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Related Concept Videos

Cancer02:18

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
The Retinoblastoma Gene01:20

The Retinoblastoma Gene

Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
The first-ever tumor suppressor gene called Rb was identified in retinoblastoma - a rare eye tumor in children. In inherited forms of the disease, a child inherits one defective copy of the Rb gene, which predisposes them to retinoblastoma. However,...
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

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Updated: Jun 3, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
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A guide to transcriptomic deconvolution in cancer.

Yaoyi Dai1,2, Shuai Guo1, Yidan Pan3

  • 1Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Nature Reviews. Cancer
|December 2, 2025
PubMed
Summary
This summary is machine-generated.

This guide helps cancer researchers understand tumor heterogeneity using computational deconvolution. It details 43 methods to analyze cell mixtures and cell-type-specific expression for cancer biology advancements.

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Cancer tissues are complex mixtures of diverse cell types, including tumor, stromal, and immune cells.
  • Tumor heterogeneity significantly impacts cancer progression and treatment response.
  • High-throughput expression data from tumors represent combined signals, masking individual cell-type contributions.

Purpose of the Study:

  • To provide a comprehensive guide to transcriptomic deconvolution for cancer researchers.
  • To offer a systematic framework for selecting and applying deconvolution methods tailored to tumor complexities.
  • To detail 43 deconvolution methods and their applications in cancer research.

Main Methods:

  • Review and categorization of 43 computational deconvolution methods.
  • Framework for method selection based on tumor tissue characteristics, data availability, and method assumptions.
  • Analysis of deconvolution applications in cancer research, including tumor-immune interactions, subtype identification, biomarker discovery, and spatial architecture.

Main Results:

  • Transcriptomic deconvolution is a powerful computational approach to dissect cellular composition and cell-type-specific expression from mixed tumor signals.
  • Different deconvolution methods serve distinct applications, aiding in understanding tumor-immune surveillance, identifying cancer subtypes, discovering prognostic biomarkers, and characterizing spatial tumor architecture.
  • Examination of method capabilities and limitations highlights emerging trends, particularly for addressing tumor cell plasticity and dynamic cell states.

Conclusions:

  • Computational deconvolution is essential for mapping cancer cell heterogeneity and understanding cell-type-specific contributions to the tumor transcriptome.
  • This guide empowers cancer researchers to effectively utilize deconvolution tools for advancing cancer biology and precision medicine.
  • Future directions emphasize deconvolution's role in characterizing dynamic cellular states and plasticity within the tumor microenvironment.