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- Immune Metabolism Dysregulation and Efficacy of Anti-PD-1/PD-L1 Agents in Non-Small Cell Lung Cancer (NSCLC)
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- Exploring the role of Bcl-2 family in the immune surveillance of melanoma: from mechanisms to therapeutic perspectives
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Artificial Intelligence and Machine Learning Based Risk Prediction Model for Improving Endometrial Cancer Clinical Management
Project description
PI: Enrico Vizza
Other IRE Principal Collaborators Involved: Bagnato Anna Teresa, Strano Sabrina, Bruno Valentina
Project duration: 24 months
Project code: PNRR-MCNT1-2023-12378252
The project, titled "Artificial Intelligence and Machine Learning Based Risk Prediction Model for Improving Endometrial Cancer Clinical Management", focuses on enhancing precision oncology and surgery for endometrial cancer (EC). The study integrates multi-omics immune and iconographic data (MOMIMIC score) to develop predictive tools. Advanced AI algorithms are applied to preoperative endometrial biopsies and hysteroscopic imaging, creating a comprehensive model to predict recurrence, progression, and prognosis. The MOMIMIC score combines omics and imaging data, improving risk stratification and tailoring treatment strategies.
Purpose
The main goal is to identify novel risk factors and biomarkers for EC recurrence and progression using an AI-driven multi-omics approach. By combining immunological, molecular, and imaging data, the project aims to refine risk stratification, guide surgical radicality, and improve fertility-sparing treatments in young patients. Additionally, AI tools will assist surgeons in decision-making during hysteroscopic and robotic procedures by integrating radiogenomic and digital pathology information.
Results
The expected outcomes include:
- Development of the MOMIMIC score for early detection of EC progression and recurrence.
- Improved patient stratification through a predictive AI model that integrates multi-omics and imaging data.
- Enhanced precision surgery, enabling tailored surgical radicality based on real-time imaging and molecular data.
- Creation of a virtual “patient avatar” to simulate prognosis and guide treatment decisions, contributing to novel precision medicine approaches for EC management.
Financial Support
PNRR, financed by Ministero della Salute
The total grant of the project is: € 1.000.000,00
The grant assigned to IFO – IRE is: € 310.000,00
Other Institution involved: Università degli studi di Roma Tor Vergata, Ospedale Casa Sollievo della Sofferenza, Università degli Studi di Palermo
The funding resources are from the public notice 2° Avviso pubblico per la presentazione e selezione di progetti di ricerca da finanziare nell’ambito del PNRR sulle seguenti tematiche:
- Proof of concept (PoC);
- Tumori Rari (TR);
- Malattie Rare (MR);
- Malattie Croniche non Trasmissibili (MCnT) ad alto impatto sui sistemi sanitari e socio-assistenziali:
- Innovazione in campo diagnostico,
- Innovazione in campo terapeutico;
- Malattie Croniche non Trasmissibili (MCnT) ad alto impatto sui sistemi sanitari e socio-assistenziali:
- Fattori di rischio e prevenzione,
- Eziopatogenesi e meccanismi di malattia
Piano Nazionale di Ripresa e Resilienza - Missione M6 - Componente C2 - Investimento 2.1 Valorizzazione e potenziamento della ricerca biomedica del SSN finanziato dall’Unione europea - NextGenerationEU.