The Fidelity of Cancer Cells in PDX Models: Characteristics, Mechanism and Clinical Significance.

Clicks: 166
ID: 34661
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #29 of 32 articles by views in International journal of cancer

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Patient-derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next-generation preclinical models. This article is protected by copyright. All rights reserved.
Reference Key
shi2019theinternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Shi, Jiahao;Li, Yongyun;Jia, Renbing;Fan, Xianqun;
Journal International journal of cancer
Year 2019
DOI
10.1002/ijc.32662
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.