Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine. Academic Article uri icon

Overview

abstract

  • Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board-approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high-throughput drug screening to discover effective treatment strategies. Analysis of tumor-derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3-D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.Significance: Integration of genomic data with drug screening from personalized in vitro and in vivo cancer models guides precision cancer care and fuels next-generation research. Cancer Discov; 7(5); 462-77. ©2017 AACR.See related commentary by Picco and Garnett, p. 456This article is highlighted in the In This Issue feature, p. 443.

authors

publication date

  • March 22, 2017

Research

keywords

  • Drug Screening Assays, Antitumor
  • Exome Sequencing
  • Organoids
  • Precision Medicine
  • Whole Exome Sequencing
  • Xenograft Model Antitumor Assays

Identity

PubMed Central ID

  • PMC5413423

Scopus Document Identifier

  • 85018414262

Digital Object Identifier (DOI)

  • 10.1158/2159-8290.CD-16-1154

PubMed ID

  • 28331002

Additional Document Info

volume

  • 7

issue

  • 5