Browsing by Author "Walker, Brian A."

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    The Chromosome 13 Conundrum in Multiple Myeloma
    (American Association for Cancer Research, 2020-06-22) Walker, Brian A.; Medicine, School of Medicine
    In this issue of Blood Cancer Discovery, Chesi and colleagues have performed a series of mouse experiments, combined with patient sample analysis, to delineate the role of del(13) in multiple myeloma. They identify loss of the miRNA cluster MIR15A/16-1 as critical for myelomagenesis and progression of disease.
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    Corrigendum: Protein arginine methyltransferase 1 is a therapeutic vulnerability in multiple myeloma
    (Frontiers Media, 2023-11-15) Nguyen, Hong Phuong; Le, Anh Quynh; Liu, Enze; Cesarano, Annamaria; DiMeo, Francesco; Perna, Fabiana; Kapur, Reuben; Walker, Brian A.; Tran, Ngoc Tung; Pediatrics, School of Medicine
    [This corrects the article DOI: 10.3389/fimmu.2023.1239614.].
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    Cryopreservation Preserves Cell-Type Composition and Gene Expression Profiles in Bone Marrow Aspirates From Multiple Myeloma Patients
    (Frontiers Media, 2021-04-21) Chen, Duojiao; Abu Zaid, Mohammad I.; Reiter, Jill L.; Czader, Magdalena; Wang, Lin; McGuire, Patrick; Xuei, Xiaoling; Gao, Hongyu; Huang, Kun; Abonour, Rafat; Walker, Brian A.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Single-cell RNA sequencing reveals gene expression differences between individual cells and also identifies different cell populations that are present in the bulk starting material. To obtain an accurate assessment of patient samples, single-cell suspensions need to be generated as soon as possible once the tissue or sample has been collected. However, this requirement poses logistical challenges for experimental designs involving multiple samples from the same subject since these samples would ideally be processed at the same time to minimize technical variation in data analysis. Although cryopreservation has been shown to largely preserve the transcriptome, it is unclear whether the freeze-thaw process might alter gene expression profiles in a cell-type specific manner or whether changes in cell-type proportions might also occur. To address these questions in the context of multiple myeloma clinical studies, we performed single-cell RNA sequencing (scRNA-seq) to compare fresh and frozen cells isolated from bone marrow aspirates of six multiple myeloma patients, analyzing both myeloma cells (CD138+) and cells constituting the microenvironment (CD138-). We found that cryopreservation using 90% fetal calf serum and 10% dimethyl sulfoxide resulted in highly consistent gene expression profiles when comparing fresh and frozen samples from the same patient for both CD138+ myeloma cells (R ≥ 0.96) and for CD138- cells (R ≥ 0.9). We also demonstrate that CD138- cell-type proportions showed minimal alterations, which were mainly related to small differences in immune cell subtype sensitivity to the freeze-thaw procedures. Therefore, when processing fresh multiple myeloma samples is not feasible, cryopreservation is a useful option in single-cell profiling studies.
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    Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
    (BMC, 2022-02-01) Johnson, Travis S.; Yu, Christina Y.; Huang, Zhi; Xu, Siwen; Wang, Tongxin; Dong, Chuanpeng; Shao, Wei; Zaid, Mohammad Abu; Huang, Xiaoqing; Wang, Yijie; Bartlett, Christopher; Zhang, Yan; Walker, Brian A.; Liu, Yunlong; Huang, Kun; Zhang, Jie; Medicine, School of Medicine
    We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information "impressions," which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy. Using simulated data and ten diverse single-cell and patient bulk tissue transcriptomic datasets from glioblastoma multiforme (GBM), Alzheimer's disease (AD), and multiple myeloma (MM), we demonstrate the feasibility, flexibility, and broad applications of the DEGAS framework. DEGAS analysis on myeloma single-cell transcriptomics identified PHF19high myeloma cells associated with progression.
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    Differential RNA splicing as a potentially important driver mechanism in multiple myeloma
    (Ferrata Storti Foundation, 2021-03-01) Bauer, Michael A.; Ashby, Cody; Wardell, Christopher; Boyle, Eileen M.; Ortiz, Maria; Flynt, Erin; Thakurta, Anjan; Morgan, Gareth; Walker, Brian A.; Medicine, School of Medicine
    Disruption of the normal splicing patterns of RNA is a major factor in the pathogenesis of a number of diseases. Increasingly research has shown the strong influence that splicing patterns can have on cancer progression. Multiple Myeloma is a molecularly heterogeneous disease classified by the presence of key translocations, gene expression profiles and mutations but the splicing patterns in MM remains largely unexplored. We take a multifaceted approach to define the extent and impact of alternative splicing in MM. We look at the spliceosome component, SF3B1, with hotspot mutations (K700E and K666T/Q) shown to result in an increase in alternative splicing in other cancers. We discovered a number of differentially spliced genes in comparison of the SF3B1 mutant and wild type samples that included, MZB1, DYNLL1, TMEM14C and splicing related genes DHX9, CLASRP, and SNRPE. We identified a broader role for abnormal splicing showing clear differences in the extent of novel splice variants in the different translocation groups. We show that a high number of novel splice loci is associated with adverse survival and an ultra-high risk group. The enumeration of patterns of alternative splicing has the potential to refine MM classification and to aid in the risk stratification of patients.
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    Epigenomic translocation of H3K4me3 broad domains over oncogenes following hijacking of super-enhancers
    (CSH Press, 2021-12) Mikulasova, Aneta; Kent, Daniel; Trevisan-Herraz, Marco; Karataraki, Nefeli; Fung, Kent T. M.; Ashby, Cody; Cieslak, Agata; Yaccoby, Shmuel; Rhee, Frits van; Zangari, Maurizio; Thanendrarajan, Sharmilan; Schinke, Carolina; Morgan, Gareth J.; Asnafi, Vahid; Spicuglia, Salvatore; Brackley, Chris A.; Corcoran, Anne E.; Hambleton, Sophie; Walker, Brian A.; Rico, Daniel; Russell, Lisa J.; Medicine, School of Medicine
    Chromosomal translocations are important drivers of hematological malignancies whereby proto-oncogenes are activated by juxtaposition with super-enhancers, often called enhancer hijacking. We analysed the epigenomic consequences of rearrangements between the super-enhancers of the immunoglobulin heavy locus (IGH) and proto-oncogene CCND1 that are common in B cell malignancies. By integrating BLUEPRINT epigenomic data with DNA breakpoint detection, we characterised the normal chromatin landscape of the human IGH locus and its dynamics after pathological genomic rearrangement. We detected an H3K4me3 broad domain (BD) within the IGH locus of healthy B cells that was absent in samples with IGH-CCND1 translocations. The appearance of H3K4me3-BD over CCND1 in the latter was associated with overexpression and extensive chromatin accessibility of its gene body. We observed similar cancer-specific H3K4me3-BDs associated with super-enhancer hijacking of other common oncogenes in B cell (MAF, MYC and FGFR3/NSD2) and in T-cell malignancies (LMO2, TLX3 and TAL1). Our analysis suggests that H3K4me3-BDs can be created by super-enhancers and supports the new concept of epigenomic translocation, where the relocation of H3K4me3-BDs from cell identity genes to oncogenes accompanies the translocation of super-enhancers.
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    The functional epigenetic landscape of aberrant gene expression in molecular subgroups of newly diagnosed multiple myeloma
    (BMC, 2020-08-06) Choudhury, Samrat Roy; Ashby, Cody; Tytarenko, Ruslana; Bauer, Michael; Wang, Yan; Deshpande, Shayu; Den, Judith; Schinke, Carolina; Zangari, Maurizio; Thanendrarajan, Sharmilan; Davies, Faith E.; van Rhee, Frits; Morgan, Gareth J.; Walker, Brian A.; Medicine, School of Medicine
    Background Multiple Myeloma (MM) is a hematological malignancy with genomic heterogeneity and poor survival outcome. Apart from the central role of genetic lesions, epigenetic anomalies have been identified as drivers in the development of the disease. Methods Alterations in the DNA methylome were mapped in 52 newly diagnosed MM (NDMM) patients of six molecular subgroups and matched with loci-specific chromatin marks to define their impact on gene expression. Differential DNA methylation analysis was performed using DMAP with a ≥10% increase (hypermethylation) or decrease (hypomethylation) in NDMM subgroups, compared to control samples, considered significant for all the subsequent analyses with p<0.05 after adjusting for a false discovery rate. Results We identified differentially methylated regions (DMRs) within the etiological cytogenetic subgroups of myeloma, compared to control plasma cells. Using gene expression data we identified genes that are dysregulated and correlate with DNA methylation levels, indicating a role for DNA methylation in their transcriptional control. We demonstrated that 70% of DMRs in the MM epigenome were hypomethylated and overlapped with repressive H3K27me3. In contrast, differentially expressed genes containing hypermethylated DMRs within the gene body or hypomethylated DMRs at the promoters overlapped with H3K4me1, H3K4me3, or H3K36me3 marks. Additionally, enrichment of BRD4 or MED1 at the H3K27ac enriched DMRs functioned as super-enhancers (SE), controlling the overexpression of genes or gene-cassettes. Conclusions Therefore, this study presents the underlying epigenetic regulatory networks of gene expression dysregulation in NDMM patients and identifies potential targets for future therapies.
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    Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes
    (Springer, 2022-06-15) Bustoros, Mark; Anand, Shankara; Sklavenitis-Pistofidis, Romanos; Redd, Robert; Boyle, Eileen M.; Zhitomirsky, Benny; Dunford, Andrew J.; Tai, Yu-Tzu; Chavda, Selina J.; Boehner, Cody; Neuse, Carl Jannes; Rahmat, Mahshid; Dutta, Ankit; Casneuf, Tineke; Verona, Raluca; Kastritis, Efstathis; Trippa, Lorenzo; Stewart, Chip; Walker, Brian A.; Davies, Faith E.; Dimopoulos, Meletios-Athanasios; Bergsagel, P. Leif; Yong, Kwee; Morgan, Gareth J.; Aguet, François; Getz, Gad; Ghobrial, Irene M.; Medicine, School of Medicine
    Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models.
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    High-resolution simulations of chromatin folding at genomic rearrangements in malignant B cells provide mechanistic insights into proto-oncogene deregulation
    (Cold Spring Harbor Laboratory Press, 2022-07-21) Rico, Daniel; Kent, Daniel; Karataraki, Nefeli; Mikulasova, Aneta; Berlinguer-Palmini, Rolando; Walker, Brian A.; Javierre, Biola M.; Russell, Lisa J.; Brackley, Chris A.; Medicine, School of Medicine
    Genomic rearrangements are known to result in proto-oncogene deregulation in many cancers, but the link to 3D genome structure remains poorly understood. Here, we used the highly predictive heteromorphic polymer (HiP-HoP) model to predict chromatin conformations at the proto-oncogene CCND1 in healthy and malignant B cells. After confirming that the model gives good predictions of Hi-C data for the nonmalignant human B cell-derived cell line GM12878, we generated predictions for two cancer cell lines, U266 and Z-138. These possess genome rearrangements involving CCND1 and the immunoglobulin heavy locus (IGH), which we mapped using targeted genome sequencing. Our simulations showed that a rearrangement in U266 cells where a single IGH super-enhancer is inserted next to CCND1 leaves the local topologically associated domain (TAD) structure intact. We also observed extensive changes in enhancer-promoter interactions within the TAD, suggesting that it is the downstream chromatin remodeling which gives rise to the oncogene activation, rather than the presence of the inserted super-enhancer DNA sequence per se. Simulations of the IGH-CCND1 reciprocal translocation in Z-138 cells revealed that an oncogenic fusion TAD is created, encompassing CCND1 and the IGH super-enhancers. We predicted how the structure and expression of CCND1 changes in these different cell lines, validating this using qPCR and fluorescence in situ hybridization microscopy. Our work demonstrates the power of polymer simulations to predict differences in chromatin interactions and gene expression for different translocation breakpoints.
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    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 Medicine
    Multiple 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.