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

  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Six-gene Signature For Differential Diagnosis And Therapeutic Decisions In Non-small-cell Lung Cancer-a Validation Study

Six-Gene Signature for Differential Diagnosis and Therapeutic Decisions in Non-Small-Cell Lung Cancer-A Validation Study

Radoslaw Charkiewicz1,2, Anetta Sulewska2, Piotr Karabowicz3

  • 1Center of Experimental Medicine, Medical University of Bialystok, 15-369 Bialystok, Poland.

International Journal of Molecular Sciences
|April 13, 2024

Related Experiment Videos

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
07:59

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

1.1K
Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
08:49

Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool

Published on: May 27, 2016

11.1K
MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

Published on: October 26, 2017

15.6K

View abstract on PubMed

Summary
This summary is machine-generated.

This study validates six genes for distinguishing non-small-cell lung cancer (NSCLC) subtypes, squamous cell carcinoma (SCC) and adenocarcinoma (ADC). While effective for classification, these markers do not predict early-stage NSCLC progression.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Non-small-cell lung cancer (NSCLC) heterogeneity complicates diagnosis and treatment.
  • Molecular markers offer a promising approach to overcome limitations of traditional histopathology.
  • Accurate subtyping is crucial for personalized NSCLC treatment strategies.

Purpose of the Study:

  • To validate the diagnostic potential of six specific genes (MIR205HG, KRT5, KRT6A, KRT6C, SERPINB5, DSG3) for NSCLC subtyping.
  • To assess the predictive value of these gene expression profiles for early-stage NSCLC progression.
  • To evaluate the performance of machine learning models in classifying NSCLC subtypes based on validated gene expression.

Main Methods:

  • Gene expression analysis using microarray and real-time PCR on 140 early-stage NSCLC samples.
Keywords:
ADCNSCLC subtypingSCCgene expression

Related Experiment Videos

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
07:59

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

1.1K
Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
08:49

Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool

Published on: May 27, 2016

11.1K
MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

Published on: October 26, 2017

15.6K
  • Validation of six previously identified genes within a 53-gene signature.
  • Application of logistic regression and gradient boosting decision tree classifiers for subtype discrimination.

    • Main Results:

    • All six genes were significantly upregulated in squamous cell carcinoma (SCC) compared to adenocarcinoma (ADC).
    • Logistic regression models effectively separated SCC and ADC based on gene expression, with exceptions for KRT6C.
    • Machine learning classifiers achieved high accuracy (AUC ~0.89) in distinguishing NSCLC subtypes.
    • Gene expression profiles did not predict progression in early-stage NSCLC.

    Conclusions:

    • The validated six-gene signature shows strong potential for molecular subtyping of NSCLC.
    • These molecular diagnostic models can aid in comprehensive NSCLC characterization.
    • Personalized treatment decisions and improved clinical management for NSCLC patients are potential benefits.
    personalized medicine
    prognosis
    qPCR
    validation study