Your browser doesn't support javascript.
loading
Comparison of the Genetic Alterations between Primary Colorectal Cancers and Their Corresponding Patient-Derived Xenograft Tissues
Genomics & Informatics ; : 30-35, 2018.
Article Dans Anglais | WPRIM | ID: wpr-714915
ABSTRACT
Patient-derived xenograft (PDX) models are useful tools for tumor biology research and testing the efficacy of candidate anticancer drugs targeting the druggable mutations identified in tumor tissue. However, it is still unknown how much of the genetic alterations identified in primary tumors are consistently detected in tumor tissues in the PDX model. In this study, we analyzed the genetic alterations of three primary colorectal cancers (CRCs) and matched xenograft tissues in PDX models using a next-generation sequencing cancer panel. Of the 17 somatic mutations identified from the three CRCs, 14 (82.4%) were consistently identified in both primary and xenograft tumors. The other three mutations identified in the primary tumor were not detected in the xenograft tumor tissue. There was no newly identified mutation in the xenograft tumor tissues. In addition to the somatic mutations, the copy number alteration profiles were also largely consistent between the primary tumor and xenograft tissue. All of these data suggest that the PDX tumor model preserves the majority of the key mutations detected in the primary tumor site. This study provides evidence that the PDX model is useful for testing targeted therapies in the clinical field and research on precision medicine.
Sujets)

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Sujet Principal: Biologie / Tumeurs colorectales / Médecine de précision / Hétérogreffes Type d'étude: Étude pronostique langue: Anglais Texte intégral: Genomics & Informatics Année: 2018 Type: Article

Documents relatifs à ce sujet

MEDLINE

...
LILACS

LIS

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Sujet Principal: Biologie / Tumeurs colorectales / Médecine de précision / Hétérogreffes Type d'étude: Étude pronostique langue: Anglais Texte intégral: Genomics & Informatics Année: 2018 Type: Article