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.
| Original language | English |
|---|---|
| Pages (from-to) | 5884-5896 |
| Number of pages | 13 |
| Journal | Cancer Research |
| Volume | 79 |
| Issue number | 22 |
| DOIs | |
| Publication status | Published - Nov 15 2019 |
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ASJC Scopus subject areas
- Oncology
- Cancer Research
Cite this
A comprehensive PDX gastric cancer collection captures cancer cell–intrinsic transcriptional MSI traits. / Corso, Simona; Isella, Claudio; Bellomo, Sara E.; Apicella, Maria; Durando, Stefania; Migliore, Cristina; Ughetto, Stefano; D'Errico, Laura; Menegon, Silvia; Moya-Rull, Daniel; Cargnelutti, Marilisa; Capelôa, Tânia; Conticelli, Daniela; Giordano, Jessica; Venesio, Tiziana; Balsamo, Antonella; Marchio, Caterina; Degiuli, Maurizio; Reddavid, Rossella; Fumagalli, Uberto; de Pascale, Stefano; Sgroi, Giovanni; Rausa, Emanuele; Baiocchi, Gian Luca; Molfino, Sarah; Pietrantonio, Filippo; Morano, Federica; Siena, Salvatore; Sartore-Bianchi, Andrea; Bencivenga, Maria; Mengardo, Valentina; Rosati, Riccardo; Marrelli, Daniele; Morgagni, Paolo; Rausei, Stefano; Pallabazzer, Giovanni; de Simone, Michele; Ribero, Dario; Marsoni, Silvia; Sottile, Antonino; Medico, Enzo; Cassoni, Paola; Sapino, Anna; Pectasides, Eirini; Thorner, Aaron R.; Nag, Anwesha; Drinan, Samantha D.; Wollison, Bruce M.; Bass, Adam J.; Giordano, Silvia.
In: Cancer Research, Vol. 79, No. 22, 15.11.2019, p. 5884-5896.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A comprehensive PDX gastric cancer collection captures cancer cell–intrinsic transcriptional MSI traits
AU - Corso, Simona
AU - Isella, Claudio
AU - Bellomo, Sara E.
AU - Apicella, Maria
AU - Durando, Stefania
AU - Migliore, Cristina
AU - Ughetto, Stefano
AU - D'Errico, Laura
AU - Menegon, Silvia
AU - Moya-Rull, Daniel
AU - Cargnelutti, Marilisa
AU - Capelôa, Tânia
AU - Conticelli, Daniela
AU - Giordano, Jessica
AU - Venesio, Tiziana
AU - Balsamo, Antonella
AU - Marchio, Caterina
AU - Degiuli, Maurizio
AU - Reddavid, Rossella
AU - Fumagalli, Uberto
AU - de Pascale, Stefano
AU - Sgroi, Giovanni
AU - Rausa, Emanuele
AU - Baiocchi, Gian Luca
AU - Molfino, Sarah
AU - Pietrantonio, Filippo
AU - Morano, Federica
AU - Siena, Salvatore
AU - Sartore-Bianchi, Andrea
AU - Bencivenga, Maria
AU - Mengardo, Valentina
AU - Rosati, Riccardo
AU - Marrelli, Daniele
AU - Morgagni, Paolo
AU - Rausei, Stefano
AU - Pallabazzer, Giovanni
AU - de Simone, Michele
AU - Ribero, Dario
AU - Marsoni, Silvia
AU - Sottile, Antonino
AU - Medico, Enzo
AU - Cassoni, Paola
AU - Sapino, Anna
AU - Pectasides, Eirini
AU - Thorner, Aaron R.
AU - Nag, Anwesha
AU - Drinan, Samantha D.
AU - Wollison, Bruce M.
AU - Bass, Adam J.
AU - Giordano, Silvia
PY - 2019/11/15
Y1 - 2019/11/15
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85075062195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075062195&partnerID=8YFLogxK
U2 - 10.1158/0008-5472.CAN-19-1166
DO - 10.1158/0008-5472.CAN-19-1166
M3 - Article
C2 - 31585941
AN - SCOPUS:85075062195
VL - 79
SP - 5884
EP - 5896
JO - Journal of Cancer Research
JF - Journal of Cancer Research
SN - 0008-5472
IS - 22
ER -