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
  1. Home
  3. Protocol To Develop A Chemotherapy Drug Screening Process By Constructing A Cancer Prognostic Model Using Public Databases.
  1. Home
  3. Protocol To Develop A Chemotherapy Drug Screening Process By Constructing A Cancer Prognostic Model Using Public Databases.

Related Concept Videos

Related Experiment Videos

Protocol to develop a chemotherapy drug screening process by constructing a cancer prognostic model using public

Weiyu Bai1

  • 1Center for Life Sciences, School of Life Sciences, State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan University, Kunming 650091, China.

STAR Protocols
|June 29, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a method to create cancer prognostic models (PM) from public data to aid chemotherapy drug screening. This approach helps predict patient survival and identify effective treatments for drug-resistant cancers.

Keywords:
BioinformaticsCancerClinical Protocol

Related Experiment Videos

Area of Science:

  • Oncology
  • Bioinformatics
  • Computational Biology

Background:

  • Drug resistance is a major obstacle in cancer chemotherapy.
  • Developing effective screening processes for chemotherapy drugs is crucial.
  • Public databases offer valuable resources for cancer research.

Purpose of the Study:

  • To present a protocol for developing a cancer prognostic model (PM).
  • To establish a chemotherapy drug screening process using the developed PM.
  • To create predictive websites for cancer patient survival analysis.

Main Methods:

  • Utilizing public databases for data and code acquisition.
  • Preparing expression matrices and metadata for analysis.
  • Screening genes for prognostic model construction.
  • Building predictive websites integrating patient data (age, tumor stage, gene expression, risk scores).

Main Results:

  • A protocol for constructing a cancer prognostic model (PM) has been successfully developed.
  • The protocol enables the screening of chemotherapy drugs.
  • Predictive websites for cancer patient survival can be generated.

Conclusions:

  • The developed protocol provides a framework for chemotherapy drug screening.
  • Prognostic models constructed from public data can aid in predicting patient survival.
  • This approach offers a valuable tool for personalized cancer treatment strategies.