ABSTRACT
Regulatory regions harbor multiple transcription factor (TF) recognition sites; however, the contribution of individual sites to regulatory function remains challenging to define. We describe an approach that exploits the error-prone nature of genome editing-induced double-strand break repair to map functional elements within regulatory DNA at nucleotide resolution. We demonstrate the approach on a human erythroid enhancer, revealing single TF recognition sites that gate the majority of downstream regulatory function.
Subject(s)
Carrier Proteins/genetics , DNA Footprinting/methods , Genomics/methods , Nuclear Proteins/genetics , Regulatory Sequences, Nucleic Acid , Base Sequence , Binding Sites , DNA Breaks, Double-Stranded , DNA Repair , Enhancer Elements, Genetic , Erythrocytes/physiology , Erythropoiesis , Genome, Human , Humans , Mutation , Repressor Proteins , Transcription Factors/metabolismABSTRACT
The analytical validation is reported for a targeted methylation-based cell-free DNA multi-cancer early detection test designed to detect cancer and predict the cancer signal origin (tissue of origin). A machine-learning classifier was used to analyze the methylation patterns of >105 genomic targets covering >1 million methylation sites. Analytical sensitivity (limit of detection [95% probability]) was characterized with respect to tumor content by expected variant allele frequency and was determined to be 0.07%-0.17% across five tumor cases and 0.51% for the lymphoid neoplasm case. Test specificity was 99.3% (95% confidence interval, 98.6-99.7%). In the reproducibility and repeatability study, results were consistent in 31/34 (91.2%) pairs with cancer and 17/17 (100%) pairs without cancer; between runs, results were concordant for 129/133 (97.0%) cancer and 37/37 (100%) non-cancer sample pairs. Across 3- to 100-ng input levels of cell-free DNA, cancer was detected in 157/182 (86.3%) cancer samples but not in any of the 62 non-cancer samples. In input titration tests, cancer signal origin was correctly predicted in all tumor samples detected as cancer. No cross-contamination events were observed. No potential interferent (hemoglobin, bilirubin, triglycerides, genomic DNA) affected performance. The results of this analytical validation study support continued clinical development of a targeted methylation cell-free DNA multi-cancer early detection test.