Dataset Information

The long noncoding RNA MALAT1 predicts human pancreatic islet isolation quality.

ABSTRACT: Human islet isolation is a cost-/resource-intensive program generating islets for cell therapy in Type 1 diabetes. However, only a third of cadaveric pancreas get to clinical transplantation due to low quality/number of islets. There is a need to identify biomarker(s) that predict the quality of islets, prior to initiating their isolation. Here, we sequenced transcriptome from 18 human islet preparations stratified into three groups (Gr.1: Best quality/transplantable islets, Gr.2: Intermediary quality, Gr.3: Inferior quality/non-transplantable islets) based on routine measurements including islet purity/viability. Machine-learning algorithms involving penalized regression analyses identified 10 long-non-coding(lnc)RNAs significantly different across all group-wise comparisons (Gr1VsGr2, Gr2vsGr3, Gr1vsGr3). Two variants of Metastasis-Associated Lung Adenocarcinoma Transcript-1(MALAT1) lncRNA were common across all comparisons. We confirmed RNA-seq findings in a "validation set" of 75 human islet preparations. Finally, in 19 pancreas samples, we demonstrate that assessing the levels of MALAT1 variants alone (ROC curve AUC: 0.83) offers highest specificity in predicting post-isolation islet quality and improves the predictive potential for clinical islet transplantation when combined with Edmonton Donor Points/Body Mass Index(BMI)/North American Islet Donor Score(NAIDS). We present this resource of islet-quality-stratified lncRNA transcriptome data and identify MALAT1 as a biomarker that significantly enhances current selection methods for clinical (GMP)-grade islet isolation.

SUBMITTER: Wong WK

PROVIDER: S-EPMC6777802 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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The long noncoding RNA MALAT1 predicts human pancreatic islet isolation quality.

Wong Wilson Km WK Jiang Guozhi G Sørensen Anja E AE Chew Yi Vee YV Lee-Maynard Cody C Liuwantara David D Williams Lindy L O'Connell Philip J PJ Dalgaard Louise T LT Ma Ronald C RC Hawthorne Wayne J WJ Joglekar Mugdha V MV Hardikar Anandwardhan A AA

JCI insight 20190730

Human islet isolation is a cost-/resource-intensive program generating islets for cell therapy in Type 1 diabetes. However, only a third of cadaveric pancreas get to clinical transplantation due to low quality/number of islets. There is a need to identify biomarker(s) that predict the quality of islets, prior to initiating their isolation. Here, we sequenced transcriptome from 18 human islet preparations stratified into three groups (Gr.1: Best quality/transplantable islets, Gr.2: Intermediary q ...[more]

PMID: 31361602

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Project description:BackgroundMetastasis-associated lung adenocarcinoma transcript 1 (MALAT1) participates in the occurrence and development of cardiovascular and cerebrovascular diseases such as stroke and coronary heart disease by regulating inflammatory reactions, programmed cell death, and other pathological processes. Previous studies revealed that the MALAT1 gene polymorphism was associated with cardiac and cerebrovascular diseases. However, the prognostic role of the MALAT1 polymorphism in major adverse cardiac and cerebrovascular events (MACCEs) remains unknown. Therefore, this study intends to explore the association between the MALAT1 rs3200401 polymorphism and MACCEs.MethodWe enrolled 617 myocardial infarction (MI) patients and 1125 control participants who attended the First Affiliated Hospital of Xinjiang Medical University from January 2010 to 2018. SNPscan™ typing assays were used to detect the MALAT1 rs3200401 genotype. During the follow-up, MACCEs were recorded. Kaplan-Meier curves and univariate and multivariate Cox survival analyses were used to explore the correlation between MALAT1 gene polymorphisms and the occurrence of MACCEs.ResultsAmong the total participants and MI patients, the frequencies of the T allele (total Participants 19.5% vs. 15.3%, P = 0.047, MI patients 20.7% vs. 14.1%, P = 0.014) and CT + TT genotypes (total Participants 37.4% vs. 28.1%, P = 0.013, MI patients 39.5% vs. 25.8%, P = 0.003) were significantly higher in subjects with MACCEs than in subjects without MACCEs. However, in control participants, the frequencies of the T allele (16.6% vs. 16.0%, P = 0.860) and CT + TT genotypes (31.4% vs. 29.3%, P = 0.760) were not higher in subjects with MACCEs than in subjects without MACCEs. In addition, among the total participants and MI patients, the Kaplan-Meier curve analysis indicated that the subjects with rs3200401 CT + TT genotypes had a higher incidence of MACCEs than CC genotype carriers (P = 0.015, P = 0.001). Nevertheless, similar results were not observed in the control participants (P = 0.790). Multivariate Cox regression indicated that compared with patients with the CC genotype, patients with CT + TT genotypes had a 1.554-fold increase in MACCE risk (hazard ratio: 1.554, 95% confidence interval: 1.060-2.277, P = 0.024).ConclusionsThe MALAT1 rs3200401 CT + TT genotypes could be a risk factor for MACCEs in MI patients, suggesting that the MALAT1 gene may become a biomarker for poor prognosis in MI patients.

Project description:The study was designed to determine the role of long noncoding RNA (lncRNA), metastasis-associated lung adenocarcinoma transcript 1 (Malat1), in ischemic stroke outcome. Primary mouse brain microvascular endothelial cells (BMECs) were cultured and treated with Malat1 GapmeR before 16 h oxygen and glucose depravation (OGD). Cell death was assayed by LDH and MTT methods. Malat1 knock-out and wild-type mice were subjected to 1 h of middle cerebral artery occlusion (MCAO) and 24-72 h of reperfusion. To explore the underlying mechanism, apoptotic and inflammatory factors were measured by qPCR, ELISA, and Western blotting. The physical interaction between Malat1 and apoptotic or inflammatory factors was measured by RNA immunoprecipitation. Increased Malat1 levels were found in cultured mouse BMECs after OGD as well as in isolated cerebral microvessels in mice after MCAO. Silencing of Malat1 by Malat1 GapmeR significantly increased OGD-induced cell death and Caspase 3 activity in BMECs. Silencing of Malat1 also significantly aggravated OGD-induced expression of the proapoptotic factor Bim and proinflammatory cytokines MCP-1, IL-6, and E-selectin. Moreover, Malat1 KO mice presented larger brain infarct size, worsened neurological scores, and reduced sensorimotor functions. Consistent with in vitro findings, significantly increased expression of proapoptotic and proinflammatory factors was also found in the cerebral cortex of Malat1 KO mice after ischemic stroke compared with WT controls. Finally, we demonstrated that Malat1 binds to Bim and E-selectin both in vitro and in vivo Our study suggests that Malat1 plays critical protective roles in ischemic stroke.SIGNIFICANCE STATEMENT Accumulative studies have demonstrated the important regulatory roles of microRNAs in vascular and neural damage after ischemic stroke. However, the functional significance and mechanisms of other classes of noncoding RNAs in cerebrovascular pathophysiology after stroke are less studied. Here we demonstrate a novel role of Malat1, a long noncoding RNA that has been originally identified as a prognostic marker for non-small cell lung cancer, in cerebrovascular pathogenesis of ischemic stroke. Our experiments have provided the first evidence that Malat1 plays anti-apoptotic and anti-inflammatory roles in brain microvasculature to reduce ischemic cerebral vascular and parenchymal damages. Our studies also suggest that lncRNAs can be therapeutically targeted to minimize poststroke brain damage.

Project description:BackgroundThe aberrant regulation of MALAT1 has been indicated to be involved in various carcinogenic pathways contributing to the tumourigenesis and progression of cancers. The current meta-analysis summarized the research advances of MALAT1 functions and analyzed its prognostic value among multiple types of cancers.MethodsEligible studies were identified through retrieving the PubMed, Web of Science, and CNKI databases, up to Mar 1, 2018. 28 studies of 5436 patients and 36 studies of 3325 patients were enrolled in the meta-analysis to evaluate the association of MALAT1 expression with survival outcomes and clinical parameters.ResultsThe results demonstrated that over-expression of MALAT1 may predict lymph node metastasis (pooled OR = 2.335, 95% CI 1.606-3.395, P = 0.000) and distant metastasis (pooled OR = 2.456, 95% CI 1.407-4.286, P = 0.002). Moreover, MALAT1 was also related with tumour size (pooled OR = 1.875, 95% CI 1.257-2.795, P = 0.002) and TNM stage (pooled OR = 2.034, 95% CI 1.111-3.724, P = 0.021). Additionally, elevated MALAT1 expression could predict poor OS (pooled HR = 2.298, 95% CI 1.953-2.704, P = 0.000), DFS (pooled HR = 2.036, 95% CI 1.240-3.342, P = 0.005), RFS (pooled HR = 2.491, 95% CI 1.505-4.123, P = 0.000), DSS (pooled HR = 2.098, 95% CI 1.372-3.211, P = 0.001) and PFS (pooled HR = 1.842, 95% CI 1.138-2.983, P = 0.013) in multivariate model. Importantly, subgroup analyses disclosed that increased MALAT1 expression had a poor OS among different cancer types (Estrogen-dependent cancer: pooled HR = 2.656, 95% CI 1.560-4.523; urological cancer: pooled HR = 1.952, 95% CI 1.189-3.204; glioma: pooled HR = 2.315, 95% CI 1.643-3.263; digestive cancer: pooled HR = 2.451, 95% CI 1.862-3.227).ConclusionsThe present findings demonstrated that MALAT1 may be a novel biomarker for predicting survival outcome, lymph node metastasis and distant metastasis.

Dataset Information

The long noncoding RNA MALAT1 predicts human pancreatic islet isolation quality.

Publications

The long noncoding RNA MALAT1 predicts human pancreatic islet isolation quality.

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