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

Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

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

Cancers Originate from Somatic Mutations in a Single Cell

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...
Cancer Stem Cells and Tumor Maintenance02:40

Cancer Stem Cells and Tumor Maintenance

Early diagnosis and treatment can often cure cancer. However, even with treatment, residual cells called cancer stem cells (CSC) might remain, often causing tumor recurrence. These cancer stem cells possess the potential for self-renewal and multi-lineage differentiation and are often responsible for the therapeutic resistance displayed in most cancers.
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

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,...

You might also read

Related Articles

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

Sort by
Same author

Clinical implications of the new definition of obesity among persons with HIV.

AIDS (London, England)·2026
Same author

Proteomic Profile After Intervention With Eplerenone Among Persons With HIV.

Open forum infectious diseases·2026
Same author

Asymptomatic Brown Penile Lesions: Answer.

The American Journal of dermatopathology·2026
Same author

Asymptomatic Brown Penile Lesions: Challenge.

The American Journal of dermatopathology·2026
Same author

Should We Treat SIBO Patients? Impact on Quality of Life and Response to Comprehensive Treatment: A Real-World Clinical Practice Study.

Nutrients·2025
Same author

Do Herbal Supplements and Probiotics Complement Antibiotics and Diet in the Management of SIBO? A Randomized Clinical Trial.

Nutrients·2024

Related Experiment Video

Updated: Jun 28, 2026

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication
09:52

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Published on: September 20, 2016

A fully continuous individual-based model of tumor cell evolution.

Pablo Gómez-Mourelo1, Eva Sánchez, Luis Casasús

  • 1Dpto. Matemática Aplicada. ETSI Industriales (Universidad Politécnica de Madrid), c/ José Gutiérrez Abascal 2, Madrid, Spain. pablo.gomez.mourelo@upm.es

Comptes Rendus Biologies
|October 23, 2008
PubMed
Summary

This study introduces a continuous individual-based model (IBM) for cancer invasion, improving upon discrete models. Simulations reveal spatial fingering patterns in tumor growth, regardless of initial extracellular macromolecule distribution.

More Related Videos

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

Modeling and Imaging 3-Dimensional Collective Cell Invasion
07:08

Modeling and Imaging 3-Dimensional Collective Cell Invasion

Published on: December 7, 2011

Related Experiment Videos

Last Updated: Jun 28, 2026

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication
09:52

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Published on: September 20, 2016

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

Modeling and Imaging 3-Dimensional Collective Cell Invasion
07:08

Modeling and Imaging 3-Dimensional Collective Cell Invasion

Published on: December 7, 2011

Area of Science:

  • Computational Biology
  • Mathematical Oncology
  • Biophysics

Background:

  • Cancer invasion models are crucial for understanding tumor progression.
  • Previous models were often limited by spatial discretization.
  • A continuous approach offers greater flexibility and realism.

Purpose of the Study:

  • To develop and analyze a fully continuous individual-based model (IBM) for cancer tumor invasion.
  • To compare the IBM with a derived partial differential equation (PDE) model.
  • To investigate the impact of initial extracellular macromolecule distribution on tumor morphology.

Main Methods:

  • Development of a continuous individual-based model (IBM) incorporating tumor cells, extracellular macromolecules (MM), matrix degradative enzyme (MDE), and oxygen.
  • Formulation of stochastic differential equations (SDEs) to describe IBM evolution.
  • Scaling the IBM to a system of partial differential equations (PDEs) for large numbers of individuals.
  • Numerical simulation of both IBM and PDE models with homogeneous and heterogeneous initial MM distributions.

Main Results:

  • Spatial fingering patterns were observed in tumor growth simulations for both IBM and PDE models.
  • Simulation outputs were notably similar across both modeling approaches.
  • The model captures complex invasion dynamics influenced by cellular and molecular interactions.

Conclusions:

  • The continuous IBM provides a robust framework for studying cancer invasion dynamics.
  • The emergence of spatial fingering patterns is a key characteristic of tumor invasion in this model.
  • The study highlights the utility of continuous modeling in advancing cancer research.