JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

Deciphering the role of cuproptosis-related lncRNAs in shaping the lung cancer immune microenvironment: A comprehensive prognostic model

  • 0Tuberculosis ward No.2, Wuhan Pulmonary Hospital, Wuhan Institute for Tuberculosis Control, Wuhan, Hubei, China.
Journal of Cellular and Molecular Medicine +

|

July 8, 2024

|

July 8, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Cuproptosis, a cell death process, is significant in lung cancer. Researchers developed a prognostic model using four key long non-coding RNAs (lncRNAs) to predict patient survival and guide treatment strategies.

Area Of Science

  • Oncology
  • Molecular Biology
  • Genomics

Background

  • Cuproptosis is implicated in various cancers, but its specific role in lung cancer pathogenesis and prognosis is not well understood.
  • Long non-coding RNAs (lncRNAs) are increasingly recognized as critical regulators in cancer development and progression.

Purpose Of The Study

  • To investigate the role of cuproptosis-related genes and lncRNAs in lung cancer.
  • To develop and validate a prognostic model based on cuproptosis-related lncRNAs for lung cancer patients.

Main Methods

  • Utilized transcriptional profiles, clinical data, and mutation data from TCGA and GEO databases.
  • Performed co-expression analysis to identify cuproptosis-related lncRNAs and constructed a prognostic model using R software.
  • Validated the model's predictive performance through survival analysis, ROC curves, and independent datasets.
  • Conducted functional enrichment, tumor mutation load, drug sensitivity, and immune infiltration analyses.

Main Results

  • Identified 129 cuproptosis-related lncRNAs and established a four-lncRNA prognostic model (LINC00996, RPARP-AS1, SND1-IT1, TMPO-AS1).
  • The model effectively stratified lung cancer patients into high- and low-risk groups with significant survival differences.
  • Distinct biological pathways, immune functions, and mutation profiles were observed between the risk groups.
  • The model demonstrated strong predictive accuracy and potential for guiding treatment decisions.

Conclusions

  • lncRNAs play a crucial role in cuproptosis-associated lung cancer.
  • The developed four-lncRNA prognostic model serves as a potential biomarker for predicting lung cancer prognosis.
  • This model may aid in understanding the immune microenvironment and optimizing therapeutic strategies for lung cancer.

Keywords: