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NCI SEER-Linked Virtual Tissue Repository Pilot.

Pamela Sanchez1, Alison L Van Dyke1, Valentina I Petkov1

  • 1Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.

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|August 5, 2024
PubMed
Summary
This summary is machine-generated.

Population-based cancer registries can successfully acquire tissue and data for research. The Virtual Tissue Repository (VTR) Pilot shows SEER registries act as honest brokers for cancer case data.

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Area of Science:

  • Oncology
  • Cancer Research
  • Biorepository Science

Background:

  • The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program evaluated population-based cancer registries.
  • The SEER-Linked Virtual Tissue Repository (VTR) Pilot aimed to assess registries' role as honest brokers for tissue and data acquisition.

Purpose of the Study:

  • To determine the feasibility of using SEER cancer registries to collect tissue and clinical data for research.
  • To compare cancer cases with unusual survival outcomes to matched controls.

Main Methods:

  • Collected formalin-fixed, paraffin-embedded tissue and clinical data for pancreatic ductal adenocarcinoma (PDAC) and breast cancer (BC).
  • Compared cases with highly unusual survival (e.g., ≥5 years for PDAC, ≤30 months for BC) to pair-matched controls with usual survival.
  • Defined success by the registries' ability to acquire tissue and data for these specific cancer cases.

Main Results:

  • Tissue meeting study criteria was obtained for 70% of PDAC and 72% of BC cases.
  • Attrition sources included unavailable tissue, failed case pairings, and poor tissue quality (necrosis, low cellularity).
  • Clinical data completeness exceeded 95% for key variables like margin status and treatment administration, but was lower for CA-19-9 post-treatment.

Conclusions:

  • The VTR Pilot confirmed the feasibility of SEER registries serving as honest brokers for secondary research use of tissue and clinical data.
  • Recommendations include oversampling by 45-50% and involving expert pathologists for optimal sample selection.