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

Cancers Originate from Somatic Mutations in a Single Cell

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...

Cancer

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.

Tumor Progression

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

Cancer Stem Cells and Tumor Maintenance

Cancer Stem Cells and Tumor Maintenance

Early diagnosis and treatment can often cure cancer. However, even with treatment, residual cells called cancer stem cells (CSC) might remain, often causing tumor recurrence. These cancer stem cells possess the potential for self-renewal and multi-lineage differentiation and are often responsible for the therapeutic resistance displayed in most cancers.
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...

Cancer-Critical Genes I: Proto-oncogenes

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...

You might also read

Related Articles

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

Sort by

Same author

NSD Family-Mediated H3K36 Methylation in Human Cancer: Mechanisms and Therapeutic Opportunities.

Biomedicines·2025

Same author

O-GlcNAcylation of NONO regulates paraspeckle component assembly and contributes to colon cancer cell proliferation.

Cell death discovery·2025

Same author

Single-cell mapping of regulatory DNA:Protein interactions.

bioRxiv : the preprint server for biology·2025

Same author

Optimal design of synthetic circular RNAs.

Experimental & molecular medicine·2024

Same author

Comparative interactome analysis of α-arrestin families in human and <i>Drosophila</i>.

eLife·2024

Same author

Molecular traces of Drosophila hemocytes reveal transcriptomic conservation with vertebrate myeloid cells.

PLoS genetics·2023

Same journal

Literature-informed gene extraction and ranking for multimodal data fusion.

Briefings in bioinformatics·2026

Same journal

SA-MTP: a structure-aware framework for multifunctional therapeutic peptide annotation.

Briefings in bioinformatics·2026

Same journal

Genome assemblies and annotations are not static and need support for tracking their evolution.

Briefings in bioinformatics·2026

Same journal

A historical journey of metabolite-protein interaction discovery: from data harmonization to AI-driven prediction.

Briefings in bioinformatics·2026

Same journal

Bridging local-global transmembrane protein contexts with contrastive pretraining for alignment-free pathogenicity prediction.

Briefings in bioinformatics·2026

Same journal

Prediction of drug hypersensitivity by comprehensive modeling of HLA-peptidomes.

Briefings in bioinformatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 8, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Published on: July 22, 2020

Clustering malignant cell states using universally variable genes.

Sang-Ho Yoon^1,2,3, Jin-Wu Nam^1,2,4,3

¹Department of Life Science, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea.

Briefings in Bioinformatics

|December 12, 2023

Summary

This summary is machine-generated.

This study introduces universally variable genes (UVGs) to improve single-cell RNA sequencing (scRNA-seq) analysis. UVGs reduce sample-specific biases, revealing true molecular hallmarks of malignant cells.

Keywords:

clustering feature selection scRNA-seq tumor microenvironment

More Related Videos

Micromanipulation of Circulating Tumor Cells for Downstream Molecular Analysis and Metastatic Potential Assessment

Micromanipulation of Circulating Tumor Cells for Downstream Molecular Analysis and Metastatic Potential Assessment

Published on: May 14, 2019

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

Related Experiment Videos

Last Updated: Jul 8, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Published on: July 22, 2020

Micromanipulation of Circulating Tumor Cells for Downstream Molecular Analysis and Metastatic Potential Assessment

Micromanipulation of Circulating Tumor Cells for Downstream Molecular Analysis and Metastatic Potential Assessment

Published on: May 14, 2019

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

Area of Science:

Genomics
Bioinformatics
Cancer Research

Background:

Single-cell RNA sequencing (scRNA-seq) offers insights into malignant cell heterogeneity.
Patient-specific genomic alterations complicate scRNA-seq data interpretation, leading to artifactual clusters.
Existing methods struggle to distinguish true biological variation from sample-specific noise.

Purpose of the Study:

To develop a novel method for analyzing scRNA-seq data that mitigates sample-specific biases.
To identify universally variable genes (UVGs) as a more robust metric for analyzing malignant cell populations.
To improve the detection of underlying molecular hallmarks and distinct malignant cell states.

Main Methods:

Normalization of gene expression variances across samples.
Identification of universally variable genes (UVGs) by comparing gene expression variability.
Application of UVGs to cluster analysis of scRNA-seq data from malignant cells.

Main Results:

The proposed approach successfully reduced the formation of sample-specific clusters.
Universally variable genes (UVGs) demonstrated superior performance compared to standard highly variable genes.
UVGs enabled more accurate detection of distinct malignant cell states and their molecular characteristics.

Conclusions:

Universally variable genes (UVGs) provide a robust method for analyzing scRNA-seq data in the presence of genomic alterations.
This approach enhances the interpretability of malignant cell heterogeneity in cancer research.
The findings suggest new avenues for exploring the complex biology of cancer cells.