Ultra-Rapid ddPCR

The pre-print by ZR Murphy et al., 2024 (can also be found as a limited access publication here) introduces an accelerated droplet digital PCR (ddPCR) method, termed Ultra-Rapid ddPCR (UR-ddPCR), designed for swift genetic analysis during surgical procedures. This technique facilitates the detection of specific tumor mutations within approximately 15 minutes, thereby aiding real-time surgical decision-making.

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source: ZR Murphy et al., 2024, Figure 1A adapted

Key Methodological Enhancements:

  • Expedited DNA Extraction: The study employs a rapid DNA extraction protocol compatible with subsequent ddPCR analysis, significantly reducing preparation time.
  • Optimized Thermal Cycling: Utilizing preheated water baths and thin stainless steel capillaries, the method achieves ultra-fast thermal cycling, enhancing heat transfer efficiency compared to conventional plastic plates.
  • Increased Reagent Concentrations: Adjustments include elevating the concentrations of primers, probes, and Aptamer Hot-Start Taq polymerase, alongside increasing the number of PCR cycles, which collectively enable a reduction in the annealing/extension step to 1 second, culminating in a total PCR duration of 3 minutes.

Performance and Accuracy:

  • Mutation Detection Sensitivity: UR-ddPCR demonstrated the capability to detect IDH1 R132H and BRAF V600E mutations at a 0.1% frequency, with false positive rates of 0.05% and 0.04%, respectively, aligning closely with standard ddPCR protocols.
  • Droplet Amplification Efficiency: The UR-ddPCR protocol was shown to yield fewer (15%) positive droplets, compared to standard protocols (29%). Since this was observed for both wild-type and mutant templates, the proportionality rescues the accuracy (down to 0.1%) of the method.

Clinical Application:

The study validated UR-ddPCR by analyzing 49 samples across 13 surgical cases. The results were consistent with those obtained from standard ddPCR, underscoring UR-ddPCR’s reliability. The rapid turnaround of this technique holds potential to guide surgical decisions in real-time, optimizing tumor resection strategies.