Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer

Zhou, Meng; Zhang, Zicheng; Bao, Siqi; Hou, Ping; Yan, Congcong; Su, Jianzhong; Sun, Jie

doi:10.1093/bib/bbaa047

Cited by 137 publications

(115 citation statements)

References 58 publications

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“…Moreover, the relationship between 23-IRGP and ICIs indicated an integrated prognostic power on patient OS, which is associated with previous result that M1 macrophages, activated CD4+ memory T cells, monocytes, plasma cells, CD8+ T cells, follicular helper T cells, and gamma delta T cells infiltration and ICIs expression may make a difference on patients' OS and patients' immunotherapy effect. Collectively, it may suggested that the 23-IRGP may have a predictive ability of the response to CM immunotherapy (25).…”

Section: Discussionmentioning

confidence: 98%

A Novel Signature of 23 Immunity-Related Gene Pairs Is Prognostic of Cutaneous Melanoma

Xue

et al. 2020

Front. Immunol.

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In this study, we aimed to identify an immune-related signature for predicting prognosis in cutaneous melanoma (CM). Sample data from The Cancer Genome Atlas (TCGA; n = 460) were used to develop a prognostic signature with 23 immune-related gene pairs (23 IRGPs) for CM. Patients were divided into high-and low-risk groups using the TCGA and validation datasets GSE65904 (n = 214), GSE59455 (n = 141), and GSE22153 (n = 79). The ability of the 23-IRGP signature to predict CM was precise, with the stratified high-risk groups showing a poor prognosis, and it had a significant predictive power when used for immune microenvironment and biological analyses. We subsequently established a novel promising prognostic model in CM to determine the association between the immune microenvironment and CM patient results. This approach may be used to discover signatures in other diseases while avoiding the technical biases associated with other platforms.

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Section: Discussionmentioning

confidence: 98%

A Novel Signature of 23 Immunity-Related Gene Pairs Is Prognostic of Cutaneous Melanoma

Xue

et al. 2020

Front. Immunol.

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“…Currently, a lot of attention has been given to the field of immune therapies that could regulate the tumor microenvironment ( 8 – 10 ). For example, a study shows the relationship between the lncRNA signature of tumor-infiltrating B lymphocytes and the immune therapies of bladder cancer ( 11 ). Additionally, lncRNAs have several significant biological functions.…”

Section: Introductionmentioning

confidence: 99%

A Seven Immune-Related lncRNAs Model to Increase the Predicted Value of Lung Adenocarcinoma

Liu

et al. 2020

Front. Oncol.

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Background Recent research has shown that immune-related lncRNA plays a crucial part in the tumor immune microenvironment. This study tried to identify immune-related lncRNAs and construct a robust prediction model to increase the predicted value of lung adenocarcinoma (LUAD). Methods RNA expression data of LUAD were download from the Cancer Genome Atlas (TCGA) database. Immune genes were acquired from the Molecular Signatures Database (MSigDB). The immune gene related lncRNAs were acquired by the “limma R” package and Cytoscape3.7.1. Cox regression analysis was applied to construct this forecast model. The prognostic model was validated by the testing cohort which was acquired by the bootstrap method. Results A total of 551 lncRNA expression profiles including 497 LUAD tissues and 54 non-LUAD tissues were obtained. A total of 331 immune genes were acquired. The result of the Cox regression analysis showed that seven lncRNAs (AC022784-1, NKILA, AC026355-1, AC068338-3, LINC01843, SYNPR-AS1, and AC123595-1) can be performed to construct the prediction model to forecast the prognosis of LUAD. Kaplan–Meier curves indicated that our prediction model can distribute LUAD patients into two different risk groups (high and low) with significant statistical significance ( P = 1.484e-07). Cox analysis and independent analysis illustrated that the seven-lncRNAs prediction model was an isolated factor by comparing it with other clinical variables. We validated the accuracy of our model in the testing dataset. Furthermore, the prognostic model also showed higher predictive efficiency than three other published prognostic models. The two different survival groups represented diverse immune features according to principal components analysis. GSEA analysis (gene set enrichment analysis) indicated that seven-lncRNAs signatures may be involved in the progression of tumorigenesis. Conclusions We have established a seven immune-related lncRNAs prediction model. This prognostic model had significant clinical significance that increased the predicted value and guided the personalized treatment for LUAD patients.

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“…Furthermore, altered lncRNAs expression has been widely discovered in various cancers and have been used as novel biomarkers for cancer diagnosis and prognosis (Prensner and Chinnaiyan, 2011;Qiu et al, 2013;Zhou et al, 2018a;Bao et al, 2019;Sun et al, 2020). Increasing evidence indicated that lncRNA is emerging a key regulator of TLR signaling and innate immunity (Murphy and Medvedev, 2016;Zhang et al, 2020;Zhou et al, 2020), altered lncRNAs expression mediated via control of TLR signaling have been implicated in ESCA (Tang et al, 2015). However, a comprehensive analysis of lncRNAs changes induced by TLRs and their roles in diagnosis and prognosis in ESCA is lacking.…”

Section: Introductionmentioning

confidence: 99%

Identification of a TLR-Induced Four-lncRNA Signature as a Novel Prognostic Biomarker in Esophageal Carcinoma

Liu

Chu

et al. 2020

Front. Cell Dev. Biol.

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Long non-coding RNAs (lncRNAs) have emerged as key regulators of Toll-like receptor (TLR) signaling to control innate immunity, and this regulatory mechanism has recently been implicated in esophageal carcinoma (ESCA). However, a comprehensive analysis of TLR-induced lncRNAs and their roles in diagnosis and prognosis in ESCA is still lacking. In this study, we first investigated the precise relationship between lncRNA perturbations and alteration of TLR signaling by constructing the lncRNA-TLRs coexpression network involved in ESCA, and identified 357 TLR-related lncRNAs. Of them, four TLR-related lncRNAs (AP000696.1, LINC00689, LINC00900, and AP000487.1) are significantly associated with the overall survival (OS) of ESCA patients, and utilizing this four-lncRNA signature is capable of stratifying patients into high-risk and low-risk groups with significantly different OS in the discovery set. Further analysis in different independent patient sets also confirmed the robustness of the prognostic value of the four-TLR-lncRNA signature in predicting the OS of ESCA patients. Moreover, the results of multivariate analysis in different patient sets indicated that the four-TLR-lncRNA signature is an independent factor after adjusted by other clinical factors. Thus, we have identified a TLR-induced four-lncRNA signature, which represents a promising prognosis biomarker for ESCA, and our study might provide new candidate targets for therapeutic intervention via targeting TLR-induced lncRNAs in ESCA patients.

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Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer

Cited by 137 publications

References 58 publications

A Novel Signature of 23 Immunity-Related Gene Pairs Is Prognostic of Cutaneous Melanoma

A Novel Signature of 23 Immunity-Related Gene Pairs Is Prognostic of Cutaneous Melanoma

A Seven Immune-Related lncRNAs Model to Increase the Predicted Value of Lung Adenocarcinoma

Identification of a TLR-Induced Four-lncRNA Signature as a Novel Prognostic Biomarker in Esophageal Carcinoma

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