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Cheng S, Wang X, Yang S, Liang J, Song C, Zhu Q, Chen W, Ren Z, Zhu F. Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients. Skin Res Technol 2024; 30:e13814. [PMID: 38924611 PMCID: PMC11197043 DOI: 10.1111/srt.13814] [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: 04/26/2024] [Accepted: 06/04/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present. METHODS The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance. RESULTS A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses. CONCLUSION We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.
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Affiliation(s)
- Shengrong Cheng
- Department of Plastic SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Xin Wang
- Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
| | - Shuhan Yang
- Department of General SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Jiahui Liang
- Department of General SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Department of Breast SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Caiying Song
- Department of Plastic SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Qiuxuan Zhu
- Department of Plastic SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Wendong Chen
- Department of Plastic SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Zhiyao Ren
- Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
| | - Fei Zhu
- Department of Plastic SurgeryThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
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Chen L, Lin J, Wen Y, Lan B, Xiong J, Fu Y, Chen Y, Chen CB. A senescence-related lncRNA signature predicts prognosis and reflects immune landscape in HNSCC. Oral Oncol 2024; 149:106659. [PMID: 38134702 DOI: 10.1016/j.oraloncology.2023.106659] [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: 07/16/2023] [Revised: 11/15/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023]
Abstract
OBJECTIVE Long noncoding RNAs (lncRNAs) regulate cancer cell senescence in many cancers. However, their specific involvement in head and neck squamous cell carcinoma (HNSCC) remains unclear. We are looking for an ingenious prognostic signature that utilizes senescence-related lncRNAs (SRlncRNAs) to predict prognosis and provide insights into the immune landscape in HNSCC. MATERIALS AND METHODS HNSCC clinical and Cellular senescence genes information were collected from The Cancer Genome Atlas and Human Aging Genomic Resources. Then we performed Cox and Lasso regression to locate SRlncRNAs related to the prognosis of HNSCC and built a predictive signature. Further, prognosis assessment, potential mechanisms, and immune status were assessed by Kaplan-Meier analysis, Gene Set Enrichment Analysis (GSEA), and CIBERSORT, respectively. RESULTS A prognosis prediction model based on sixteen SRlncRNAs was identified and internally validated. Then, patients with high-risk scores suffered an unfavorable overall survival (All p < 0.05). The risk score, age, and stage were independent prognostic parameters (all p < 0.001). Our model has good predictive ability (The AUC (area under the curves) 1-year = 0.707, AUC3-year = 0.748 and AUC5-year = 0.779). Subsequently, GESA revealed SRlncRNAs regulated immune responses. Patients in the high-risk group had higher tumor mutation burden and Tumor Immune Dysfunction and Exclusion but lower levels of 37 immune checkpoint genes, immune scores, and immune cells like CD8 + T cells, follicular helper T cells, and regulatory T cells. CONCLUSIONS A prognostic model based on SRlncRNAs is the potential target for improving immunotherapy outcomes for HNSCC.
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Affiliation(s)
- Lizhu Chen
- Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China
| | - Jing Lin
- Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China
| | - Yaoming Wen
- Fujian Institute of Microbiology, Fuzhou, Fujian Province, China
| | - Bin Lan
- Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China
| | - Jiani Xiong
- Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China
| | - Yajuan Fu
- Fujian Key Laboratory of Innate Immune Biology, Biomedical Research Center of South China, College of Life Science, Fujian Normal University Qishan Campus, College Town, Fuzhou, Fujian Province, China
| | - Yu Chen
- Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China.
| | - Chuan-Ben Chen
- Cancer Bio-Immunotherapy Center, Clinical Oncology School of Fujian Medical University & Fujian Cancer Hospital, Fuzhou, Fujian Province, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian Province, China; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China.
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Han M, Wang Y, Huang X, Li P, Liang X, Wang R, Bao K. Identification of hub genes and their correlation with immune infiltrating cells in membranous nephropathy: an integrated bioinformatics analysis. Eur J Med Res 2023; 28:525. [PMID: 37974210 PMCID: PMC10652554 DOI: 10.1186/s40001-023-01311-3] [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: 03/04/2023] [Accepted: 08/24/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Membranous nephropathy (MN) is a chronic glomerular disease that leads to nephrotic syndrome in adults. The aim of this study was to identify novel biomarkers and immune-related mechanisms in the progression of MN through an integrated bioinformatics approach. METHODS The microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between MN and normal samples were identified and analyzed by the Gene Ontology analysis, the Kyoto Encyclopedia of Genes and Genomes analysis and the Gene Set Enrichment Analysis (GSEA) enrichment. Hub The hub genes were screened and identified by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm. The receiver operating characteristic (ROC) curves evaluated the diagnostic value of hub genes. The single-sample GSEA analyzed the infiltration degree of several immune cells and their correlation with the hub genes. RESULTS We identified a total of 574 DEGs. The enrichment analysis showed that metabolic and immune-related functions and pathways were significantly enriched. Four co-expression modules were obtained using WGCNA. The candidate signature genes were intersected with DEGs and then subjected to the LASSO analysis, obtaining a total of 6 hub genes. The ROC curves indicated that the hub genes were associated with a high diagnostic value. The CD4+ T cells, CD8+ T cells and B cells significantly infiltrated in MN samples and correlated with the hub genes. CONCLUSIONS We identified six hub genes (ZYX, CD151, N4BP2L2-IT2, TAPBP, FRAS1 and SCARNA9) as novel biomarkers for MN, providing potential targets for the diagnosis and treatment.
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Affiliation(s)
- Miaoru Han
- Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Yi Wang
- Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Xiaoyan Huang
- Guangdong-Hong Kong-Macau Joint Lab On Chinese Medicine and Immune Disease Research, Guangzhou, China
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Ping Li
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Xing Liang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Rongrong Wang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
| | - Kun Bao
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
- Guangdong-Hong Kong-Macau Joint Lab On Chinese Medicine and Immune Disease Research, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Disease, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
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Healthcare Engineering JO. Retracted: Construction of an Immune-Autophagy Prognostic Model Based on ssGSEA Immune Scoring Algorithm Analysis and Prognostic Value Exploration of the Immune-Autophagy Gene in Endometrial Carcinoma (EC) Based on Bioinformatics. JOURNAL OF HEALTHCARE ENGINEERING 2023; 2023:9834327. [PMID: 37860371 PMCID: PMC10584540 DOI: 10.1155/2023/9834327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 10/10/2023] [Indexed: 10/21/2023]
Abstract
[This retracts the article DOI: 10.1155/2022/7832618.].
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Shen X, Shang L, Han J, Zhang Y, Niu W, Liu H, Shi H. Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma. Front Genet 2023; 13:1095867. [PMID: 36685954 PMCID: PMC9845246 DOI: 10.3389/fgene.2022.1095867] [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: 11/11/2022] [Accepted: 12/02/2022] [Indexed: 01/06/2023] Open
Abstract
Skin cutaneous melanoma (SKCM) is the skin cancer that causes the highest number of deaths worldwide. There is growing evidence that the tumour immune microenvironment is associated with cancer prognosis, however, there is little research on the role of immune status in melanoma prognosis. In this study, data on patients with Skin cutaneous melanoma were downloaded from the GEO, TCGA, and GTEx databases. Genes associated with the immune pathway were screened from published papers and lncRNAs associated with them were identified. We performed immune microenvironment and functional enrichment analyses. The analysis was followed by applying univariate/multivariate Cox regression algorithms to finally identify three lncRNAs associated with the immune pathway for the construction of prognostic prediction models (CXCL10, RXRG, and SCG2). This stepwise downscaling method, which finally screens out prognostic factors and key genes and then uses them to build a risk model, has excellent predictive power. According to analyses of the model's reliability, it was able to differentiate the prognostic value and continued existence of Skin cutaneous melanoma patient populations more effectively. This study is an analysis of the immune pathway that leads lncRNAs in Skin cutaneous melanoma in an effort to open up new treatment avenues for Skin cutaneous melanoma.
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Yang X, Wang X, Sun X, Xiao M, Fan L, Su Y, Xue L, Luo S, Hou S, Wang H. Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma. Front Genet 2022; 13:972899. [PMID: 36160015 PMCID: PMC9490379 DOI: 10.3389/fgene.2022.972899] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022] Open
Abstract
Cuproptosis is a newly discovered new mechanism of programmed cell death, and its unique pathway to regulate cell death is thought to have a unique role in understanding cancer progression and guiding cancer therapy. However, this regulation has not been studied in SKCM at present. In this study, data on Skin Cutaneous Melanoma (SKCM) patients were downloaded from the TCGA database. We screened the genes related to cuproptosis from the published papers and confirmed the lncRNAs related to them. We applied Univariate/multivariate and LASSO Cox regression algorithms, and finally identified 5 cuproptosis-related lncRNAs for constructing prognosis prediction models (VIM-AS1, AC012443.2, MALINC1, AL354696.2, HSD11B1-AS1). The reliability and validity test of the model indicated that the model could well distinguish the prognosis and survival of SKCM patients. Next, immune microenvironment, immunotherapy analysis, and functional enrichment analysis were also performed. In conclusion, this study is the first analysis based on cuproptosis-related lncRNAs in SKCM and aims to open up new directions for SKCM therapy.
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Affiliation(s)
- Xiaojing Yang
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Xiaojing Yang, ; Huiping Wang,
| | - Xing Wang
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xinti Sun
- Department of Thoracic Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Xiao
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Liyun Fan
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yunwei Su
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Lu Xue
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Suju Luo
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Shuping Hou
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
| | - Huiping Wang
- Department of Dermatovenereology, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Xiaojing Yang, ; Huiping Wang,
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