A generalizable data-driven multicellular model of pancreatic ductal adenocarcinoma.

ABSTRACT:

Background

Mechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer.

Results

By combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic t

SUBMITTER: Aguilar B 

PROVIDER: S-EPMC7374045 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature