Davide Mascolo, Doctor of Philosophy – Ph.D., Data Science at Sapienza University of Rome, shared on LinkedIn:
“Excited and proud to share our new study, now published in Clinical Cancer Research!
Understanding complex phenomena such as intratumoral immune heterogeneity requires a truly interdisciplinary approach – bringing together oncology, immunology, digital pathology, and computational science.
By integrating multiregion tumor data, computational modelling, and digital pathology, we developed an approach to infer immune heterogeneity from individual tumor samples and assessed its clinical relevance across independent cohorts of patients with advanced NSCLC treated with immune checkpoint inhibitors.
Our findings reveal that tumors appearing similar at first glance can harbor markedly different immune landscapes, associated with divergent outcomes following PD-(L)1 blockade.
More broadly, this study demonstrates how computational methods can translate complex, spatially heterogeneous biological data into clinically meaningful insights, bringing these tools closer to potential use in routine oncology practice.
A huge thank you to Laura Cipriani, Marcello Maugeri-Saccà, all our co-authors, and the many collaborators who made this work possible!”
Title: Intratumoral Immune Heterogeneity Drives Divergent Outcomes to PD-(L)1 Blockade in Lung Cancer
Authors: Laura Cipriani, Davide Mascolo, Stefano Scalera, Giulia Bon, Giulia Schiavoni, Antonella Palmese, Irene Terrenato, Maurizio Fanciulli, Ludovica Ciuffreda, Francesca De Nicola, Federico Bartoccini, Aldo Palange, Enzo Gallo, Edoardo Pescarmona, Simonetta Buglioni, Daniele Marinelli, Marco Mazzotta, Alessandro Di Federico, Ruggero De Maria, Giovanni Blandino, Biagio Ricciuti, Wael Salem. Zrafi, Lodovica Zullo, Yohann Loriot, Mihaela Aldea, Benjamin Besse, Federico Cappuzzo, Marcello Maugeri‐Saccà
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