Abstract
Background: Advances in sequencing technologies have greatly improved our understanding of long noncoding RNA (lncRNA). These transcripts with lengths of >200 nucleotides may play significant regulatory roles in various biological processes. Importantly, the dysregulation of better characterized lncRNAs has been associated with multiple types of cancers, including hepatocellular carcinoma (HCC). There are many studies on altered lncRNA expression levels, very few, however, have focused on their subcellular localizations, from which accumulating evidences have indicated their close relationships to lncRNA functions. A transcriptome-wide investigation of the subcellular distributions of lncRNAs might thus provide new insights into their roles and functions in cancers. Results: In this study, we subjected eight patient-derived HCC cell lines to subcellular fractionation and independently sequenced RNAs from the nuclear and cytoplasmic compartments. With the integration of tumor and tumor-adjacent RNA-seq datasets of liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas (TCGA), de novo transcriptome assembly and differential expression analysis were conducted successively and identified 26 nuclear-enriched HCC-associated lncRNAs shared between the HCC samples and the TCGA datasets, including the reported cancer driver PXN-AS1. The majority of nuclear-enriched HCC-associated lncRNAs were associated with the survival outcomes of HCC patients, exhibited characteristics similar to those of many experimentally supported HCC prognostic lncRNAs, and were co-expressed with protein-coding genes that have been linked to disease progression in various cancer types. Conclusion: We adopted a fractionation-then-sequencing approach on multiple patient-derived HCC samples and identified nuclear-enriched, HCC-associated lncRNAs that could serve as important targets for HCC diagnosis and therapeutic development. This approach could be widely applicable to other studies into the disease etiologies of lncRNA.
Highlights
Notorious for a rapid progression, poor prognosis, and limited therapeutic options, hepatocellular carcinoma (HCC) is among the most prevalent types of cancer and causes of cancer-related deaths worldwide
The resolution of RNAseq data from The Cancer Genome Atlas (TCGA) is not sufficient to decode clear strands for assembled transcripts because of a lack of strand information. We overcame this limitation by integrating a set of strandspecific RNA-seq data from in-house HCC cell lines into our pipeline
A total of 216 unique transcriptome assemblies were produced from 108 datasets (8 from in-house HCC cell lines, 100 from 50 pairs of TCGA-LIHC tumor/tumor-adjacent samples)
Summary
Notorious for a rapid progression, poor prognosis, and limited therapeutic options, hepatocellular carcinoma (HCC) is among the most prevalent types of cancer and causes of cancer-related deaths worldwide. The MiTranscriptome study, which curated thousands of TCGA (The Cancer Genome Atlas) RNA-seq datasets, suggested that the cancer lncRNA transcriptome may be considerably more complex and diverse than the normal transcriptome and that a significant fraction of the lncRNAs expressed by tumor cells might not yet be annotated (Iyer et al, 2015) These findings provide strong motivations for the systematic identification of new HCC-associated lncRNAs through a de novo transcriptome assembly of public RNA-seq datasets, as well as additional RNAseq datasets from in-house samples. Advances in sequencing technologies have greatly improved our understanding of long noncoding RNA (lncRNA) These transcripts with lengths of >200 nucleotides may play significant regulatory roles in various biological processes. A transcriptome-wide investigation of the subcellular distributions of lncRNAs might provide new insights into their roles and functions in cancers
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