Correlation between tumor engraftment in patient-derived xenograft models and clinical outcomes in colorectal cancer patients
- Authors
- Oh, Bo Young; Lee, Woo Yong; Jung, Sungwon; Hong, Hye Kyung; Nam, Do-Hyun; Park, Yoon Ah; Huh, Jung Wook; Yun, Seong Hyeon; Kim, Hee Cheol; Chun, Ho-Kyung; Cho, Yong Beom
- Issue Date
- 30-Jun-2015
- Publisher
- IMPACT JOURNALS LLC
- Keywords
- colorectal cancer; survival; xenograft; genomic profile; drug response
- Citation
- ONCOTARGET, v.6, no.18, pp.16059 - 16068
- Journal Title
- ONCOTARGET
- Volume
- 6
- Number
- 18
- Start Page
- 16059
- End Page
- 16068
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10411
- DOI
- 10.18632/oncotarget.3863
- ISSN
- 1949-2553
- Abstract
- Despite numerous studies involving patient-derived xenograft (PDX) models, few studies have investigated the relationship between the ability of the tumor to engraft (tumorigenicity) and the clinical features of colorectal cancer (CRC). The aim of this study was to determine whether tumorigenicity correlates with clinical outcomes of CRC patients. We included 241 CRC patients who underwent radical surgery from 2010 to 2013. PDX models were established by implanting tumor fragments obtained from these patients into the subcutaneous layer of immunodeficient mice. Xenografts were successfully established from 62.2%. Successful engraftment was associated with advanced stage (p <0.001) and moderate/poor differentiation (p = 0.029). Three-year disease-free survival (DFS) rates were lower for patients with tumorigenicity (p = 0.011). In stage III patients, tumorigenicity was an independent predictor of poor DFS (p = 0.034). In addition, mutation of TP53 was most frequently detected in stage III patients with tumorigenicity. Two models of stage IV disease without KRAS mutations showed high sensitivity to EGFR-targeted agents, while none of the models with KRAS mutations showed high sensitivity. In conclusion, PDX models may provide an effective preclinical tool for predicting cancer progression and could be used to further genomic and pharmacologic research on personalized treatments.
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