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Empower Novel CpG Methylation Biomarkers for Multi-Cancer Early Detection

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The milestone to improving the clinical outcome in cancer patients is the urgently unmet need to detect the disease at its earliest possible stage, which translates into a survival benefit for the patients De regulation of DNA methylation is an early event in tumorigenesis CpG methylation markers for multi cancer early detection were conducted using genome wide methylation profiling Approximately 18 000 high confidence hits of differentially methylated CpG islands between early stage cancer and normal samples from 3 cancer types were identified Ten top performing cancer specific CpG loci with the lowest p values were selected for in silico validation in TCGA database of approx 1500 samples across 14 major cancer types.Analysis of TCGA data obtained with these 10 CpG loci yielded area under the ROC curve of 0 86-0 97 for discrimination of lung, colon, liver and kidney cancers, significantly outperforming randomly selected 10 CpG sites (AUC of 0 55 0 90 When removing one, two, three, four or five markers from the best performing 10 CpG panel, the AUC dropped to 0 63 0 84 AUC were between 0 48 0 88 with randomly selected 5 or 20 CpG markers The 10 CpG panel demonstrated a composite AUC of 0 895 for all 14 major cancer types The 10 CpGpanel thus achieved the best performance with no other panels outperforming this combination.The training and validation datasets demonstrated the robustness and accuracy of our 10 CpG classifier to effectively differentiate early stage tumor from the normal tissues.
ScienceOpen
Title: Empower Novel CpG Methylation Biomarkers for Multi-Cancer Early Detection
Description:
The milestone to improving the clinical outcome in cancer patients is the urgently unmet need to detect the disease at its earliest possible stage, which translates into a survival benefit for the patients De regulation of DNA methylation is an early event in tumorigenesis CpG methylation markers for multi cancer early detection were conducted using genome wide methylation profiling Approximately 18 000 high confidence hits of differentially methylated CpG islands between early stage cancer and normal samples from 3 cancer types were identified Ten top performing cancer specific CpG loci with the lowest p values were selected for in silico validation in TCGA database of approx 1500 samples across 14 major cancer types.
Analysis of TCGA data obtained with these 10 CpG loci yielded area under the ROC curve of 0 86-0 97 for discrimination of lung, colon, liver and kidney cancers, significantly outperforming randomly selected 10 CpG sites (AUC of 0 55 0 90 When removing one, two, three, four or five markers from the best performing 10 CpG panel, the AUC dropped to 0 63 0 84 AUC were between 0 48 0 88 with randomly selected 5 or 20 CpG markers The 10 CpG panel demonstrated a composite AUC of 0 895 for all 14 major cancer types The 10 CpGpanel thus achieved the best performance with no other panels outperforming this combination.
The training and validation datasets demonstrated the robustness and accuracy of our 10 CpG classifier to effectively differentiate early stage tumor from the normal tissues.

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