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Volume 32, Issue 7
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X

Abstract

Background

Lung cancer is a frequent malignancy with a poor prognosis. Extensive metabolic alterations are involved in carcinogenesis and could, therefore, serve as a reliable prognostic phenotype.

Aims

Our study aimed to develop a prognosis signature and explore the relationship between metabolic characteristic-related signature and immune infiltration in lung adenocarcinoma (LUAD).

Objective

TCGA-LUAD and GSE31210 datasets were used as a training set and a validation set, respectively.

Methods

A total of 513 LUAD samples collected from The Cancer Genome Atlas database (TCGA-LUAD) were used as a training dataset. Molecular subtypes were classified by consensus clustering, and prognostic genes related to metabolism were analyzed based on Differentially Expressed Genes (DEGs), Protein-Protein Interaction (PPI) network, the univariate/multivariate- and Lasso- Cox regression analysis.

Results

Two molecular subtypes with significant survival differences were divided by the metabolism gene sets. The DEGs between the two subtypes were identified by integrated analysis and then used to develop an 8-gene signature (TTK, TOP2A, KIF15, DLGAP5, PLK1, PTTG1, ECT2, and ANLN) for predicting LUAD prognosis. Overexpression of the 8 genes was significantly correlated with worse prognostic outcomes. RiskScore was an independent factor that could divide LUAD patients into low- and high-risk groups. Specifically, high-risk patients had poorer prognoses and higher immune escape. The Receiver Operating Characteristic (ROC) curve showed strong performance of the RiskScore model in estimating 1-, 3- and 5-year survival in both training and validation sets. Finally, an optimized nomogram model was developed and contributed the most to the prognostic prediction in LUAD.

Conclusion

The current model could help effectively identify high-risk patients and suggest the most effective drug and treatment candidates for patients with LUAD.

© 2025 Bentham Science Publishers
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2025-06-17

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Identification and Verification of Metabolism-related Immunotherapy Features and Prognosis in Lung Adenocarcinoma
Curr. Med. Chem. 32, 1423 (2025); https://doi.org/10.2174/0109298673293414240314043529
/content/journals/cmc/10.2174/0109298673293414240314043529
/content/journals/cmc/10.2174/0109298673293414240314043529
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  • Article Type:     Research Article
Keyword(s): immune infiltration; Lung adenocarcinoma; metabolism-related feature; prognostic factor; RiskScore; urothelial carcinoma

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