Abstract 2611: Transcription factor-nucleosome dynamics inferred from plasma cfDNA delineates tumor and tumor-microenvironment phenotype

Abstract

Abstract Our current understanding of solid tumors and their progression primarily relies on in vitro models, cell lines, patient-derived xenografts, and scarce data from invasive tissue biopsies from patients. The ability to monitor changes in chromatin structure and transcription factor binding in tumor cells using a minimally invasive approach in humans has the potential to revolutionize our understanding of disease progression and treatment resistance. In this study, we use the example of estrogen receptor (ER) positive breast cancer, the most common disease subtype, and define the ER axis from plasma cell-free DNA (cfDNA). While lymphoid/myeloid cell turnover represents the dominant source of cfDNA in the bloodstream, a detectable fraction of DNA from tumor tissue-of-origin can be found in patients with solid cancers. cfDNA is the product of the action of endogenous nucleases on chromatin; and retains the map of epigenomes from cells of origin. Our method therefore non-invasively captures TF-nucleosome dynamics in tumor tissue-of-origin using plasma cfDNA. First, we show that we can reliably identify the active binding of hematopoietic pioneer factor PU.1 and CTCF from cfDNA of healthy humans and cancer patients. Then to define cfDNA binding of disease specific TF ER, we used ER+ patient-derived xenograft (PDX) models allowing for a clear separation of tumor signal from hematopoietic background. This allowed us to establish the sensitivity and specificity of our approach. We also identified the subset of CUT&RUN-defined ER binding sites that feature the strongest binding in vivo from both lymphocyte background as well as cancer cells. Furthermore, we can define the active binding sites of pioneer factor FOXA1, which facilitates ER binding by opening the chromatin. Based on the TF protection levels from cfDNA we were able to define tumor as well as hematopoietic-specific TF binding sites that can serve as potential hotspots to monitor ER+ disease state at around 1% tumor fraction. These data demonstrate our ability to simultaneously monitor TF and nucleosome dynamics at disease sites just from plasma that can enable real-time monitoring of disease phenotype in a minimally invasive manner. Citation Format: Satyanarayan Rao, Amy Han, Alexis Zukowski, Etana Kopin, Peter Kabos, Srinivas Ramachandran. Transcription factor-nucleosome dynamics inferred from plasma cfDNA delineates tumor and tumor-microenvironment phenotype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2611.