Bioinformatics Approaches to Profile the Tumor Microenvironment for Immunotherapeutic Discovery.

Curr Pharm Des

Department of Clinical Molecular Biology (EpiGen), Division of Medicine, Akershus University Hospital, Lørenskog, and University of Oslo, Oslo. Norway.

Published: March 2019

AI Article Synopsis

  • Tumor cells exist in a complex microenvironment alongside normal cells and various immune cells, creating intricate cellular interactions that influence cancer development and treatment responses.
  • Profiling the diverse cell types in tumors is challenging but critical for discovering new therapies and biomarkers.
  • Emerging bioinformatics methods can help analyze tumor samples by extracting specific information about different cell types and their interactions, which is essential for improving immunotherapy outcomes.

Article Abstract

In the microenvironment of a malignancy, tumor cells do not exist in isolation, but rather in a diverse ecosystem consisting not only of heterogeneous tumor-cell clones, but also normal cell types such as fibroblasts, vasculature, and an extensive pool of immune cells at numerous possible stages of activation and differentiation. This results in a complex interplay of diverse cellular signaling systems, where the immune cell component is now established to influence cancer progression and therapeutic response. It is experimentally difficult and laborious to comprehensively and systematically profile these distinct cell types from heterogeneous tumor samples in order to capitalize on potential therapeutic and biomarker discoveries. One emerging solution to address this challenge is to computationally extract cell-type specific information directly from bulk tumors. Such in silico approaches are advantageous because they can capture both the cell-type specific profiles and the tissue systems level of cell-cell interactions. Accurately and comprehensively predicting these patterns in tumors is an important challenge to overcome, not least given the success of immunotherapeutic drug treatment of several human cancers. This is especially challenging for subsets of closely related immune cell phenotypes with relatively small gene expression differences, which have critical functional distinctions. Here, we outline the existing and emerging novel bioinformatics strategies that can be used to profile the tumor immune landscape.

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Source
http://dx.doi.org/10.2174/1381612823666170710154936DOI Listing

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