APOLLO11: a bio-data-driven model for clinical and translational research in lung cancer

作者：Arsela Prelaj, Leonardo Provenzano, V. Miskovic, Monica Ganzinelli, Laura Mazzeo, Maria Gemelli, Cecilia Silvestri, A. Spagnoletti, Rebecca Romanò, Marta Brambilla, Mario Occhipinti, Teresa Beninato, Paolo Ambrosini, Elisa Sottotetti, Margherita Favali, A. Zec, A. Ferrarin, Giulia Corrao, Marco Meazza Prina, Margherita Ruggirello, Moreno Marino, Andra Diana Dumitrascu, Rosa Maria Di Mauro, Claudia Giani, Chiara Cavalli, Roberta Serino, Chiara Catania, Antonella Panzardi, Giulio Metro, Chiara Bennati, Roberto Ferrara, Marianna Macerelli, Alberto Servetto, Maria Silvia Cona, Nicla La Verde, Luca Toschi, Paolo Baili, Federica Corso, Emanuela Zito, Saverio Cinieri, Rossana Berardi, Giovanni Scoazec, Alessandro Inno, Stefania Gori, Salvatore Pisconti, Federica Buzzacchino, Matteo Brighenti, Federica Biello, Alfredo Tartarone, Giancarlo Pruneri, Antonino Belfiore, Luca Agnelli, Alessandro Guidi, Luca Invernizzi, Noemi Salmistraro, Andrea Riccardo Filippi, Piergiorgio Solli, Giulia Galli, Daniele Lorenzini, Elio Gregory Pizzutilo, Filippo G. De Braud, Alessandra Pedrocchi, Francesco Trovò, C Genova, Carminia Maria Della Corte, Giuseppe Viscardi, Marina Chiara Garassino, Alessio Cortellini, Emanuele Claudio Mingo, M. Russano, Diego Signorelli, Claudia Proto, Andrea Vingiani, Sabina Sangaletti, Giuseppe Lo Russo, the APOLLO11 study group, Giorgia Di Liberti, C. Agosta, Ghazal Farhikhteh, Daniela Miliziano, Giorgia Corbo, B. Guirges, Cristina Licciardello, Lorenzo Antonuzzo, Francesco Verderame, Giulia Barletta, Gianpaolo Spinelli, Rita Chiari, Rita Emili, Federica Bertolini, Grisanti Salvatore, Emanuele Vita, C. Bonalume, Michele Aieta, Luigi Lacriola, Michele Borraccino, Claudia Bareggi, Fabrizio Citarella, Giovanni Apolone, Silvia Taverna, Antonio Lugini, Cesare Fattoi, Alfonso Marchianò, Alessandro Leonetti · 发表于：npj Precision Oncology · 年份：2026 · DOI：10.1038/s41698-026-01295-3 · 被引用次数：2 · 研究领域：Lung Cancer Treatments and Mutations、Lung Cancer Research Studies、Ferroptosis and cancer prognosis

Identifying predictive and resistance biomarkers remains one of the most relevant unmet needs in clinical cancer research. Artificial Intelligence (AI) represents a powerful tool to develop predictive algorithms tailored to individual patients. Thanks to its ability to process large quantities of heterogeneous, patient-level information, the AI-based approach is progressively fostering the growth of a data-driven paradigm to complement traditional, hypothesis-driven clinical research. However, the development of reliable AI models requires access to large, high-quality, and continuously updated datasets. Despite this necessity, no infrastructure currently exists to enable federated, multi-omic, standardized, prospective, and large-scale collection and analysis of real-world clinical and biological data in the context of lung cancer. We established the APOLLO11 consortium, a distributed, nationwide, updated Italian lung cancer network designed to build a decentralized, long-term, population-based, real-world data repository and a multilevel biobank, locally stored and centrally annotated. This strategy seeks to lay the foundation for the clinical implementation of data-driven research, ultimately advancing precision oncology.