The long noncoding RNA MALAT1 predicts human pancreatic islet isolation quality

JCI Insight
Wilson Km WongAnandwardhan A Hardikar

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 pot...Continue Reading

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Citations

Jan 22, 2021·Diabetes·Aaron L GliebermanKevin Kit Parker
Mar 9, 2021·American Journal of Physiology. Endocrinology and Metabolism·Alex-Xianghua ZhouMagnus Althage

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Datasets Mentioned

BETA
GSE134068

Methods Mentioned

BETA
RNA-Seq
PCR
Assay
lncRNA-Seq

Software Mentioned

GraphPad
GraphPad Prism
house
TopHat
phyloCSF
Bowtie
scan
CPS
R glmnet
perl scripts

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