Publications by authors named "Yeqiao Zhou"

8 Publications

  • Page 1 of 1

ALC1 links chromatin accessibility to PARP inhibitor response in homologous recombination-deficient cells.

Nat Cell Biol 2021 02 18;23(2):160-171. Epub 2021 Jan 18.

Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

The response to poly(ADP-ribose) polymerase inhibitors (PARPi) is dictated by homologous recombination (HR) DNA repair and the abundance of lesions that trap PARP enzymes. It remains unclear, however, if the established role of PARP in promoting chromatin accessibility impacts viability in these settings. Using a CRISPR-based screen, we identified the PAR-binding chromatin remodeller ALC1/CHD1L as a key determinant of PARPi toxicity in HR-deficient cells. ALC1 loss reduced viability of breast cancer gene (BRCA)-mutant cells and enhanced sensitivity to PARPi by up to 250-fold, while overcoming several resistance mechanisms. ALC1 deficiency reduced chromatin accessibility concomitant with a decrease in the association of base damage repair factors. This resulted in an accumulation of replication-associated DNA damage, increased PARP trapping and a reliance on HR. These findings establish PAR-dependent chromatin remodelling as a mechanistically distinct aspect of PARPi responses and therapeutic target in HR-deficient cancers.
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http://dx.doi.org/10.1038/s41556-020-00624-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880902PMC
February 2021

TooManyCells identifies and visualizes relationships of single-cell clades.

Nat Methods 2020 04 2;17(4):405-413. Epub 2020 Mar 2.

Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Identifying and visualizing transcriptionally similar cells is instrumental for accurate exploration of the cellular diversity revealed by single-cell transcriptomics. However, widely used clustering and visualization algorithms produce a fixed number of cell clusters. A fixed clustering 'resolution' hampers our ability to identify and visualize echelons of cell states. We developed TooManyCells, a suite of graph-based algorithms for efficient and unbiased identification and visualization of cell clades. TooManyCells introduces a visualization model built on a concept intentionally orthogonal to dimensionality-reduction methods. TooManyCells is also equipped with an efficient matrix-free divisive hierarchical spectral clustering different from prevalent single-resolution clustering methods. TooManyCells enables multiresolution and multifaceted exploration of single-cell clades. An advantage of this paradigm is the immediate detection of rare and common populations that outperforms popular clustering and visualization algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resistance acquisition in leukemic T cells.
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http://dx.doi.org/10.1038/s41592-020-0748-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439807PMC
April 2020

Genetic Variation in Type 1 Diabetes Reconfigures the 3D Chromatin Organization of T Cells and Alters Gene Expression.

Immunity 2020 02 11;52(2):257-274.e11. Epub 2020 Feb 11.

Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; The Human Pancreas Analysis Program, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA, https://hpap.pmacs.upenn.edu/. Electronic address:

Genetics is a major determinant of susceptibility to autoimmune disorders. Here, we examined whether genome organization provides resilience or susceptibility to sequence variations, and how this would contribute to the molecular etiology of an autoimmune disease. We generated high-resolution maps of linear and 3D genome organization in thymocytes of NOD mice, a model of type 1 diabetes (T1D), and the diabetes-resistant C57BL/6 mice. Multi-enhancer interactions formed at genomic regions harboring genes with prominent roles in T cell development in both strains. However, diabetes risk-conferring loci coalesced enhancers and promoters in NOD, but not C57BL/6 thymocytes. 3D genome mapping of NODxC57BL/6 F1 thymocytes revealed that genomic misfolding in NOD mice is mediated in cis. Moreover, immune cells infiltrating the pancreas of humans with T1D exhibited increased expression of genes located on misfolded loci in mice. Thus, genetic variation leads to altered 3D chromatin architecture and associated changes in gene expression that may underlie autoimmune pathology.
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http://dx.doi.org/10.1016/j.immuni.2020.01.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152927PMC
February 2020

Oncogenic Notch Promotes Long-Range Regulatory Interactions within Hyperconnected 3D Cliques.

Mol Cell 2019 03 7;73(6):1174-1190.e12. Epub 2019 Feb 7.

Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Chromatin loops enable transcription-factor-bound distal enhancers to interact with their target promoters to regulate transcriptional programs. Although developmental transcription factors such as active forms of Notch can directly stimulate transcription by activating enhancers, the effect of their oncogenic subversion on the 3D organization of cancer genomes is largely undetermined. By mapping chromatin looping genome-wide in Notch-dependent triple-negative breast cancer and B cell lymphoma, we show that beyond the well-characterized role of Notch as an activator of distal enhancers, Notch regulates its direct target genes by instructing enhancer repositioning. Moreover, a large fraction of Notch-instructed regulatory loops form highly interacting enhancer and promoter spatial clusters termed "3D cliques." Loss- and gain-of-function experiments show that Notch preferentially targets hyperconnected 3D cliques that regulate the expression of crucial proto-oncogenes. Our observations suggest that oncogenic hijacking of developmental transcription factors can dysregulate transcription through widespread effects on the spatial organization of cancer genomes.
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http://dx.doi.org/10.1016/j.molcel.2019.01.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6485942PMC
March 2019

Classes of ITD Predict Outcomes in AML Patients Treated with FLT3 Inhibitors.

Clin Cancer Res 2019 01 4;25(2):573-583. Epub 2018 Sep 4.

Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.

Purpose: Recurrent internal tandem duplication (ITD) mutations are observed in various cancers including acute myeloid leukemia (AML), where ITD mutations in tyrosine kinase receptor FLT3 are associated with poor prognostic outcomes. Several FLT3 inhibitors (FLT3i) are in clinical trials for high-risk -ITD-positive AML. However, the variability of survival following FLT3i treatment suggests that the mere presence of -ITD mutations might not guarantee effective clinical response. Motivated by the heterogeneity of -ITD mutations, we investigated the effects of -ITD structural features on the response of AML patients to treatment. We developed the HeatITup (HEAT diffusion for Internal Tandem dUPlication) algorithm to identify and quantitate ITD structural features including nucleotide composition. Using HeatITup, we studied the impact of ITD structural features on the clinical response to FLT3i and induction chemotherapy in -ITD-positive AML patients.

Results: HeatITup accurately identifies and classifies ITDs into newly defined categories of "typical" or "atypical" based on their nucleotide composition. A typical ITD's insert sequence completely matches the wild-type whereas an atypical ITD's insert contains nucleotides exogenous to the wild-type . Our analysis shows marked divergence between typical and atypical ITD mutation features. Furthermore, our data suggest that AML patients carrying typical -ITDs benefited significantly more from both FLT3i and induction chemotherapy treatments than patients with atypical -ITDs.

Conclusions: These results underscore the importance of structural discernment of complex somatic mutations such as ITDs in progressing toward personalized treatment of AML patients, and enable researchers and clinicians to unravel ITD complexity using the provided software..
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http://dx.doi.org/10.1158/1078-0432.CCR-18-0655DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335170PMC
January 2019

Differential Integration of Transcriptome and Proteome Identifies Pan-Cancer Prognostic Biomarkers.

Front Genet 2018 15;9:205. Epub 2018 Jun 15.

Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.

High-throughput analysis of the transcriptome and proteome individually are used to interrogate complex oncogenic processes in cancer. However, an outstanding challenge is how to combine these complementary, yet partially disparate data sources to accurately identify tumor-specific gene products and clinical biomarkers. Here, we introduce inteGREAT for robust and scalable differential integration of high-throughput measurements. With inteGREAT, each data source is represented as a co-expression network, which is analyzed to characterize the local and global structure of each node across networks. inteGREAT scores the degree by which the topology of each gene in both transcriptome and proteome networks are conserved within a tumor type, yet different from other normal or malignant cells. We demonstrated the high performance of inteGREAT based on several analyses: deconvolving synthetic networks, rediscovering known diagnostic biomarkers, establishing relationships between tumor lineages, and elucidating putative prognostic biomarkers which we experimentally validated. Furthermore, we introduce the application of a clumpiness measure to quantitatively describe tumor lineage similarity. Together, inteGREAT not only infers functional and clinical insights from the integration of transcriptomic and proteomic data sources in cancer, but also can be readily applied to other heterogeneous high-throughput data sources. inteGREAT is open source and available to download from https://github.com/faryabib/inteGREAT.
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http://dx.doi.org/10.3389/fgene.2018.00205DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018483PMC
June 2018

A B Cell Regulome Links Notch to Downstream Oncogenic Pathways in Small B Cell Lymphomas.

Cell Rep 2017 Oct;21(3):784-797

Department of Pathology and Laboratory Medicine, Abramson Family Cancer Research Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Gain-of-function Notch mutations are recurrent in mature small B cell lymphomas such as mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL), but the Notch target genes that contribute to B cell oncogenesis are largely unknown. We performed integrative analysis of Notch-regulated transcripts, genomic binding of Notch transcription complexes, and genome conformation data to identify direct Notch target genes in MCL cell lines. This B cell Notch regulome is largely controlled through Notch-bound distal enhancers and includes genes involved in B cell receptor and cytokine signaling and the oncogene MYC, which sustains proliferation of Notch-dependent MCL cell lines via a Notch-regulated lineage-restricted enhancer complex. Expression of direct Notch target genes is associated with Notch activity in an MCL xenograft model and in CLL lymph node biopsies. Our findings provide key insights into the role of Notch in MCL and other B cell malignancies and have important implications for therapeutic targeting of Notch-dependent oncogenic pathways.
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http://dx.doi.org/10.1016/j.celrep.2017.09.066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5687286PMC
October 2017

Functional proteogenomics reveals biomarkers and therapeutic targets in lymphomas.

Proc Natl Acad Sci U S A 2017 06 12;114(25):6581-6586. Epub 2017 Jun 12.

Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104;

Identification of biomarkers and therapeutic targets is a critical goal of precision medicine. N-glycoproteins are a particularly attractive class of proteins that constitute potential cancer biomarkers and therapeutic targets for small molecules, antibodies, and cellular therapies. Using mass spectrometry (MS), we generated a compendium of 1,091 N-glycoproteins (from 40 human primary lymphomas and cell lines). Hierarchical clustering revealed distinct subtype signatures that included several subtype-specific biomarkers. Orthogonal immunological studies in 671 primary lymphoma tissue biopsies and 32 lymphoma-derived cell lines corroborated MS data. In anaplastic lymphoma kinase-positive (ALK) anaplastic large cell lymphoma (ALCL), integration of N-glycoproteomics and transcriptome sequencing revealed an ALK-regulated cytokine/receptor signaling network, including vulnerabilities corroborated by a genome-wide clustered regularly interspaced short palindromic screen. Functional targeting of IL-31 receptor β, an ALCL-enriched and ALK-regulated N-glycoprotein in this network, abrogated ALKALCL growth in vitro and in vivo. Our results highlight the utility of functional proteogenomic approaches for discovery of cancer biomarkers and therapeutic targets.
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http://dx.doi.org/10.1073/pnas.1701263114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5488937PMC
June 2017