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

7.9K
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...
7.9K

You might also read

Related Articles

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

Sort by
Same author

Bi-allelic missense variants in human GPN2 result in Perrault syndrome.

American journal of human genetics·2026
Same author

Trials for Rare Cancers Are More Successful than those for Common Cancers.

ESMO rare cancers·2026
Same author

TMPRSS2-ERG confers resistance of prostate cancer to antiandrogens.

EMBO molecular medicine·2026
Same author

Identifying Robust Subclonal Structures through Tumor Progression Tree Alignment.

bioRxiv : the preprint server for biology·2026
Same author

Publisher Correction: Integrated Liquid Biopsy and Tumor Tissue Genomic Profiling of Appendiceal Cancer: cfDNA Burden, Mutation Landscapes, and Clinical Outcomes.

Annals of surgical oncology·2026
Same author

The effect of prior transarterial chemoembolization on response to immune checkpoint inhibitor treatment in patients with hepatocellular carcinoma.

Clinical and molecular hepatology·2026

Related Experiment Video

Updated: Apr 4, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

863

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case

Daniele Catanzaro, Stanley E Shackney, Alejandro A Schaffer

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |September 10, 2015
    PubMed
    Summary

    This study models breast cancer progression from Ductal Carcinoma In Situ (DCIS) to Invasive Ductal Carcinoma (IDC) using integer linear programming. The model predicts evolutionary pathways, aiding in developing diagnostic tools for DCIS cases likely to become IDC.

    More Related Videos

    Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology
    09:45

    Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology

    Published on: November 14, 2025

    932
    Pancreatic Tissue Dissection to Isolate Viable Single Cells
    08:04

    Pancreatic Tissue Dissection to Isolate Viable Single Cells

    Published on: May 26, 2023

    4.3K

    Related Experiment Videos

    Last Updated: Apr 4, 2026

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
    07:13

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

    Published on: April 18, 2025

    863
    Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology
    09:45

    Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology

    Published on: November 14, 2025

    932
    Pancreatic Tissue Dissection to Isolate Viable Single Cells
    08:04

    Pancreatic Tissue Dissection to Isolate Viable Single Cells

    Published on: May 26, 2023

    4.3K

    Area of Science:

    • Oncology
    • Computational Biology
    • Genomics

    Background:

    • Ductal Carcinoma In Situ (DCIS) is a non-invasive breast cancer precursor.
    • Invasive Ductal Carcinoma (IDC) develops from DCIS, but predicting progression is challenging.
    • Understanding DCIS to IDC transition is crucial for early detection and treatment.

    Purpose of the Study:

    • To reconstruct plausible temporal progression pathways of breast cancer from single-cell data.
    • To develop a predictive model for DCIS progression to IDC using computational methods.
    • To identify distinct evolutionary characteristics of tumor progression.

    Main Methods:

    • Utilized integer linear programming (ILP) to model tumor evolution.
    • Incorporated assumptions based on cellular atypia observed in IDC.
    • Applied the model to single-cell sampled data from patients with synchronous DCIS and IDC.

    Main Results:

    • Developed a predictive model capable of reconstructing plausible progression scenarios.
    • Classified predicted progression models into categories with distinct evolutionary features.
    • Demonstrated the model's effectiveness on a dataset of 13 patients.

    Conclusions:

    • The ILP approach offers novel insights into clonal progression mechanisms in breast cancer.
    • The developed model can aid in understanding tumor evolution under complex constraints.
    • This methodology can be applied to reconstruct other complex biological scenarios.