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Sesé L, Annesi-Maesano I. Lung cancer and idiopathic pulmonary fibrosis: environmental exposures are the key. Eur Respir J 2024; 63:2400760. [PMID: 38816038 DOI: 10.1183/13993003.00760-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 05/03/2024] [Indexed: 06/01/2024]
Affiliation(s)
- Lucile Sesé
- Department of Physiology and Functional Explorations, AP-HP, Hôpital Avicenne, INSERM UMR 1272 "Hypoxia and the Lung", Université Sorbonne Paris Nord, Bobigny, France
- Department of Pneumology, Constitutive Reference Center for Rare Lung Diseases, AP-HP, Hôpital Avicenne, Bobigny, France
| | - Isabella Annesi-Maesano
- Desbrest Institute of Epidemiology and Public Health, Univ Montpellier, INSERM, Montpellier, France
- Division of Respiratory Medicine, Allergology, and of Thoracic Oncology, University Hospital of Montpellier, Montpellier, France
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Tomoto M, Mineharu Y, Sato N, Tamada Y, Nogami-Itoh M, Kuroda M, Adachi J, Takeda Y, Mizuguchi K, Kumanogoh A, Natsume-Kitatani Y, Okuno Y. Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information. Sci Rep 2024; 14:1315. [PMID: 38225283 PMCID: PMC10789725 DOI: 10.1038/s41598-023-50905-8] [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: 08/17/2023] [Accepted: 12/27/2023] [Indexed: 01/17/2024] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-β signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.
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Affiliation(s)
- Mei Tomoto
- Department of Biomedical Data Intelligence, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Yohei Mineharu
- Department of Biomedical Data Intelligence, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
- Department of Artificial Intelligence in Healthcare and Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Noriaki Sato
- Department of Biomedical Data Intelligence, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
- Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokane-Dai, Minato-Ku, Tokyo, 108-8639, Japan
| | - Yoshinori Tamada
- Innovation Center for Health Promotion, Hirosaki University, 5 Zaifu-Cho Hirosaki City, Aomori, 036-8562, Japan
| | - Mari Nogami-Itoh
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, 3-17, Senrioka-Shinmachi, Settsu City, Osaka, 566-0002, Japan
| | - Masataka Kuroda
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, 3-17, Senrioka-Shinmachi, Settsu City, Osaka, 566-0002, Japan
- Discovery Technology Laboratories, Mitsubishi Tanabe Pharma Corporation, 1000, Kamoshida-cho, Aoba-ku, Yokohama, Kanagawa, 227-0033, Japan
| | - Jun Adachi
- Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito-Asagi, Ibaraki, Osaka, 567-0085, Japan
| | - Yoshito Takeda
- Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, 2-2 Yamada-Oka, Suita City, Osaka, 565-0871, Japan
| | - Kenji Mizuguchi
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, 3-17, Senrioka-Shinmachi, Settsu City, Osaka, 566-0002, Japan
- Institute for Protein Research, Osaka University, 3-2 Yamada-Oka, Suita City, Osaka, 565-0871, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, 2-2 Yamada-Oka, Suita City, Osaka, 565-0871, Japan
| | - Yayoi Natsume-Kitatani
- Innovation Center for Health Promotion, Hirosaki University, 5 Zaifu-Cho Hirosaki City, Aomori, 036-8562, Japan.
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, 3-17, Senrioka-Shinmachi, Settsu City, Osaka, 566-0002, Japan.
- Institute of Advanced Medical Sciences, Tokushima University, 3-18-15, Kuramoto-Cho, Tokushima City, Tokushima, 770-8503, Japan.
| | - Yasushi Okuno
- Department of Biomedical Data Intelligence, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
- Department of Artificial Intelligence in Healthcare and Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
- Biomedical Computational Intelligence Unit, HPC- and AI-Driven Drug Development Platform Division, RIKEN Center for Computational Science, 7-1-26, Minatojima-Minami-Machi, Chuo-Ku, Kobe, Hyogo, 650-0047, Japan.
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