Evolving Landscape of Molecular Prescreening Strategies for Oncology Early Clinical Trials

Rodrigo Dienstmann1, Elena Garralda2, Susana Aguilar1

  • 1Oncology Data Science, Vall d'Hebron Institute of Oncology, Barcelona, Spain.

JCO Precision Oncology
|September 14, 2020
PubMed

Insights

Precision oncology programs evolved to adapt to new molecular targets and drug development, enhancing clinical trial matching. This dynamic approach, integrating multiomics, improves patient opportunities in targeted cancer therapies.

Area of Science:

  • Oncology
  • Genomics
  • Translational Medicine

Background:

  • Precision oncology programs initially focused on early clinical trials for targeted agents.
  • The landscape of targetable molecular alterations and drug development has significantly changed over the past decade.

Purpose of the Study:

  • To describe the adaptation of the Vall d'Hebron Institute of Oncology's molecular prescreening program.
  • To illustrate the evolution towards a dynamic biomarker-drug co-development model in precision oncology.

Main Methods:

  • Transitioned from hotspot mutation panels and IHC/FISH to tumor-specific amplicon-based next-generation sequencing (NGS).
  • Developed custom panels for copy number, fusion, and outlier gene expression, optimized for formalin-fixed paraffin-embedded tissues.
  • Integrated molecular tumor board meetings and considered immunotherapy trial impacts for target prioritization.

Main Results:

  • Biomarker-matched trials shifted from broad targets to numerous specific targets for smaller patient populations.
  • Recruitment rates in biomarker-mandatory trials have declined in recent years.
  • Increased use of larger exon-based NGS assays and gene expression signatures for immunotherapy markers like tumor mutational burden.

Conclusions:

  • The Vall d'Hebron Institute of Oncology's program adapted successfully to a dynamic precision oncology landscape.
  • Molecular tumor boards are crucial for guiding oncologists in interpreting complex genomic data and emerging biomarkers.
  • The multiomics era is poised to expand early clinical trial matching opportunities for cancer patients.

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