Understanding the complexities of the tumor microenvironment and its response to ablation is crucial for developing strategies to mitigate local tumor recurrence. Advancing technologies allow to microscopically characterize tumor composition and microenvironment in all its complexity, specifically immune landscape, genomic composition and radiomic features. This thesis project presents an insight of their value as biomarkers of response, the interplay among them and ablative therapies. In the first part of the research, an analysis of the immune landscape of HCC undergoing microwave ablations found that an increase in neutrophil to lymphocyte ratio (NLR) may independently predict local tumor progression. Moreover, higher ablation energy may induce lower post-ablation NLR. In the second chapter, a prospective analysis of blood-based genomic biomarkers (tumor mutational burden, circulating tumor DNA) on patients undergoing curative ablative therapies for primary and metastatic disease was carried out offering preliminary insights about interaction between ablation protocol and biomarker variation one-month post-ablation. In the final chapter, radiomic analysis on MRI images of colorectal liver metastases was found to be able to predict LTP after microwave ablation. Furthermore, radiomic models for non-invasive identification of pathologically relevant mutations and intratumoral CD8+ T lymphocytes clusters were built. Overall, this thesis contributes to the growing field of personalized medicine in oncology, highlighting the importance of a multi-dimensional approach that combines radiomic, genomic, and immunological data for better understanding and predicting treatment outcomes in cancer patients.

Understanding the complexities of the tumor microenvironment and its response to ablation is crucial for developing strategies to mitigate local tumor recurrence. Advancing technologies allow to microscopically characterize tumor composition and microenvironment in all its complexity, specifically immune landscape, genomic composition and radiomic features. This thesis project presents an insight of their value as biomarkers of response, the interplay among them and ablative therapies. In the first part of the research, an analysis of the immune landscape of HCC undergoing microwave ablations found that an increase in neutrophil to lymphocyte ratio (NLR) may independently predict local tumor progression. Moreover, higher ablation energy may induce lower post-ablation NLR. In the second chapter, a prospective analysis of blood-based genomic biomarkers (tumor mutational burden, circulating tumor DNA) on patients undergoing curative ablative therapies for primary and metastatic disease was carried out offering preliminary insights about interaction between ablation protocol and biomarker variation one-month post-ablation. In the final chapter, radiomic analysis on MRI images of colorectal liver metastases was found to be able to predict LTP after microwave ablation. Furthermore, radiomic models for non-invasive identification of pathologically relevant mutations and intratumoral CD8+ T lymphocytes clusters were built. Overall, this thesis contributes to the growing field of personalized medicine in oncology, highlighting the importance of a multi-dimensional approach that combines radiomic, genomic, and immunological data for better understanding and predicting treatment outcomes in cancer patients.

INVESTIGATION OF BIOMARKERS OF TREATMENT RESPONSE IMPACT OF LOCO-REGIONAL THERAPIES ON TUMOR MICROENVIRONMENT AND IMMUNOGENICITY

DELLA CORTE, ANGELO
2024

Abstract

Understanding the complexities of the tumor microenvironment and its response to ablation is crucial for developing strategies to mitigate local tumor recurrence. Advancing technologies allow to microscopically characterize tumor composition and microenvironment in all its complexity, specifically immune landscape, genomic composition and radiomic features. This thesis project presents an insight of their value as biomarkers of response, the interplay among them and ablative therapies. In the first part of the research, an analysis of the immune landscape of HCC undergoing microwave ablations found that an increase in neutrophil to lymphocyte ratio (NLR) may independently predict local tumor progression. Moreover, higher ablation energy may induce lower post-ablation NLR. In the second chapter, a prospective analysis of blood-based genomic biomarkers (tumor mutational burden, circulating tumor DNA) on patients undergoing curative ablative therapies for primary and metastatic disease was carried out offering preliminary insights about interaction between ablation protocol and biomarker variation one-month post-ablation. In the final chapter, radiomic analysis on MRI images of colorectal liver metastases was found to be able to predict LTP after microwave ablation. Furthermore, radiomic models for non-invasive identification of pathologically relevant mutations and intratumoral CD8+ T lymphocytes clusters were built. Overall, this thesis contributes to the growing field of personalized medicine in oncology, highlighting the importance of a multi-dimensional approach that combines radiomic, genomic, and immunological data for better understanding and predicting treatment outcomes in cancer patients.
16-apr-2024
Inglese
Understanding the complexities of the tumor microenvironment and its response to ablation is crucial for developing strategies to mitigate local tumor recurrence. Advancing technologies allow to microscopically characterize tumor composition and microenvironment in all its complexity, specifically immune landscape, genomic composition and radiomic features. This thesis project presents an insight of their value as biomarkers of response, the interplay among them and ablative therapies. In the first part of the research, an analysis of the immune landscape of HCC undergoing microwave ablations found that an increase in neutrophil to lymphocyte ratio (NLR) may independently predict local tumor progression. Moreover, higher ablation energy may induce lower post-ablation NLR. In the second chapter, a prospective analysis of blood-based genomic biomarkers (tumor mutational burden, circulating tumor DNA) on patients undergoing curative ablative therapies for primary and metastatic disease was carried out offering preliminary insights about interaction between ablation protocol and biomarker variation one-month post-ablation. In the final chapter, radiomic analysis on MRI images of colorectal liver metastases was found to be able to predict LTP after microwave ablation. Furthermore, radiomic models for non-invasive identification of pathologically relevant mutations and intratumoral CD8+ T lymphocytes clusters were built. Overall, this thesis contributes to the growing field of personalized medicine in oncology, highlighting the importance of a multi-dimensional approach that combines radiomic, genomic, and immunological data for better understanding and predicting treatment outcomes in cancer patients.
DE COBELLI, FRANCESCO
Università Vita-Salute San Raffaele
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/87592
Il codice NBN di questa tesi è URN:NBN:IT:UNISR-87592