The PhD Programme provided a structured three-year training pathway for researchers in translational oncology, precision medicine, and network medicine.
The training activities for the 38th (Year 1), 37th (Year 2), and 36th (Year 3) cycles included institutional courses introducing the PhD programme and network oncology, modules on statistics and programming (R language), and lecture series on database management and computational methods for the integration of clinical and molecular data. The academic calendar also included seminars on preclinical models, microbiota and oncology, cardio-oncology, open innovation, and academia–industry interaction, as well as lectures delivered by international experts on applications of artificial intelligence and machine learning in clinical settings.
A major component of the training offer was represented by the laboratory “Network Medicine in Oncology,” organised in working groups dedicated to specific pathologies, including lung cancer and glioblastoma. This activity enabled Year 2 and Year 3 PhD students to apply network analysis tools to clinical, biomolecular, and immunological data in close integration with their research projects.
Workshop: Network medicine in Oncology
The doctoral students of the 37th and 36th cycles participated in interdisciplinary working groups for the application of the network medicine analysis process to clinical, bio-molecular, immune and diagnostic data of oncological diseases, which involved close collaboration between faculty members of the college.
The workflow within these groups started with a clinical question posed by the clinically trained doctoral students, then data generated by the research groups or available in public databases were collected and analysed by the computer-trained doctoral students and lecturers. Finally, the results were discussed within the group.
Paediatric Brain Cancer' group
The aim of the work was to build a database that included clinical and molecular data from a range of paediatric brain tumour patients. Four different groups of molecularly distinct diagnoses were identified and subsequent investigations will focus on the diagnostic role of mutations defined as uncertain to date.
Non-smoker lung cancer' group
The clinical question concerned the molecular characterisation of non-smoker lung cancer patients. For this purpose, four different datasets were identified and the molecular signatures of non-smoker patients were identified and compared.
Two orientation meetings were held, followed by 12 meetings for the 'Non-smoker lung cancer' group and 8 meetings for the 'Paediatric Brain Cancer' group, as detailed in the attached table.
The
36th cycle doctoral students followed the teaching activities of their third year, as listed below (Details of the date, time, lecturer and delivery methods are given in the attached table):
Network Oncology and Precision Medicine presentation, experience of 36th cycle PhD students
European Society for Medical Oncology 2022 update How to set up a data base (2 meetings)
Legislation and regulation in clinical practice in oncology Preclinical models (2 meetings)
Cardio-oncology Open innovation: collaboration between academia, scientific institutions and industry Microbiota and oncology Artificial Intelligence and Machine Learning Applications in Cardiac Transplantation
The
37th cycle doctoral students followed their second year activities, listed below (Details of date, time and lecturer and delivery methods are given in the attached table):
Network Oncology and Precision Medicine presentation, experience of 36th cycle PhD students
European Society for Medical Oncology 2022 update
Computational methods for the processing and integration of clinical and molecular data. (4 meetings)
Network Oncology and Precision Medicine presentation How to set up a data base (2 meetings)
Legislation and regulation in clinical practice in oncology Preclinical models (2 meetings)
Cardio-oncology Open innovation: collaboration between academia, scientific institutions and industry Microbiota and oncology Artificial Intelligence and Machine Learning Applications in Cardiac Transplantation
The
38th cycle doctoral students followed the activities of their first year, which are listed below (Details of the date, time and lecturer and delivery methods are given in the attached table):
Coordination meeting and presentation Presentation Network Oncology and Precision Medicine (2 meetings)
Presentation Network Oncology and Precision Medicine, experience of 36th cycle PhD students
R language (4 meetings)
Basic immunology (2 meetings)
How to set up a Database (2 meetings)
Acquired Immunity Legislation and regulation in clinical practice in oncology Preclinical models (2 meetings)
Tracking the evolution of non-small cell lung cancer Mechanisms of anti-tumour immune response and innate immunity Cardio-oncology Open innovation: collaboration between academia, scientific institutions and industry Microbiota and oncology Artificial Intelligence and Machine Learning Applications in Cardiac Transplantation