An Immune-Related Signature Predicts Survival in Patients With Lung Adenocarcinoma

Zhang, Minghui; Zhu, Kaibin; Pu, Haihong; Wang, Zhuozhong; Zhao, Hongli; Zhang, Jinfeng; Wang, Yan

doi:10.3389/fonc.2019.01314

Cited by 129 publications

(104 citation statements)

References 37 publications

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“…Recently pro les of 14 IRGs in lung adenocarcinoma that showed high prediction accuracy and stability in identifying immune features [42]. Our research differed from previous studies in several ways.…”

Section: Discussioncontrasting

confidence: 81%

Construction of a Prognostic Value Model in Papillary Renal Cell Carcinoma by Immune-Related Genes

Wang¹,

Gu²,

Ni³

2020

Preprint

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Papillary renal cell carcinoma (PRCC) is the second most common type of renal carcinoma following clear cell renal cell carcinoma, and the role of immune-related genes (IRGs) in tumorigenesis and metastasis is evident; its prognostic value in PRCC remains unclear. In this study, we downloaded the gene expression profiles and clinical data of patients with PRCC from The Cancer Genome Atlas (TCGA) database and obtained IRGs from the ImmPort database. A total of 371 differentially expressed IRGs (DEIRGs) were discovered between PRCC and normal kidney tissues. Prognostic DEIRGs (PDEIRGs) were identified by univariate Cox regression analysis. Then, we screened the four most representative PDEIRGs (IL13RA2, CCL19, BIRC5, and INHBE) and used them to construct a risk model to predict the prognosis of patients with PRCC. This model precisely stratified survival outcome and accurately identified mutation burden in PRCC. Thus, our results suggest that these four PDEIRGs are available prognostic predictors for PRCC. They could be used to assess the prognosis and to guide individualized treatments for patients with PRCC.

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Section: Discussioncontrasting

confidence: 81%

Construction of a Prognostic Value Model in Papillary Renal Cell Carcinoma by Immune-Related Genes

Wang¹,

Gu²,

Ni³

2020

Preprint

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“…The AUC for 1-and 3-year of the immune signature in training cohort was 0.70 and 0.68, respectively, and in validation cohort was 0.72 and 0.73, respectively, all of which were inferior to that in this study. Similarly, a study reported an immune-related signature [17], which AUC of 1-(0.78) and 3-(0.76) year was also lower than that of this study. In addition, Zhang et al constructed a glycolysis-related gene prognostic signature with the AUC = 0.72 [18].…”

Section: Discussioncontrasting

confidence: 65%

Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

2020

Preprint

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Background Lung adenocarcinoma (LUAD) is the main pathological subtype of Non-small cell lung cancer. The aim of this study was to establish an immune-related gene pairs (IRGPs) signature for predicting the prognosis of LUAD patients.Methods We downloaded the gene expression profile and immune-related gene set from TCGA and ImmPort database, respectively, to establish IRGPs. Then, IRGPs subjected to univariate Cox regression analysis, LASSO regression analysis and multivariable Cox regression analysis to screen and develop a IRGPs signature. The receiver operating characteristic curve (ROC) was applied for evaluating the predicting accuracy of this signature by calculating the area under ROC (AUC) and data from GEO was used to validate this signature.Results A IRGPs signature with 8 IRGPs was constructed. The AUC for 1- and 3-year overall survival in TCGA set was 0.867 and 0.870, respectively. Similar result was observed in the AUC of GEO set and Total set (GEO set [1-year: 0.819; 3-years: 0.803]; Total set [1-year: 0.845; 3-years: 0.801]). Survival analysis of three sets demonstrated high-risk LUAD patients exhibited poorer prognosis. The multivariable Cox regression indicated that risk score was independent prognostic factors.Conclusions We developed a novel IRGPs signature for predicting prognosis of LUAD.

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“…This analysis involved data from 192 1p19q codeletion LGG samples and 394 non-deletion LGG samples. 1p19q co-deletion associated immune-related DEGs were identi ed from the DEGs based on immune-related gene annotation on the IMMPORT website (https://www.immport.org/) [11]. Only genes shared by CGGA and TCGA were included in downstream analyses.…”

Section: Identi Cation Of Immune-related Genes Correlated With 1p19qmentioning

confidence: 99%

A 1p/19q Codeletion-Associated Immune Signature for Predicting Lower Grade Glioma Prognosis

Liu

et al. 2020

Cell Mol Neurobiol

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Background: Lower grade gliomas (LGGs) with codeletion of chromosomal arms 1p and 19q (1p/19 codeletion) has a favorable outcome. However, its overall survival (OS) varies. Here, we established an immune signature associated with 1p/19q codeletion for accurate prediction of prognosis of LGGs. Methods: We extracted RNA sequencing and corresponding clinical data of LGGs from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). The CGGA and TCGA databases were dichotomized into training group and testing group. The immune-related differentially expressed genes (DEGs) associated with 1p/19q codeletion were screened using Cox proportional hazards regression analyses. A prognostic signature was established using dataset from CGGA and tested in TCGA datasets. Subsequently, we explored the correlation between the prognostic signature and immune response. Results: Thirteen immune genes associated with 1p/19q codeletion were identi ed and used to construct a prognostic signature. The 1-, 3-, 5-year survival rates of the low-risk group were approximately 97%, 89%, and 79%, while those of the high-risk group were 81%, 50% and 34%, respectively in the training group. The nomogram which comprised of age, world health organization (WHO) grade, primary or recurrent types, 1p/19q codeletion status and risk score provided accurate prediction for the survival rate of glioma. DEGs that were highly expressed in the high-risk group clustered with many immune-related pathways. Immune checkpoints including T cell immunoglobulin domain and mucin domain 3 (TIM3), programmed cell death 1 (PD1), PD1 interacting with programmed death ligand 1 (PDL1), cytotoxic T lymphocyte antigen 4 (CTLA4), T cell immunoreceptor with Ig and ITIM domains (TIGIT), long non-coding RNA MIR 155 host gene (MIR155HG), and CD48 were correlated with the risk score. VAV3 and TNFRFSF11B were found to be candidate immune checkpoints. Conclusion: The 1p/19q codeletion-associated immune signature provides accurate prediction of OS. VAV3 and TNFRFSF11B are novel immune checkpoints.

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An Immune-Related Signature Predicts Survival in Patients With Lung Adenocarcinoma

Cited by 129 publications

References 37 publications

Construction of a Prognostic Value Model in Papillary Renal Cell Carcinoma by Immune-Related Genes

Construction of a Prognostic Value Model in Papillary Renal Cell Carcinoma by Immune-Related Genes

Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

A 1p/19q Codeletion-Associated Immune Signature for Predicting Lower Grade Glioma Prognosis

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