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

Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

9.3K
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...
9.3K
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

11.1K
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...
11.1K
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

7.1K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
7.1K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

6.9K
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,...
6.9K
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

14.5K
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...
14.5K
Cancer Prevention02:59

Cancer Prevention

7.6K
Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
7.6K

You might also read

Related Articles

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

Sort by
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

Globo-H diagnostic stratification and identification of DUSP14 as a candidate target in colorectal cancer.

International journal of cancer·2026
Same author

Manipulating PARK7/DJ-1 Levels by Genotoxic Stress Alters Noncoding RNAs and Cellular Homeostasis.

Cells·2025
Same author

Protein Language Models Expose Viral Immune Mimicry.

Viruses·2025
Same author

Nuclear Roles of Spliceosome-Associated microRNAs in Neuronal Cancer Cells.

International journal of molecular sciences·2025
Same author

Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease.

GeroScience·2025

Related Experiment Video

Updated: Jan 7, 2026

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair
08:15

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

12.6K

Integrative Gene-Centric Analysis Reveals Cellular Pathways Associated with Heritable Breast Cancer Predisposition.

Roei Zucker1, Shirel Schreiber2, Amos Stern1

  • 1The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.

Cancers
|December 30, 2025
PubMed
Summary
This summary is machine-generated.

This study identifies 38 high-confidence breast cancer (BC) predisposition genes using an integrative genomic approach. The findings prioritize key genes and pathways for future research into heritable BC risk.

Keywords:
FinnGenGWASMVPPWASPhecodeUK Biobankbioinformaticspopulation structurerare variants

More Related Videos

Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1
08:53

Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1

Published on: February 17, 2011

15.0K
Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
09:08

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

7.1K

Related Experiment Videos

Last Updated: Jan 7, 2026

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair
08:15

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

12.6K
Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1
08:53

Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1

Published on: February 17, 2011

15.0K
Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
09:08

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

7.1K

Area of Science:

  • Genomics
  • Cancer Genetics
  • Bioinformatics

Background:

  • Heritable breast cancer (BC) predisposition is influenced by high-penetrance genes (e.g., BRCA1, BRCA2), but many moderate- and low-penetrance genes are poorly understood.
  • Over 100 reported loci for BC risk often contain false positives or uncertain associations, necessitating refined identification methods.

Purpose of the Study:

  • To apply a gene-centric, integrative genomic approach to identify high-confidence breast cancer predisposition genes.
  • To leverage multi-ethnic genomic datasets and complementary association methods for robust gene discovery.
  • To prioritize candidate genes and associated cellular pathways for further functional investigation.

Main Methods:

  • Utilized a gene-centric, integrative framework on multi-ethnic genomic datasets (UK Biobank, FinnGen).
  • Assessed gene consistency across multiple Genome-Wide Association Studies (GWAS) and complementary methods (ExPheWAS, TWAS, PWAS).
  • Collapsed variant-level effects to a gene-level view to enhance confidence and identify novel associations, including potential recessive effects.

Main Results:

  • Identified 38 high-confidence breast cancer predisposition genes, including 8 previously reported drivers and 13 supported by multiple lines of evidence.
  • Discovered novel candidate genes such as APOBEC3A, TNS1, and PEX14 with emerging evidence for BC predisposition.
  • PWAS revealed genes with potential recessive effects, and findings were robust in European ancestry populations but showed limited transferability to other ancestries.

Conclusions:

  • The gene-centric, integrative framework effectively prioritizes high-confidence breast cancer predisposition genes.
  • This approach highlights key cellular pathways involved in BC risk and identifies new candidates for functional studies.
  • Provides a reliable foundation for advancing research into the genetic architecture of heritable breast cancer.