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Alizadeh J, da Silva Rosa SC, Cordani M, Ghavami S. Evaluation of Mitochondrial Phagy (Mitophagy) in Human Non-small Adenocarcinoma Tumor Cells. Methods Mol Biol 2024. [PMID: 38607594 DOI: 10.1007/7651_2024_532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Non-small cell lung cancer (NSCLC) is a predominant form of lung cancer characterized by its aggressive nature and high mortality rate, primarily due to late-stage diagnosis and metastatic spread. Recent studies underscore the pivotal role of mitophagy, a selective form of autophagy targeting damaged or superfluous mitochondria, in cancer biology, including NSCLC. Mitophagy regulation may influence cancer cell survival, proliferation, and metastasis by modulating mitochondrial quality and cellular energy homeostasis. Herein, we present a comprehensive methodology developed in our laboratory for the evaluation of mitophagy in NSCLC tumor cells. Utilizing a combination of immunoblotting, immunocytochemistry, and fluorescent microscopy, we detail the steps to quantify early and late mitophagy markers and mitochondrial dynamics. Our findings highlight the potential of targeting mitophagy pathways as a novel therapeutic strategy in NSCLC, offering insights into the complex interplay between mitochondrial dysfunction and tumor progression. This study not only sheds light on the significance of mitophagy in NSCLC but also establishes a foundational approach for its investigation, paving way for future research in this critical area of cancer biology.
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Affiliation(s)
- Javad Alizadeh
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Simone C da Silva Rosa
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Marco Cordani
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Complutense University of Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
| | - Saeid Ghavami
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
- Faculty of Medicine in Zabrze, University of Technology in Katowice, Zabrze, Poland.
- Research Institute of Oncology and Hematology, Cancer Care Manitoba, University of Manitoba, Winnipeg, MB, Canada.
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Wang F, Zhao D, Xu WY, Liu Y, Sun H, Lu S, Ji Y, Jiang J, Chen Y, He Q, Gong C, Liu R, Su Z, Dong Y, Yan Z, Liu L. Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study. BMC Med 2024; 22:147. [PMID: 38561764 PMCID: PMC10986011 DOI: 10.1186/s12916-024-03368-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy. METHODS This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes. RESULTS The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies. CONCLUSIONS This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.
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Affiliation(s)
- Feihang Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Danyang Zhao
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Wang-Yang Xu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Yiying Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Huiyi Sun
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Shanshan Lu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jingjing Jiang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yi Chen
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Qiye He
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | | | - Rui Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Zhixi Su
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China.
| | - Yi Dong
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
| | - Zhiping Yan
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
| | - Lingxiao Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
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Li Q, Liu G, Qiu Q, Zhang J, Li R, Zhao J, She J, Chen Y. Establish a novel tumor budding-related signature to predict prognosis and guide clinical therapy in colorectal cancer. Sci Rep 2024; 14:2180. [PMID: 38273073 PMCID: PMC10810877 DOI: 10.1038/s41598-024-52596-1] [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: 10/12/2023] [Accepted: 01/21/2024] [Indexed: 01/27/2024] Open
Abstract
Tumor budding is a long-established independent adverse prognostic marker for colorectal cancer (CRC), yet assessment of tumor budding was not reproducible. Therefore, development of precise diagnostic approaches to tumor budding is in demand. In this study, we first performed bioinformatic analysis in our single-center CRC patients' cohort (n = 84) and identified tumor budding-associated hub genes using the weighted gene co-expression network analysis (WGCNA). A machine learning methodology was used to identify hub genes and construct a prognostic signature. Nomogram model was used to identified hub genes score for tumor budding, and the receiver operating characteristic (ROC) curve and calibration plot indicated high accuracy and stability of hub gene score for predicted the prognosis of CRC. The association between budding-associated hub genes and score and prognosis of CRC were further verified in TCGA CRC cohort (n = 342). Then gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied to explore the signaling pathways related to the tumor budding and validated by immunohistochemistry (IHC) of our clinical samples. Subsequently, immune infiltration analysis demonstrated that there was a high correlation between hub genes score and M2-like macrophages infiltrated in tumor tissue. In addition, somatic mutation and chemotherapeutic response prediction were analyzed based on the risk signature. In summary, we established a tumor budding diagnostic molecular model, which can improve tumor budding assessment and provides a promising novel molecular marker for immunotherapy and prognosis of CRC.
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Affiliation(s)
- Qixin Li
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Gaixia Liu
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Quanpeng Qiu
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jiaqi Zhang
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Ruizhe Li
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jiamian Zhao
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Junjun She
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China.
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
| | - Yinnan Chen
- Center for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China.
- Department of High Talent, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
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Li X, Li J, Li J, Liu N, Zhuang L. Development and validation of epigenetic modification-related signals for the diagnosis and prognosis of colorectal cancer. BMC Genomics 2024; 25:51. [PMID: 38212708 PMCID: PMC10782594 DOI: 10.1186/s12864-023-09815-2] [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: 03/21/2023] [Accepted: 11/18/2023] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is one of the world's most common malignancies. Epigenetics is the study of heritable changes in characteristics beyond the DNA sequence. Epigenetic information is essential for maintaining specific expression patterns of genes and the normal development of individuals, and disorders of epigenetic modifications may alter the expression of oncogenes and tumor suppressor genes and affect the development of cancer. This study elucidates the relationship between epigenetics and the prognosis of CRC patients by developing a predictive model to explore the potential value of epigenetics in the treatment of CRC. METHODS Gene expression data of CRC patients' tumor tissue and controls were downloaded from GEO database. Combined with the 720 epigenetic-related genes (ERGs) downloaded from EpiFactors database, prognosis-related epigenetic genes were selected by univariate cox and LASSO analyses. The Kaplan-Meier and ROC curve were used to analyze the accuracy of the model. Data of 238 CRC samples with survival data downloaded from the GSE17538 were used for validation. Finally, the risk model is combined with the clinical characteristics of CRC patients to perform univariate and multivariate cox regression analysis to obtain independent risk factors and draw nomogram. Then we evaluated the accuracy of its prediction by calibration curves. RESULTS A total of 2906 differentially expressed genes (DEGs) were identified between CRC and control samples. After overlapping DEGs with 720 ERGs, 56 epigenetic-related DEGs (DEERGs) were identified. Combining univariate and LASSO regression analysis, the 8 epigenetic-related genes-based risk score model of CRC was established. The ROC curves and survival difference of high and low risk groups revealed the good performance of the risk score model based on prognostic biomarkers in both training and validation sets. A nomogram with good performance to predict the survival of CRC patients were established based on age, NM stage and risk score. The calibration curves showed that the prognostic model had good predictive performance. CONCLUSION In this study, an epigenetically relevant 8-gene signature was constructed that can effectively predict the prognosis of CRC patients and provide potential directions for targeted therapies for CRC.
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Affiliation(s)
- Xia Li
- Department of Gastroenterology and Hepatology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China
| | - Jingjing Li
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, Heilongjiang Province, China
| | - Jie Li
- Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, Heilongjiang Province, China
| | - Nannan Liu
- Department of Gastroenterology and Hepatology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China
| | - Liwei Zhuang
- Department of Gastroenterology and Hepatology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China.
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Gao H, Zou Q, Ma L, Cai K, Sun Y, Lu L, Ren D, Hu B. Unveiling mitophagy-mediated molecular heterogeneity and development of a risk signature model for colorectal cancer by integrated scRNA-seq and bulk RNA-seq analysis. Gastroenterol Rep (Oxf) 2023; 11:goad066. [PMID: 37886241 PMCID: PMC10598840 DOI: 10.1093/gastro/goad066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/03/2023] [Accepted: 09/22/2023] [Indexed: 10/28/2023] Open
Abstract
Background Accumulating researchers have recognized mitophagy as a key player in tumors, but few studies have investigated its role in the tumor microenvironment (TME). Advances in the technology of single-cell RNA sequencing (scRNA-seq) have allowed unveiling the concealed features of the TME at cellular resolution. This study aimed to elucidate the role of mitophagy within the TME of colorectal cancer (CRC) and to establish a mitophagy-mediated risk model. Methods We assessed mitophagy-related pathway activities at both single-cell and tissue levels. Subsequently, an unsupervised clustering algorithm was employed to identify mitophagy-mediated subtypes. Furthermore, we developed a mitophagy-mediated risk signature (MMRS) using least absolute shrinkage and selection operator (LASSO) Cox analysis and constructed a MMRS model incorporating the risk score and clinical variables. Subsequently, we used quantitative reverse transcription polymerase chain reaction analysis to verify the expression of the screened genes. Results We retrieved and annotated a total of 14,719 cells from eight samples in the scRNA-seq GSE132465 data set. The activities of mitophagy-related pathways were uniformly upregulated in cancer cells. Integrating with bulk RNA-seq data, we identified two mitophagy-mediated clusters (C1 and C2) with distinct characteristics and prognoses. C2 was identified as a mitophagy-high cluster. Then, we developed a five-gene MMRS via LASSO Cox analysis in The Cancer Genome Atlas (TCGA) cohort. We utilized the GSE39582 cohort to validate the efficacy of our model. The expression of CX3CL1 and INHBB was upregulated in CRC tissues. Conclusions The present study identified two mitophagy-mediated CRC subtypes with distinct features. Our MMRS may provide potential therapeutic strategies for CRC. The findings of our work offer novel insights into the involvement of mitophagy in CRC.
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Affiliation(s)
- Han Gao
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Qi Zou
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Linyun Ma
- Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Keyu Cai
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Yi Sun
- Department of Pathology, Kingmed Pathology Center, Guangzhou, Guangdong, P. R. China
| | - Li Lu
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Donglin Ren
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Bang Hu
- Department of General Surgery (Coloproctology), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
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Pei Y, Chen S, Zhou F, Xie T, Cao H. Construction and evaluation of Alzheimer's disease diagnostic prediction model based on genes involved in mitophagy. Front Aging Neurosci 2023; 15:1146660. [PMID: 37032823 PMCID: PMC10077494 DOI: 10.3389/fnagi.2023.1146660] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is a common neurodegenerative disease. The concealment of the disease is the difficulty of its prevention and treatment. Previous studies have shown that mitophagy is crucial to the development of AD. However, there is a lack of research on the identification and clinical significance of mitophagy-related genes in AD. Therefore, the purpose of this study was to identify the mitophagy-related genes with the diagnostic potential for AD and establish a diagnostic model for AD. Methods Firstly, we download the AD gene expression profile from Gene Expression Omnibus (GEO). Limma, PPI, functional enrichment analysis and WGCNA were used to screen the differential expression of mitophagy-related AD gene. Then, machine learning methods (random forest, univariate analysis, support vector machine, LASSO regression and support vector machine classification) were used to identify diagnostic markers. Finally, the diagnostic model was established and evaluated by ROC, multiple regression analysis, nomogram, calibration curve and other methods. Moreover, multiple independent datasets, AD cell models and AD clinical samples were used to verify the expression level of characteristic genes in the diagnostic model. Results In total, 72 differentially expressed mitophagy-related related genes were identified, which were mainly involved in biological functions such as autophagy, apoptosis and neurological diseases. Four mitophagy-related genes (OPTN, PTGS2, TOMM20, and VDAC1) were identified as biomarkers. A diagnostic prediction model was constructed, and the reliability of the model was verified by receiver operating characteristic (ROC) curve analysis of GSE122063 and GSE63061. Then, we combine four mitophagy-related genes with age to establish a nomogram model. The ROC, C index and calibration curve show that the model has good prediction performance. Finally, multiple independent datasets, AD cell model samples and clinical peripheral blood samples confirmed that the expression levels of four mitophagy-related genes were consistent with the results of bioinformatics analysis. Discussion The analysis results and diagnostic model of this study are helpful for the follow-up clinical work and mechanism research of AD.
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Affiliation(s)
- Yongyan Pei
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, China
| | - Sijia Chen
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, China
| | - Fengling Zhou
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, China
| | - Tao Xie
- Department of Neurology, The Third Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Hua Cao
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, China
- *Correspondence: Hua Cao,
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