A panel of DNA methylation signature from peripheral blood may predict colorectal cancer susceptibility

Abstract

Background: Differential DNA methylation panel derived from peripheral blood could serve as biomarkers of CRC susceptibility. However, most of the previous studies utilized post-diagnostic blood DNA which may be markers of disease rather than susceptibility. In addition, only a few studies have evaluated the predictive potential of differential DNA methylation in CRC in a prospective cohort and on a genome-wide basis. The aim of this study was to identify a potential panel of DNA methylation biomarkers in peripheral blood that is associated with CRC risk and therefore serve as epigenetic biomarkers of disease susceptibility. Methods: DNA methylation profile of a nested case-control study with 166 CRC and 424 healthy normal subjects were obtained from the Gene Expression Omnibus (GEO) database. The differentially methylated markers were identified by moderated t-statistics. The DNA methylation panel was constructed by stepwise logistic regression and the least absolute shrinkage and selection operator in the training dataset. A methylation risk score (MRS) model was constructed and the association between MRS and CRC risk assessed. Results: We identified 48 differentially methylated CpGs sites, of which 33 were hypomethylated. Of these, sixteen-CpG based MRS that was associated with CRC risk (OR = 2.68, 95% CI: 2.13, 3.38, P < 0.0001) was constructed. This association is confirmed in the testing dataset (OR = 2.02, 95% CI: 1.48, 2.74, P < 0.0001) and persisted in both males and females, younger and older subjects, short and long time-to-diagnosis. The MRS also predicted CRC with AUC 0.82 (95% CI: 0.76, 0.88), indicating high accuracy. Conclusions: Our study has identified a novel DNA methylation panel that is associated with CRC and could, if validated be useful for the prediction of CRC risk in the future.

Combined Identification of Novel Markers for Diagnosis and Prognostic of Classic Hodgkin Lymphoma

“… 12 Another research to assess the accuracy of a signature for detecting colorectal cancer patients in the training dataset and validation dataset, the results showed the AUC of 0.851 and 0.923, respectively. 13 In the present study, our diagnostic prediction signature showed better performance in differentiating cHL from normal controls and yielded new insights into the diagnosis of cHL. FOCX1 in our signature is an essential component of FOX family members which involved in carcinogenesis and the growth tumor cell and express a higher level in a variety of carcinomas.…”

Discovery of novel DNA methylation biomarkers for non‐invasive sporadic breast cancer detection in the Latino population

“…Even in the study of Heyn et al [37], in which genetic noise is removed and other sources of confounders are reduced by analyzing identical twin pairs discordant for breast cancer, they detected 403 differentially methylated sites in blood DNA between discordant twins, all with < 8% differences between the two groups. Despite the small change in magnitude, the integration of multiple epigenetic biomarkers as a predictive signature and/ or in combination with genetic markers could be of high translational value [9]. Importantly, among the CpGDMs panel detected in leukocytes, CpG sites in genes previously associated with breast cancer are described, including Cytoplasmic FMR1 interacting protein 1 (CYFIP1), reinforcing the utility of this approach in the search for biomarkers associated with breast cancer in peripheral blood.…”

Pre-diagnostic DNA methylation in blood leucocytes in cutaneous melanoma; a nested case–control study within the Norwegian Women and Cancer cohort

“…A prediction model was trained on the same CpG sites (p-value < 10 –10 , N CpG = 2176) from the GSE120878 data, using a regression and decision tree algorithm 40 similar to that of Onwuka et al 41 . The prediction model was applied on the NOWAC data set of incident melanoma cases and controls.…”