Resources

Updates

Follow @iatlas_cri on Twitter for latest developments!

Source code and data resources

iAtlas app, tools, and data and annotations

• GitHub: https://github.com/CRI-iAtlas
• GitLab: https://gitlab.com/cri-iatlas
• Synapse: https://www.synapse.org/#!Synapse:syn10337516/wiki/458420
• Immune Subtype Classifier: https://github.com/CRI-iAtlas/ImmuneSubtypeClassifier

Single-cell RNA-seq data sources

These data sets were generated as part of the NCI Human Tumor Atlas Network, shared via https://humantumoratlas.org/:

• • • Chan et al. Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer. Cancer Cell. 2021 Nov 8;39(11):1479-1496.e18.
    • Chen et al. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps. Cell. 2021 Dec 22;184(26):6262-6280.e26

Immunotherapy data sources

• • • CRI Landscape of Immuno-Oncology Drug Development: https://www.cancerresearch.org/scientists/immuno-oncology-landscape
    • Source for data in the Molecular Response to Immune Checkpoint Inhibitor modules:
      • Choueiri et al. Immunomodulatory Activity of Nivolumab in Metastatic Renal Cell Carcinoma. Clin Cancer Res. 2016;22(22):5461-5471
      • Cloughesy et al. Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma. Nat Med. 2019 Mar;25(3):477-486
      • Gide et al. Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy. Cancer Cell. 2019 Feb 11;35(2):238-255.e6
      • Hugo et al. Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma. Cell. 2016 Mar 24;165(1):35-44
      • Kim et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med. 2018 Sep;24(9):1449-1458. doi: 10.1038/s41591-018-0101-z. Epub 2018 Jul 16. PMID: 30013197
      • Liu et al. Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma [published correction appears in Nat Med. 2020 Jul;26(7):1147]. Nat Med. 2019;25(12):1916-1927
      • Mariathasan et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 2018 Feb 22;554(7693):544-548
      • McDermott et al. Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma. Nat Med. 2018 Dec;24(12):1941. Nat Med. 2018;24(6):749-757
      • Miao et al. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science. 2018;359(6377):801-806
      • Riaz et al. Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab. Cell. 2017 Nov 2;171(4):934-949.e16
      • Van Allen et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015 Oct 9;350(6257):207-211
      • Zhao et al. Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma [published correction appears in Nat Med. 2019 Apr 17;:]. Nat Med. 2019;25(3):462-469

TCGA originating sources

• • • TCGA PanCancer Atlas: https://gdc.cancer.gov/about-data/publications/pancanatlas
    • Immune Landscape of Cancer Manuscript Page: https://gdc.cancer.gov/about-data/publications/panimmune
    • The Cancer Genome Atlas: http://cancergenome.nih.gov/
    • NCI Genomic Data Commons: https://portal.gdc.cancer.gov/

Workflows

Workflows for characterization of immune environment in cancer

• • • CWL workflows: https://github.com/CRI-iAtlas/iatlas-workflows
    • Docker tools: https://quay.io/organization/cri-iatlas

Manuscripts

• • • Eddy et al. CRI iAtlas: an interactive portal for immuno-oncology research. F1000Research 2020, 9:1028
    • Gibbs DL, Robust classification of Immune Subtypes in Cancer, bioRxiv 2020.01.17.910950
    • Saltz et al. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images. Cell Rep. 2018 Apr 3;23(1):181-193.e7
    • Sayaman et al. Germline genetic contribution to the immune landscape of cancer. Immunity. 2021 Feb 9;54(2):367-386.e8
    • Thorsson et al. The Immune Landscape of Cancer. Immunity. 2018 Apr 17;48(4):812-830.e14
    • Upadhaya et al. Immuno-oncology drug development forges on despite COVID-19. Nat Rev Drug Discov. 2020 Nov;19(11):751-752
    • Vensko et al. LENS: Landscape of Effective Neoantigens Software, Bioinformatics. 2023 May 4;39(6)

Organizations contributing to iAtlas

• • • Sage Bionetworks: https://www.sagebionetworks.org
    • Institute for Systems Biology: https://isbscience.org/
    • UNC Lineberger – Vincent Lab: https://unclineberger.org/vincentlab/
    • Cancer Research Institute: https://cancerresearch.org/