Identification of a Five Autophagy Subtype-Related Gene Expression Pattern for Improving the Prognosis of Lung Adenocarcinoma

• DOI: 10.3389/fcell.2021.756911
• Publication Date: 2021-11-18T05:16:27Z
• Authors: Meng-Yu Zhang; Chen Huo; Jian-Yu Liu; Zhuang-E. Shi; Wen-Di Zhang; Jia-Jia Qu; Yue-Liang Yue; Yi-Qing Qu
• Keywords: Univariate; KEGG

Background: Autophagy plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the autophagy-related gene (ARG) expression pattern and identify promising biomarkers improve prognosis of LUAD. Methods: The profiles clinical information LUAD patients were downloaded from Cancer Genome Atlas (TCGA), validation cohort was extracted Gene Expression Omnibus database. Human Database (HADb) used extract ARGs. data analyzed using limma package visualized ggplot2 as well pheatmap R software. Functional enrichment analysis also performed for differentially expressed ARGs (DEARGs). Then, consensus clustering revealed tumor subtypes, genes (DEGs) screened according subtypes. Next, univariate Cox multivariate regression analyses independent prognostic After overlapping DEGs ARGs, predictive risk model established validated. Correlation between clinicopathological variables explored. Finally, TIMER TISIDB databases further correlation immune cell infiltration levels score model. Results: A total 222 HADb identified 28 pooled DEARGs. most significant GO term autophagy (p = 3.05E-07), KEGG results indicated that DEARGs significantly enriched ErbB signaling pathway < 0.001). divided into two clusters, a 168 cluster Then 12 could serve indicators. genes, 10 (ATG4A, BAK1, CAPNS1, CCR2, CTSD, EIF2AK3, ITGB1, MBTPS2, SPHK1, ST13) selected exploration pattern. Survival 4.379E-10). Combined with variables, five genes. Among them, SPHK1 positively correlated CD4+ T cells dendritic levels. Conclusions: constructed subtype-related Understanding subtypes is helpful accurately characterize develop personalized treatment.