LINC00892 Is an lncRNA Induced by T Cell Activation and Expressed by Follicular Lymphoma-Resident T Helper Cells

Iaccarino, Ingram; Mourtada, Fatme; Reinke, Sarah; Patil, Paurnima; Doose, Gero; Monaco, Gianni; Hoffmann, Steve; Siebert, Reiner; Klapper, Wolfram

doi:10.3390/ncrna8030040

Cited by 6 publications

(3 citation statements)

References 45 publications

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“…The results showed that compared to IOSE80 cells, exosomes from SKOV3 and OVCAR8 cells had higher expression of AC134312.1, AC010834.3, LEMD1.AS1, PCOLCE.AS1, LINC00892, and AL138820.1. Research has shown that high expression of lncRNA is associated with the proliferation of ovarian cancer cells, activation of the PI3K-AKT pathway, T cell activation, and immune infiltration in the tumor microenvironment (63)(64)(65)(66). However, this trend was not observed in OC tissues from the TCGA datasets except LINC00892.…”

Section: Discussionmentioning

confidence: 96%

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

Cui,

Zhang,

et al. 2024

Front. Immunol.

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BackgroundOvarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust.Methods420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed.Results64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes.ConclusionOur study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.

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Section: Discussionmentioning

confidence: 96%

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

Cui,

Zhang,

et al. 2024

Front. Immunol.

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“…In particular, CD4 + effector memory subtypes exhibit the highest expression of LINC00892. This enables LINC00892 to be a potential biomarker for activated T cells [60]. LINC01352 is notably downregulated in hepatitis B virus (HBV)/HBV X protein (HBx)-positive liver cancer cells and tissues.…”

Section: Discussionmentioning

confidence: 99%

Identification of lncRNAs associated with T cells as potential biomarkers and therapeutic targets in lung adenocarcinoma

SUN,

TAN,

et al. 2023

Oncology Research

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Lung adenocarcinoma (LUAD) is the most common and deadliest subtype of lung cancer. To select more targeted and effective treatments for individuals, further advances in classifying LUAD are urgently needed. The number, type, and function of T cells in the tumor microenvironment (TME) determine the progression and treatment response of LUAD. Long noncoding RNAs (lncRNAs), may regulate T cell differentiation, development, and activation. Thus, our aim was to identify T cell-related lncRNAs (T cell-Lncs) in LUAD and to investigate whether T cell-Lncs could serve as potential stratifiers and therapeutic targets. Seven T cell-Lncs were identified to further establish the T cell-related lncRNA risk score (TRS) in LUAD. Low TRS individuals were characterized by robust immune status, fewer genomic alterations, and remarkably longer survival than high TRS individuals. The excellent accuracy of TRS in predicting overall survival (OS) was validated in the TCGA-LUAD training cohort and the GEO-LUAD validation cohort. Our data demonstrated the favorable predictive power of the TRS-based nomogram, which had important clinical significance in estimating the survival probability for individuals. In addition, individuals with low TRS could respond better to chemotherapy and immunotherapy than those with high TRS. LINC00525 was identified as a valuable study target, and the ability of LUAD to proliferate or invade was significantly attenuated by downregulation of LINC00525. In conclusion, the TRS established by T cell-Lncs could unambiguously classify LUAD patients, predict their prognosis and guide their management. Moreover, our identified T cell-Lncs could provide potential therapeutic targets for LUAD.

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“… 2018 ; Iaccarino et al. 2022 ). These ncRNAs can regulate gene expression through epigenetic modification, transcription and post-transcription, and participate in various biological processes such as cell differentiation, proliferation and apoptosis (Zhong et al.…”

Section: Introductionmentioning

confidence: 99%

Icariin restrains NLRP3 inflammasome-mediated Th2 immune responses and ameliorates atopic dermatitis through modulating a novel lncRNA MALAT1/miR-124-3p axis

Zhao,

Yu,

Meng

et al. 2023

Pharmaceutical Biology

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Context Atopic dermatitis (AD) is a common inflammatory skin disease characterized with hyperactivation of type 2 T helper (Th2) immune responses. Icariin is a flavonoid glucoside with anti-inflammatory activities, which has been used to treat multiple diseases. Objective The present study investigates the underlying mechanisms by which icariin regulates Th2 responses and AD development. Materials and methods BALB/c mice were induced by DNFB to establish AD models, and injected with or without 10 mg/kg icariin for 2 weeks (i.p., daily). CD4 + T cells were induced by Th2 condition to simulate AD in vitro , and also treated with or without 100 µM icariin. Results Icariin ameliorated AD-like skin lesion, manifested as a significant decrease in dermatitis scores (from 8.00 ± 1.00 to 3.67 ± 0.58), serum IgE levels (from 3119.15 ± 241.81 to 948.55 ± 182.51 ng/mL), epidermal thickness (from 93.86 ± 4.61 to 42.67 ± 2.48 µm) and infiltration of mast cells (from 60.67 ± 3.21 cells to 36.00 ± 2.65 cells). Also, icariin inactivated NLRP3 inflammasome, inhibited Th2 skewing, reduced lncRNA MALAT1 expression, but elevated miR-124-3p expression in vivo and in vitro . MALAT1 increased NLRP3 expression through targeting miR-124-3p. Knockdown of MALAT1 repressed NLRP3 inflammasome activation and mitigated Th1/Th2 imbalance in Th2-conditioned CD4 + T cells, whereas both MALAT1 overexpression and miR-124-3p inhibition ablated the inhibitory effects of icariin on Th2 immune responses. Discussion and conclusions The findings further improve our understanding of the mechanism by which icariin affects AD progression, and highlights the potential of icariin in the treatment of AD.

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LINC00892 Is an lncRNA Induced by T Cell Activation and Expressed by Follicular Lymphoma-Resident T Helper Cells

Cited by 6 publications

References 45 publications

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

Identification of lncRNAs associated with T cells as potential biomarkers and therapeutic targets in lung adenocarcinoma

Icariin restrains NLRP3 inflammasome-mediated Th2 immune responses and ameliorates atopic dermatitis through modulating a novel lncRNA MALAT1/miR-124-3p axis

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