Development and validation of an immune‐related prognostic signature in lung adenocarcinoma

Abstract

Background Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune‐related signature of LUAD. Methods A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co‐expression network analysis (WGCNA) was applied to identify immune‐related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune‐related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA). Results In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses ( P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune‐related genes, and after univariate Cox regression analysis ( P < .005), a total of 133 genes were screened out for subsequent model constructions. A four‐gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan‐Meier survival analysis that eight out of nine patients in high‐risk groups had significantly worse prognoses in validation data sets ( P < .05). IPSLUAD outperformed other signatures in two independent cohorts. Conclusions A robust immune‐related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

Upregulation of ARNTL2 Predicts Poor Survival for Clear Cell Renal Cell Carcinoma and Explores its Associations with PD-L1 and Immune Infiltration

“…These results implied that low ARNTL2 expression ccRCC patients with high PBRM1 mutation rates might obtain more clinical bene ts from ICI therapy. Furthermore, two recent studies have revealed that ARNTL2 correlated with prognosis and immune in ltration of lung adenocarcinoma [10,11]. Which also indicated ARNTL2 might in uence the TIME of cancer.…”

“…Aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) pertain to the PAS superfamily and can encode a transcription factor, whose protein structure is remarkably similar to hypoxia-inducible factors, such as HIF1alpha, ARNTL2 was reported to play important roles in circadian and hypoxia process [7]. Emerging evidences have demonstrated the carcinogenesis roles of ARNTL2 in human malignancies such as breast carcinoma and colorectal adenocarcinoma [8,9], there are also two recent researches have showed that ARNTL2 correlated with the poor survival and immune in ltration level of lung adenocarcinoma [10,11]. However, the potential roles of ARNTL2 in ccRCC have not been investigated thus far.…”

Gene signature based on B cell predicts clinical outcome of radiotherapy and immunotherapy for patients with lung adenocarcinoma

“…Other gene signature in LUAD also showed B cells were highly infiltrated in the low‐risk group. A 10‐immune‐related‐genes signature constructed by Jiaona Zhu et al 57 and IPSLUAD signature developed by Jie He 58 were predicted the prognosis of patients well. Both of the two gene signatures suggested that B cells were highly infiltrated in the low‐risk group, but the role of B cells in tumor immune infiltration was not explored.…”

Large-Scale Transcriptome Analysis Identified Novel Ferroptosis-Related Gene Signatures for Predicting the Prognostic of Patients with Lung Adenocarcinoma

“…For example, based on the Cancer Genome Atlas (TCGA) database, many new molecules were found to be involved in the malignant progression of tumors, and different molecular signatures can be used to predict the prognosis of tumors [7]. Immunotherapy is an effective treatment for lung cancer, and tumor signatures based on immune-related genes can effectively predict the survival and recurrence of patients [8,9]. In addition, there are other signatures for lung cancer prognosis such as autophagy, RNA methylation [10,11].…”