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Machine Learning and Weighted Gene Coexpression Network-Based Identification of Biomarkers Predicting Immune Profiling and Drug Resistance in Lung Adenocarcinoma

  • 0Pharmacy Department, Xiangxi Autonomous Prefecture People's Hospital, Jishou, China.
International Journal of Genomics +

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March 31, 2025

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March 31, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

New prognostic markers for lung adenocarcinoma (LUAD) were identified using gene expression analysis. A risk model incorporating ANLN, CASS4, and NMUR1 improved prognosis prediction and revealed therapeutic targets for LUAD patients.

Area Of Science

  • Oncology
  • Genomics
  • Bioinformatics

Background

  • Lung adenocarcinoma (LUAD) has a poor prognosis and high recurrence rates.
  • There is a critical need for novel prognostic markers to guide treatment decisions in LUAD.
  • Current therapeutic strategies require refinement through better patient stratification.

Purpose Of The Study

  • To identify novel prognostic biomarkers for lung adenocarcinoma (LUAD).
  • To develop a predictive risk model for LUAD patient outcomes.
  • To explore the role of identified genes in LUAD progression and therapeutic response.

Main Methods

  • Weighted gene coexpression network analysis (WGCNA) to identify LUAD-associated gene modules.
  • Differential gene expression analysis between LUAD and normal samples.
  • Stepwise regression and LASSO for risk model construction and gene selection.
  • Nomogram validation, drug sensitivity analysis, immune infiltration, and in vitro experiments for ANLN.

Main Results

  • A risk model was developed using three key genes: ANLN, CASS4, and NMUR1.
  • The risk model effectively stratified LUAD patients into high- and low-risk groups with distinct overall survival (OS).
  • Gene expression correlated with immune cell infiltration, and ANLN knockdown inhibited LUAD cell viability, migration, and invasion.

Conclusions

  • The identified risk model and genes (ANLN, CASS4, NMUR1) show potential as prognostic biomarkers for LUAD.
  • The study provides insights into the immune microenvironment and therapeutic vulnerabilities in LUAD.
  • ANLN plays a significant role in LUAD progression, suggesting it as a potential therapeutic target.

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