Metabólica y aprendizaje automático en la identificación de biomarcadores plasmáticos de cáncer de pulmón no microcítico: Impacto de la radioterapia

Identificador:  TDX:4527

Handle: https://hdl.handle.net/20.500.11797/TDX4527

Autores:  Murcia Mejia, Mauricio

Resumen:
diferentes respuestas metabólicas a la CRT y SBRT reflejan los diferentes impactos terapéuticos de estos tratamientos, subrayando la utilidad de la metabolómica para mejorar el diagnóstico y la respuesta al tratamiento en el CPNM. Lung cancer (LC) is the most commonly occurring cancer worldwide and the leading cause of cancer-related deaths globally, reported by Globocan 2022. In Spain LC is the fourth site of cancer in incidence and cancer deaths. Ideally what is needed is identifying sensitive and specific non-invasive blood biomarkers for early detection of LC and also biomarkers to determinate tumour response and progression. In cancer, metabolomics can be used to search and interpret the relationship between metabolites or intermediate metabolites and pathological mechanisms of diseases. The quantitative metabolomic profiling of plasma has been proposed as LC screening and prognostic biomarker. This PhD thesis explored shifts in circulating metabolite levels in NSCLC patients versus healthy controls and examined the effects of conventionally fractionated radiation therapy (CFRT) and stereotactic body radiation therapy (SBRT). We enrolled 91 NSCLC patients (38 CFRT and 53 SBRT) and 40 healthy controls. Plasma metabolite levels were assessed using semi-targeted metabolomics, revealing 32 elevated and 18 reduced metabolites in patients. Key discriminatory metabolites included ethylmalonic acid, maltose, 3-phosphoglyceric acid, taurine, glutamic acid, glycocolic acid, and d-arabinose, with a combined Receiver Operating Characteristics curve indicating perfect discrimination between patients and controls.