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

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.9K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
4.9K

You might also read

Related Articles

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

Sort by
Same author

Immunotherapy in Localized Colorectal Cancer: Current Practice and Future Directions.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting·2026
Same author

Ensuring the Future of Cooperative Group Cancer Clinical Trials: A Call for Comprehensive Support and Prioritization.

JCO oncology practice·2026
Same author

NCI9673 (Part B): ETCTN Randomized Phase II Study of Nivolumab With or Without Ipilimumab in Refractory, Metastatic Squamous Cell Carcinoma of the Anal Canal.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2026
Same author

Clinical, manometric, genetic, and histologic associations in pediatric intestinal pseudo-obstruction: A case series.

Journal of pediatric gastroenterology and nutrition·2026
Same author

Preoperative 24-hour movement behaviors and early weight loss after metabolic bariatric surgery: a compositional analysis.

International journal of obesity (2005)·2025
Same author

Phase II Clinical Trial and Preclinical Evaluation of a Novel CD47 Blockade Combination in Refractory Microsatellite-Stable Metastatic Colorectal Cancer.

Cancer research communications·2025
Same journal

Development and Validation of Salivary Exosomal Tri-RNA Liquid Biopsy in Esophageal Carcinoma: A Multicenter Study.

JCO precision oncology·2026
Same journal

Implementing Timely Germline Genetic Testing for Patients With Pancreatic Cancer Using a Genetics Copilot for Point-of-Care Education and Health Assessment.

JCO precision oncology·2026
Same journal

Integrating DNA Mutations and RNA Expression of Cancer Driver Genes in Asian Rare Cancers: A Pan-Cancer Analysis.

JCO precision oncology·2026
Same journal

Sustained Response to Trametinib in Central Giant Cell Granuloma With <i>KRAS</i> Gain-of-Function Mutation: A Case Report.

JCO precision oncology·2026
Same journal

DNA Damage Response Alterations and Immune Checkpoint Blockade Outcomes Across Multiple Cancers.

JCO precision oncology·2026
Same journal

Prediction of Anthracycline Benefit in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Early-Stage Breast Cancer by the MammaPrint 70-Gene Signature for Patients Enrolled in the FLEX Study.

JCO precision oncology·2026
See all related articles

Related Experiment Video

Updated: Jun 9, 2025

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines
10:16

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines

Published on: October 8, 2015

13.2K

Using Artificial Intelligence to Support Informed Decision-Making on BRAF Mutation Testing.

Jennifer Webster1, Jennifer Ghith1, Orion Penner2

  • 1Pfizer Inc, New York, NY.

JCO Precision Oncology
|October 30, 2024
PubMed
Summary
This summary is machine-generated.

An AI platform was developed to analyze BRAFV600 mutation rates in cancers. While AI showed strong filtering, manual review revealed inconsistencies in reporting, highlighting the need for standardized data for precision oncology.

More Related Videos

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.3K
Author Spotlight: Integrating BRET-Based Assays and Rare Mutation Analysis to Decipher RAF Kinase Regulation in Live Cells
06:44

Author Spotlight: Integrating BRET-Based Assays and Rare Mutation Analysis to Decipher RAF Kinase Regulation in Live Cells

Published on: March 1, 2024

967

Related Experiment Videos

Last Updated: Jun 9, 2025

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines
10:16

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines

Published on: October 8, 2015

13.2K
Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.3K
Author Spotlight: Integrating BRET-Based Assays and Rare Mutation Analysis to Decipher RAF Kinase Regulation in Live Cells
06:44

Author Spotlight: Integrating BRET-Based Assays and Rare Mutation Analysis to Decipher RAF Kinase Regulation in Live Cells

Published on: March 1, 2024

967

Area of Science:

  • Biomedical Informatics
  • Oncology
  • Computational Biology

Background:

  • Precision oncology requires accurate reporting of biomarker testing and mutation rates.
  • BRAFV600 mutations are critical in colorectal carcinoma, non-small-cell lung carcinoma, and melanoma.

Purpose of the Study:

  • To develop an AI and NLP pipeline for annotating BRAFV600 testing and mutation rates from literature.
  • To create an interactive platform for exploring these rates across different cancer types.

Main Methods:

  • Utilized AI for identifying and filtering relevant publications reporting testing or mutation rates.
  • Employed manual curation by experts for data validation.
  • Evaluated AI performance using precision and recall metrics.

Main Results:

  • Developed an interactive dashboard to visualize annotated BRAFV600 mutation and testing rates.
  • AI achieved >90% precision and recall for publication filtering.
  • Manual annotation revealed significant inter-rater disagreement (19% for testing, 70% for mutation rates), indicating reporting inconsistencies.

Conclusions:

  • AI-driven NLP shows promise for annotating biomarker rates.
  • Inconsistent reporting necessitates improved AI-powered literature searching and standardized data presentation.
  • Standardization will enhance clinical decision-making and research in precision oncology.