An overview of the NCI precision medicine trials-NCI MATCH and MPACT

Khanh Do1, Geraldine O'Sullivan Coyne2, Alice P Chen3

  • 1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.

Chinese Clinical Oncology
|September 27, 2015
PubMed

Insights

Tumor genomic complexity challenges the oncogene addiction theory. Precision medicine trials like NCI MATCH and MPACT investigate targeted therapies and biomarkers for improved cancer treatment outcomes.

Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • The oncogene addiction theory proposed tumors rely on a single "driver" mutation.
  • Tumor genomic landscapes are now understood to be complex and heterogeneous.
  • Advances in biotechnology and bioinformatics have driven the development of targeted therapeutics.

Purpose of the Study:

  • To evaluate the efficacy of targeted therapies in cancer treatment.
  • To determine if targeting specific molecular aberrations improves clinical benefit.
  • To explore the utility of genomic profiling in guiding treatment strategies.

Main Methods:

  • The National Cancer Institute (NCI) launched precision medicine trials, including NCI Molecular Analysis for Therapy Choice (MATCH) and Molecular Profiling-based Assignment of Cancer Therapy (MPACT).
  • These trials involve genomic pre-screening of tumor tissue to identify molecular aberrations.
  • The Exceptional Responders initiative analyzes tumors from patients with durable responses to identify predictive biomarkers.

Main Results:

  • Genomic screens of patient tumor tissue are increasingly relied upon for treatment decisions.
  • The clinical benefit of targeted treatment strategies is still under evaluation.
  • Ongoing trials aim to elucidate the efficacy of targeting specific oncogenic drivers across different tumor subtypes.

Conclusions:

  • Results from NCI MATCH, MPACT, and the Exceptional Responders initiative will guide the field of precision medicine.
  • Understanding tumor heterogeneity is crucial for developing effective personalized cancer care.
  • Identifying predictive biomarkers is essential for optimizing targeted therapy selection and improving patient outcomes.

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