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Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis.

ABSTRACT: The use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens are restricted by the limited power of conventional reference-based protocols relying on unique and annotated transcripts. Here, we implemented a blind reference-free computational protocol, DE-kupl, to infer yet unreferenced RNA variations from total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into putative long noncoding (lnc)RNAs expressed in prostate cancer. Through filtering of 1,179 candidates, we defined 21 lncRNAs that were further validated by NanoString for robust tumor-specific expression in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling more than 90% of true-positive detections of cancer in an independent The Cancer Genome Atlas cohort. Remarkably, this clinical signature made of only nine unannotated lncRNAs largely outperformed PCA3, the only used prostate cancer lncRNA biomarker, in detection of high-risk tumors. This modular workflow is highly sensitive and can be applied to any pathology or clinical application.

SUBMITTER: Pinskaya M

PROVIDER: S-EPMC6858606 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis.

Pinskaya Marina M Saci Zohra Z Gallopin Mélina M Gabriel Marc M Nguyen Ha Tn HT Firlej Virginie V Descrimes Marc M Rapinat Audrey A Gentien David D Taille Alexandre de la A Londoño-Vallejo Arturo A Allory Yves Y Gautheret Daniel D Morillon Antonin A

Life science alliance 20191115 6

The use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens are restricted by the limited power of conventional reference-based protocols relying on unique and annotated transcripts. Here, we implemented a blind reference-free computational protocol, DE-kupl, to infer yet unreferenced RNA variations from total stranded RNA-sequencing datasets of tis ...[more]

PMID: 31732695

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Project description:BackgroundGene profiling of diffuse large B cell lymphoma (DLBCL) has revealed broad gene expression deregulation compared to normal B cells. While many studies have interrogated well known and annotated genes in DLBCL, none have yet performed a systematic analysis to uncover novel unannotated long non-coding RNAs (lncRNA) in DLBCL. In this study we sought to uncover these lncRNAs by examining RNA-seq data from primary DLBCL tumors and performed supporting analysis to identify potential role of these lncRNAs in DLBCL.MethodsWe performed a systematic analysis of novel lncRNAs from the poly-adenylated transcriptome of 116 primary DLBCL samples. RNA-seq data were processed using de novo transcript assembly pipeline to discover novel lncRNAs in DLBCL. Systematic functional, mutational, cross-species, and co-expression analyses using numerous bioinformatics tools and statistical analysis were performed to characterize these novel lncRNAs.ResultsWe identified 2,632 novel, multi-exonic lncRNAs expressed in more than one tumor, two-thirds of which are not expressed in normal B cells. Long read single molecule sequencing supports the splicing structure of many of these lncRNAs. More than one-third of novel lncRNAs are differentially expressed between the two major DLBCL subtypes, ABC and GCB. Novel lncRNAs are enriched at DLBCL super-enhancers, with a fraction of them conserved between human and dog lymphomas. We see transposable elements (TE) overlap in the exonic regions; particularly significant in the last exon of the novel lncRNAs suggest potential usage of cryptic TE polyadenylation signals. We identified highly co-expressed protein coding genes for at least 88 % of the novel lncRNAs. Functional enrichment analysis of co-expressed genes predicts a potential function for about half of novel lncRNAs. Finally, systematic structural analysis of candidate point mutations (SNVs) suggests that such mutations frequently stabilize lncRNA structures instead of destabilizing them.ConclusionsDiscovery of these 2,632 novel lncRNAs in DLBCL significantly expands the lymphoma transcriptome and our analysis identifies potential roles of these lncRNAs in lymphomagenesis and/or tumor maintenance. For further studies, these novel lncRNAs also provide an abundant source of new targets for antisense oligonucleotide pharmacology, including shared targets between human and dog lymphomas.

Dataset Information

Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis.

Publications

Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis.

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