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      Long Noncoding RNAs as Biomarkers in Cancer

      review-article
      Author(s): , , *
      Publication date (Electronic):
      Journal: Disease Markers
      Publisher: Hindawi

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          Abstract

          Long noncoding RNAs (lncRNAs) are a relatively well-characterized class of noncoding RNA (ncRNA) molecules, involved in the regulation of various cell processes, including transcription, intracellular trafficking, and chromosome remodeling. Their deregulation has been associated with the development and progression of various cancer types, the fact which makes them suitable as biomarkers for cancer diagnosis and prognosis. In recent years, detection of cancer-associated lncRNAs in body fluids of cancer patients has proven itself as an especially valuable method to effectively diagnose cancer. Cancer diagnosis and prognosis employing circulating lncRNAs are preferential when compared to classical biopsies of tumor tissues, especially due to their noninvasiveness, and have great potential for routine usage in clinical practice. Thus, this review focuses on summarizing the perspectives of lncRNAs as biomarkers in cancer, based on evaluating their expression profiles determined in body fluids of cancer patients.

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          RNA maps reveal new RNA classes and a possible function for pervasive transcription.

          Philipp Kapranov, Jill Cheng, Sujit Dike … (2007)
          Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the associations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides (nt) and whole-cell RNAs less than 200 nt were investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a novel role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome.
          Article 0 comments Cited 989 times – based on 0 reviews     Review now
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            A coding-independent function of gene and pseudogene mRNAs regulates tumour biology

            Laura Poliseno, Leonardo Salmena, JiangWen Zhang … (2010)
            The canonical role of messenger RNA (mRNA) is to deliver protein-coding information to sites of protein synthesis. However, given that microRNAs bind to RNAs, we hypothesized that RNAs possess a biological role in cancer cells that relies upon their ability to compete for microRNA binding and is independent of their protein-coding function. As a paradigm for the protein-coding-independent role of RNAs, we describe the functional relationship between the mRNAs produced by the PTEN tumour suppressor gene and its pseudogene (PTENP1) and the critical consequences of this interaction. We find that PTENP1 is biologically active as determined by its ability to regulate cellular levels of PTEN, and that it can exert a growth-suppressive role. We also show that PTENP1 locus is selectively lost in human cancer. We extend our analysis to other cancer-related genes that possess pseudogenes, such as oncogenic KRAS. Further, we demonstrate that the transcripts of protein coding genes such as PTEN are also biologically active. Together, these findings attribute a novel biological role to expressed pseudogenes, as they can regulate coding gene expression, and reveal a non-coding function for mRNAs.
            Article 0 comments Cited 978 times – based on 0 reviews     Review now
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              Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs.

              Y Takenaka, Rodrigo Nakamura, C Bult … (2002)
              Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.
              Article 0 comments Cited 499 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Dis Markers
                Journal ID (iso-abbrev): Dis. Markers
                Journal ID (publisher-id): DM
                Title: Disease Markers
                Publisher: Hindawi
                ISSN (Print): 0278-0240
                ISSN (Electronic): 1875-8630
                Publication date (Print): 2017
                Publication date (Electronic): 29 May 2017
                Volume: 2017
                Electronic Location Identifier: 7243968
                Affiliations
                Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
                Author notes

                Academic Editor: Wai K. Chu

                Author information
                http://orcid.org/0000-0002-3716-4215
                http://orcid.org/0000-0001-9912-3331
                Article
                DOI: 10.1155/2017/7243968
                PMC ID: 5467329
                PubMed ID: 28634418
                SO-VID: 7b8682c0-369c-4aa1-ad40-97aa928ac9e2
                Copyright © Copyright © 2017 Luka Bolha et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 3 March 2017
                Date accepted : 20 April 2017
                Categories
                Subject: Review Article

                Data availability:

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