Using saliva epigenetic data to develop and validate a multivariable predictor of esophageal cancer status.

Autor: Stone TC; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Ward V; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Hogan A; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Ho KMA; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK.; Wellcome/EPSRC Centre for Interventional & Surgical Sciences (WEISS), University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Wilson A; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., McBain H; Wellcome/EPSRC Centre for Interventional & Surgical Sciences (WEISS), University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Duku M; Wellcome/EPSRC Centre for Interventional & Surgical Sciences (WEISS), University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Wolfson P; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Cheung S; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK., Rosenfeld A; Department of Computer Science, Jerusalem College of Technology, Havaad Haleumi 21, Givat Mordechai, 91160, Jerusalem, Israel., Lovat LB; Division of Surgery & Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK.; Wellcome/EPSRC Centre for Interventional & Surgical Sciences (WEISS), University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TY, UK.; Department of Gastrointestinal Services, University College London Hospital, 235 Euston Road, London, NW1 2BU, UK.
Jazyk: angličtina
Zdroj: Epigenomics [Epigenomics] 2024 Jan; Vol. 16 (2), pp. 109-125. Date of Electronic Publication: 2024 Jan 16.
DOI: 10.2217/epi-2023-0248
Abstrakt: Background: Salivary epigenetic biomarkers may detect esophageal cancer. Methods: A total of 256 saliva samples from esophageal adenocarcinoma patients and matched volunteers were analyzed with Illumina EPIC methylation arrays. Three datasets were created, using 64% for discovery, 16% for testing and 20% for validation. Modules of gene-based methylation probes were created using weighted gene coexpression network analysis. Module significance to disease and gene importance to module were determined and a random forest classifier generated using best-scoring gene-related epigenetic probes. A cost-sensitive wrapper algorithm maximized cancer diagnosis. Results: Using age, sex and seven probes, esophageal adenocarcinoma was detected with area under the curve of 0.72 in discovery, 0.73 in testing and 0.75 in validation datasets. Cancer sensitivity was 88% with specificity of 31%. Conclusion: We have demonstrated a potentially clinically viable classifier of esophageal cancer based on saliva methylation.
Databáze: MEDLINE
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