Immunity. Volume 48 p1-19, 17 April 2018 10.1016/j.immuni.2018.03.023
We performed an extensive immunogenomic analysis of over 10,000 tumors comprising 33 diverse cancer types utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes: Wound Healing, IFN-γ Dominant, Inflammatory, Lymphocyte Depleted, Immunologically Quiet, and TGF-β Dominant, characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF,TP53, orCASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
Data in the GDC
- GDC Manifests
- Open-Access Data - Download Manifest (33 Files)
- Controlled-Access Data - Download Manifest (8 Files)
Supplemental Data
- Gene Expression Signatures
- Gene sets used in single sample scoring and clustering - PanImmune_GeneSet_Definitions.xlsx
- Scores for 160 Genes Signatures in Tumor Samples - Scores_160_Signatures.tsv.gz
- Cellular Fraction Estimates
- Leukocyte Fraction - TCGA_all_leuk_estimate.masked.20170107.tsv
- CIBERSORT immune fractions - TCGA.Kallisto.fullIDs.cibersort.relative.tsv
- Peptide-MHC Predictions
- HLA class I type calls from tumor RNA-seq using fastq as input - OptiTypeCallsHLA_20171207.tsv
- HLA class I type calls from tumor RNA-seq using bam as input - OptiTypeCallsHLA_bams_20170323.tsv
- Predicted SNV Neoantigen Counts Per Sample - TCGA_pMHC_SNV_sampleSummary_MC3_v0.2.8.CONTROLLED_170404.tsv
- Predicted SNV Peptide binding data from NetMHCpan - TCGA_peptideMHC_binding_MC3_v0.2.8.CONTROLLED_genomicCoord_withExpression_170403.tsv
- Predicted Indel Neoantigen Counts Per Sample - TCGA_PCA.mc3.v0.2.8.CONTROLLED.filtered.sample_neoantigens_10062017.tsv
- Predicted Indel Neoantigens - TCGA_PCA.mc3.v0.2.8.CONTROLLED.filtered.indel_neoantigens_10062017.tsv
- Genes Mapping to Indel pMHCs - TCGA_PCA.mc3.v0.2.8.CONTROLLED.filtered.neoantigen_genes_10062017.tsv
- Adaptive Immune Cell Receptor Sequences
- TCR Summary File - mitcr_sampleStatistics_20160714.tsv
- TCR CDR3 sequences, including flanking V, D, and J gene - TCGA_mitcr_cdr3_result_161008.tsv
- Immunoglobulin Heavy Chain - tcga.pancan.igh.div.txt
- Predicted IgH VDJ and CDR3 sequences - tcga.pancan.igh.with_barcode.txt
- Viral Sequences
- Filter set for Viral Scans with BioBloom Tools - ViralListForBBT.tsv
- Viral Read Counts - viral.tsv
- Molecular Networks
- Subtype-specific cytokine network with scores - panimmune_cytokine_network_all_edges_july202018.tsv
- Master Regulator MR-PanImmune Network in .sif (Cytoscape) format - TieDIE_PancancerImmuneModulators_1.0.sif
- SYGNAL-PanImmune network in .sif (Cytoscape) format - SYGNAL_immune_subtype_network.sif
- SYGNAL-PanImmune Cytoscape Attribute file - SYGNAL_immune_subtype_network_att.txt
- Other Data Files
- sample annotations - merged_sample_quality_annotations.tsv
- RNA (final) - EBPlusPlusAdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.tsv
- RPPA (final) - TCGA-RPPA-pancan-clean.txt
- DNA methylation 450K only - jhu-usc.edu_PANCAN_HumanMethylation450.betaValue_whitelisted.tsv
- DNA methylation (Merged 27K+450K) - jhu-usc.edu_PANCAN_merged_HumanMethylation27_HumanMethylation450.betaValue_whitelisted.tsv
- miRNA - pancanMiRs_EBadjOnProtocolPlatformWithoutRepsWithUnCorrectMiRs_08_04_16.csv
- miRNA sample information - PanCanAtlas_miRNA_sample_information_list.txt
- GISTIC2.0 all_thresholded.by_genes file - all_thresholded.by_genes_whitelisted.tsv
- GISTIC2.0 all_data_by_genes file - all_data_by_genes_whitelisted.tsv
- CNV burden scores - seg_based_scores.tsv
- Aneuploidy and LOH Scores - ABSOLUTE_scores.tsv
- ABSOLUTE purity/ploidy file - TCGA_mastercalls.abs_tables_JSedit.fixed.txt
- Controlled mutation annotation file - mc3.v0.2.8.CONTROLLED.maf.gz
- Public mutation annotation file - mc3.v0.2.8.PUBLIC.maf.gz
- Mutation Load - mutation-load_updated.txt
- Homologous Repair Deficiency - TCGA.HRD_withSampleID.txt
- Annotated TCGA Subtypes by Noushmehr and Malta - TCGASubtype.20170308.tsv
- PanCancer Atlas Color Scheme (Allison Kudla, ISB) - PanCanAtlasTumors_color_coded_by_organ_system_20170302.tsv
- ISAR-corrected GISTIC2.0 all_thresholded.by_genes file - ISAR_GISTIC.all_thresholded.by_genes.txt.gz
- gzipped ISAR-corrected GISTIC2.0 all_data_by_genes file - ISAR_GISTIC.all_data_by_genes.txt.gz
Additional Resources
- CRI-iAtlas (link is external)
- PanCanAtlas Additional Files
- Extended Data (link is external)
- BigQuery Tables (link is external)
Instructions for Data Download
Open Access Data
- Download the appropriate manifest file from the publication page
- Use the manifest file to download data using the GDC Data Transfer Tool (DTT) or the GDC API
- GDC DTT ( Download, User's Guide)
- GDC API ( User’s Guide)
Controlled Access Data
- Download the appropriate manifest file from the publication page
- Download a token from the GDC Data Portal
- GDC Data Portal ( Launch, User’s Guide)
- Use the manifest file and token to download data using the GDC DTT or the GDC API
- GDC DTT ( Download, User’s Guide)
- GDC API ( User’s Guide)
For assistance, please contact the GDC Help Desk: support@nci-gdc.datacommons.io.