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Department of Biostatistics and Health Data Science
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A dual department of the Richard M. Fairbanks School of Public Health and the IU School of Medicine.
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Browsing Department of Biostatistics and Health Data Science by Author "Abu Zaid, Mohammad"
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Item Identifying 1q amplification and PHF19 expressing high-risk cells associated with relapsed/refractory multiple myeloma(Research Square, 2023-08-16) Johnson, Travis S.; Sudha, Parvathi; Liu, Enze; Blaney, Patrick; Morgan, Gareth; Chopra, Vivek S.; Dos Santos, Cedric; Nixon, Michael; Huang, Kun; Suvannasankha, Attaya; Abu Zaid, Mohammad; Abonour, Rafat; Walker, Brian A.; Biostatistics and Health Data Science, School of MedicineMultiple Myeloma is an incurable plasma cell malignancy with a poor survival rate that is usually treated with immunomodulatory drugs (iMiDs) and proteosome inhibitors (PIs). The malignant plasma cells quickly become resistant to these agents causing relapse and uncontrolled growth of resistant clones. From whole genome sequencing (WGS) and RNA sequencing (RNA-seq) studies, different high-risk translocation, copy number, mutational, and transcriptional markers have been identified. One of these markers, PHF19, epigenetically regulates cell cycle and other processes and has already been studied using RNA-seq. In this study a massive (325,025 cells and 49 patients) single cell multiomic dataset was generated with jointly quantified ATAC- and RNA-seq for each cell and matched genomic profiles for each patient. We identified an association between one plasma cell subtype with myeloma progression that we have called relapsed/refractory plasma cells (RRPCs). These cells are associated with 1q alterations, TP53 mutations, and higher expression of PHF19. We also identified downstream regulation of cell cycle inhibitors in these cells, possible regulation of the transcription factor (TF) PBX1 on 1q, and determined that PHF19 may be acting primarily through this subset of cells.