Immune-Blood. Peripheral Immune Response Biomarkers Study On Blood And Tissue Samples Collected Over Time

[eng] Background: Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer but many patients remain not benefiting from them. Improve patient selection is mandatory. Methods: Blood samples were collected at cycle 1 (C1D1) and 2 (C2D1) and at the time of every tumora...

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Detalles Bibliográficos
Autor: García Corbacho, Javier
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/228374
Acceso en línea:https://hdl.handle.net/2445/228374
http://hdl.handle.net/10803/697048
Access Level:acceso abierto
Palabra clave:Immunoteràpia
Limfòcits
Immunotheraphy
Lymphocytes
Descripción
Sumario:[eng] Background: Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer but many patients remain not benefiting from them. Improve patient selection is mandatory. Methods: Blood samples were collected at cycle 1 (C1D1) and 2 (C2D1) and at the time of every tumoral response assessment until the occurrence of progressive disease (PD). Electronic patient charts were reviewed to collect relevant clinical information and blood test results. Baseline prognostic scores were calculated (LNR: lymphocyte neutrophil ratio. dNLR: derive neutrophil lymphocyte ratio. LIPI: lung immune prognosis index. RMH: Royal Marsden Hospital score. PMH: Princess Margaret Hospital score. GRIm: Gustave Roussy Immune Score. PIPO: Phase I Prognostic Online score). Once we had selected the best score, we analyzed its association at C1D1, C2D1 and its dynamics with overall survival (OS) and progression free survival (PFS). PDL1 status was collected from patient charts. Pre-ICI archived tissues were retrieved to evaluate tumor-infiltrating lymphocytes (TILs) and PD1 mRNA levels. Tumor assessments were centrally reviewed by RECIST 1.1 / RANO criteria. Associations with objective response rates (ORR), durable clinical benefit (DCB), PFS and OS were performed with univariable/multivariable logistic and Cox regressions, where appropriate. Mean and standard deviations of each subpopulation/timepoint were calculated. Kapplan Meier curves, ANOVA, pairwise comparison, logistic regressions, hazard ratios (HR), odd ratios (OR), Cox regressions and area under curve (AUC), were performed where appropriate. Objectives: Primary objective was the serial assessment of lymphocytes subpopulation levels over time as biomarker of response or resistance to immunotherapies. Secondary objectives included the study of 1) the correlation of baseline clinicopathological factors to response and survival in ICI a multitumor ICI treated population, 2) the role of PD1 mRNA levels, PD-L1 and TILs levels as predictor of response or resistance to immunotherapies and 3) the correlation of published prognosis scores and early dynamics with ICI outcomes.