This repository contains the code and resources for classifying the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) based on functional gene signatures (FGEs) calculated on bulk RNA-Seq or microarray gene expressions data.
PDAC presents a complex tumor environment, which has historically posed challenges in the development of reliable predictive biomarkers for targeted therapies and immunomodulation. To address this, we've implemented a classification approach based on transcriptomic profiling of the TME.
Four TME subtypes were developed:
- Immune Enriched (IE)
- Immune Enriched, Fibrotic (IE/F)
- Fibrotic (F)
- Immune Depleted (D)
Developed classification is described in details in [DOI link - TODO]
This repository contains:
- Data
- PDAC Meta-Cohort: annotation & calculated FGEs for all samples
- ICGC PACA-CA (test cohort): annotation & expressions
- Genesets
- genesets/PAAD_genesets.gmt - table of all used genesets
- Code
- utils/ - scripts for data preprocessing, ssGSEA score calculation, median scaling and plots
- Notebook MFP_TME_classificataion.ipynb with a classification of ICGC PACA-CA samples into four TME subtypes using supervised clustering
- Python 3.x - Python 3.9 is advised
- Required Python libraries: please see requirements.txt
Clone the repository:
git clone https://github.com/BostonGene/PDAC.TME.George.git
Navigate to the repository directory:
cd PDAC.TME.George
Install required dependencies:
python3.9 -m venv venv
source venv/bin/activate
venv/bin/python3.9 -m pip install --upgrade pip
pip install --no-deps -r requirements.txt
jupyter nbextension enable --py widgetsnbextension
python -m ipykernel install --user --name=pdac_tme_venv
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