Immunophenotyping: a promising non-invasive approach to predict response to atezolizumab-bevacizumab in advanced hepatocellular carcinoma

Suzzi, Fabrizia (2024) Immunophenotyping: a promising non-invasive approach to predict response to atezolizumab-bevacizumab in advanced hepatocellular carcinoma, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Scienze mediche generali e scienze dei servizi, 36 Ciclo.
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Abstract

The combination of atezolizumab plus bevacizumab represents improvement in the treatment of advanced HCC. Yet, the challenge of primary non-responses underscores the need for robust predictive biomarkers. Ongoing research efforts are crucial to address this gap to improve the effectiveness of immunotherapy in advanced HCC. Aiming to identify possible biomarkers predicting response to immunotherapy, we studied the immunophenotype of granulocytes and lymphocytes from peripheral blood using a simple cytofluorimetric test. A low baseline PD1+ granulocyte percentage is predictive of a benefit from atezolizumab–bevacizumab. We also observed that baseline CD8+ and CD8+PD-L1+ peripheral lymphocytes, as well as early changes in CD8+PD1+ lymphocytes in the first 3 weeks of treatment, could serve as predictors of response to atezolizumab–bevacizumab. Our observations highlight the potential utility of studying the immunophenotype of white blood cell populations as noninvasive markers in the setting of PD-L1 blockade in advanced HCC patients. Specifically, these markers could be used to predict treatment response before initiating therapy as well as early on treatment response. This approach aligns with the broader trend in medicine towards personalized approaches to better meet the needs of individual patients.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Suzzi, Fabrizia
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
36
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Hepatocellular carcinoma, immunophenotyping, PD1, PDL1, Imaging Mass Cytometry, tumor microenvironment.
URN:NBN
Data di discussione
24 Giugno 2024
URI

Altri metadati

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