Student Name: Alessio Fiorin​
Summary:
I am Alessio Fiorin, a PhD student of the Oncological Pathology and Bioinformatics group, located in the Hospital Tortosa Virgen de la Cinta, and part of the Pere Virgili Institute for Health Research (IISPV). I am enrolled in the Computer Science and Mathematics of Security doctoral program at the University of Rovira i Virgili. I completed my Master of Science degree in Artificial Intelligence & Cybersecurity in October 2022, with a mark of 110 cum laude. This is a double degree from the University of Udine and the University of Klagenfurt. Before that, I obtained my Bachelor of Science degree in Internet of Things, Big Data & Web from the University of Udine in October 2020, with a mark of 110 cum laude. I am always exploring new areas of interest, and I am currently fascinated by the potential of artificial intelligence to revolutionize the medical and healthcare fields. In my free time, I enjoy coding, expanding my network by meeting new people, and engaging in various sports activities. I hope to be a valuable addition to the BosomShield project.
Objectives:
The main objective is the identification of specific immune response patterns present in the primary tumour and in the axillary lymph nodes associated to the survival and relapse of the patients. This project will be performed in WSI of tissue microarrays (TMAs) obtained from biopsies of patients diagnosed with BC. The specific objectives will be: (1) To scan BC samples in different scanners and to test colour standardization procedures to the WSI that can be done by using a) colour remodelling or calibrating WSI images with (8 or 9) colours phantoms, and b) a nonlinear dependence of the colour intensity and its transmittance, taking into consideration the nonlinear model of light transitions. (2) To apply image analysis algorithms for quantifying tissue immunohistochemical stained immune biomarkers of standardized WSI. (3) To investigate immunohistochemistry biomarkers relevant to BC relapse with special regard to intra-tumour heterogeneity and microenvironment aspects (4) To identify novel BC prognostic factors related to BC relapse based on image analysis algorithms of HE stained histopathology WSI images. (5) correlation between different BC subtypes and RNAm immune genes expression in primary tumour and axillary lymph nodes. (6) To evaluate the association between the presence of some specific immune response patterns in the primary tumour and in the axillary metastasis with the survival. (This project will depend on our retrospective cohort study introduced in “Differences in the Immune Response of the Nonmetastatic ANL between Triple-Negative and Luma A Subtypes).
Outcomes:
The expected results of the project are 1) to obtain a clear map of those immune cells infiltrating the primary tumour and the axillary lymph nodes that could be associated with relapse or survival of the patients, and 2) the possible interactions between the different immune cells populations. The identification of patients with high or low risk based on the patterns of immune cells populations could help 3) to test and develop an automatic and standardized tool for the evaluation of immune response in BC patients but also to provide possible keys to changing and/or modifying the administration of classical treatments in those patients who present a high risk and also to find new therapies based on these immune cells. In addition, 4) Integration of the immune information together with the pathological and genetic information of the primary tumour and ANL in the clinical decision support system developed as the main scope in the proposal.