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Published November 2023 | Published
Journal Article Open

A rapid, multiplex digital PCR assay for EGFR, KRAS, BRAF, ERBB2 variants and ALK, RET, ROS1, NTRK1 gene fusions in non-small cell lung cancer

Abstract

Digital PCR (dPCR) is emerging as an ideal platform for the detection and tracking of genomic variants in cancer due to its high sensitivity and simple workflow. The growing number of clinically actionable cancer biomarkers creates a need for fast, accessible methods that allow for dense information content and high accuracy. Here, we describe a proof‐of‐concept amplitude modulation‐based multiplex dPCR assay capable of detecting 12 single‐nucleotide and insertion/deletion (indel) variants in EGFR, KRAS, BRAF, and ERBB2, 14 gene fusions in ALK, RET, ROS1, and NTRK1, and MET exon 14 skipping present in non‐small cell lung cancer (NSCLC). We also demonstrate the use of multi‐spectral target‐signal encoding to improve the specificity of variant detection by reducing background noise by up to an order of magnitude. The assay reported an overall 100% positive percent agreement (PPA) and 98.5% negative percent agreement (NPA) compared with a sequencing‐based assay in a cohort of 62 human formalin‐fixed paraffin‐embedded (FFPE) samples. In addition, the dPCR assay rescued actionable information in 10 samples that failed to sequence, highlighting the utility of a multiplexed dPCR assay as a potential reflex solution for challenging NSCLC samples.

Copyright and License

© 2023 ChromaCode and The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Acknowledgement

The authors wish to acknowledge the support of the Pathology Shared Resource in the Laboratory for Clinical Genomics and Advanced Technology of the Dartmouth Hitchcock Health System and the Dartmouth Cancer Center with NCI Cancer Center Support Grant 5P30 CA023108‐37. The authors also thank Janine Wiese for helping to organize the biological sample data.

Contributions

BL, KM, HKKS, JA, MW, DCG, GJT, AR, and JJS designed experiments. BL, KM, HKKS, JA, DCG, GJT, and JJS performed experiments and analyzed the data. DY and LJ wrote the algorithms and analyzed the data. BL, KM, HKKS, LJ, DY, and JJS wrote the manuscript.

Data Availability

The raw dPCR data that support the findings of this study are available from the corresponding author (jschwartz@chromacode.com) upon reasonable request.

Conflict of Interest

BL, KM, HKKS, LJ, JA, DY, AR, and JS are employees and equity holders of ChromaCode Inc.

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Additional details

Created:
November 9, 2023
Modified:
November 9, 2023