Isabelle Neefs, Nele De Meulenaere, Thomas Vanpoucke, Janah Vandenhoeck, Dieter Peeters, Marc Peeters, Guy Van Camp, Ken Op de Beeck
{"title":"Simultaneous detection of eight cancer types using a multiplex droplet digital PCR assay.","authors":"Isabelle Neefs, Nele De Meulenaere, Thomas Vanpoucke, Janah Vandenhoeck, Dieter Peeters, Marc Peeters, Guy Van Camp, Ken Op de Beeck","doi":"10.1002/1878-0261.13708","DOIUrl":null,"url":null,"abstract":"<p><p>DNA methylation biomarkers have emerged as promising tools for cancer detection. Common methylation patterns across tumor types allow multi-cancer detection. Droplet digital PCR (ddPCR) has gained considerable attention for methylation detection. However, multi-cancer detection using multiple targets in ddPCR has never been performed before. Therefore, we developed a multiplex ddPCR assay for multi-cancer detection. Based on previous data analyses using The Cancer Genome Atlas (TCGA), we selected differentially methylated targets for eight frequent tumor types (lung, breast, colorectal, prostate, pancreatic, head and neck, liver, and esophageal cancer). Three targets were validated using ddPCR in 103 tumor and 109 normal adjacent fresh frozen samples. Two distinct ddPCR assays were successfully developed. Output data from both assays is combined to obtain a read-out from the three targets together. Our overall ddPCR assay has a cross-validated area under the curve (cvAUC) of 0.948. Performance between distinct cancer types varies, with sensitivities ranging from 53.8% to 100% and specificities ranging from 80% to 100%. Compared to previously published single-target parameters, we show that combining targets can drastically increase sensitivity and specificity, while lowering DNA input. In conclusion, we are the first to report a multi-cancer methylation ddPCR assay, which allows for highly accurate tumor predictions.</p>","PeriodicalId":18764,"journal":{"name":"Molecular Oncology","volume":" ","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/1878-0261.13708","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
Abstract
DNA methylation biomarkers have emerged as promising tools for cancer detection. Common methylation patterns across tumor types allow multi-cancer detection. Droplet digital PCR (ddPCR) has gained considerable attention for methylation detection. However, multi-cancer detection using multiple targets in ddPCR has never been performed before. Therefore, we developed a multiplex ddPCR assay for multi-cancer detection. Based on previous data analyses using The Cancer Genome Atlas (TCGA), we selected differentially methylated targets for eight frequent tumor types (lung, breast, colorectal, prostate, pancreatic, head and neck, liver, and esophageal cancer). Three targets were validated using ddPCR in 103 tumor and 109 normal adjacent fresh frozen samples. Two distinct ddPCR assays were successfully developed. Output data from both assays is combined to obtain a read-out from the three targets together. Our overall ddPCR assay has a cross-validated area under the curve (cvAUC) of 0.948. Performance between distinct cancer types varies, with sensitivities ranging from 53.8% to 100% and specificities ranging from 80% to 100%. Compared to previously published single-target parameters, we show that combining targets can drastically increase sensitivity and specificity, while lowering DNA input. In conclusion, we are the first to report a multi-cancer methylation ddPCR assay, which allows for highly accurate tumor predictions.
Molecular OncologyBiochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
11.80
自引率
1.50%
发文量
203
审稿时长
10 weeks
期刊介绍:
Molecular Oncology highlights new discoveries, approaches, and technical developments, in basic, clinical and discovery-driven translational cancer research. It publishes research articles, reviews (by invitation only), and timely science policy articles.
The journal is now fully Open Access with all articles published over the past 10 years freely available.