RESUMEN
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.
RESUMEN
BACKGROUND: Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking. METHODS: We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built. RESULTS: We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS's potential for liquid biopsies. CONCLUSIONS: We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.
RESUMEN
Malignant mesothelioma is an aggressive cancer type linked to asbestos exposure. Because of several intrinsic challenges, mesothelioma is often diagnosed in an advanced disease stage. Therefore, there is a need for diagnostic biomarkers that may contribute to early detection. Recently, the epigenome of tumors is being extensively investigated to identify biomarkers. This manuscript is a systematic review summarizing the state-of-the-art research investigating DNA methylation in mesothelioma. Four literature databases (PubMed, Scopus, Web of Science, MEDLINE) were systematically searched for studies investigating DNA methylation in mesothelioma up to October 16, 2020. A meta-analysis was performed per gene investigated in at least two independent studies. A total of 53 studies investigated DNA methylation of 97 genes in mesothelioma and are described in a qualitative overview. Furthermore, ten studies investigating 13 genes (APC, CDH1, CDKN2A, DAPK, ESR1, MGMT, miR-34b/c, PGR, RARß, RASSF1, SFRP1, SFRP4, WIF1) were included in the quantitative meta-analysis. In this meta-analysis, the APC gene is significantly hypomethylated in mesothelioma, whereas CDH1, ESR1, miR-34b/c, PGR, RARß, SFRP1, and WIF1 are significantly hypermethylated in mesothelioma. The three genes that are the most appropriate candidate biomarkers from this meta-analysis are APC, miR-34b/c, and WIF1. Nevertheless, both study number and study objects comprised in this meta-analysis are too low to draw final conclusions on their clinical applications. The elucidation of the genome-wide DNA methylation profile of mesothelioma is desirable in the future, using a standardized genome-wide methylation analysis approach. The most informative CpG sites from this signature could then form the basis of a panel of highly sensitive and specific biomarkers that can be used for the diagnosis of mesothelioma and even for the screening of an at high-risk population of asbestos-exposed individuals.