Biology subjects

Walker, B. A.

Publications and source records attributed to Walker, B. A..

8 recordsLinked to original sources

bioRxiv2026

Genomic characterization of patient derived xenograft models of multiple myeloma reveals selection of multiple pre-existing high risk clones

Multiple myeloma (MM) is a genomically complex malignancy of terminally differentiated plasma cells. Here, we have utilized the SCID-rab patient derived xenograft (PDX) model as a platform to expand scarce primary MM samples across disease stages and major cytogenetic subgroups for comprehensive molecular analysis. The model generated abundant CD138+ cells while retaining key genomic, transcriptomic and proteomic features of corresponding patient tumors. Compared with human myeloma cell lines, PDX cells more closely resembled primary MM in proliferative state and expression of therapeutically relevant targets. WGS and single cell WGS showed that PDXs arose from the selection of pre-existing subclones, including clones harboring high-risk alterations and convergent mechanisms of tumor suppressor inactivation. These findings establish SCID-rab PDX models as a platform for multiomic profiling, studies of clonal evolution, and determining therapeutic response in MM.

cancer biology↗

bioRxiv2025

Utilizing Genomics to Identify Novel Immunotherapeutic Targets in Multiple Myeloma High-Risk Subgroups

Immunotherapy is now standard of care for multiple myeloma, where the most common targets are B cell maturation antigen, CD38, and G protein-coupled receptor class C group 5 member D but strategies to identify additional targets are needed. We have utilized two large datasets of genomic data and integrated them with existing databases to identify expressed cell surface targets in myeloma patients. Importantly, we also identify targets specific to genomic defined subgroups of patients including primary translocations and high-risk subgroups. Examples of subgroup targets include ROBO3 in t(4;14), CD109 in t(14;16), CD20 in t(11;14), GPRC5D in 1q+, and ADAM28 in biallelic TP53 samples. Expression was validated by flow cytometry and CRISPR-Cas9 knock out models. Sub-clonal differences in expression were noted, as was alternative splicing of existing immunotherapy targets such as FCRL5. These results highlight the use of genomic stratification to identify novel therapeutic targets. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=157 HEIGHT=200 SRC="FIGDIR/small/635544v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@6965e6org.highwire.dtl.DTLVardef@1a0e567org.highwire.dtl.DTLVardef@34fc30org.highwire.dtl.DTLVardef@98c3d4_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2021

Genetic Subtypes of Smoldering Multiple Myeloma are associated with Distinct Pathogenic Phenotypes and Clinical Outcomes

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 integrated 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identified six distinct genetic subtypes. These subtypes were differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three subtypes were 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 model.

cancer biology↗

bioRxiv2021

High-resolution simulations of chromatin folding at genomic rearrangements in malignant B-cells provide mechanistic insights on proto-oncogene deregulation

Genomic rearrangements are known to result in proto-oncogene deregulation in many cancers, but the link to genome 3D 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 non-malignant 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 chain 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 remodelling 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 break-points.

genomics↗

bioRxiv2020

Epigenomic translocation of H3K4me3 broad domains following super-enhancer hijacking

Chromosomal translocations are important drivers of haematological malignancies whereby proto-oncogenes are activated by juxtaposition with 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 hijacking of super-enhancers of other common oncogenes in B-cell (MAF, MYC and FGFR3/NSD2) and 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.

genomics↗

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗

bioRxiv2019

Microhomology-mediated end joining drives complex rearrangements and over expression of MYC and PVT1 in multiple myeloma

MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3. We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in over-expression of key genes and ChIP-seq identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.

cancer biology↗

bioRxiv2017

Development of a targeted sequencing approach to identify prognostic, predictive and diagnostic markers in paediatric solid tumours

The implementation of personalised medicine in childhood cancers has been limited by a lack of clinically validated multi-target sequencing approaches specific for paediatric solid tumours. In order to support innovative clinical trials in high-risk patients with unmet need, we have developed a clinically relevant targeted sequencing panel spanning 311 kb and comprising 78 genes involved in childhood cancers. A total of 132 samples were used for the validation of the panel, including Horizon Discovery cell blends (n=4), cell lines (n=15), formalin-fixed paraffin embedded (FFPE, n=83) and fresh frozen tissue (FF, n=30) patient samples. Cell blends containing known single nucleotide variants (SNVs, n=528) and small insertion-deletions (indels n=108) were used to define panel sensitivities of [≥]98% for SNVs and [≥]83% for indels [95% CI] and panel specificity of [≥]98% [95% CI] for SNVs. FFPE samples performed comparably to FF samples (n=15 paired). Of 95 well-characterised genetic abnormalities in 33 clinical specimens and 13 cell lines (including SNVs, indels, amplifications, rearrangements and chromosome losses), 94 (98.9%) were detected by our approach. We have validated a robust and practical methodology to guide clinical management of children with solid tumours based on their molecular profiles. Our work demonstrates the value of targeted gene sequencing in the development of precision medicine strategies in paediatric oncology.

genomics↗