1
|
Gu J, Ding B. Cross-talk of pyroptosis-based subtypes, the development of a risk classifier and immune responses in cervical cancer. J Gene Med 2024; 26:e3566. [PMID: 37469224 DOI: 10.1002/jgm.3566] [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: 05/16/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Cervical cancer (CC) is one of the most common gynecology malignancies and has a dismal survival outcome. The prognostic value of pyroptosis and its role in the regulation of immune metabolism in CC remain unclear. METHODS Two independent CC cohorts collected from public databases were integrated for unsupervised cluster analysis. All CC cases were assigned to different subsets based on the pyroptosis-related genes (PRGs). The differentially expressed genes (DEGs) between different subclusters were included in stepwise Cox regression for the risk classifier establishment. Next, single-cell sequencing analysis was conducted to explore the cellular location of each model gene. The CIBERSORT algorithm was applied to estimate immunocytes infiltration. Finally, a series of functional experiments were performed to detect the role of CDH3 in CC. RESULTS Based on the 52 PRGs, the combined CC cohort was clustered into two subsets (C1 (n = 259) and C2 (n = 242)). Survival and Cox regression methods were used to create a pyroptosis-based risk classifier including four PRGs (PEG3, FSCN1, CDH3 and SLC2A1). For the immune environment in CC, the high-risk group had a lower infiltration level of B cells, memory-activated CD4 T cells and CD8 T cells and a higher infiltration abundance of neutrophils. The expression pattern of model genes was confirmed in CC cell lines by PCR assay. Furthermore, we observed that knockdown of CDH3 could suppress CC cell proliferation. CONCLUSION Our project could offer promising reference for prognosis assessment, immune metabolism prediction and clinical decision-making of patients with CC.
Collapse
Affiliation(s)
- Jiamin Gu
- Department of Obstetrics and Gynecology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Bo Ding
- Department of Obstetrics and Gynecology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| |
Collapse
|
2
|
Hong L, Wang X, Cui W, Wang F, Shi W, Yu S, Luo Y, Zhong L, Zhao X. Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma. Front Pharmacol 2023; 13:1098136. [PMID: 36686701 PMCID: PMC9846555 DOI: 10.3389/fphar.2022.1098136] [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: 11/14/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Background: Ferroptosis is a novel process of programmed cell death driven by excessive lipid peroxidation that is associated with the development of lung adenocarcinoma. N6-methyladenosine (m6a) modification of multiple genes is involved in regulating the ferroptosis process, while the predictive value of N6-methyladenosine- and ferroptosis-associated lncRNA (FMRlncRNA) in the prognosis of patients remains with LUAD remains unknown. Methods: Unsupervised cluster algorithm was applied to generate subcluster in LUAD according to ferroptosis-associated lncRNA. Stepwise Cox analysis and LASSO algorithm were applied to develop a prognostic model. Cellular location was detected by single-cell analysis. Also, we conducted Gene set enrichment analysis (GSEA) enrichment, immune microenvironment and drug sensitivity analysis. In addition, the expression and function of the LINC01572 were investigated by several in vitro experiments including qRT-PCR, cell viability assays and ferroptosis assays. Results: A novel ferroptosis-associated lncRNAs-based molecular subtype containing two subclusters were determined in LUAD. Then, we successfully created a risk model according to five ferroptosis-associated lncRNAs (LINC00472, MBNL1-AS1, LINC01572, ZFPM2-AS1, and TMPO-AS1). Our nominated model had good stability and predictive function. The expression patterns of five ferroptosis-associated lncRNAs were confirmed by polymerase chain reaction (PCR) in LUAD cell lines. Knockdown of LINC01572 significantly inhibited cell viability and induced ferroptosis in LUAD cell lines. Conclusion: Our data provided a risk score system based on ferroptosis-associated lncRNAs with prognostic value in LUAD. Moreover, LINC01572 may serve as a novel ferroptosis suppressor in LUAD.
Collapse
Affiliation(s)
- Lingling Hong
- Nantong Hospital of Traditional Chinese Medicine, Affiliated Traditional Chinese Medicine Hospital of Nantong University, Nantong, China
| | - Xuehai Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Weiming Cui
- Department of Thoracic and Cardiac Surgery, Nanjing Brain Hospital, Nanjing, China
| | - Fengxu Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Weiwei Shi
- Nantong Hospital of Traditional Chinese Medicine, Affiliated Traditional Chinese Medicine Hospital of Nantong University, Nantong, China
| | - Shali Yu
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Yonghua Luo
- Nantong Fourth People’s Hospital, Nantong, China,*Correspondence: Yonghua Luo, ; Lixin Zhong, ; Xinyuan Zhao,
| | - Lixin Zhong
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China,*Correspondence: Yonghua Luo, ; Lixin Zhong, ; Xinyuan Zhao,
| | - Xinyuan Zhao
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China,*Correspondence: Yonghua Luo, ; Lixin Zhong, ; Xinyuan Zhao,
| |
Collapse
|
3
|
Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma. BIOMED RESEARCH INTERNATIONAL 2022; 2022:8776678. [DOI: 10.1155/2022/8776678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/22/2022] [Accepted: 10/27/2022] [Indexed: 11/27/2022]
Abstract
Background. N7-methylguanosine (m7G) has been implicated in the development of cancer. The role of m7G-related miRNAs in the survival prediction of UCEC patients has not been investigated. Current research was the first to construct an m7G-related miRNA model to accurately predict the survival of patients with uterine corpus endometrial carcinoma (UCEC) and to explore immune cell infiltration and immune activity in the tumor microenvironment. Methods. RNA-seq data and clinical information of UCEC patients were derived from The Cancer Genome Atlas (TCGA) database. Using the TargetScan online database, we predicted miRNAs linked to the m7G-related genes and identified miRNAs which were significantly associated with the survival in UCEC patients and constructed a risk scoring model. The TCGA-UCEC cases were scored according to the risk model, and the high- and low-risk groups were divided by the median risk value. Gene enrichment analysis and immune cell infiltration and immune function analysis were performed using “clusterProfiler” and “GSVA” packages in R. Results. The survival prediction model consisted of 9 miRNAs, namely, hsa-miR-1301, hsa-miR-940, hsa-miR-592, hsa-miR-3170, hsa-miR-876, hsa-miR-215, hsa-miR-934, hsa-miR-3920, and hsa-miR-216b. Survival of UCEC patients in the high-risk group was worse than that in the low-risk group (
). The receiver operating characteristic (ROC) curve showed that the model had good predictive performance, and the area under the curve was 0.800, 0.690, and 0.705 for 1-, 3-, and 5-year survival predictions, respectively. There were differences in the degree of immune cell infiltration and immune activity between the low-risk and high-risk groups. The expression levels of the identified differentially expressed genes correlated with the susceptibility to multiple anticancer drugs. Conclusions. The survival prediction model constructed based on 9 m7G-related miRNAs had good predictive performance.
Collapse
|