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Get Free Access<div>Abstract<p>Cancer evolution is a process that is still poorly understood because of the lack of versatile <i>in vivo</i> longitudinal studies. By generating murine non–small cell lung cancer (NSCLC) orthoallobanks and paired primary cell lines, we provide a detailed description of an <i>in vivo</i>, time-dependent cancer malignization process. We identify the acquisition of metastatic dissemination potential, the selection of co-driver mutations, and the appearance of naturally occurring intratumor heterogeneity, thus recapitulating the stochastic nature of human cancer development. This approach combines the robustness of genetically engineered cancer models with the flexibility of allograft methodology. We have applied this tool for the preclinical evaluation of therapeutic approaches. This system can be implemented to improve the design of future treatments for patients with NSCLC. <i>Cancer Res; 74(21); 5978–88. ©2014 AACR</i>.</p></div>
Chiara Ambrogio, Francisco J. Carmona, August Vidal, Mattia Falcone, Patricia Nieto, Octavio A. Romero, Sara Puertas, Miguel Vizoso, Ernest Nadal, Teresa Poggio, Montse Sánchez‐Céspedes, Manel Esteller, Francisca Mulero, Claudia Voena, Roberto Chiarle, Mariano Barbacid, David Santamarı́a, Alberto Villanueva (2023). Data from Modeling Lung Cancer Evolution and Preclinical Response by Orthotopic Mouse Allografts. , DOI: https://doi.org/10.1158/0008-5472.c.6506384.v1.
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Type
Preprint
Year
2023
Authors
18
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1158/0008-5472.c.6506384.v1
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