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LncRNA PANTR1 is Associated with Poor Prognostic and Suppresses Apoptosis in Glioma.

ABSTRACT: Glioma is the most common tumor in the central nervous system. High-grade gliomas confer a poor prognosis, being a serious health and economic burden. Current literature suggests the important role of long noncoding RNA (lncRNA) in mammals, especially in tumorigenesis of various tumors. The functions of lncRNA POU3F3 adjacent noncoding transcript 1 (PANTR1) have been investigated in hepatocellular carcinoma but remain yet unclear in gliomas. We evaluated the role of PANTR1 in glioma cells using published data from The Cancer Genome Atlas (TCGA), then validated it by ex vivo experiments. To investigate the potential cellular mechanism of different levels of PANTR1 expression in glioma cells, we used siRNA-mediated knockdown in low-grade (grade II) cell lines and GBM (grade IV) cell lines (SW1088 and SHG44, respectively). On the molecular level, low expression of PANTR1 caused significantly reduced glioma cell viability and enhanced cell death. Moreover, we identified the importance of PANTR1 expression for cell migration in both cell lines, a critical foundation for invasiveness in recurrent gliomas. In conclusion, this study provides the first evidence that PANTR1 has a relevant role in human glioma by influencing cell viability and cell death.

SUBMITTER: Shi F

PROVIDER: S-EPMC9970703 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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LncRNA PANTR1 is Associated with Poor Prognostic and Suppresses Apoptosis in Glioma.

Shi Fei F Hu Jie J Zheng Ping P Lv Yisong Y Liu Hongyu H Zhang Guiyun G Jiang Hongyu H

Journal of oncology 20230220

Glioma is the most common tumor in the central nervous system. High-grade gliomas confer a poor prognosis, being a serious health and economic burden. Current literature suggests the important role of long noncoding RNA (lncRNA) in mammals, especially in tumorigenesis of various tumors. The functions of lncRNA POU3F3 adjacent noncoding transcript 1 (PANTR1) have been investigated in hepatocellular carcinoma but remain yet unclear in gliomas. We evaluated the role of PANTR1 in glioma cells using ...[more]

PMID: 36861062

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Project description:BackgroundGlioma is one of the deadliest malignant brain tumors in adults, which is highly invasive and has a poor prognosis, and long non-coding RNAs (lncRNAs) have key roles in the progression of glioma. Amino acid metabolism reprogramming is an emerging hallmark in cancer. However, the diverse amino acid metabolism programs and prognostic value remain unclear during glioma progression. Thus, we aim to find potential amino-related prognostic glioma hub genes, elaborate and verify their functions, and explore further their impact on glioma.MethodsGlioblastoma (GBM) and low-grade glioma (LGG) patients' data were downloaded from TCGA and CCGA datasets. LncRNAs associated with amino acid metabolism were discriminated against via correlation analysis. LASSO analysis and Cox regression analysis were conducted to identify lncRNAs related to prognosis. GSVA and GSEA were performed to predict the potential biological functions of lncRNA. Somatic mutation data and CNV data were further built to demonstrate genomic alterations and the correlation between risk scores. Human glioma cell lines U251 and U87-MG were used for further validation in vitro experiments.ResultsThere were eight amino-related lncRNAs in total with a high prognostic value that were identified via Cox regression and LASSO regression analyses. The high risk-score group presented a significantly poorer prognosis compared with the low risk-score group, with more clinicopathological features and characteristic genomic aberrations. Our results provided new insights into biological functions in the above signature lncRNAs, which participate in the amino acid metabolism of glioma. LINC01561 is one of the eight identified lncRNAs, which was adopted for further verification. In in vitro experiments, siRNA-mediated LINC01561 silencing suppresses glioma cells' viability, migration, and proliferation.ConclusionNovel amino-related lncRNAs associated with the survival of glioma patients were identified, and a lncRNA signature can predict glioma prognosis and therapy response, which possibly has vital roles in glioma. Meanwhile, it emphasized the importance of amino acid metabolism in glioma, particularly in providing deeper research at the molecular level.

Project description:Background: Glioma has the highest fatality rate among intracranial tumours. Besides, the heterogeneity of gliomas leads to different therapeutic effects even with the same treatment. Developing a new signature for glioma to achieve the concept of "personalised medicine" remains a significant challenge. Method: The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were searched to acquire information on glioma patients. Initially, correlation and univariate Cox regression analyses were performed to screen for prognostic pyroptosis-related long noncoding RNAs (PRLs). Secondly, 11 PRLs were selected to construct the classifier using certain algorithms. The efficacy of the classifier was then detected by the "timeROC" package for both the training and validation datasets. CIBERSORT and ESTIMATE packages were applied for comparing the differences (variations) in the immune landscape between the high- and low-risk groups. Finally, the therapeutic efficacy of the chemotherapy, radiotherapy, and immunotherapy were assessed using the "oncoPredict" package, survival analysis, and the tumour immune dysfunction and exclusion (TIDE) score, respectively. Results: A classifier comprising 11 PRLs was constructed. The PRL classifier exhibits a more robust prediction capacity for the survival outcomes in patients with gliomas than the clinical characteristics irrespective of the dataset (training or validation dataset). Moreover, it was found that the tumour landscape between the low- and high-risk groups was significantly different. A high-risk score was linked to a more immunosuppressive tumour microenvironment. According to the outcome prediction and analysis of the chemotherapy, patients with different scores showed different responses to various chemotherapeutic drugs and immunotherapy. Meanwhile, the patient with glioma of WHO grade Ⅳ or aged >50 years in the high risk group had better survival following radiotherapy. Conclusion: We constructed a PRL classifier to roughly predict the outcome of patients with gliomas. Furthermore, the PRL classifier was linked to the immune landscape of glioma and may guide clinical treatments.

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Dataset Information

LncRNA PANTR1 is Associated with Poor Prognostic and Suppresses Apoptosis in Glioma.

Publications

LncRNA PANTR1 is Associated with Poor Prognostic and Suppresses Apoptosis in Glioma.

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