PURPOSE OF REVIEW: Patient-derived xenografts (PDXs) are becoming increasing popular as a preclinical tool for evaluating novel therapeutic strategies in cancer. These models maintain the biological characteristics of the donor tumours and have a predictive power in the translation of cancer therapeutics into clinical settings. This review focuses on the rapidly growing body of literature on PDX models of breast cancer and their applications and challenges in cancer drug development. RECENT FINDINGS: Several articles in the last 2 years have reported that breast cancer PDXs can reproduce the phenotype and diversity of patients' tumours. This preservation of breast cancer biology involves a number of different aspects, including gene expression patterns, mutational status, drug response and tumour architecture. These models have been shown to be a valuable tool for the identification of new treatment targets, rational drug combinations, biomarkers and mechanisms of drug resistance. SUMMARY: The development of relevant, predictive models is key to increase the success rate for new drugs. PDX models of breast cancer hold the promise for the development of new and more efficient therapeutic strategies.
PURPOSE OF REVIEW: Patient-derived xenografts (PDXs) are becoming increasing popular as a preclinical tool for evaluating novel therapeutic strategies in cancer. These models maintain the biological characteristics of the donortumours and have a predictive power in the translation of cancer therapeutics into clinical settings. This review focuses on the rapidly growing body of literature on PDX models of breast cancer and their applications and challenges in cancer drug development. RECENT FINDINGS: Several articles in the last 2 years have reported that breast cancer PDXs can reproduce the phenotype and diversity of patients' tumours. This preservation of breast cancer biology involves a number of different aspects, including gene expression patterns, mutational status, drug response and tumour architecture. These models have been shown to be a valuable tool for the identification of new treatment targets, rational drug combinations, biomarkers and mechanisms of drug resistance. SUMMARY: The development of relevant, predictive models is key to increase the success rate for new drugs. PDX models of breast cancer hold the promise for the development of new and more efficient therapeutic strategies.
Authors: Logan C DeBord; Ravi R Pathak; Mariana Villaneuva; Hsuan-Chen Liu; Daniel A Harrington; Wendong Yu; Michael T Lewis; Andrew G Sikora Journal: Am J Cancer Res Date: 2018-08-01 Impact factor: 6.166
Authors: Alejandra Bruna; Oscar M Rueda; Wendy Greenwood; Ankita Sati Batra; Maurizio Callari; Rajbir Nath Batra; Katherine Pogrebniak; Jose Sandoval; John W Cassidy; Ana Tufegdzic-Vidakovic; Stephen-John Sammut; Linda Jones; Elena Provenzano; Richard Baird; Peter Eirew; James Hadfield; Matthew Eldridge; Anne McLaren-Douglas; Andrew Barthorpe; Howard Lightfoot; Mark J O'Connor; Joe Gray; Javier Cortes; Jose Baselga; Elisabetta Marangoni; Alana L Welm; Samuel Aparicio; Violeta Serra; Mathew J Garnett; Carlos Caldas Journal: Cell Date: 2016-09-15 Impact factor: 41.582