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

The Ras Gene02:38

The Ras Gene

6.3K
The Ras-gene-encoded proteins are regulators of signaling pathways controlling cell proliferation, differentiation, or cell survival. The Ras-gene family in humans constitutes three primary members—the HRas, NRas, and KRas. These genes code for four functionally distinct yet closely related proteins—the HRas, NRas, KRas4A, and KRas4B. The involvement of mutant Ras genes in human cancer was first discovered in 1982 and is among the most common causes of human tumorigenesis.
Ras is a...
6.3K
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

832
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
832
MAPK Signaling Cascades01:07

MAPK Signaling Cascades

5.7K
Mitogen-activated protein kinase, or MAPK pathway, activates three sequential kinases to regulate cellular responses such as proliferation, differentiation, survival, and apoptosis. The canonical MAPK pathway starts with a mitogen or growth factor binding to an RTK. The activated RTKs stimulate Ras, which recruits Raf or MAP3 Kinase (MAPKKK), the first kinase of the MAPK signaling cascade. Raf further phosphorylates and activates MEK or MAP2 Kinases (MAPKK), which in turn phosphorylates MAP...
5.7K
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

190
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
190
Small GTPases - Ras and Rho01:24

Small GTPases - Ras and Rho

4.0K
Ras and Rho are small monomeric GTPases that act downstream of receptor tyrosine kinase (RTK) and regulate various cellular processes. These GTPases switch between active and inactive states by binding to guanine nucleotides.
Three regulatory proteins control their activity:
4.0K
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

149
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
149

You might also read

Related Articles

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

Sort by
Same author

Replication of Endotypes in Eosinophilic Esophagitis Using a Curated Gene Panel Compared to Bulk Sequencing and Assessing Stability Over Time.

Clinical and translational gastroenterology·2026
Same author

Shared PRAME epitopes are T-cell targets in NUT carcinoma.

Journal for immunotherapy of cancer·2026
Same author

Pathobiology and clinical significance of malignant pleural effusions.

EMBO molecular medicine·2026
Same author

Multi-targeting RNAi approaches for cancer treatment.

Expert opinion on therapeutic targets·2025
Same author

Associations of the HER2DX Genomic Test with Biological and Pathologic Features in HER2-Positive Breast Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research·2025
Same author

HER2DX in older patients with HER2-positive early breast cancer: extended follow-up from the RESPECT trial of trastuzumab ± chemotherapy.

Nature communications·2025

Related Experiment Video

Updated: Jul 31, 2025

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein
07:08

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein

Published on: January 16, 2020

5.8K

An integrated model for predicting KRAS dependency.

Yihsuan S Tsai1,2, Yogitha S Chareddy1, Brandon A Price1,2

  • 1UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.

Plos Computational Biology
|May 4, 2023
PubMed
Summary

A new K20 model predicts KRAS dependency to improve patient selection for KRAS G12C inhibitors. This tool identifies tumors most likely to respond, enhancing precision oncology outcomes.

More Related Videos

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
13:34

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Published on: April 6, 2016

10.3K
Development and Maintenance of a Preclinical Patient Derived Tumor Xenograft Model for the Investigation of Novel Anti-Cancer Therapies
09:29

Development and Maintenance of a Preclinical Patient Derived Tumor Xenograft Model for the Investigation of Novel Anti-Cancer Therapies

Published on: September 30, 2016

13.8K

Related Experiment Videos

Last Updated: Jul 31, 2025

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein
07:08

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein

Published on: January 16, 2020

5.8K
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
13:34

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Published on: April 6, 2016

10.3K
Development and Maintenance of a Preclinical Patient Derived Tumor Xenograft Model for the Investigation of Novel Anti-Cancer Therapies
09:29

Development and Maintenance of a Preclinical Patient Derived Tumor Xenograft Model for the Investigation of Novel Anti-Cancer Therapies

Published on: September 30, 2016

13.8K

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • KRAS G12C inhibitors offer precision oncology advances, but modest response rates necessitate improved patient selection.
  • Predicting KRAS dependency is crucial for optimizing treatment efficacy.

Purpose of the Study:

  • To develop and validate an integrated model (K20) for predicting KRAS dependency.
  • To enhance patient stratification for KRAS G12C inhibitor therapy.

Main Methods:

  • Integrated molecular profiles from the DEMETER2 dataset using ElasticNet for binary classification.
  • Validated the K20 model with genetic depletion assays and external lung cancer cell line data.
  • Applied the K20 model to Cancer Genome Atlas (TCGA) datasets.

Main Results:

  • The K20 model, comprising 19 genes and KRAS mutation status, achieved an AUC of 0.94 in validation.
  • Accurately predicted KRAS dependency in both KRAS mutant and wild-type cell lines.
  • Identified specific subpopulations in colorectal and pancreatic cancers with predicted higher KRAS dependency.

Conclusions:

  • The K20 model offers robust predictive capabilities for KRAS dependency.
  • This tool can aid in selecting patients with KRAS mutant tumors most likely to benefit from KRAS G12C inhibitors.
  • Enhances precision oncology by improving patient selection for targeted therapies.