, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
| | - Limei Zhang
- Department of Oncology, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
| | - Shi Xu
- Department of Burn and Plastic Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
| |
Collapse
|
6
|
Zhao J, Guan K, Xing J. Construction and evaluation of an aging-associated genes-based model for pancreatic adenocarcinoma prognosis and therapies. Int J Immunopathol Pharmacol 2023; 37:3946320231172072. [PMID: 37072128 PMCID: PMC10127222 DOI: 10.1177/03946320231172072] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023] Open
Abstract
Objectives: Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor. Despite extensive research, the precise role of aging-related genes in the initiation, microenvironment regulation, and progression of PAAD remains unclear.Methods: Patients with PAAD were selected from the International Cancer Genome Consortium (ICGC), and The Cancer Genome Atlas (TCGA) cohorts and the cell senescence-associated genes were obtained from CellAge. ConsensusClusterPlus was utilized for cluster identification. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct a prognosis prediction model.Results: We identified three clusters (C1, C2, and C3) based on aging-associated gene profiles. The C1 cluster had a shorter overall survival time, advanced clinical grades, lower immune ESTIMATE score, and tumor immune dysfunction and exclusion (TIDE) score than the C3 subgroup. Moreover, signaling pathways for cell cycle activation were enriched in the C1 cluster. We also identified eight hub genes and constructed a risk model. The high cellular senescence-related signature (CSRS) score subtype exhibited poor prognosis, advanced clinical grades, M2 macrophage infiltration, higher immune checkpoint gene expression, and lower immunotherapeutic benefits.Conclusion: Our risk score model shows high prediction accuracy and survival prediction ability in individual clinical prognosis and pre-immunotherapy evaluation.
Collapse
Affiliation(s)
- Junjie Zhao
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Chin
| | - Kelei Guan
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Chin
| | - Jiyuan Xing
- Infectious Diseases Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| |
Collapse
|
7
|
Dai YY, Gao YP, Chen LX, Liu JS, Zeng C, Zhou JD, Wu HL. Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs. Front Genet 2022; 13:930446. [PMID: 36110218 PMCID: PMC9468367 DOI: 10.3389/fgene.2022.930446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 07/12/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Hepatocellular carcinoma (HCC), which has high rates of recurrence and metastasis and is the main reason and the most common tumor for cancer mortality worldwide, has an unfavorable prognosis. N7-methylguanosine (m7G) modification can affect the formation and development of tumors by affecting gene expression and other biological processes. In addition, many previous studies have confirmed the unique function of long noncoding RNAs (lncRNAs) in tumor progression; however, studies exploring the functions of m7G-related lncRNAs in HCC patients has been limited. Methods: Relevant RNA expression information was acquired from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov), and m7G-related lncRNAs were identified via gene coexpression analysis. Afterward, univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate regression analyses were implemented to construct an ideal risk model whose validity was verified using Kaplan–Meier survival, principal component, receiver operating characteristic (ROC) curve, and nomogram analyses. In addition, the potential functions of lncRNAs in the novel signature were explored through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses and gene set enrichment analysis (GSEA). At last, in both risk groups and subtypes classified based on the expression of the risk-related lncRNAs, we analyzed the immune characteristics and drug sensitivity of patients. Results: After rigorous screening processes, we built a model based on 11 m7G-related lncRNAs for predicting patient overall survival (OS). The results suggested that the survival status of patients with high-risk scores was lower than that of patients with low-risk scores, and a high-risk score was related to malignant clinical features. Cox regression analysis showed that the m7G risk score was an independent prognostic parameter. Moreover, immune cell infiltration and immunotherapy sensitivity differed between the risk groups. Conclusion: The m7G risk score model constructed based on 11 m7G-related lncRNAs can effectively assess the OS of HCC patients and may offer support for making individualized treatment and immunotherapy decisions for HCC patients.
Collapse
Affiliation(s)
- Yu-yang Dai
- Department of Radiology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu Province, China
- Department of Radiology, The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
| | - Yi-ping Gao
- Department of Interventional Radiology, Nanfang Hospital Affiliated to Southern Medical University, Guangzhou, Guangdong, China
| | - Lin-xin Chen
- State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, School of Ophthalmology and Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jin-song Liu
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu, China
- Department of Oncology, The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
| | - Cheng Zeng
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu, China
- Department of Oncology, The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
| | - Jian-dong Zhou
- Department of Nephrology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu, China
- Department of Nephrology, The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
| | - Hong-lin Wu
- Department of Radiology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu Province, China
- Department of Radiology, The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
- *Correspondence: Hong-lin Wu,
| |
Collapse
|