Establishment and Evaluation of a 6-Gene Survival Risk Assessment Model Related to Lung Adenocarcinoma Microenvironment

Abstract

Objective. A survival risk assessment model associated with a lung adenocarcinoma (LUAD) microenvironment was established and evaluated to identify effective independent prognostic factors for LUAD. Methods. The public data were downloaded from the TCGA database, and ESTIMATE prediction software was used to score immune cells and stromal cells for tumor purity prediction. The samples were divided into the high-score group and the low-score group by the median value of the immune score (or stromal score). The Wilcoxon test was used for differential analysis. GO and KEGG enrichment analysis of differentially expressed genes (DEGs) was performed using “clusterProfiler” of R package. Meanwhile, univariate and multivariate regression analysis was performed on DEGs to construct a multivariate Cox risk regression model with variable gene expression levels as independent prognostic factors affecting a tumor microenvironment (TME) and tumor immunity. Results. This study found that LUAD patients with high immune cell (stromal cell) infiltration had better prognosis and were in earlier staging. Functional enrichment analysis revealed that most DEGs were related to the proliferation and activation of immune cells or stromal cells. A survival prediction model composed of 6 TME-related genes (CLEC17A, TAGAP, ABCC8, BCAN, FLT3, and CCR2) was established, and finally, the 6 feature genes closely related to the prognosis of LUAD were proved. The AUC value of the ROC curve in this model was 0.7, indicating that the model was reliable. Conclusion. Six genes related to the LUAD microenvironment have a predictive prognostic value in LUAD.

A Prognostic Nomogram Combining Immune-Related Gene Signature and Clinical Factors Predicts Survival in Patients With Lung Adenocarcinoma

“…Immune score, which can promote the quantification of immune components (such as immune cells) in tumors, can significantly affect the prognosis of patients. In several studies (32)(33)(34)(35), it has been confirmed that high immune scores were associated with better prognosis. Similarly, high-risk patients with worse prognosis had lower immune scores in our study, which further suggested the validity and accuracy of the signature constructed in this study in identifying high-risk patients.…”

“…Some studies have reported that poor prognosis was closely related to low tumor purity in glioma (30) and colorectal cancer (31). Contrary to the poorer prognosis of low tumor purity in glioma and colorectal cancer, Wang et al (32) observed that patients with low LUAD purity tended to have a better prognosis. This finding was in line with that of our study.…”

ABCC8 mRNA expression is an independent prognostic factor for glioma and can predict chemosensitivity

“…It was concluded that stem cells might play a role in the development and progression of ductal adenocarcinoma of the pancreas. Wang et al 12 screened 6 genes (CLEC17A, TAGAP, ABCC8, BCAN, FLT3, and CCR2) related to immune and stromal cells in the tumor microenvironment through bioinformatics and constructed a risk assessment model to predict the prognosis of lung adenocarcinoma. They found patients with high expressions of CLEC17A, TAGAP, ABCC8, FLT3, and CCR2 had better prognosis and higher OS within 5 years.…”

“…ATP-binding cassette (ABC) transporters play a crucial role in the development of resistance by the efflux of anticancer agents outside of cancer cells. It was found that the expression of ABCC8 was down-regulated in pancreatic cancer 11 , lung adenocarcinoma 12 and triple negative breast cancer 13 . The low expression of ABCC8 was associated with poor prognosis in these tumors.…”

The role of CD28 in the prognosis of young lung adenocarcinoma patients

“…Previous work on nomograms mostly focused on the basic characteristics and clinical information of patients but paid less attention to the pathological changes, especially the TIME status. Wang et al [ 13 ] confirmed the important role of TME-related molecules in the prognosis of LUAD in a recent study and established a risk assessment model based on the TME. In this study, we included immune factors in a prognostic model for LUAD and constructed a novel nomogram with robust efficacy for young patients with LUAD to establish a novel method to predict the prognosis of young patients with LUAD and further discuss the essential role of the TIME in LUAD.…”