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Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

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Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
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The Tumor Microenvironment02:17

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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Related Experiment Video

Updated: Jan 18, 2026

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors
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TMEtyper: A computational method for tumor microenvironment subtyping with applications in immunotherapy.

Yaru Miao1, Tong Zhou2, Yan Li2

  • 1Institute of Medical Technology, Shanxi Medical University, Taiyuan, China.

Computational and Structural Biotechnology Journal
|January 16, 2026
PubMed
Summary

TMEtyper, a new computational framework, characterizes tumor microenvironment (TME) heterogeneity to predict immune checkpoint blockade (ICB) therapy response. It identifies seven TME subtypes, aiding personalized immunotherapy strategies.

Keywords:
ImmunotherapyNeural networkRegulatory networksStructural causal modelTMEtyperTumor microenvironment

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Area of Science:

  • Computational biology
  • Cancer immunology
  • Bioinformatics

Background:

  • Tumor microenvironment (TME) heterogeneity impacts immune checkpoint blockade (ICB) therapy outcomes.
  • Current methods lack systematic frameworks for TME characterization and identifying treatment response regulators.

Purpose of the Study:

  • To develop TMEtyper, a computational framework for comprehensive TME characterization.
  • To identify TME subtypes and their causal regulators for predicting ICB therapy response.

Main Methods:

  • Constructed a pan-cancer TME signature integrating cellular composition, pathway activity, and intercellular communication.
  • Utilized consensus clustering and topological feature extraction to define TME subtypes.
  • Employed machine learning and structural causal modeling to identify key genes and regulatory mechanisms.

Main Results:

  • Defined seven distinct TME subtypes with prognostic implications using 231 TME signatures.
  • Validated TMEtyper's predictive power across 11 immunotherapy cohorts.
  • Identified a Lymphocyte-Rich Hot subtype associated with superior clinical outcomes.

Conclusions:

  • TMEtyper offers an integrative framework for advanced TME characterization beyond conventional methods.
  • Provides biological insights and clinical utility for personalized immunotherapy.
  • Facilitates TME analysis and biomarker discovery through an open-source R package and web interface.