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Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy

Cite this dataset

Subramanian, Madhav; Choi, Kyunghee (2024). Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy [Dataset]. Dryad. https://doi.org/10.5061/dryad.v41ns1s11

Abstract

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment. However, only a fraction of the patients respond to ICB therapy. Accurate prediction of patients to likely respond to ICB would maximize the efficacy of ICB therapy. The tumor microenvironment (TME) dictates tumor progression and therapy outcome. Here, we classify the TME by analyzing the transcriptome from 11,069 cancer patients based on angiogenesis and T-cell activity. We find three distinct angio-immune TME subtypes conserved across 30 non-hematological cancers. There is a clear inverse relationship between angiogenesis and anti-tumor immunity in TME. Remarkably, patients displaying TME with low angiogenesis with strong anti-tumor immunity show the most significant responses to ICB therapy in four cancers. Re-evaluation of the renal cell carcinoma clinical trials provides compelling evidence that the baseline angio-immune state is robustly predictive of ICB responses. This study offers a rationale for incorporating baseline angio-immune scores for future ICB treatment strategies.

README: Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy

Data files are derived from processing as derived from manuscript. Code to generate angio-immune clusters is provided.

All data analyzed is from previously published datasets. Enrichment results files contain GSVA enrichment results used to derive angio-immune clusters. Clinical files contain information on response/survival status. R code to generate clusters 

Description of the data and file structure

Data hosted on Dryad:

  • angio-immune-clusters.xlsx - provides the cluster information for all TCGA patients analyzed
    • cluster = Pan cancer angio-immune cluster label 
    • x = TCGA sample names

Data hosted on Zenodo:

  • Bladder-Cancer-Enrichment-Results.txt - provides enrichment results for anti-PDL1 pre-treatment patients with bladder cancer. Enrichment results range from -1 to 1
    • Column names are sample IDs 
    • Row names are individual pathways for which enrichment is calculated
  • Bladder-Cancer-Clinical.txt - provides clinical information for anti-PDL1 pre-treatment patients with bladder cancer
    • Best Confirmed Overall Response: Response label for each sample
    • Binary response: Binary version of Best Confirmed Overall Response
    • FMOne mutation burden per MB: mutational burden per MB
    • Tissue: Tissue of origin of sample
    • os: overall survival time
    • cencos: censoring info for overall survival
    • TCGA subtype: TCGA molecular subtype defined by transcriptomic data
    • Cluster: angio-immune cluster
    • CXCL9 and PD1: expression level of CXCL9 and PD1
    • Ifngsigentrez Mhc1sigentrez and Mhc2sigentrez: Enrichment score (-1 to 1) of published signatures associated with clinical response to immune checkpoint blockade 
  • Gastric-Cancer-Enrichment-Results.txt - provides enrichment results for anti-PD1 pre-treatment patients with gastric cancer. Enrichment results range from -1 to 1
    • Column names are sample IDs 
    • Row names are individual pathways for which enrichment is calculated
  • Gastric-Cancer-Angio-Immune-Clusters-Response.txt - provides treatment response information for anti-PD1 pre-treatment patients with gastric cancer
    • Angio-immune cluster for each sample
    • Binary response for each sample
  • Melanoma-Enrichment-Results.txt - provides enrichment results for anti-PD1 pre-treatment patients with melanoma. Enrichment results range from -1 to 1
    • For each patient sample, enrichment results for each pathway queried
    • Column names are sample IDs 
    • Row names are individual pathways for which enrichment is calculated
  • Melanoma-Angio-Immune-Cluster-and-Clinical.txt - provides clinical information for anti-PD1 pre-treatment patients with melanoma
    • ID: Sample ID
    • pfs
    • pfs.event
    • OS
    • OS.Event
    • Response: best classified response
    • Angio-Immune Cluster: label for angio-immune cluster
    • CXCL9, PDL1 & PD1: TCGA expression of genes
    • IMPRES mhc2sig mhc1sig ifngsig: Calculation of previously published signatures as described in the manuscript
  • Javelin-Renal-Enrichment-and-Cluster-Results.txt - provides clinical information for pre-treatment patients with renal cancer.  Enrichment results range from -1 to 1
    • For each patient sample, enrichment results for each pathway queried, and the angio-immune cluster label
    • Column names are sample IDs 
    • Row names are individual pathways for which enrichment is calculated
  • Genesets_File.txt - provides all genesets used to derive angio-immune clusters
  • pan-cancer-xcell-results.txt - provides xCell enrichment results for all pan-cancer patients. Enrichment values range from -1 to 1
    • Provides the enrichment of deconvoluted cell types for each sample in the TCGA that was analyzed
  • Angio-Immune_Cluster_Identification.R - R code to derive angio-immune clusters
  • Pan-Cancer-Enrichment-Results.txt - Pan cancer enrichment results for all TCGA patients. 

    • Column names are sample IDs 
    • Row names are individual pathways for which enrichment is calculated

    Structure of files

  • Enrichment results data files contain the GSVA enrichment of 91 gene sets as defined in the anchoring manuscript for each sample.

  • Clinical data files minimally contain response, survival information for samples included in analysis

Sharing/Access information

Data was derived from the following sources:

Code/Software

R script to identify angio-immune clusters is included in this dataset. Code uses GSVA package in R to calculate enrichment of genesets presented in Genesets_File.txt.

Methods

Data files are derived from processing as derived from manuscript. Code to generate angio-immune clusters is provided.

Funding

National Heart Lung and Blood Institute, Award: HL55337

National Heart Lung and Blood Institute, Award: HL149954