Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

14.2K
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...
14.2K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

6.7K
Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
6.7K

You might also read

Related Articles

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

Sort by
Same author

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026
Same author

<i>SPP1</i><sup>hi</sup> macrophages in fibrin niches promote hyperplastic tissue remodeling in rheumatoid arthritis synovium.

Science translational medicine·2026
Same author

Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart.

bioRxiv : the preprint server for biology·2026
Same author

scLASER: a robust framework for simulating and detecting time-dependent single-cell dynamics in longitudinal studies.

bioRxiv : the preprint server for biology·2026
Same author

Evidence of off-target probe binding affecting 10x Genomics Xenium gene panels compromise accuracy of spatial transcriptomic profiling.

eLife·2026
Same author

Longitudinal peripheral blood multi-omic profiling in seropositive individuals identifies immune endotypes and predictive models for future rheumatoid arthritis conversion.

medRxiv : the preprint server for health sciences·2026

Related Experiment Video

Updated: Dec 9, 2025

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors
05:58

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Published on: August 16, 2024

3.6K

Single-cell transcriptomics in cancer: computational challenges and opportunities.

Jean Fan1, Kamil Slowikowski2, Fan Zhang3,4

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. jeanfan@fas.harvard.edu.

Experimental & Molecular Medicine
|September 15, 2020
PubMed
Summary

Single-cell transcriptomics reveals cancer

More Related Videos

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

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

Published on: April 18, 2025

730
Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies
09:01

Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies

Published on: July 3, 2025

683

Related Experiment Videos

Last Updated: Dec 9, 2025

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors
05:58

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Published on: August 16, 2024

3.6K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

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

Published on: April 18, 2025

730
Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies
09:01

Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies

Published on: July 3, 2025

683

Area of Science:

  • Computational biology
  • Genomics
  • Cancer research

Background:

  • Intratumor heterogeneity poses challenges to cancer treatment.
  • High-throughput sequencing and imaging advance heterogeneity characterization.
  • Single-cell transcriptomics quantifies molecular activity underlying tumor cell diversity.

Purpose of the Study:

  • Review emerging computational analysis themes for single-cell transcriptomics in cancer research.
  • Highlight downstream analytical challenges and opportunities.
  • Discuss translational potential for cancer patient care.

Main Methods:

  • Focus on computational analysis of single-cell transcriptomic data.
  • Discuss methods for unified analysis across patient cohorts and disease states.
  • Examine trajectory and RNA velocity analysis for tumor evolution.

Main Results:

  • Single-cell transcriptomics provides quantitative molecular insights into tumor heterogeneity.
  • Computational methods are crucial for extracting biological insights from high-dimensional data.
  • Key challenges include distinguishing cell types and inferring microenvironment interactions.

Conclusions:

  • Computational analysis of single-cell transcriptomics is vital for understanding cancer.
  • Addressing analytical challenges will enhance the clinical application of these technologies.
  • Future methodological advancements are needed to realize the full translational potential.