[HTML][HTML] Using heterogeneity of the patient-derived xenograft model to identify the chemoresistant population in ovarian cancer

ZC Dobbin, AA Katre, AD Steg, BK Erickson… - Oncotarget, 2014 - ncbi.nlm.nih.gov
ZC Dobbin, AA Katre, AD Steg, BK Erickson, MM Shah, RD Alvarez, MG Conner…
Oncotarget, 2014ncbi.nlm.nih.gov
A cornerstone of preclinical cancer research has been the use of clonal cell lines. However,
this resource has underperformed in its ability to effectively identify novel therapeutics and
evaluate the heterogeneity in a patient's tumor. The patient-derived xenograft (PDX) model
retains the heterogeneity of patient tumors, allowing a means to not only examine efficacy of
a therapy, but also basic tenets of cancer biology in response to treatment. Herein we
describe the development and characterization of an ovarian-PDX model in order to study …
Abstract
A cornerstone of preclinical cancer research has been the use of clonal cell lines. However, this resource has underperformed in its ability to effectively identify novel therapeutics and evaluate the heterogeneity in a patient's tumor. The patient-derived xenograft (PDX) model retains the heterogeneity of patient tumors, allowing a means to not only examine efficacy of a therapy, but also basic tenets of cancer biology in response to treatment. Herein we describe the development and characterization of an ovarian-PDX model in order to study the development of chemoresistance. We demonstrate that PDX tumors are not simply composed of tumor-initiating cells, but recapitulate the original tumor's heterogeneity, oncogene expression profiles, and clinical response to chemotherapy. Combined carboplatin/paclitaxel treatment of PDX tumors enriches the cancer stem cell populations, but persistent tumors are not entirely composed of these populations. RNA-Seq analysis of six pair of treated PDX tumors compared to untreated tumors demonstrates a consistently contrasting genetic profile after therapy, suggesting similar, but few, pathways are mediating chemoresistance. Pathways and genes identified by this methodology represent novel approaches to targeting the chemoresistant population in ovarian cancer
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