Modified SureSelectQXT Target Enrichment Protocol for Illumina Multiplexed Sequencing of FFPE Samples

J M Rosa-Rosa1, T Caniego-Casas2, S Leskela1,2

  • 11CIBER-ONC, Instituto de Salud Carlos III, Madrid, Spain.

Abstract

Insights

Optimized protocols significantly improve next-generation sequencing (NGS) of low-quality FFPE DNA. This advancement enhances the utility of FFPE samples for personalized oncology, increasing usable reads over threefold.

Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Personalized medicine in oncology relies on molecular tumor characterization.
  • Next-generation sequencing (NGS) enables efficient identification of therapeutic targets.
  • Low-quality DNA from FFPE samples poses challenges for NGS library preparation.

Purpose of the Study:

  • To investigate the behavior of FFPE DNA during SureSelect QXT library construction.
  • To develop optimized protocols for FFPE DNA library preparation and sequencing.
  • To improve the yield of usable sequencing reads from low-quality FFPE samples.

Main Methods:

  • Development of a quality checkpoint (qcPCR) for FFPE DNA samples.
  • Classification of FFPE DNA into unusable, low-quality (LQ), and good-quality (GQ) categories.
  • Modification of input DNA amounts, digestion times, PCR cycles, and reagent volumes for SureSelect QXT library preparation.
  • Design of a decision flowchart for achieving optimal seeding concentration for MiSeq sequencing.

Main Results:

  • FFPE DNA samples can be reliably classified using DIN value and qcPCR concentration.
  • Optimized SureSelect QXT protocol parameters were determined for both GQ and LQ FFPE DNA.
  • Reduced reagent volumes were found to be beneficial for library preparation.

Conclusions:

  • The modified SureSelect QXT protocol significantly enhances sequencing of low-quality FFPE DNA.
  • Usable sequencing reads from LQ FFPE samples increased more than threefold.
  • Achieved median depth/million reads values approach those of high-quality DNA samples, enabling better molecular profiling for personalized medicine.

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