Construction of a lung adenocarcinoma prognostic model based on KEAP1/NRF2/HO‑1 mutation‑mediated upregulated genes and bioinformatic analysis.

Abstract

Lung adenocarcinoma (LUAD) is a prevalent malignant tumor of the respiratory tract. The Kelch like ECH associated protein 1 (KEAP1)/nuclear factor erythroid 2-related factor 2 (NRF2)/heme oxygenase 1 (HO-1) axis serves a pivotal role in the occurrence and progression of LUAD. The present study aimed to identify specific genes regulated by mutations of the KEAP1/NRF2/HO-1 axis and to investigate their prognostic potential in LUAD, as well as their association with the tumor microenvironment. Immunohistochemistry was performed to assess the expression levels of KEAP1, NRF2 and HO-1 in LUAD tissues and to evaluate their association with clinical pathology. Sequencing data and clinical information were obtained from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GSE68465) databases, whilst mutation information was sourced from the cBio Cancer Genomics Portal website. The R package 'limma' and Venn diagram were utilized to identify upregulated differentially expressed genes. Subsequently, a prognostic model was constructed using univariate Cox regression analysis and 101 machine learning methods. A nomogram of the prognostic model was generated to assess its efficacy in evaluating survival among patients with LUAD. The 'ImmuCellAI' and 'oncoPredict' R packages were used to compare and evaluate differences in immune cell infiltration and immunotherapy between high- and low-risk groups, as well as the sensitivity of LUAD to chemotherapy drugs. Compared with the group with negative expression, the results revealed that the group with positive expression of NRF2 and HO-1 exhibited advanced tumor, lymph node and clinical stages and a worse prognosis. A predictive model incorporating four genes (kynureninase, serpin family B member 5, insulin like 4 and γ-aminobutyric acid type A receptor subunit α3) was constructed based on KEAP1/NRF2/HO-1 mutation-mediated upregulated genes (KNHMUGs). Risk score was an independent prognostic factor for patients with LUAD (hazard ratio, 1.038; 95% confidence interval, 1.034-1.043; P<0.001). A nomogram was developed to predict the prognosis of patients with LUAD, which was validated as a reliable prognostic tool. The low-risk group exhibited higher immune cell infiltration, including CD4⁺ T, CD8⁺ T, natural killer (NK) and NKT cells, compared with the high-risk group. In addition, it demonstrated increased expression levels of immune checkpoint inhibitory genes such as cytotoxic T-lymphocyte associated protein 4, T cell immunoreceptor with Ig and ITIM domains, hepatitis A virus cellular receptor 2 and B and T lymphocyte associated protein. Moreover, it displayed enhanced sensitivity to immunotherapy. Drug sensitivity analysis revealed that the high-risk group exhibited increased sensitivity towards vinblastine, docetaxel and cisplatin, whereas the low-risk group showed increased sensitivity to BMS_754807, SB505124_1194 and JQ1_2172. In conclusion, a KNHMUGs-based gene signature was constructed in the present study, which holds promise as a biomarker for evaluating patient prognosis and guiding treatment by effectively assessing immunotherapy response and chemotherapy sensitivity in patients with LUAD.