| Literature DB >> 31585941 |
Simona Corso1,2, Claudio Isella2, Sara E Bellomo2, Maria Apicella2, Stefania Durando2, Cristina Migliore3,2, Stefano Ughetto3,2, Laura D'Errico3,2, Silvia Menegon2, Daniel Moya-Rull3,2, Marilisa Cargnelutti2, Tânia Capelôa2, Daniela Conticelli3,2, Jessica Giordano3,2, Tiziana Venesio2, Antonella Balsamo2, Caterina Marchiò2,4, Maurizio Degiuli5, Rossella Reddavid5, Uberto Fumagalli6, Stefano De Pascale6, Giovanni Sgroi7, Emanuele Rausa7, Gian Luca Baiocchi8, Sarah Molfino8, Filippo Pietrantonio9,10, Federica Morano9, Salvatore Siena10,11, Andrea Sartore-Bianchi10,11, Maria Bencivenga12, Valentina Mengardo12, Riccardo Rosati13, Daniele Marrelli14, Paolo Morgagni15, Stefano Rausei16, Giovanni Pallabazzer17, Michele De Simone2, Dario Ribero2, Silvia Marsoni2, Antonino Sottile2, Enzo Medico3,2, Paola Cassoni4, Anna Sapino2,4, Eirini Pectasides18, Aaron R Thorner19, Anwesha Nag19, Samantha D Drinan19, Bruce M Wollison19, Adam J Bass18, Silvia Giordano1,2.
Abstract
Gastric cancer is the world's third leading cause of cancer mortality. In spite of significant therapeutic improvements, the clinical outcome for patients with advanced gastric cancer is poor; thus, the identification and validation of novel targets is extremely important from a clinical point of view. We generated a wide, multilevel platform of gastric cancer models, comprising 100 patient-derived xenografts (PDX), primary cell lines, and organoids. Samples were classified according to their histology, microsatellite stability, Epstein-Barr virus status, and molecular profile. This PDX platform is the widest in an academic institution, and it includes all the gastric cancer histologic and molecular types identified by The Cancer Genome Atlas. PDX histopathologic features were consistent with those of patients' primary tumors and were maintained throughout passages in mice. Factors modulating grafting rate were histology, TNM stage, copy number gain of tyrosine kinases/KRAS genes, and microsatellite stability status. PDX and PDX-derived cells/organoids demonstrated potential usefulness to study targeted therapy response. Finally, PDX transcriptomic analysis identified a cancer cell-intrinsic microsatellite instability (MSI) signature, which was efficiently exported to gastric cancer, allowing the identification, among microsatellite stable (MSS) patients, of a subset of MSI-like tumors with common molecular aspects and significant better prognosis. In conclusion, we generated a wide gastric cancer PDX platform, whose exploitation will help identify and validate novel "druggable" targets and optimize therapeutic strategies. Moreover, transcriptomic analysis of gastric cancer PDXs allowed the identification of a cancer cell-intrinsic MSI signature, recognizing a subset of MSS patients with MSI transcriptional traits, endowed with better prognosis. SIGNIFICANCE: This study reports a multilevel platform of gastric cancer PDXs and identifies a MSI gastric signature that could contribute to the advancement of precision medicine in gastric cancer. ©2019 American Association for Cancer Research.Entities:
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Year: 2019 PMID: 31585941 DOI: 10.1158/0008-5472.CAN-19-1166
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701