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Xu H, Jiang Y, Wen Y, Liu Q, Du HG, Jin X. Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning. Sci Rep 2024; 14:19294. [PMID: 39164344 PMCID: PMC11336120 DOI: 10.1038/s41598-024-69700-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 08/07/2024] [Indexed: 08/22/2024] Open
Abstract
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating the GSE124272 and GSE150408 datasets for differential gene expression profiles associated with CRGs and immune characteristics. Molecular clustering was performed on LDH samples, followed by expression and immune infiltration analyses. Using the WGCNA algorithm, specific genes within CRG clusters were identified. After selecting the most predictive genes from the optimal model, four machine learning models were constructed and validated. This study identified nine CRGs associated with copper-regulated cell death. Two copper-containing molecular clusters linked to death were detected in LDH samples. Elevated expression and immune infiltration levels were found in LDH patients, particularly in CRG cluster C2. Utilizing XGB, five genes were identified for constructing a diagnostic model, achieving an area under the curve values of 0.715. In conclusion, this research provides valuable insights into the association between LDH and copper-regulated cell death, alongside proposing a promising predictive model.
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Affiliation(s)
- Haipeng Xu
- Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China
| | - Yaheng Jiang
- Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China
| | - Ya Wen
- Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China
| | - Qianqian Liu
- Respiratory Department, The First People's Hospital of Lanzhou, Lanzhou, Gansu, China
| | - Hong-Gen Du
- Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China.
| | - Xin Jin
- Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China.
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Chen C, Wang C, Li Y, Jiang S, Yu N, Zhou G. Prognosis and chemotherapy drug sensitivity in liver hepatocellular carcinoma through a disulfidptosis-related lncRNA signature. Sci Rep 2024; 14:7157. [PMID: 38531953 DOI: 10.1038/s41598-024-57954-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/23/2024] [Indexed: 03/28/2024] Open
Abstract
Disulfidptosis, a new type of regulated cell death associated with the actin cytoskeleton, provides a new therapeutic tool for cancers. The direct relationship between disulfidptosis-related lncRNAs(DRLs) in liver hepatocellular carcinoma(HCC) remains unclear. We acquired transcriptomic data, corresponding clinical data, and tumor mutation data of HCC from the TCGA database. First of all, DRLs were determined through correlation analysis. Then, a prognostic model containing six DRLs was created by adopting univariate Cox regression, LASSO algorithm and multivariate Cox regression analysis. Based on the model, 424 HCC patients were divided into high- and low-risk groups. Next, we structured ROC curves and PCA through combining the model and clinical data. Enrichment analysis and immune infiltration analysis were adopted to further explore the relationship between the model and prognosis. In addition, we explored the relationship between the model and tumor mutation burden (TMB). There were significant differences between high- and low- risk groups, and patients in the high-risk group showed poor prognosis. Enrichment analysis suggested that metabolic progress was obviously different between the two groups. According to the analysis of immune infiltration, there were several differences in immune cells, function, and checkpoints. Patients with high-risk and high TMB demonstrated the least favorable prognosis. The two risk groups both manifested visiblly in chemotherapy drug sensitivity. To sum up, we set up a DRL-based signature and that may provide a predictable value for the prognosis and use of chemotherapy drugs for HCC patients.
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Affiliation(s)
- Chao Chen
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China
| | - Chaoyang Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China
| | - Yi Li
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China
| | - Shanshan Jiang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China
| | - Ningjun Yu
- Department of Radiology, Sichuan Science Hospital, Mianyang, 621022, Sichuan, China
| | - Guofeng Zhou
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China.
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Mo JQ, Zhang SY, Li Q, Chen MX, Zheng YQ, Xie X, Zhang R, Wang SS. Immunomodulation of cuproptosis and ferroptosis in liver cancer. Cancer Cell Int 2024; 24:22. [PMID: 38200525 PMCID: PMC10777659 DOI: 10.1186/s12935-023-03207-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/30/2023] [Indexed: 01/12/2024] Open
Abstract
According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.
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Affiliation(s)
- Jia-Qian Mo
- School of Life Sciences and Biopharmaceutics, Guang Dong Pharmaceutical University, Guangzhou, 51006, China
| | - Shen-Yan Zhang
- School of Life Sciences and Biopharmaceutics, Guang Dong Pharmaceutical University, Guangzhou, 51006, China
| | - Qiang Li
- School of Life Sciences and Biopharmaceutics, Guang Dong Pharmaceutical University, Guangzhou, 51006, China
| | - Mo-Xian Chen
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China and College of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China
| | - Yue-Qing Zheng
- Guang Zhou Zengcheng District Centre for Disease Control and Prevention, Guang Dong, 511300, China
| | - Xin Xie
- School of Life and Environmental Sciences, Shaoxing University, Shaoxing, 312000, Zhejiang, China
| | - Rongxin Zhang
- School of Life Sciences and Biopharmaceutics, Guang Dong Pharmaceutical University, Guangzhou, 51006, China.
| | - Shan-Shan Wang
- School of Life Sciences and Biopharmaceutics, Guang Dong Pharmaceutical University, Guangzhou, 51006, China.
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