Integrated next-generation sequencing and avatar mouse models for personalized cancer treatment. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Current technology permits an unbiased massive analysis of somatic genetic alterations from tumor DNA as well as the generation of individualized mouse xenografts (Avatar models). This work aimed to evaluate our experience integrating these two strategies to personalize the treatment of patients with cancer. METHODS: We performed whole-exome sequencing analysis of 25 patients with advanced solid tumors to identify putatively actionable tumor-specific genomic alterations. Avatar models were used as an in vivo platform to test proposed treatment strategies. RESULTS: Successful exome sequencing analyses have been obtained for 23 patients. Tumor-specific mutations and copy-number variations were identified. All samples profiled contained relevant genomic alterations. Tumor was implanted to create an Avatar model from 14 patients and 10 succeeded. Occasionally, actionable alterations such as mutations in NF1, PI3KA, and DDR2 failed to provide any benefit when a targeted drug was tested in the Avatar and, accordingly, treatment of the patients with these drugs was not effective. To date, 13 patients have received a personalized treatment and 6 achieved durable partial remissions. Prior testing of candidate treatments in Avatar models correlated with clinical response and helped to select empirical treatments in some patients with no actionable mutations. CONCLUSION: The use of full genomic analysis for cancer care is encouraging but presents important challenges that will need to be solved for broad clinical application. Avatar models are a promising investigational platform for therapeutic decision making. While limitations still exist, this strategy should be further tested.

publication date

  • March 14, 2014

Research

keywords

  • High-Throughput Nucleotide Sequencing
  • Molecular Targeted Therapy
  • Neoplasms
  • Precision Medicine

Identity

PubMed Central ID

  • PMC4322867

Scopus Document Identifier

  • 84899707234

Digital Object Identifier (DOI)

  • 10.1158/1078-0432.CCR-13-3047

PubMed ID

  • 24634382

Additional Document Info

volume

  • 20

issue

  • 9