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

15.0K
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...
15.0K
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

9.9K
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...
9.9K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

7.2K
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,...
7.2K
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

11.5K
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...
11.5K

You might also read

Related Articles

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

Sort by
Same author

Differential T cell clonal dynamics underlie outcomes to frontline chemoimmunotherapy in advanced gastric cancer.

Cell reports. Medicine·2026
Same author

ESR1 mutations and CDK4/6 inhibitor choice shape clonal selection and adaptive cell states during acquired resistance.

Genome medicine·2026
Same author

Publisher Correction: Tumor transcriptional state predicts survival in immune-checkpoint-blockade-treated glioblastoma.

Nature cancer·2026
Same author

Tumor transcriptional state predicts survival in immune-checkpoint-blockade-treated glioblastoma.

Nature cancer·2026
Same author

Myeloma Precursors Erode Durable Immunity: Results of the IMPACT study.

Research square·2026
Same author

A 15-layer multi-omics analysis of gastric cancer ecotypes provides therapeutic insights.

Cell reports. Medicine·2026

Related Experiment Video

Updated: Feb 17, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
07:41

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

2.9K

NetSig: network-based discovery from cancer genomes.

Heiko Horn1,2, Michael S Lawrence2,3, Candace R Chouinard2

  • 1Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Nature Methods
|December 5, 2017
PubMed
Summary
This summary is machine-generated.

A new method, NetSig, integrates molecular networks and tumor genomes to discover novel cancer genes. This approach successfully identifies potential drivers with significant in vivo tumor-forming capabilities, advancing cancer genome research.

More Related Videos

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
06:52

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

Published on: July 22, 2020

7.0K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.6K

Related Experiment Videos

Last Updated: Feb 17, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
07:41

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

2.9K
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
06:52

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

Published on: July 22, 2020

7.0K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.6K

Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Identifying novel cancer genes is crucial for understanding tumorigenesis.
  • Integrating molecular network data with tumor genomics presents challenges in validation and predictive power.

Purpose of the Study:

  • To develop a robust statistical method (NetSig) for integrating protein interaction networks and tumor exome data.
  • To validate the predictive value of NetSig in identifying and experimentally confirming new cancer driver genes.

Main Methods:

  • Developed NetSig, a statistic integrating protein-protein interaction networks with 4,742 tumor exome datasets.
  • Quantitatively assessed the in vivo tumorigenic potential of NetSig-predicted driver candidates in mice.
  • Reanalyzed candidate genes in human lung adenocarcinoma patient data.

Main Results:

  • NetSig accurately classified known cancer driver genes in 60% of tumor types.
  • Identified 62 novel driver gene candidates with significant in vivo tumorigenic potential.
  • Found AKT2 and TFDP2 amplified in oncogene-negative lung adenocarcinomas.

Conclusions:

  • NetSig offers a scalable computational and experimental workflow for expanding cancer gene discovery from genomic data.
  • The validated candidates represent promising targets for further investigation in cancer research.
  • This integrated approach enhances the identification and validation of novel cancer drivers.