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Published on: October 26, 2017
A Lactylation-based Gene Signature in Lung Adenocarcinoma Provides a Novel Perspective to Predict the Prognosis and
Ming Zhao1, Ben Li2, Honghai Li1
1Department of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, 100039, China.
Introduction:
Lactylation, a novel post-translational modification in tumor cells, is studied here to explore its relevant gene signature in lung adenocarcinoma (LUAD).
Materials And Methods:
Transcriptome data of LUAD from The Cancer Genome Atlas (TCGA) were retrieved from UCSC Xena, while the gene expression dataset GSE31210 was acquired from the Gene Expression Omnibus (GEO) database. Lactation-related genes (LRGs) were identified based on previous literature. Lactation levels were quantified using single-sample gene set enrichment analysis (ssGSEA). After screening LRGs associated with prognosis, the ConsensusClusterPlus package was employed for clustering. Subsequently, a RiskScore model was constructed through univariate Cox and LASSO analyses. The prognostic relevance and robustness of the RiskScore were evaluated, and the association of the RiskScore with both immunotherapy response and the tumor microenvironment (TME) was determined.
Results:
An overall high lactylation score was noticed in the LUAD sample, which could be assigned into 2 molecular subtypes (C1 and C2). Meanwhile, 83 LRGs were preliminarily explored to have prognostic relevance, of which 5 genes (CDKN3, FSCN1, PKP2, FAM83A, and ABCC2) were further revealed as the hub genes for the RiskScore model. Such RiskScore, independent of other clinicopathological features, displayed a satisfying efficacy in predicting the prognosis and the response to immunotherapy. Additionally, the formulated RiskScore, including the expression level of each gene, displayed a varied correlation with the predicted drug candidates.
Discussion:
From the lactylation perspective, this study reveals LUAD's molecular heterogeneity, proposes and externally validates a 5-gene RiskScore model. The model independently predicts prognosis, correlates with immunotherapeutic response and drug sensitivity, and points to potential links among lactate metabolism, key signaling pathways, and clinical outcomes.
Conclusion:
5 prognosis-relevant LRGs could provide a novel perspective for the individualized therapeutic regimens for LUAD.
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