Abstract
3052 Background: CfmeDNA is a promising biomarker for non-invasive assessment of solid tumors: i) MeDNA is tissue- and tumor-specific ii) cfDNA methylation changes are stable unlike DNA alterations iii) ‘methylation target size’ is larger than identifying specific genomic alterations and, therefore, more sensitive. CfMeDIP-seq is a sensitive assay for genome-wide bisulfite-free cfMeDNA profiling, that requires 1-10 ng input DNA. We tested the feasibility of cfMeDIP-seq to detect ccRCC across TNM stages. Methods: We evaluated plasma cfDNA collected prior to nephrectomy in 46 pts with ccRCC: 25 stage I, 7 stage II, 6 stage III, 8 stage IV. cfMeDIP-seq involves four steps: 1) cfDNA end-repair, A-tailing, and adapter ligation 2) cfMeDNA immunoprecipitation and enrichment using an Ab targeting 5-methylcytosine (quality control by qPCR to ensure <1% of unMeDNA and >99% reaction specificity) 3) adapter-mediated PCR to amplify cfMeDNA 4) high-throughput NGS for cfMeDNA data. A previously-derived model (Shen et al, Nature, 2018) was used to classify pts as having ccRCC or not based on cfMeDNA. cfMeDIP-seq paired end data was reduced to 300 bp windows of the genome that map to CpG islands, shores, shelves, and FANTOM5 enhancers; a classifier was then built using the top 1,000 most variable fragments between pts with ccRCC and cancer-free controls. Statistical comparisons were performed in the R statistical environment, with the caret package being used for classifier construction and evaluation. Results: The average amount of cfDNA isolated from 1 ml of ccRCC plasma was 19.8±39.8 ng/µL [1.95-260]. Greater than 99% specificity of reaction and <1% of unMeDNA was achieved in 46/46 samples (100%). The previously-derived classifier of ccRCC correctly predicted 46/46 pts (100%) as having ccRCC. Across 3 rounds of 5-fold cross-validation, the classifier performed with a Cohen’s Kappa of 0.93. Conclusions: CfMeDIP-seq is a non-invasive, cost-effective, and sensitive assay to detect cancer-specific cfmeDNA in ccRCC pts prior to nephrectomy. With further validation, cfmeDNA may detect minimal residual disease after nephrectomy for ‘precision’ adjuvant therapy.
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