Abstract 4411: Enhancing scalability and consistency in clinical multiomics via an optimized fixed cell ATAC-seq method​

Abstract ATAC-seq has an emerging role in decoding mechanisms of gene regulation, offering valuable insights into pathology and treatment response in disease models. However, clinical adoption of ATAC-seq methods has been limited by logistical hurdles, including time-sensitive processing of fresh samples and compromised viability of cryopreserved cells. These constraints, compounded by changes in open chromatin regions (OCRs) following cryopreservation, introduce unintended bias and pose significant obstacles for the translational impact of ATAC-seq experiments. ​ Here, we introduce an optimized fixed-cell ATAC-seq approach to overcome these limitations and unlock new sample types for ATAC-seq analyses. Our solution improves and simplifies the workflow from sample collection to clinical deliverable. This method enables ATAC-seq investigation of a diverse range of samples and facilitates the execution of complex experimental designs, including time course studies and high throughput screening. ​To demonstrate the effectiveness of this method, we compared our optimized fixed-cell method with traditional ATAC-seq preparations in both fresh and cryopreserved GM12878 cells in parallel. Human GM12878 cell line was obtained from Coriell Institute for Medical Research5. Remarkably, we observed consistent genome-wide patterns of OCR enrichment at key regulatory elements across the three sample preparation methods. We observed consistent OCR enrichment across the promoter region of known highly-expressed B-cell genes including CD48 and LCP1, underscoring this assay’s ability to detect chromatin changes at key genes in human disease models. ​ To investigate the potential for multiomic analysis using this method, we prepared RNA-seq libraries from fixed-cell samples in parallel to ATAC-seq. We observed significantly elevated gene expression related to B-cell function and B-cell diseases, demonstrating our method’s compatibility with RNA-seq data collection and integration. This optimized fixed-cell ATAC-seq approach offers enhanced scalability and consistency over conventional methods and presents new opportunities for the multiomic analysis of chromatin and transcriptional activity genome-wide from a single sample in both clinical and research settings. Citation Format: Dafne Alves Winders, Riley Graham, Xiangying Mao, Ilaria De Vito, Andrea O'Hara, Laure Turner, Haythem Latif. Enhancing scalability and consistency in clinical multiomics via an optimized fixed cell ATAC-seq method​ abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 4411.