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Up-front mutation detection in circulating tumor DNA by droplet digital PCR has added diagnostic value in lung cancer.
- Source :
-
Translational oncology [Transl Oncol] 2023 Jan; Vol. 27, pp. 101589. Date of Electronic Publication: 2022 Nov 19. - Publication Year :
- 2023
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Abstract
- Identification of actionable mutations in advanced stage non-squamous non-small-cell lung cancer (NSCLC) patients is recommended by guidelines as it enables treatment with targeted therapies. In current practice, mutations are identified by next-generation sequencing of tumor DNA (tDNA-NGS), which requires tissue biopsies of sufficient quality. Alternatively, circulating tumor DNA (ctDNA) could be used for mutation analysis. This prospective, multicenter study establishes the diagnostic value of ctDNA analysis by droplet digital PCR (ctDNA-ddPCR) in patients with primary lung cancer. CtDNA from 458 primary lung cancer patients was analyzed using a panel of multiplex ddPCRs for EGFR (Ex19Del, G719S, L858R, L861Q and S768I), KRAS G12/G13 and BRAF V600 mutations. For 142 of 175 advanced stage non-squamous NSCLC patients tDNA-NGS results were available to compare to ctDNA-ddPCR. tDNA-NGS identified 98 mutations, of which ctDNA-ddPCR found 53 mutations (54%), including 32 of 45 (71%) targetable driver mutations. In 2 of these 142 patients, a mutation was found by ctDNA-ddPCR only. In 33 advanced stage patients lacking tDNA-NGS results, ctDNA-ddPCR detected 15 additional mutations, of which 7 targetable. Overall, ctDNA-ddPCR detected 70 mutations and tDNA-NGS 98 mutations in 175 advanced NSCLC patients. Using an up-front ctDNA-ddPCR strategy, followed by tDNA-NGS only if ctDNA-ddPCR analysis is negative, increases the number of mutations found from 98 to 115 (17%). At the same time, up-front ctDNA-ddPCR reduces tDNA-NGS analyses by 40%, decreasing the need to perform (additional) biopsies.<br /> (Copyright © 2022. Published by Elsevier Inc.)
Details
- Language :
- English
- ISSN :
- 1936-5233
- Volume :
- 27
- Database :
- MEDLINE
- Journal :
- Translational oncology
- Publication Type :
- Academic Journal
- Accession number :
- 36413862
- Full Text :
- https://doi.org/10.1016/j.tranon.2022.101589