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1.
Cancer Cell ; 41(10): 1803-1816.e8, 2023 10 09.
Article in English | MEDLINE | ID: mdl-37738974

ABSTRACT

Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.


Subject(s)
Leukemia, Lymphocytic, Chronic, B-Cell , Lymphoma, Large B-Cell, Diffuse , Humans , Leukemia, Lymphocytic, Chronic, B-Cell/pathology , CD8-Positive T-Lymphocytes , Lymphoma, Large B-Cell, Diffuse/drug therapy , Lymphoma, Large B-Cell, Diffuse/genetics , Lymphoma, Large B-Cell, Diffuse/pathology , Gene Expression Regulation , Immunotherapy
2.
J Clin Invest ; 132(13)2022 07 01.
Article in English | MEDLINE | ID: mdl-35775490

ABSTRACT

Cancers avoid immune surveillance through an array of mechanisms, including perturbation of HLA class I antigen presentation. Merkel cell carcinoma (MCC) is an aggressive, HLA-I-low, neuroendocrine carcinoma of the skin often caused by the Merkel cell polyomavirus (MCPyV). Through the characterization of 11 newly generated MCC patient-derived cell lines, we identified transcriptional suppression of several class I antigen presentation genes. To systematically identify regulators of HLA-I loss in MCC, we performed parallel, genome-scale, gain- and loss-of-function screens in a patient-derived MCPyV-positive cell line and identified MYCL and the non-canonical Polycomb repressive complex 1.1 (PRC1.1) as HLA-I repressors. We observed physical interaction of MYCL with the MCPyV small T viral antigen, supporting a mechanism of virally mediated HLA-I suppression. We further identify the PRC1.1 component USP7 as a pharmacologic target to restore HLA-I expression in MCC.


Subject(s)
Carcinoma, Merkel Cell , Merkel cell polyomavirus , Polyomavirus Infections , Skin Neoplasms , Antigens, Viral, Tumor/genetics , Antigens, Viral, Tumor/metabolism , Carcinoma, Merkel Cell/genetics , Carcinoma, Merkel Cell/pathology , Epigenesis, Genetic , Humans , Merkel cell polyomavirus/genetics , Merkel cell polyomavirus/metabolism , Polyomavirus Infections/genetics , Skin Neoplasms/pathology , Ubiquitin-Specific Peptidase 7/metabolism
4.
Blood Cancer Discov ; 2(1): 54-69, 2021 01.
Article in English | MEDLINE | ID: mdl-33604581

ABSTRACT

Most human cancers converge to a deregulated methylome with reduced global levels and elevated methylation at select CpG islands. To investigate the emergence and dynamics of the cancer methylome, we characterized genome-wide DNA methylation in pre-neoplastic monoclonal B cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL), including serial samples collected across disease course. We detected the aberrant tumor-associated methylation landscape at CLL diagnosis and found no significantly differentially methylated regions in the high-count MBL-to-CLL transition. Patient methylomes showed remarkable stability with natural disease and post-therapy progression. Single CLL cells were consistently aberrantly methylated, indicating a homogeneous transition to the altered epigenetic state, and a distinct expression profile together with MBL cells compared to normal B cells. Our longitudinal analysis reveals the cancer methylome to emerge early, which may provide a platform for subsequent genetically-driven growth dynamics and together with its persistent presence suggests a central role in the normal-to-cancer transition.


Subject(s)
Epigenome , Leukemia, Lymphocytic, Chronic, B-Cell , CpG Islands/genetics , DNA Methylation/genetics , Disease Progression , Humans , Leukemia, Lymphocytic, Chronic, B-Cell/diagnosis
5.
Bioinformatics ; 37(5): 705-710, 2021 05 05.
Article in English | MEDLINE | ID: mdl-33031509

ABSTRACT

SUMMARY: Here, we present an automated pipeline for Download Of NCBI Entries (DONE) and continuous updating of a local sequence database based on user-specified queries. The database can be created with either protein or nucleotide sequences containing all entries or complete genomes only. The pipeline can automatically clean the database by removing entries with matches to a database of user-specified sequence contaminants. The default contamination entries include sequences from the UniVec database of plasmids, marker genes and sequencing adapters from NCBI, an E.coli genome, rRNA sequences, vectors and satellite sequences. Furthermore, duplicates are removed and the database is automatically screened for sequences from green fluorescent protein, luciferase and antibiotic resistance genes that might be present in some GenBank viral entries, and could lead to false positives in virus identification. For utilizing the database, we present a useful opportunity for dealing with possible human contamination. We show the applicability of DONE by downloading a virus database comprising 37 virus families. We observed an average increase of 16 776 new entries downloaded per month for the 37 families. In addition, we demonstrate the utility of a custom database compared to a standard reference database for classifying both simulated and real sequence data. AVAILABILITYAND IMPLEMENTATION: The DONE pipeline for downloading and cleaning is deposited in a publicly available repository (https://bitbucket.org/genomicepidemiology/done/src/master/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Subject(s)
Databases, Genetic , Databases, Nucleic Acid , Genome , Humans , Proteins
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