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Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer.

ABSTRACT: BACKGROUND:Increasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored. METHODS:We developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patients with NSCLC through integrative analysis for lncRNA, immune and clinical profiles of 115 immune cell lines, 187 NSCLC cell lines and 1533 patients with NSCLC. Then the influence of the TILSig on the prognosis and immunotherapy in NSCLC was comprehensively investigated. RESULTS:Computational immune and lncRNA profiling analysis identified an lncRNA signature (TILSig) consisting of seven lncRNAs associated with tumor immune infiltration. The TILSig significantly stratified patients into the immune-cold group and immune-hot group in both training and validation cohorts. These immune-hot patients exhibit significantly improved survival outcome and greater immune cell infiltration compared with immune-cold patients. Multivariate analysis revealed that the TILSig is an independent predictive factor after adjusting for other clinical factors. Further analysis accounting for TILSig and immune checkpoint gene revealed that the TILSig has a discriminatory power in patients with similar expression levels of immune checkpoint genes and significantly prolonged survival was observed for patients with low TILSig and low immune checkpoint gene expression implying a better response to immune checkpoint inhibitor (ICI) immunotherapy. CONCLUSIONS:Our finding demonstrated the importance and value of lncRNAs in evaluating the immune infiltrate of the tumor and highlighted the potential of lncRNA coupled with specific immune checkpoint factors as predictive biomarkers of ICI response to enable a more precise selection of patients.

SUBMITTER: Sun J

PROVIDER: S-EPMC7057423 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer.

Sun Jie J Zhang Zicheng Z Bao Siqi S Yan Congcong C Hou Ping P Wu Nan N Su Jianzhong J Xu Liangde L Zhou Meng M

Journal for immunotherapy of cancer 20200201 1

<h4>Background</h4>Increasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored.<h4>Methods</h4>We developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patie ...[more]

PMID: 32041817

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Project description:BackgroundLung adenocarcinoma (LUAD) has become one of the most lethal cancers, for which the recurrence and survival rates remain unfavorable. The tumor necrosis factor (TNF) family is involved in tumorigenesis and tumor progression. Various long non-coding RNAs (lncRNAs) play important roles by mediating the TNF family in cancer. Therefore, this study aimed to construct a TNF-related lncRNA signature to predict prognosis and immunotherapy response in LUAD.MethodsThe expression of TNF family members and their related lncRNAs in a total of 500 enrolled LUAD patients was collected from The Cancer Genome Atlas (TCGA). Univariate Cox and the least absolute shrinkage and selection operator (LASSO)-Cox analysis was used to construct a TNF family-related lncRNA prognostic signature. Kaplan-Meier (KM) survival analysis was used to evaluate survival status. The time-dependent area under the receiver operating characteristic (ROC) curve (AUC) values were used to assess the predictive value of the signature to 1-, 2-, and 3-year overall survival (OS). Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to identify the signature-related biological pathways. Furthermore, tumor immune dysfunction and exclusion (TIDE) analysis was employed to evaluate immunotherapy response.ResultsA total of 8 TNF-related lncRNAs significantly associated with OS of LUAD patients were used to construct a TNF family-related lncRNA prognostic signature. According to risk score, these patients were divided into high- and low-risk subgroups. The KM survival analysis indicated that patients in the high-risk group showed significantly less favorable OS than that of low-risk group. The AUC values in predicting 1-, 2-, and 3-year OS were 0.740, 0.738, and 0.758, respectively. Moreover, the GO and KEGG pathway analyses demonstrated that these lncRNAs were closely involved in immune-related signaling pathways. The further TIDE analysis indicated that high-risk patients had a lower TIDE score than that of low-risk patients, indicating that high-risk patients may be appropriate candidates for immunotherapy.ConclusionsFor the first time, this study constructed and validated a prognostic predictive signature of LUAD patients based on TNF-related lncRNAs, and the signature showed good performance to predict immunotherapy response. Therefore, this signature may provide new strategies for individualized treatment of LUAD patients.

Project description:ObjectiveThis study aims to evaluate the prognostic value of m6A-associated long noncoding RNAs (lncRNAs) and their interaction with tumour microenvironment in thyroid cancer (THCA).MethodsThe clinical and gene expression data of tumours from 502 patients with THCA and 58 adjacent normal tissues were retrieved from The Cancer Genome Atlas (TCGA)-THCA dataset. The Pearson test was utilized to identify potential m6A-associated lncRNAs (p < 0.001 and Pearson correlation coefficient > 0.4). Quantitative real-time polymerase chain reaction was performed to verify the expression levels of lncRNAs in tissues. MTT, EdU, colony formation and wound-healing assays were performed to determine the functions of m6A-associated lncRNAs in THCA cell proliferation and metastasis.ResultsM6A-associated lncRNAs were identified in three cluster groups. A significant survival difference was found among them, with cluster 1 patients showing worse survival. Moreover, lower immune and estimate scores were correlated to poorer prognosis, and CD8+ T cell and memory CD4+ T cell levels were increased in cluster 1. Cluster 2, with better overall survival, had high expression of PD-L1 and CTLA-4. Eleven of the m6A-associated lncRNAs were screened to establish the risk model, including AC007365.1, AC008555.1, AC040160.1, AC064807.1, AC126773.4, AL023583.1, AL512306.2, EIF2AK3-DT, LINC00667, LYPLAL1-DT and MIR181A2HG. Based on the median risk score, THCA patients were stratified into low-risk and high-risk groups. Overall survival analysis showed a dramatic difference between the two groups. qRCR was performed to verify the expression levels of lncRNA (LYPLAL1-DT, EIF2AK3-DT and MIR181A2HG) in THCA and adjacent normal tissues. Furthermore, functional experiments showed that knockdown of MIR181A2HG obviously inhibited the proliferation and migration of papillary thyroid cancer (PTC) cells in vitro, whereas LYPLAL1-DT overexpression promoted PTC cell proliferation and migration.ConclusionsEleven of the m6A-associated lncRNAs were identified as a risk model to predict clinical outcomes and provide a novel and efficient immunotherapeutic strategy for THCA patients.Key messagesm6A-associated lncRNAs can be used to predict the clinical outcomes of thyroid cancer patients.An m6A-associated lncRNAs risk model, which can accurately evaluate the immune status and risk stratification in individual thyroid cancer patients, was established.Knockdown/overexpression of representative lncRNAs in the risk model significantly affected the proliferation and migration of papillary thyroid cancer cells.

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Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer.

Publications

Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer.

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