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DUX4 Suppresses MHC Class I to Promote Cancer Immune Evasion and Resistance to Checkpoint Blockade.

Developmental cell | 2019

Advances in cancer immunotherapies make it critical to identify genes that modulate antigen presentation and tumor-immune interactions. We report that DUX4, an early embryonic transcription factor that is normally silenced in somatic tissues, is re-expressed in diverse solid cancers. Both cis-acting inherited genetic variation and somatically acquired mutations in trans-acting repressors contribute to DUX4 re-expression in cancer. Although many DUX4 target genes encode self-antigens, DUX4-expressing cancers were paradoxically characterized by reduced markers of anti-tumor cytolytic activity and lower major histocompatibility complex (MHC) class I gene expression. We demonstrate that DUX4 expression blocks interferon-γ-mediated induction of MHC class I, implicating suppressed antigen presentation in DUX4-mediated immune evasion. Clinical data in metastatic melanoma confirmed that DUX4 expression was associated with significantly reduced progression-free and overall survival in response to anti-CTLA-4. Our results demonstrate that cancers can escape immune surveillance by reactivating a normal developmental pathway and identify a therapeutically relevant mechanism of cell-intrinsic immune evasion.

Pubmed ID: 31327741 RIS Download

Additional research tools detected in this publication

Associated grants

  • Agency: NINDS NIH HHS, United States
    Id: P01 NS069539
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR045203
  • Agency: NIH HHS, United States
    Id: S10 OD020069
  • Agency: NIGMS NIH HHS, United States
    Id: T32 GM007270

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This is a list of tools and resources that we have found mentioned in this publication.


The Cancer Genome Atlas (tool)

RRID:SCR_003193

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

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HUGO (tool)

RRID:SCR_012800

Human Genome Organisation (HUGO) is the international organization of scientists involved in human genetics. HUGO was conceived in 1988, at the first meeting on genome mapping and sequencing at Cold Spring Harbor. From a 42 scientists of 17 countries membership association, HUGO has increased its membership base to over 1,200 members, both established and aspiring of 69 countries after two decades. HUGO has, over the years, played an essential role behind the scenes of the human genome project. With its mission to promote international collaborative effort to study the human genome and the myriad issues raised by knowledge of the genome, HUGO has had noteworthy successes in some of the less glamorous, but nonetheless vital, aspects of the human genome project. As a truly international organization, HUGO is entering its 20th year of its history by making an inflection in its direction seeking the biological meaning of its information content. To this end, HUGO is focusing on the medical implications of genomic knowledge. Moving forward, HUGO is also working to enhance the genomic capabilities in the emerging countries of the world. The excitement and interest in genomic sciences in Asia, Middle East, South America and Africa are palpable and the hope is that these technologies will help in national development and health.

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ZSCAN4 Polyclonal Antibody (antibody)

RRID:AB_2549579

This unknown targets ZSCAN4

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FITC anti-human HLA-A,B,C (antibody)

RRID:AB_314873

This monoclonal targets HLA-A

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GAPDH antibody [6C5] (antibody)

RRID:AB_370675

This monoclonal targets GAPDH

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MHC class I (F-3) (antibody)

RRID:AB_831547

This monoclonal targets Human HLA-B

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Cancer Genomics Hub (data repository)

RRID:SCR_002657

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

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A-204 (cell line)

RRID:CVCL_1058

Cell line A-204 is a Cancer cell line with a species of origin Homo sapiens (Human)

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Genotype-Tissue Expression (data repository)

RRID:SCR_013042

Project to study human gene expression and regulation in multiple tissues, providing valuable insights into mechanisms of gene regulation and its disease related perturbations. Genetic variation between individuals will be examined for correlation with differences in gene expression level to identify regions of the genome that influence whether and how much a gene is expressed. Includes initiatives: Novel Statistical Methods for Human Gene Expression Quantitative Trait Loci (eQTL) Analysis ,Laboratory, Data Analysis, and Coordinating Center (LDACC), caHUB Acquisition of Normal Tissues in Support of GTEx Project.

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BD FACSDiva Software (software resource)

RRID:SCR_001456

A collection of tools for flow cytometer and application setup, data acquisition, and data analysis that help streamline flow cytometry workflows. It provides features to help users integrate flow systems into new application areas, including index sorting for stem cell and single-cell applications, as well as automation protocols for high-throughput and robotic laboratories.

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FlowJo (software resource)

RRID:SCR_008520

Software for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.

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GraphPad Prism (software resource)

RRID:SCR_002798

Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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ggplot2 (data processing software)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

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Goseq (software resource)

RRID:SCR_017052

Software application for performing Gene Ontology analysis on RNAseq data and other length biased data. Used to reduce complexity and highlight biological processes in genome wide expression studies.

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dplyr (software resource)

RRID:SCR_016708

Software tool for working with data frame like objects, both in memory and out of memory. It is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges: mutate, select, filer, summerise, arrange.

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Bioconductor (software resource)

RRID:SCR_006442

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

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Integrative Genomics Viewer (software resource)

RRID:SCR_011793

A high-performance visualization tool for interactive exploration of large, integrated genomic datasets.

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MACS (software resource)

RRID:SCR_013291

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

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HeLa (cell line)

RRID:CVCL_0030

Cell line HeLa is a Cancer cell line with a species of origin Homo sapiens

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SAMTOOLS (software resource)

RRID:SCR_002105

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

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kallisto (software resource)

RRID:SCR_016582

Software tool for quantifying abundances of transcripts from RNA-Seq data or target sequences using high-throughput sequencing reads.

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TopHat (software resource)

RRID:SCR_013035

Software tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.

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MISO (software resource)

RRID:SCR_003124

Probabilistic framework that quantitates the expression level of alternatively spliced genes from RNA-Seq and identifies differentially regulated isoforms or exons across samples.

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Bowtie (software resource)

RRID:SCR_005476

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

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RSEM (software resource)

RRID:SCR_013027

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

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SuSa (cell line)

RRID:CVCL_L280

Cell line SuSa is a Cancer cell line with a species of origin Homo sapiens

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NCBI database of Genotypes and Phenotypes (dbGap) (data repository)

RRID:SCR_002709

Database developed to archive and distribute clinical data and results from studies that have investigated interaction of genotype and phenotype in humans. Database to archive and distribute results of studies including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits.

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Japanese Genotype-phenotype Archive (JGA) (data repository)

RRID:SCR_003118

A service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The JGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the JGA. Once processed, all data are encrypted. The JGA accepts only de-identified data approved by JST-NBDC. The JGA implements access-granting policy whereby the decisions of who will be granted access to the data resides with the JST-NBDC. After data submission the JGA team will process the data into databases and archive the original data files. The accepted data types include manufacturer-specific raw data formats from the array-based and new sequencing platforms. The processed data such as the genotype and structural variants or any summary level statistical analyses from the original study authors are stored in databases. The JGA also accepts and distributes any phenotype data associated with the samples. For other human biological data, please contact the NBDC human data ethical committee.

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European Genome phenome Archive (software resource)

RRID:SCR_004944

Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.

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Gene Expression Omnibus (GEO) (data repository)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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NCBI Sequence Read Archive (SRA) (data repository)

RRID:SCR_004891

Repository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.

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MCF-7 (cell line)

RRID:CVCL_0031

Cell line MCF-7 is a Cancer cell line with a species of origin Homo sapiens (Human)

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