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Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer
BACKGROUND: Thyroid cancer is the most frequent malignancy of the endocrine system, of which papillary thyroid cancer (PTC) is the predominant form with a rapid increasing incidence worldwide. Rearranged during transfection (RET) fusions are common genetic drivers of PTC and the potent RET inhibitor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120194/ https://www.ncbi.nlm.nih.gov/pubmed/37081420 http://dx.doi.org/10.1186/s12885-023-10852-z |
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author | Chen, Mengke Xue, Junyu Sang, Ye Jiang, Wenting He, Weiman Hong, Shubin Lv, Weiming Xiao, Haipeng Liu, Rengyun |
author_facet | Chen, Mengke Xue, Junyu Sang, Ye Jiang, Wenting He, Weiman Hong, Shubin Lv, Weiming Xiao, Haipeng Liu, Rengyun |
author_sort | Chen, Mengke |
collection | PubMed |
description | BACKGROUND: Thyroid cancer is the most frequent malignancy of the endocrine system, of which papillary thyroid cancer (PTC) is the predominant form with a rapid increasing incidence worldwide. Rearranged during transfection (RET) fusions are common genetic drivers of PTC and the potent RET inhibitor selpercatinib has been recently approved for treating advanced or metastatic RET fusion-positive thyroid cancer. In this study we aimed to develop a droplet digital PCR (ddPCR) system to accurately detect RET fusion in PTC samples. METHODS: The frequency and distribution of RET fusions in PTC were analyzed using genomic data of 402 PTC patients in The Cancer Genome Atlas (TCGA) database. To establish the ddPCR system for detecting CCDC6::RET fusion, a plasmid containing CCDC6::RET infusion fragment was constructed as standard template, the annealing temperature and concentrations of primers and probe were optimized. The analytical performance of ddPCR and quantitative reverse transcription PCR (qRT-PCR) were assessed in standard templates and tissue samples from 112 PTC patients. Sanger sequencing was performed in all the RET fusion-positive samples identified by ddPCR. RESULTS: RET fusions were observed in 25 (6.2%) of the 402 TCGA samples, and 15 (60%) of the RET fusion-positive patients had the CCDC6::RET fusion. Compared with qRT-PCR, the ddPCR method showed a lower limit of detection (128.0 and 430.7 copies/reaction for ddPCR and qRT-PCR, respectively). When applying the two methods to 112 tissue samples of PTC, eleven (9.8%) CCDC6::RET fusion-positive samples were detected by qRT-PCR, while ddPCR identified 4 additional positive samples (15/112, 13.4%). All the CCDC6::RET fusion-positive cases identified by ddPCR were confirmed by Sanger sequencing except for one case with 0.14 copies/uL of the fusion. CONCLUSION: The accurate and sensitive ddPCR method reported here is powerful to detection CCDC6::RET fusion in PTC samples, application of this method would benefit more RET fusion-positive patients in the clinic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10852-z. |
format | Online Article Text |
id | pubmed-10120194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101201942023-04-22 Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer Chen, Mengke Xue, Junyu Sang, Ye Jiang, Wenting He, Weiman Hong, Shubin Lv, Weiming Xiao, Haipeng Liu, Rengyun BMC Cancer Research BACKGROUND: Thyroid cancer is the most frequent malignancy of the endocrine system, of which papillary thyroid cancer (PTC) is the predominant form with a rapid increasing incidence worldwide. Rearranged during transfection (RET) fusions are common genetic drivers of PTC and the potent RET inhibitor selpercatinib has been recently approved for treating advanced or metastatic RET fusion-positive thyroid cancer. In this study we aimed to develop a droplet digital PCR (ddPCR) system to accurately detect RET fusion in PTC samples. METHODS: The frequency and distribution of RET fusions in PTC were analyzed using genomic data of 402 PTC patients in The Cancer Genome Atlas (TCGA) database. To establish the ddPCR system for detecting CCDC6::RET fusion, a plasmid containing CCDC6::RET infusion fragment was constructed as standard template, the annealing temperature and concentrations of primers and probe were optimized. The analytical performance of ddPCR and quantitative reverse transcription PCR (qRT-PCR) were assessed in standard templates and tissue samples from 112 PTC patients. Sanger sequencing was performed in all the RET fusion-positive samples identified by ddPCR. RESULTS: RET fusions were observed in 25 (6.2%) of the 402 TCGA samples, and 15 (60%) of the RET fusion-positive patients had the CCDC6::RET fusion. Compared with qRT-PCR, the ddPCR method showed a lower limit of detection (128.0 and 430.7 copies/reaction for ddPCR and qRT-PCR, respectively). When applying the two methods to 112 tissue samples of PTC, eleven (9.8%) CCDC6::RET fusion-positive samples were detected by qRT-PCR, while ddPCR identified 4 additional positive samples (15/112, 13.4%). All the CCDC6::RET fusion-positive cases identified by ddPCR were confirmed by Sanger sequencing except for one case with 0.14 copies/uL of the fusion. CONCLUSION: The accurate and sensitive ddPCR method reported here is powerful to detection CCDC6::RET fusion in PTC samples, application of this method would benefit more RET fusion-positive patients in the clinic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10852-z. BioMed Central 2023-04-20 /pmc/articles/PMC10120194/ /pubmed/37081420 http://dx.doi.org/10.1186/s12885-023-10852-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Chen, Mengke Xue, Junyu Sang, Ye Jiang, Wenting He, Weiman Hong, Shubin Lv, Weiming Xiao, Haipeng Liu, Rengyun Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title | Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title_full | Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title_fullStr | Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title_full_unstemmed | Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title_short | Highly sensitive droplet digital PCR for detection of RET fusion in papillary thyroid cancer |
title_sort | highly sensitive droplet digital pcr for detection of ret fusion in papillary thyroid cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120194/ https://www.ncbi.nlm.nih.gov/pubmed/37081420 http://dx.doi.org/10.1186/s12885-023-10852-z |
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