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Unlocking the Potential of Disulfidptosis-Related LncRNAs in Lung Adenocarcinoma: A Promising Prognostic LncRNA Model for Survival and Immunotherapy Prediction

  • 0Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, People's Republic of China.
Cancer Medicine +

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October 21, 2024

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October 21, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study identifies five disulfidptosis-related long non-coding RNAs (lncRNAs) to predict survival in lung adenocarcinoma (LUAD). The developed risk model aids in forecasting tumor microenvironment, mutation burden, and drug sensitivity for better clinical decisions.

Area Of Science

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background

  • Disulfidptosis, a newly identified form of regulated cell death, is linked to glucose starvation in cells with high SLC7A11 expression.
  • Long non-coding RNAs (lncRNAs) play crucial roles in various biological processes, including cancer development and progression.

Purpose Of The Study

  • To identify disulfidptosis-related lncRNAs (DRLs) in lung adenocarcinoma (LUAD).
  • To construct a prognostic model based on DRLs for predicting patient survival.
  • To analyze the tumor microenvironment (TME) and its correlation with DRLs and patient outcomes.

Main Methods

  • Utilized The Cancer Genome Atlas (TCGA) database for data acquisition.
  • Employed Cox regression and LASSO methods to build a DRL-based risk model.
  • Validated prognostic ability using GEO database and assessed TME via ESTIMATE, TMB, CIBERSORT, and TIDE scores.

Main Results

  • Identified 91 DRLs, with five (AC092718.4, AL365181.2, AL606489.1, EMSLR, ENTPD3-AS1) forming the prognostic model.
  • The DRL risk model demonstrated excellent survival prediction accuracy.
  • Low-risk patients showed higher immune and stromal scores but lower tumor mutation burden (TMB), while high-risk patients exhibited the opposite trend.
  • Lower risk scores combined with higher TMB correlated with favorable survival and potential response to immunotherapy.
  • lncRNA AC092718.4 was found to promote LUAD cell invasion, migration, and proliferation in vitro.

Conclusions

  • Developed a robust 5-lncRNA prognostic model for disulfidptosis in LUAD.
  • The model effectively predicts patient survival, TME characteristics, TMB, and potential drug sensitivity.
  • This DRL-based risk model serves as a valuable tool for clinical decision-making and outcome prediction in LUAD.

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