Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

The Tumor Microenvironment

The Tumor Microenvironment

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Multi-modal data integration reveals functionally credible predictive biomarkers in ovarian cancer.

Genome medicine·2026

Same author

Autoinfarction of the Parathyroid Gland: An Unusual Presentation of Primary Hyperparathyroidism.

Case reports in endocrinology·2026

Same author

Phase I study of oral azacitidine plus salvage chemotherapy in relapsed/refractory diffuse large B-cell lymphoma.

Annals of hematology·2026

Same author

Identification of monotonically classifying pairs of genes for ordinal disease outcomes.

Bioinformatics advances·2026

Same author

Immunotherapy Response and Survival Outcome by Immunophenotypic Signature in Non-Small Cell Lung Cancer.

JCO precision oncology·2026

Same author

Evaluating once-weekly insulin efsitora alfa for adults with type 2 diabetes.

Expert opinion on pharmacotherapy·2026

Search research articles

Related Experiment Video

Updated: Sep 2, 2025

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial

Aleksandr Zaitsev¹, Maksim Chelushkin¹, Daniiar Dyikanov¹

¹BostonGene, Corp., 95 Sawyer Road, Waltham, MA 02453, USA.

|August 9, 2022

Summary

This summary is machine-generated.

Kassandra, a novel machine learning algorithm, reconstructs the tumor microenvironment (TME) from gene expression data. This tool accurately identifies immune cells, predicting immunotherapy response and aiding clinical applications.

Keywords:

bulk RNA sequencing deconvolution tumor microenvironment

More Related Videos

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Published on: August 16, 2024

Related Experiment Videos

Last Updated: Sep 2, 2025

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Published on: August 16, 2024

Area of Science:

Computational biology
Bioinformatics
Machine learning

Background:

Cellular deconvolution algorithms analyze gene expression to infer tissue composition.
Accurate reconstruction of the tumor microenvironment (TME) is crucial for understanding cancer biology and treatment response.

Purpose of the Study:

To introduce Kassandra, a decision tree machine learning algorithm for accurate TME reconstruction.
To validate Kassandra's performance and assess its potential in clinical applications.

Main Methods:

Kassandra was trained on >9,400 sorted cell RNA profiles, creating millions of artificial transcriptomes.
Bioinformatics corrections addressed technical/biological variability and included aberrant cancer cell expression.
Performance was validated against cytometric, immunohistochemical, and single-cell RNA-seq data using 4,000 H&E slides and 1,000 tissues.

Main Results:

Kassandra accurately deconvolved TME elements, revealing their roles in tumor pathogenesis.
The presence of PD-1-positive CD8+ T cells, identified by Kassandra, strongly correlated with immunotherapy response.
Kassandra enhanced the predictive power of existing biomarkers for immunotherapy.

Conclusions:

Kassandra provides a robust and accurate method for digital TME reconstruction.
The algorithm's ability to predict immunotherapy response suggests potential for future clinical utility.
Kassandra facilitates the study of immune cell populations within the TME and their biological significance.