| Grant number: | 22/02821-0 |
| Support Opportunities: | Research Grants - Initial Project |
| Start date: | February 01, 2023 |
| End date: | January 31, 2028 |
| Field of knowledge: | Health Sciences - Medicine - Medical Clinics |
| Principal Investigator: | Alexandre Todorovic Fabro |
| Grantee: | Alexandre Todorovic Fabro |
| Host Institution: | Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil |
| Associated researchers: | Andrea de Cássia Vernier Antunes Cetlin ; Fernando de Queiroz Cunha ; Grazyna Kwapiszewska - Marsh ; Karin Mueller Storrer ; Marcel Koenigkam Santos ; Paulo Mazzoncini de Azevedo Marques ; Robson Francisco Carvalho ; Rodrigo do Tocantins Calado de Saloma Rodrigues ; Tales Rubens de Nadai |
| Associated scholarship(s): | 23/10186-6 - Pathology of Progressive Fibrosing Interstitial Lung Disease,
BP.DR 23/04199-8 - Biomarker Profiling of the Progressive Fibrosing Interstitial Lung Disease. Why does it progress and how to identify it early?, BP.IC |
Abstract
Patients with fibrosing interstitial lung disease (ILD), such as hypersensitivity pneumonitis, highly prevalent in Brazil, may develop acute exacerbations, despite an optimal treatment established, thus promoting a progressive phenotype of high morbidity and mortality in one third of them. Objectives: to unravel the pathophysiology of progressive fibrosing ILDs by validating biomarkers of its progression. Patient and Methods: Spatial transcriptome will be performed on surgical lung biopsy of 5 patients with progressive fibrosing ILD and 5 with stable ILD, in addition to 6 with exacerbations by minimally invasive autopsy. Confirmation of the findings will be performed by immunohistochemistry, qPCR and transmission electron microscopy with immunogold. Validation will be performed in 200 patients with fibrosing ILDs and 50 controls (lung cancer) by immunohostochemistry/morphometry and qPCR in transbronchial biopsy and flow cytometry in bronchoalveolar lavage. Clinical-radiopathological evaluation will be performed in all cases, including radiogenomics. Data integration will be analyzed by bioinformatics, deep learning and artificial intelligence. Expected Results: to identify the molecular pathways that promote exacerbations and the consequent progression of fibrosis through the integration of transcriptomic, molecular and clinical-radiopathological data, in order to temporally make up the natural history of disease, thus determining the pathophysiological process and its biomarkers capable of predicting the phenotype of progressive fibrosing ILD in the initial phase of disease. (AU)
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