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...

You might also read

Related Articles

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

Sort by

Same author

Mast cell-derived IL-13 as a driver of Crohn disease-associated intestinal fibrosis.

Inflammatory bowel diseases·2026

Same author

Nur77 agonism invigorates Natural Killer cell immunity against hepatocellular carcinoma.

Nature communications·2026

Same author

Resolving the Haplotype Complexity of Colorectal Cancer Genomes with Droplet Barcode Sequencing.

Life (Basel, Switzerland)·2026

Same author

NBSR: a Negative Binomial Softmax Regression model for microRNA-seq data analysis.

Biostatistics (Oxford, England)·2026

Same author

PARiS: Probabilistic Assignment and Repartitioning of isomiR Sequences: A data-driven method for denoising isomiR read count data.

bioRxiv : the preprint server for biology·2026

Same author

Neoadjuvant palbociclib and endocrine therapy versus chemotherapy in ER + /HER2- breast cancer: a randomized phase II trial.

Nature communications·2026

Search research articles

Related Experiment Video

Updated: Aug 9, 2025

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics.

Seong-Hwan Jun^1,2, Hosein Toosi¹, Jeff Mold³

¹SciLifeLab, School of EECS, KTH Royal Institute of Technology, Stockholm, Sweden.

Nature Communications

|February 22, 2023

Summary

PhylEx reconstructs cancer clonal trees using bulk genomics and single-cell RNA sequencing data. This method accurately identifies cancer clones and their evolutionary paths, improving our understanding of cancer progression.

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

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

Related Experiment Videos

Last Updated: Aug 9, 2025

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

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

Area of Science:

Oncology
Genomics
Bioinformatics

Background:

Understanding cancer clone evolution is crucial for identifying proliferation and relapse mechanisms.
Single-cell RNA sequencing (scRNA-seq) offers insights into cancer's functional state but reconstructing clonal relationships remains challenging.
Accurate characterization of individual cancer clone functions requires robust clonal tree reconstruction.

Purpose of the Study:

To present PhylEx, a novel computational method for high-fidelity clonal tree reconstruction.
To integrate bulk genomics data with mutation co-occurrences from scRNA-seq data.
To enable accurate inference of clonal trees and facilitate robust phylo-phenotypic analysis of cancer.

Main Methods:

PhylEx integrates bulk genomics data with mutation co-occurrence information derived from scRNA-seq.
The method was evaluated on synthetic datasets and well-characterized high-grade serous ovarian cancer cell lines.
Performance was compared against state-of-the-art clonal tree reconstruction methods.

Main Results:

PhylEx demonstrated superior performance in clonal tree reconstruction compared to existing methods.
The method showed enhanced accuracy in identifying distinct cancer clones.
Analysis of high-grade serous ovarian cancer and breast cancer data revealed PhylEx's ability to leverage clonal expression profiles effectively.

Conclusions:

PhylEx provides a robust framework for reconstructing high-fidelity cancer clonal trees.
The method surpasses current state-of-the-art approaches in accuracy and clonal identification.
PhylEx enables advanced phylo-phenotypic analysis, advancing cancer research and therapeutic strategies.