About OncoPeptTUME v1.0.0

Cancer immunotherapy is now established as a major therapeutic modality, and 70% of all cancer patients are estimated to receive some form of immunotherapy treatment as a part of their disease control by 2025. Cancer immunotherapy drugs elicit their anti-tumor immune response in a subset of the treated patients by activating CD8 T-cells and provide sustainable and long lasting benefit in a few. Many different tumor cell-intrinsic and extrinsic features, including the tumor microenvironment, driver gene mutations, host genetics, microbiome and environmental factors modulate response to immune checkpoint inhibitors.

Existing methods of analyzing the tumor microenvironment at a deeper level are limited by 1) availability of adequate tumor tissue from needle biopsy material; 2) restricted set of cell surface and phenotypic markers to analyze the cellular composition with limited tissue availability, and 3) loss of tissue integrity during processing for downstream analysis. Genomic methods overcome the limitations of tissue availability and generate a large amount of data that can broaden the scope of analysis required for de-convoluting the tumor microenvironment. We present OncoPeptTUME, a genomic solution to analyze the tumor microenvironment and predict its immunogenic phenotype using proprietary gene expression signatures

Input specifications:

The input file should contain tab seperated GeneID and Expression values (FPKM).
Gene			FPKM
ENSG00000273423		0.0
ENSG00000110514		1.03754629618
ENSG00000268358		0.679739227081
ENSG00000086015		0.291542986919
ENSG00000211769		0.76391860763
ENSG00000211768		0.366369128149
ENSG00000211767		2.24401090991


(Please right-click on the link and click 'Save link as' to download the examples)

Input Output
Single_sample_input.txt Single_sample_output.zip
Multi_sample_input.txt Multi_sample_output.zip

Usage steps:

  • Normalized gene expression file either for a single sample or multiple samples can be used.
  • The gene expression file needs to be filtered for protein coding genes.
  • Upload the file, choose the signatures and click analyze.