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

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

8.5K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
8.5K
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Single-cell And Bulk Rna Analysis Identifies Emt-associated Caf Signatures And Prognostic Model In Lung Adenocarcinoma.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Single-cell And Bulk Rna Analysis Identifies Emt-associated Caf Signatures And Prognostic Model In Lung Adenocarcinoma.

Related Experiment Video

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

1.0K

Single-cell and bulk RNA analysis identifies EMT-associated CAF signatures and prognostic model in lung adenocarcinoma.

He An1, Ping An2

  • 1Department of Clinical Laboratory, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China.

Discover Oncology
|June 14, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

This study identifies key genes in cancer-associated fibroblasts (CAFs) linked to epithelial-mesenchymal transition (EMT) in lung adenocarcinoma (LUAD). A novel risk score model using these genes predicts patient survival and informs personalized treatment strategies.

Keywords:
Cancer-associated fibroblastsEpithelial-mesenchymal transitionLung adenocarcinomaPrognostic model

More Related Videos

Predictive Immune Modeling of Solid Tumors
08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

6.9K
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

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

1.0K
Predictive Immune Modeling of Solid Tumors
08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

6.9K
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

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Cancer-associated fibroblasts (CAFs) play a crucial role in lung adenocarcinoma (LUAD) progression, particularly through epithelial-mesenchymal transition (EMT).
  • Understanding CAF-mediated EMT is vital for remodeling the tumor microenvironment and advancing cancer treatment strategies.

Purpose of the Study:

  • To identify specific CAF signature genes associated with EMT in LUAD.
  • To develop a prognostic model for LUAD based on these EMT-CAF genes.
  • To elucidate the clinical significance and molecular mechanisms of CAFs in LUAD.

Main Methods:

  • Integrated single-cell and bulk RNA sequencing data from LUAD patient cohorts (TCGA, GEO).
  • Utilized Seurat for cell clustering and EMT activity analysis.
Single-cell RNA sequencing
  • Applied differential gene expression, Cox, and LASSO regression to build a prognostic risk score model.
  • Evaluated model performance using survival and ROC analyses, alongside tumor microenvironment, immune infiltration, TMB, and drug sensitivity assessments.

    • Main Results:

    • Identified CAFs with significant EMT activation and 84 EMT-CAF-related genes, from which eight key genes formed a risk score model.
    • High-risk patients exhibited significantly worse survival, lower immune/stromal scores, higher tumor purity, and altered immune cell infiltration (fewer anti-tumor, more immunosuppressive cells).
    • High-risk group showed higher tumor mutational burden (TMB) and increased sensitivity to common anti-lung cancer drugs.

    Conclusions:

    • Developed a clinically valuable prognostic risk score model for LUAD based on EMT-CAF-related genes, enabling effective survival prediction and risk stratification.
    • High-risk LUAD patients display distinct tumor microenvironment characteristics, including higher TMB and immune suppression, influencing disease progression.
    • Findings offer insights for personalized treatment approaches in LUAD, warranting further validation of clinical applicability and biological mechanisms.