Publications by authors named "Allen W Zhang"

15 Publications

  • Page 1 of 1

Rethinking the need for a platelet transfusion threshold of 50 × 10 /L for lumbar puncture in cancer patients.

Transfusion 2020 Oct 18;60(10):2243-2249. Epub 2020 Aug 18.

Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

Background: Lumbar puncture (LP) is a frequently performed diagnostic and therapeutic procedure in oncology patients. Transfusing to a minimum preprocedural platelet threshold of 50 × 10 /L is widely upheld without good quality evidence. The objective was to compare the outcomes of LPs performed with platelets above and below this threshold. An increased risk of adverse events in patients with lower platelet counts was not expected. As a corollary, transfusion reaction rates incurred by transfusing to this recommended threshold are also reported.

Methods: A total of 2259 LPs performed on 1137 oncology patients (adult, n = 871, and pediatric, n = 266) were retrospectively analyzed between February 2011 and December 2017. The incidence of LP-related complications for groups above and below the minimum platelet threshold was compared. Traumatic tap was defined as 500 or more red blood cells per high-power field in the cerebral spinal fluid. Groups were compared using the 2-Proportion Z-test and Fisher exact test.

Results: At time of LP, the total number of events with platelets less than 50 × 10 /L and 50 × 10 /L or greater were 110 and 2149, respectively. There were no significant differences in LP-associated complications between patients with platelet counts above or below 50 × 10 /L (P = .29). Patients with a pre-LP platelet count of less than 50 × 10 /L had a higher proportion of traumatic taps (P < .001). Three patients developed transfusion-related adverse events.

Conclusion: Patients with platelet counts less than 50 × 10 /L did not have a higher incidence of clinically significant post-lumbar puncture complications (P = .29).
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http://dx.doi.org/10.1111/trf.15988DOI Listing
October 2020

TMEM30A loss-of-function mutations drive lymphomagenesis and confer therapeutically exploitable vulnerability in B-cell lymphoma.

Nat Med 2020 04 24;26(4):577-588. Epub 2020 Feb 24.

Centre for Lymphoid Cancer, British Columbia Cancer, Vancouver, British Columbia, Canada.

Transmembrane protein 30A (TMEM30A) maintains the asymmetric distribution of phosphatidylserine, an integral component of the cell membrane and 'eat-me' signal recognized by macrophages. Integrative genomic and transcriptomic analysis of diffuse large B-cell lymphoma (DLBCL) from the British Columbia population-based registry uncovered recurrent biallelic TMEM30A loss-of-function mutations, which were associated with a favorable outcome and uniquely observed in DLBCL. Using TMEM30A-knockout systems, increased accumulation of chemotherapy drugs was observed in TMEM30A-knockout cell lines and TMEM30A-mutated primary cells, explaining the improved treatment outcome. Furthermore, we found increased tumor-associated macrophages and an enhanced effect of anti-CD47 blockade limiting tumor growth in TMEM30A-knockout models. By contrast, we show that TMEM30A loss-of-function increases B-cell signaling following antigen stimulation-a mechanism conferring selective advantage during B-cell lymphoma development. Our data highlight a multifaceted role for TMEM30A in B-cell lymphomagenesis, and characterize intrinsic and extrinsic vulnerabilities of cancer cells that can be therapeutically exploited.
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http://dx.doi.org/10.1038/s41591-020-0757-zDOI Listing
April 2020

Single-Cell Transcriptome Analysis Reveals Disease-Defining T-cell Subsets in the Tumor Microenvironment of Classic Hodgkin Lymphoma.

Cancer Discov 2020 03 19;10(3):406-421. Epub 2019 Dec 19.

Centre for Lymphoid Cancer, British Columbia Cancer, Vancouver, British Columbia, Canada.

Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma-specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma-associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3 T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3 T cells in the direct vicinity of MHC class II-deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma. SIGNIFICANCE: We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell-like immunosuppressive subset of LAG3 T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints...
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http://dx.doi.org/10.1158/2159-8290.CD-19-0680DOI Listing
March 2020

Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses.

Genome Biol 2019 10 17;20(1):210. Epub 2019 Oct 17.

Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada.

Background: Single-cell RNA sequencing (scRNA-seq) is a powerful tool for studying complex biological systems, such as tumor heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumor tissues and patient-derived mouse xenografts for scRNA-seq are not well understood.

Results: We use low temperature (6 °C) protease and collagenase (37 °C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNA-seq dataset comprising 155,165 cells from patient cancer tissues, patient-derived breast cancer xenografts, and cancer cell lines. We observe substantial variation in standard quality control metrics of cell viability across conditions and tissues. From the contrast between tissue protease dissociation at 37 °C or 6 °C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37 °C), which are minimized by dissociation with a cold active protease (6 °C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues.

Conclusions: The method and conditions of tumor dissociation influence cell yield and transcriptome state and are both tissue- and cell-type dependent. Interpretation of stress pathway expression differences in cancer single-cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with the identification of such effects in dissociated scRNA-seq experiments.
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http://dx.doi.org/10.1186/s13059-019-1830-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6796327PMC
October 2019

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling.

Nat Methods 2019 10 9;16(10):1007-1015. Epub 2019 Sep 9.

Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.

Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.
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http://dx.doi.org/10.1038/s41592-019-0529-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485597PMC
October 2019

Cancer stemness, intratumoral heterogeneity, and immune response across cancers.

Proc Natl Acad Sci U S A 2019 04 17;116(18):9020-9029. Epub 2019 Apr 17.

Deeley Research Centre, BC Cancer, Victoria, BC V8R 6V5, Canada;

Regulatory programs that control the function of stem cells are active in cancer and confer properties that promote progression and therapy resistance. However, the impact of a stem cell-like tumor phenotype ("stemness") on the immunological properties of cancer has not been systematically explored. Using gene-expression-based metrics, we evaluated the association of stemness with immune cell infiltration and genomic, transcriptomic, and clinical parameters across 21 solid cancers. We found pervasive negative associations between cancer stemness and anticancer immunity. This occurred despite high stemness cancers exhibiting increased mutation load, cancer-testis antigen expression, and intratumoral heterogeneity. Stemness was also strongly associated with cell-intrinsic suppression of endogenous retroviruses and type I IFN signaling, and increased expression of multiple therapeutically accessible immunosuppressive pathways. Thus, stemness is not only a fundamental process in cancer progression but may provide a mechanistic link between antigenicity, intratumoral heterogeneity, and immune suppression across cancers.
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http://dx.doi.org/10.1073/pnas.1818210116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500180PMC
April 2019

Integrated structural variation and point mutation signatures in cancer genomes using correlated topic models.

PLoS Comput Biol 2019 02 22;15(2):e1006799. Epub 2019 Feb 22.

Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.

Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n = 755 samples total). We show how introducing correlated structure both within and between modes of mutation can increase accuracy of signature discovery, particularly in the context of sparse data. Our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, and provides a statistical modeling framework to incorporate additional features of interest for future studies.
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http://dx.doi.org/10.1371/journal.pcbi.1006799DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402697PMC
February 2019

Computational Analysis of Transcriptional Regulation Sites at the HTT Gene Locus.

J Huntingtons Dis 2018 ;7(3):223-237

Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, University of British Columbia, Vancouver, BC, Canada.

Background: Huntington's disease is a late onset neurological disorder caused by a trinucleotide CAG repeat expansion mutation in the HTT gene encoding for the protein huntingtin. Despite considerable ongoing research, the wild-type function of huntingtin is not yet fully understood.

Objective: To improve knowledge of HTT gene regulation at the transcriptional level and inform future studies aimed at uncovering the HTT gene's normal function.

Methods: The HTT gene region was functionally characterized through an in silico analysis using publicly available data sets. ChIP-seq data sets and the online STRING database were used to identify putative transcription factor binding sites (TFBSs) and protein-protein interactions within the HTT promoter region. siRNA-mediated knockdown and ChIP-qPCR of STAT1, a TF identified from the in silico analysis, were used to validate the bioinformatics screen.

Results: 16 regions containing potential regulatory genomic markers were identified. TFBSs for 59 transcription factors (TFs) were detected in one or more of the 16 candidate regions. Using these TFs, 15 clusters of protein-protein interactions were identified using STRING. siRNA-mediated knockdown of STAT1 resulted in an increase in HTT expression, and ChIP-qPCR detected enrichment of STAT1 binding at one of the predicted regions. These assays confirmed the utility of the bioinformatic analysis.

Conclusions: Putative regulatory regions outside of the immediate HTT promoter region have been identified with specific protein-protein interactions. Future work will focus on in vitro and in vivo studies to examine the effect of modulating identified TFBSs and altering the levels of specific TFs of interest in regulating HTT gene expression.
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http://dx.doi.org/10.3233/JHD-170272DOI Listing
October 2019

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

Cell 2018 06 10;173(7):1755-1769.e22. Epub 2018 May 10.

Department of Molecular Oncology, BC Cancer, Vancouver, BC V5Z 4E6, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada. Electronic address:

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.
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http://dx.doi.org/10.1016/j.cell.2018.03.073DOI Listing
June 2018

Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes.

Nat Genet 2017 Jun 24;49(6):856-865. Epub 2017 Apr 24.

Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.

We studied the whole-genome point mutation and structural variation patterns of 133 tumors (59 high-grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell (GCT)) as a substrate for class discovery in ovarian cancer. Ab initio clustering of integrated point mutation and structural variation signatures identified seven subgroups both between and within histotypes. Prevalence of foldback inversions identified a prognostically significant HGSC group associated with inferior survival. This finding was recapitulated in two independent cohorts (n = 576 cases), transcending BRCA1 and BRCA2 mutation and gene expression features of HGSC. CCOC cancers grouped according to APOBEC deamination (26%) and age-related mutational signatures (40%). ENOCs were divided by cases with microsatellite instability (28%), with a distinct mismatch-repair mutation signature. Taken together, our work establishes the potency of the somatic genome, reflective of diverse DNA repair deficiencies, to stratify ovarian cancers into distinct biological strata within the major histotypes.
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http://dx.doi.org/10.1038/ng.3849DOI Listing
June 2017

CuboCube: Student creation of a cancer genetics e-textbook using open-access software for social learning.

PLoS Biol 2017 03 7;15(3):e2001192. Epub 2017 Mar 7.

University of British Columbia, Vancouver, British Columbia, Canada.

Student creation of educational materials has the capacity both to enhance learning and to decrease costs. Three successive honors-style classes of undergraduate students in a cancer genetics class worked with a new software system, CuboCube, to create an e-textbook. CuboCube is an open-source learning materials creation system designed to facilitate e-textbook development, with an ultimate goal of improving the social learning experience for students. Equipped with crowdsourcing capabilities, CuboCube provides intuitive tools for nontechnical and technical authors alike to create content together in a structured manner. The process of e-textbook development revealed both strengths and challenges of the approach, which can inform future efforts. Both the CuboCube platform and the Cancer Genetics E-textbook are freely available to the community.
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http://dx.doi.org/10.1371/journal.pbio.2001192DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340349PMC
March 2017

Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer.

Nat Genet 2016 07 16;48(7):758-67. Epub 2016 May 16.

Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.

We performed phylogenetic analysis of high-grade serous ovarian cancers (68 samples from seven patients), identifying constituent clones and quantifying their relative abundances at multiple intraperitoneal sites. Through whole-genome and single-nucleus sequencing, we identified evolutionary features including mutation loss, convergence of the structural genome and temporal activation of mutational processes that patterned clonal progression. We then determined the precise clonal mixtures comprising each tumor sample. The majority of sites were clonally pure or composed of clones from a single phylogenetic clade. However, each patient contained at least one site composed of polyphyletic clones. Five patients exhibited monoclonal and unidirectional seeding from the ovary to intraperitoneal sites, and two patients demonstrated polyclonal spread and reseeding. Our findings indicate that at least two distinct modes of intraperitoneal spread operate in clonal dissemination and highlight the distribution of migratory potential over clonal populations comprising high-grade serous ovarian cancers.
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http://dx.doi.org/10.1038/ng.3573DOI Listing
July 2016

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

Nucleic Acids Res 2016 Jan 3;44(D1):D110-5. Epub 2015 Nov 3.

Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, V5Z 4H4, BC, Canada

JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release.
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http://dx.doi.org/10.1093/nar/gkv1176DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702842PMC
January 2016

Cis-regulatory somatic mutations and gene-expression alteration in B-cell lymphomas.

Genome Biol 2015 Apr 23;16:84. Epub 2015 Apr 23.

Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, V5Z 1L3, BC, Canada.

Background: With the rapid increase of whole-genome sequencing of human cancers, an important opportunity to analyze and characterize somatic mutations lying within cis-regulatory regions has emerged. A focus on protein-coding regions to identify nonsense or missense mutations disruptive to protein structure and/or function has led to important insights; however, the impact on gene expression of mutations lying within cis-regulatory regions remains under-explored. We analyzed somatic mutations from 84 matched tumor-normal whole genomes from B-cell lymphomas with accompanying gene expression measurements to elucidate the extent to which these cancers are disrupted by cis-regulatory mutations.

Results: We characterize mutations overlapping a high quality set of well-annotated transcription factor binding sites (TFBSs), covering a similar portion of the genome as protein-coding exons. Our results indicate that cis-regulatory mutations overlapping predicted TFBSs are enriched in promoter regions of genes involved in apoptosis or growth/proliferation. By integrating gene expression data with mutation data, our computational approach culminates with identification of cis-regulatory mutations most likely to participate in dysregulation of the gene expression program. The impact can be measured along with protein-coding mutations to highlight key mutations disrupting gene expression and pathways in cancer.

Conclusions: Our study yields specific genes with disrupted expression triggered by genomic mutations in either the coding or the regulatory space. It implies that mutated regulatory components of the genome contribute substantially to cancer pathways. Our analyses demonstrate that identifying genomically altered cis-regulatory elements coupled with analysis of gene expression data will augment biological interpretation of mutational landscapes of cancers.
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http://dx.doi.org/10.1186/s13059-015-0648-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4467049PMC
April 2015

JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles.

Nucleic Acids Res 2014 Jan 4;42(Database issue):D142-7. Epub 2013 Nov 4.

Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, University of British Columbia, Vancouver, BC, Canada, Department of Biology and Biotech Research and Innovation Centre, The Bioinformatics Centre, Copenhagen University, Ole Maaloes Vej 5, DK-2200, Denmark, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA, Laboratoire Physiologie Cellulaire & Végétale, Université Grenoble Alpes, CNRS, CEA, iRTSV, INRA, 38054 Grenoble, France, Computational Regulatory Genomics, MRC Clinical Sciences Centre, Imperial College London, Du Cane Road, London W12 0NN, UK, and Department of Informatics, University of Bergen, Thormøhlensgate 55, N-5008 Bergen, Norway.

JASPAR (http://jaspar.genereg.net) is the largest open-access database of matrix-based nucleotide profiles describing the binding preference of transcription factors from multiple species. The fifth major release greatly expands the heart of JASPAR-the JASPAR CORE subcollection, which contains curated, non-redundant profiles-with 135 new curated profiles (74 in vertebrates, 8 in Drosophila melanogaster, 10 in Caenorhabditis elegans and 43 in Arabidopsis thaliana; a 30% increase in total) and 43 older updated profiles (36 in vertebrates, 3 in D. melanogaster and 4 in A. thaliana; a 9% update in total). The new and updated profiles are mainly derived from published chromatin immunoprecipitation-seq experimental datasets. In addition, the web interface has been enhanced with advanced capabilities in browsing, searching and subsetting. Finally, the new JASPAR release is accompanied by a new BioPython package, a new R tool package and a new R/Bioconductor data package to facilitate access for both manual and automated methods.
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http://dx.doi.org/10.1093/nar/gkt997DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965086PMC
January 2014