Development and Validation of a Prognostic Index Based on Genes Participating in Autophagy in Patients With Lung Adenocarcinoma

Zi-Xuan Wu; Xuyan Huang; Min-Jie Cai; Pei-Dong Huang; Zunhui Guan

doi:10.3389/fonc.2021.799759

Development and Validation of a Prognostic Index Based on Genes Participating in Autophagy in Patients With Lung Adenocarcinoma

Front Oncol. 2022 Jan 25:11:799759. doi: 10.3389/fonc.2021.799759. eCollection 2021.

Authors

Zi-Xuan Wu¹, Xuyan Huang¹, Min-Jie Cai², Pei-Dong Huang³, Zunhui Guan⁴

Affiliations

¹ Guangzhou University of Chinese Medicine, Guangzhou, China.
² Shantou Health School, Shantou, China.
³ Yunnan University of Chinese Medicine, Kunming, China.
⁴ Kunming Municipal Hospital of Traditional Chinese Medicine, Kunming, China.

Abstract

Background: Lung adenocarcinoma (LUAD) is a deadly respiratory system malignancy with poor prognosis. Autophagy is essential for the beginning, development, and therapy resistance of cancer. However, the expression of genes participating in autophagy in LUAD and their associations with prognosis remain unclear.

Methods: Predictive genes participating in autophagy in LUAD samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were investigated. TCGA and GEO cohorts were divided into two risk groups, while the low-risk group having a longer overall survival (OS) time. This article aims to point out the interaction between genes participating in autophagy and immune function, immune checkpoints, and m⁶a in LUAD. The prediction model was designed for exploring least absolute shrinkage and selection operator (LASSO) regression. It has been revealed that gene expression and autophagy are inextricably connected.

Results: Genes participating in autophagy were shown to be somewhat overexpressed in the high-risk group even though no different clinical symptoms were present, indicating that they might be used in a model to predict LUAD prognosis. The majority of genes participating in autophagy prognostic signatures controlled immunological and tumor-related pathways, according to gene set enrichment analysis (GSEA). KRT6A, KYNU, IGFBP1, DKK1, PKP2, PLEK2, GAPDH, FLNC, and NTSR1 might be related to the oncology process for LUAD patients. CERS4, CMAHP, and PLEKHB1 have been identified as being associated with low risk in patients with LUAD. Furthermore, the immune function and m⁶a gene expression differed significantly between the two groups.

Conclusions: Genes participating in autophagy are connected to the development and progression of LUAD. LUAD patients' prognoses are often foreseen utilizing matched prognostic models. Genes participating in autophagy in LUAD may be therapeutic targets that ought to be investigated more.

Keywords: TCGA and GEO dataset, immunity; and immune checkpoint; bioinformatics analysis; genes participating in autophagy; lung adenocarcinoma (LUAD); m6a.