Related Experiment Video
Updated: Dec 27, 2025
Tractable In Vivo Reprogramming of Tumor Cells to Type 1 Conventional Dendritic Cell-like Cells
Published on: August 1, 2025
In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy
Gregor Sturm1, Francesca Finotello1, Markus List2
1Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria.
Insights
This study reviews computational methods for analyzing tumor cell composition from RNA sequencing data. It provides guidance for selecting the best cell-type deconvolution tools for immuno-oncology research.
Area of Science:
- Computational biology
- Immunology
- Genomics
Background:
- Tumor microenvironment analysis is key to understanding immune system status.
- Cellular composition of tumors impacts immuno-oncology treatment efficacy.
- Bulk RNA sequencing provides a source for inferring cellular makeup.
Purpose of the Study:
- To review common cell-type deconvolution methods for immuno-oncology.
- To elucidate the working principles, capabilities, and limitations of these methods.
- To offer guidelines for selecting appropriate deconvolution tools.
Main Methods:
- Review of computational methods for cell-type deconvolution.
- Analysis of RNA sequencing data from tumor biopsy samples.
- Comparative assessment of existing deconvolution algorithms.
Main Results:
- Identification of key computational methods for cell-type deconvolution.
- Evaluation of the strengths and weaknesses of each method in the immuno-oncology context.
- Development of a framework for method selection based on study needs.
Conclusions:
- Accurate cell-type deconvolution is essential for immuno-oncology research.
- Method selection should consider specific research questions and data characteristics.
- Understanding the tumor microenvironment through deconvolution aids in predicting treatment response.
Abstract:
Several computational methods have been proposed to infer the cellular composition from bulk RNA-seq data of a tumor biopsy sample. Elucidating interactions in the tumor microenvironment can yield unique insights into the status of the immune system. In immuno-oncology, this information can be crucial for deciding whether the immune system of a patient can be stimulated to target the tumor. Here, we shed a light on the working principles, capabilities, and limitations of the most commonly used methods for cell-type deconvolution in immuno-oncology and offer guidelines for method selection.
