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Liu B, Zhang X, Liu Z, Pan H, Yang H, Wu Q, Lv Y, Shen T. A novel model for predicting prognosis in patients with idiopathic pulmonary fibrosis based on endoplasmic reticulum stress-related genes. Cell Biol Int 2024; 48:483-495. [PMID: 38238919 DOI: 10.1002/cbin.12121] [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: 06/09/2023] [Revised: 12/08/2023] [Accepted: 12/21/2023] [Indexed: 03/13/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease of unknown pathogenic origin. Endoplasmic reticulum (ER) stress refers to the process by which cells take measures to ER function when the morphology and function of the reticulum are changed. Recent studies have demonstrated that the ER was involved in the evolution and progression of IPF. In this study, we obtained transcriptome data and relevant clinical information from the Gene Expression Omnibus database and conducted bioinformatics analysis. Among the 544 ER stress-related genes (ERSRGs), 78 were identified as differentially expressed genes (DEGs). These DEGs were primarily enriched in response to ER stress, protein binding, and protein processing. Two genes (HTRA2 and KTN1) were included for constructing an accurate molecular signature. The overall survival of patients was remarkably worse in the high-risk group than in the low-risk group. We further analyzed the difference in immune cells between high-risk and low-risk groups. M0 and M2 macrophages were significantly increased in the high-risk group. Our results suggested that ERSRGs might play a critical role in the development of IPF by regulating the immune microenvironment in the lungs, which provide new insights on predicting the prognosis of patients with IPF.
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Affiliation(s)
- Bin Liu
- Department of Medical Aspects of Specifc Environments, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Xiang Zhang
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Zikai Liu
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Haihong Pan
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Hongxu Yang
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Qing Wu
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Yan Lv
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Tong Shen
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
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Hu W, Xu Y. Transcriptomics in idiopathic pulmonary fibrosis unveiled: a new perspective from differentially expressed genes to therapeutic targets. Front Immunol 2024; 15:1375171. [PMID: 38566986 PMCID: PMC10985171 DOI: 10.3389/fimmu.2024.1375171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Background The underlying molecular pathways of idiopathic pulmonary fibrosis (IPF), a progressive lung condition with a high death rate, are still mostly unknown. By using microarray datasets, this study aims to identify new genetic targets for IPF and provide light on the genetic factors that contribute to the development of IPF. Method We conducted a comprehensive analysis of three independent IPF datasets from the Gene Expression Omnibus (GEO) database, employing R software for data handling and normalization. Our evaluation of the relationships between differentially expressed genes (DEGs) and IPF included differential expression analysis, expression quantitative trait loci (eQTL) analysis, and Mendelian Randomization(MR) analyses. Additionally, we used Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore the functional roles and pathways of these genes. Finally, we validated the results obtained for the target genes. Results We identified 486 highly expressed genes and 468 lowly expressed genes that play important roles in IPF. MR analysis identified six significantly co-expressed genes associated with IPF, specifically C12orf75, SPP1, ZG16B, LIN7A, PPP1R14A, and TLR2. These genes participate in essential biological processes and pathways, including macrophage activation and neural system regulation. Additionally, CIBERSORT analysis indicated a unique immune cell distribution in IPF, emphasized the significance of immunological processes in the disease. The MR analysis was consistent with the results of the analysis of variance in the validation cohort, which strengthens the reliability of our MR findings. Conclusion Our findings provide new insights into the molecular basis of IPF and highlight the promise of therapeutic interventions. They emphasize the potential of targeting specific molecular pathways for the treatment of IPF, laying the foundation for further research and clinical work.
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Affiliation(s)
- Wenzhong Hu
- Guang’anmen Hospital South Campus, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yun Xu
- People's Hospital of Beijing Daxing District, Capital Medical University, Beijing, China
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Perez-Favila A, Garza-Veloz I, Hernandez-Marquez LDS, Gutierrez-Vela EF, Flores-Morales V, Martinez-Fierro ML. Antifibrotic Drugs against Idiopathic Pulmonary Fibrosis and Pulmonary Fibrosis Induced by COVID-19: Therapeutic Approaches and Potential Diagnostic Biomarkers. Int J Mol Sci 2024; 25:1562. [PMID: 38338840 PMCID: PMC10855955 DOI: 10.3390/ijms25031562] [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: 12/30/2023] [Revised: 01/22/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024] Open
Abstract
The COVID-19 pandemic has had a significant impact on the health and economy of the global population. Even after recovery from the disease, post-COVID-19 symptoms, such as pulmonary fibrosis, continue to be a concern. This narrative review aims to address pulmonary fibrosis (PF) from various perspectives, including the fibrotic mechanisms involved in idiopathic and COVID-19-induced pulmonary fibrosis. On the other hand, we also discuss the current therapeutic drugs in use, as well as those undergoing clinical or preclinical evaluation. Additionally, this article will address various biomarkers with usefulness for PF prediction, diagnosis, treatment, prognosis, and severity assessment in order to provide better treatment strategies for patients with this disease.
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Affiliation(s)
| | | | | | | | | | - Margarita L. Martinez-Fierro
- Doctorado en Ciencias con Orientación en Medicina Molecular, Unidad Académica de Medicina Humana y CS, Universidad Autónoma de Zacatecas, Zacatecas 98160, Mexico; (A.P.-F.); (I.G.-V.); (L.d.S.H.-M.); (E.F.G.-V.); (V.F.-M.)
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Yeo HJ, Ha M, Shin DH, Lee HR, Kim YH, Cho WH. Development of a Novel Biomarker for the Progression of Idiopathic Pulmonary Fibrosis. Int J Mol Sci 2024; 25:599. [PMID: 38203769 PMCID: PMC10779374 DOI: 10.3390/ijms25010599] [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: 11/22/2023] [Revised: 12/22/2023] [Accepted: 01/01/2024] [Indexed: 01/12/2024] Open
Abstract
The progression of idiopathic pulmonary fibrosis (IPF) is diverse and unpredictable. We identified and validated a new biomarker for IPF progression. To identify a candidate gene to predict progression, we assessed differentially expressed genes in patients with advanced IPF compared with early IPF and controls in three lung sample cohorts. Candidate gene expression was confirmed using immunohistochemistry and Western blotting of lung tissue samples from an independent IPF clinical cohort. Biomarker potential was assessed using an enzyme-linked immunosorbent assay of serum samples from the retrospective validation cohort. We verified that the final candidate gene reflected the progression of IPF in a prospective validation cohort. In the RNA-seq comparative analysis of lung tissues, CD276, COL7A1, CTSB, GLI2, PIK3R2, PRAF2, IGF2BP3, and NUPR1 were up-regulated, and ADAMTS8 was down-regulated in the samples of advanced IPF. Only CTSB showed significant differences in expression based on Western blotting (n = 12; p < 0.001) and immunohistochemistry between the three groups of the independent IPF cohort. In the retrospective validation cohort (n = 78), serum CTSB levels were higher in the progressive group (n = 25) than in the control (n = 29, mean 7.37 ng/mL vs. 2.70 ng/mL, p < 0.001) and nonprogressive groups (n = 24, mean 7.37 ng/mL vs. 2.56 ng/mL, p < 0.001). In the prospective validation cohort (n = 129), serum CTSB levels were higher in the progressive group than in the nonprogressive group (mean 8.30 ng/mL vs. 3.00 ng/mL, p < 0.001). After adjusting for baseline FVC, we found that CTSB was independently associated with IPF progression (adjusted OR = 2.61, p < 0.001). Serum CTSB levels significantly predicted IPF progression (AUC = 0.944, p < 0.001). Serum CTSB level significantly distinguished the progression of IPF from the non-progression of IPF or healthy control.
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Affiliation(s)
- Hye Ju Yeo
- Department of Internal Medicine, School of Medicine, Pusan National University, Yangsan 50612, Republic of Korea;
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; (D.H.S.); (H.R.L.)
| | - Mihyang Ha
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan 46241, Republic of Korea;
- Department of Nuclear Medicine, Pusan National University Medical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
| | - Dong Hoon Shin
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; (D.H.S.); (H.R.L.)
- Department of Pathology, School of Medicine, Pusan National University, Yangsan 50612, Republic of Korea
| | - Hye Rin Lee
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; (D.H.S.); (H.R.L.)
| | - Yun Hak Kim
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan 50612, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan 50612, Republic of Korea
| | - Woo Hyun Cho
- Department of Internal Medicine, School of Medicine, Pusan National University, Yangsan 50612, Republic of Korea;
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; (D.H.S.); (H.R.L.)
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He J, Hu J, Liu H. A three-gene random forest model for diagnosing idiopathic pulmonary fibrosis based on circadian rhythm-related genes in lung tissue. Expert Rev Respir Med 2023; 17:1307-1320. [PMID: 38285622 DOI: 10.1080/17476348.2024.2311262] [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: 12/13/2023] [Accepted: 01/24/2024] [Indexed: 01/31/2024]
Abstract
BACKGROUND The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease Therefore, our study aims to determine the diagnostic value of circadian rhythm-related genes (CRRGs) in IPF. METHODS We retrieved the data on CRRGs from previous studies and the GSE150910 dataset. The participants from the GSE150910 dataset were divided into training and internal validation sets. Next, we used several various bioinformatics methods and machine learning algorithms to screen genes. Next, we identified SEMA5A, COL7A1, and TUBB3, which were included in the random forest (RF) diagnostic model. Finally, external validation was conducted on data retrieved from the GSE184316 datasets. RESULTS The results revealed that the RF diagnostic model could diagnose patients with IPF in the internal validation set with the area under the ROC curve (AUC) value of 0.905 and in the external validation with the AUC value of 0.767. Furthermore, real-time quantitative PCR and western blotting results revealed a significant decrease in SEMA5A (p < 0.05) expression level and an increase in COL7A1 and TUBB3 expression levels in TGF-β1-treated normal human lung fibroblasts. CONCLUSION We constructed an RF diagnostic model based on SEMA5A, COL7A1, and TUBB3 expression in lung tissue for diagnosing patients with IPF.
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Affiliation(s)
- Jie He
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
| | - Jun Hu
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Otolaryngology - Head and Neck Surgery, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
| | - Hairong Liu
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Geriatric Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
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Lao P, Chen J, Tang L, Zhang J, Chen Y, Fang Y, Fan X. Regulatory T cells in lung disease and transplantation. Biosci Rep 2023; 43:BSR20231331. [PMID: 37795866 PMCID: PMC10611924 DOI: 10.1042/bsr20231331] [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: 08/07/2023] [Revised: 09/28/2023] [Accepted: 10/04/2023] [Indexed: 10/06/2023] Open
Abstract
Pulmonary disease can refer to the disease of the lung itself or the pulmonary manifestations of systemic diseases, which are often connected to the malfunction of the immune system. Regulatory T (Treg) cells have been shown to be important in maintaining immune homeostasis and preventing inflammatory damage, including lung diseases. Given the increasing amount of evidence linking Treg cells to various pulmonary conditions, Treg cells might serve as a therapeutic strategy for the treatment of lung diseases and potentially promote lung transplant tolerance. The most potent and well-defined Treg cells are Foxp3-expressing CD4+ Treg cells, which contribute to the prevention of autoimmune lung diseases and the promotion of lung transplant rejection. The protective mechanisms of Treg cells in lung disease and transplantation involve multiple immune suppression mechanisms. This review summarizes the development, phenotype and function of CD4+Foxp3+ Treg cells. Then, we focus on the therapeutic potential of Treg cells in preventing lung disease and limiting lung transplant rejection. Furthermore, we discussed the possibility of Treg cell utilization in clinical applications. This will provide an overview of current research advances in Treg cells and their relevant application in clinics.
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Affiliation(s)
- Peizhen Lao
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Jingyi Chen
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Longqian Tang
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Jiwen Zhang
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Yuxi Chen
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Yuyin Fang
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
| | - Xingliang Fan
- Institute of Biological and Food Engineering, Guangdong University of Education, 351 Xingang Middle Road, Guangzhou 510303, PR China
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Velázquez-Enríquez JM, Reyes-Avendaño I, Santos-Álvarez JC, Reyes-Jiménez E, Vásquez-Garzón VR, Baltiérrez-Hoyos R. Identification of Hub Genes in Idiopathic Pulmonary Fibrosis and Their Association with Lung Cancer by Bioinformatics Analysis. Adv Respir Med 2023; 91:407-431. [PMID: 37887075 PMCID: PMC10604190 DOI: 10.3390/arm91050032] [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: 08/31/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible disease with a high mortality rate worldwide. However, the etiology and pathogenesis of IPF have not yet been fully described. Moreover, lung cancer is a significant complication of IPF and is associated with increased mortality. Nevertheless, identifying common genes involved in developing IPF and its progression to lung cancer remains an unmet need. The present study aimed to identify hub genes related to the development of IPF by meta-analysis. In addition, we analyzed their expression and their relationship with patients' progression in lung cancer. METHOD Microarray datasets GSE24206, GSE21369, GSE110147, GSE72073, and GSE32539 were downloaded from Gene Expression Omnibus (GEO). Next, we conducted a series of bioinformatics analysis to explore possible hub genes in IPF and evaluated the expression of hub genes in lung cancer and their relationship with the progression of different stages of cancer. RESULTS A total of 1888 differentially expressed genes (DEGs) were identified, including 1105 upregulated and 783 downregulated genes. The 10 hub genes that exhibited a high degree of connectivity from the PPI network were identified. Analysis of the KEGG pathways showed that hub genes correlate with pathways such as the ECM-receptor interaction. Finally, we found that these hub genes are expressed in lung cancer and are associated with the progression of different stages of lung cancer. CONCLUSIONS Based on the integration of GEO microarray datasets, the present study identified DEGs and hub genes that could play an essential role in the pathogenesis of IPF and its association with the development of lung cancer in these patients, which could be considered potential diagnostic biomarkers or therapeutic targets for the disease.
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Affiliation(s)
- Juan Manuel Velázquez-Enríquez
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
| | - Itayetzi Reyes-Avendaño
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
| | - Jovito Cesar Santos-Álvarez
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
| | - Edilburga Reyes-Jiménez
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
| | - Verónica Rocío Vásquez-Garzón
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
- CONAHCYT-Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico
| | - Rafael Baltiérrez-Hoyos
- Laboratorio de Fibrosis y Cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico; (J.M.V.-E.); (I.R.-A.); (J.C.S.-Á.); (E.R.-J.); (V.R.V.-G.)
- CONAHCYT-Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda de Aguilera S/N, Sur, San Felipe del Agua, Oaxaca 68020, Mexico
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Li Z, Wang S, Zhao H, Yan P, Yuan H, Zhao M, Wan R, Yu G, Wang L. Artificial neural network identified the significant genes to distinguish Idiopathic pulmonary fibrosis. Sci Rep 2023; 13:1225. [PMID: 36681777 PMCID: PMC9867697 DOI: 10.1038/s41598-023-28536-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/19/2023] [Indexed: 01/22/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease that causes irreversible damage to lung tissue characterized by excessive deposition of extracellular matrix (ECM) and remodeling of lung parenchyma. The current diagnosis of IPF is complex and usually completed by a multidisciplinary team including clinicians, radiologists and pathologists they work together and make decision for an effective treatment, it is imperative to introduce novel practical methods for IPF diagnosis. This study provided a new diagnostic model of idiopathic pulmonary fibrosis based on machine learning. Six genes including CDH3, DIO2, ADAMTS14, HS6ST2, IL13RA2, and IGFL2 were identified based on the differentially expressed genes in IPF patients compare to healthy subjects through a random forest classifier with the existing gene expression databases. An artificial neural network model was constructed for IPF diagnosis based these genes, and this model was validated by the distinctive public datasets with a satisfactory diagnostic accuracy. These six genes identified were significant correlated with lung function, and among them, CDH3 and DIO2 were further determined to be significantly associated with the survival. Putting together, artificial neural network model identified the significant genes to distinguish idiopathic pulmonary fibrosis from healthy people and it is potential for molecular diagnosis of IPF.
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Affiliation(s)
- Zhongzheng Li
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Shenghui Wang
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Huabin Zhao
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Peishuo Yan
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Hongmei Yuan
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Mengxia Zhao
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Ruyan Wan
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China
| | - Guoying Yu
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China.
| | - Lan Wang
- State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Science, Henan Normal University, 46 Jianshe Road, Xinxiang, 453007, Henan, China.
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