Abstract Accurate methylation sequencing from clinical samples is challenging due to DNA-damaging chemistries that reduce sequence diversity, limiting data quality and reproducibility—particularly for fragmented or low-input materials such as cfDNA. The objective of this study was to evaluate a new positive-readout methylation method (TAPS+) in a clinically relevant cohort and compare its performance to an enzymatic methylation conversion method employing a negative-readout approach. TAPS+ is a non-damaging chemistry that converts methylated cytosines to thymines while preserving unmethylated cytosines, maintaining full sequence complexity and enabling direct methylation detection. This method was applied to a 24-sample cohort comprising invasive breast carcinoma patients, healthy donors, and control samples spanning a range of methylation states. Libraries were sequenced in parallel with those from an enzymatic negative-readout method to assess conversion efficiency, background, and biological concordance of differentially methylated regions (DMRs). The R package methylKit was used for DMR analysis, and biomarker candidates were identified based on statistically significant methylation differences within annotated genomic regions. Compared to the negative-readout method, TAPS+ achieved a shorter turnaround time and higher library yields across all sample types. In cfDNA samples, TAPS+ produced significantly higher methylation ratios than the negative-readout method (p = 8.6e-10). A methylated control showed an 88.8% 5mC rate with TAPS+, versus 76.8% with the negative-readout method, suggesting greater accuracy. CpG island methylation was strongly correlated across methods, though the negative-readout method had greater noise at low coverage sites. Both breast cancer patients and healthy individuals exhibited a characteristic dip in average DNA methylation levels around transcription start sites, consistent with promoter hypomethylation, with no significant differences observed between cohorts. DMR analysis with TAPS+ identified significant biomarker candidates, including SHH hypermethylation (q = 3.15e-5), associated with cancer development and progression. Additional biomarkers were associated with developmental pathways, cancer signaling, transcriptional regulation, and immune response. The negative-readout dataset did not demonstrate strong biomarker candidates indicative of disease status. TAPS+ enables high-fidelity methylation sequencing from diverse and challenging clinical materials, supporting robust epigenetic analysis within a streamlined workflow. The positive-readout approach demonstrated superior data quality and biological relevance compared to an enzymatic negative-readout method, highlighting its potential utility for translational research, early detection, and clinical assay development. Citation Format: Kimberly A. Holden, Kerry D. Fitzgerald, Adib Shafi, Ashraf Shabaneh, Dennis D. Krutkin, Tong Liu, Eyad Almasri, Graham McLennan, Nathan Faulkner, Craig Marshall, Travis Sanders, Thomas Harrison, Eduard Casas, Kristina Giorda, Doug Wendel, Brian Kudlow, Shakti Ramkissoon, Marcia Eisenberg, Brian Caveney, Eric Severson, Taylor J. Jensen, Jonathan Williams. Utility of TAPS+: a positive-readout methylation sequencing approach for high-fidelity epigenetic profiling abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3213.
Holden et al. (Fri,) studied this question.