Wednesday, April 2, 2025
4/2/2025
Deciphering the underlying structure of the glucocorticoid gene regulatory network - ABSTRACT Gene regulatory networks (GRNs) consist of transcription factor (TF) proteins, their associated cis-regulatory elements (CREs) and target genes. These networks function as the central information processing hub within cells, orchestrating precise spatiotemporal control of gene expression in response to environmental signals, including medications. Glucocorticoids (GCs), commonly known as steroids, are among the most prescribed medications, proving highly effective in treating various conditions, from autoimmune diseases and inflammation to cancer. In B-cell acute lymphoblastic leukemia (B-ALL), GCs are a mainstay of contemporary multi-drug chemotherapy, and GC drug resistance is predictive of relapse and poor clinical outcome. We have mapped CREs that are crucial for the glucocorticoid gene regulatory network (GC-GRN), referred to as GC-response CREs (GCREs), by integrating diverse epigenomic, transcriptomic and high-throughput functional assays. Our previous work indicates that GCRE disruptions contribute to GC drug resistance in primary cells from patients through decreased cell apoptosis. Building upon our previous findings, we hypothesize that genetic alterations to GCREs impact gene regulatory responses to GCs, and they are therefore important contributors to GC drug resistance and clinical outcome in B-ALL patients. However, our knowledge on how GCREs are encoded in the human genome remains incomplete. Moreover, our comprehension of GCRE function and the impact of genetic variants within GCREs is still rudimental. To bridge this knowledge gap, we propose to: (a) utilize our extensive chromatin accessibility data that identified CREs in primary B-ALL cell from patients to expand our initial GCRE mapping in a diverse panel of human B-ALL cell lines, (b) identify the specific GCREs that impact GC drug resistance, (c) elucidate DNA sequence variants that modulate gene regulatory responses to GCs and (d) evaluate the consequences of GCRE disruptions identified in primary B-ALL cells from patients on GC drug resistance. Our long-term goal is to utilize the GC-GRN as a model for quantitatively assessing and modeling the functional effects of noncoding genetic variations on healthy traits and human disease. Collectively, these results will lead to a better understanding of how GRNs are encoded in human genomes, and how alterations to GRNs contribute to cellular phenotypes, complex traits and human disease.
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