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      Transcriptome-Wide Detection of Differentially Expressed Coding and Non-Coding Transcripts and Their Clinical Significance in Prostate Cancer

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          Abstract

          Prostate cancer is a clinically and biologically heterogeneous disease. Deregulation of splice variants has been shown to contribute significantly to this complexity. High-throughput technologies such as oligonucleotide microarrays allow for the detection of transcripts that play a role in disease progression in a transcriptome-wide level. In this study, we use a publicly available dataset of normal adjacent, primary tumor, and metastatic prostate cancer samples (GSE21034) to detect differentially expressed coding and non-coding transcripts between these disease states. To achieve this, we focus on transcript-specific probe selection regions, that is, those probe sets that correspond unambiguously to a single transcript. Based on this, we are able to pinpoint at the transcript-specific level transcripts that are differentially expressed throughout prostate cancer progression. We confirm previously reported cases and find novel transcripts for which no prior implication in prostate cancer progression has been made. Furthermore, we show that transcript-specific differential expression has unique prognostic potential and provides a clinically significant source of biomarker signatures for prostate cancer risk stratification. The results presented here serve as a catalog of differentially expressed transcript-specific markers throughout prostate cancer progression that can be used as basis for further development and translation into the clinic.

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          Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy.

          The incidence of prostate cancer is frequent, occurring in almost one-third of men older than 45 years. Only a fraction of the cases reach the stages displaying clinical significance. Despite the advances in our understanding of prostate carcinogenesis and disease progression, our knowledge of this disease is still fragmented. Identification of the genes and patterns of gene expression will provide a more cohesive picture of prostate cancer biology. In this study, we performed a comprehensive gene expression analysis on 152 human samples including prostate cancer tissues, prostate tissues adjacent to tumor, and organ donor prostate tissues, obtained from men of various ages, using the Affymetrix (Santa Clara, CA) U95a, U95b, and U95c chip sets (37,777 genes and expression sequence tags). Our results confirm an alteration of gene expression in prostate cancer when comparing with nontumor adjacent prostate tissues. However, our study also indicates that the gene expression pattern in tissues adjacent to cancer is so substantially altered that it resembles a cancer field effect. We also found that gene expression patterns can be used to predict the aggressiveness of prostate cancer using a novel model.
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            The majority of total nuclear-encoded non-ribosomal RNA in a human cell is 'dark matter' un-annotated RNA

            Background Discovery that the transcriptional output of the human genome is far more complex than predicted by the current set of protein-coding annotations and that most RNAs produced do not appear to encode proteins has transformed our understanding of genome complexity and suggests new paradigms of genome regulation. However, the fraction of all cellular RNA whose function we do not understand and the fraction of the genome that is utilized to produce that RNA remain controversial. This is not simply a bookkeeping issue because the degree to which this un-annotated transcription is present has important implications with respect to its biologic function and to the general architecture of genome regulation. For example, efforts to elucidate how non-coding RNAs (ncRNAs) regulate genome function will be compromised if that class of RNAs is dismissed as simply 'transcriptional noise'. Results We show that the relative mass of RNA whose function and/or structure we do not understand (the so called 'dark matter' RNAs), as a proportion of all non-ribosomal, non-mitochondrial human RNA (mt-RNA), can be greater than that of protein-encoding transcripts. This observation is obscured in studies that focus only on polyA-selected RNA, a method that enriches for protein coding RNAs and at the same time discards the vast majority of RNA prior to analysis. We further show the presence of a large number of very long, abundantly-transcribed regions (100's of kb) in intergenic space and further show that expression of these regions is associated with neoplastic transformation. These overlap some regions found previously in normal human embryonic tissues and raises an interesting hypothesis as to the function of these ncRNAs in both early development and neoplastic transformation. Conclusions We conclude that 'dark matter' RNA can constitute the majority of non-ribosomal, non-mitochondrial-RNA and a significant fraction arises from numerous very long, intergenic transcribed regions that could be involved in neoplastic transformation.
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              Alternative splicing in colon, bladder, and prostate cancer identified by exon array analysis.

              Alternative splicing enhances proteome diversity and modulates cancer-associated proteins. To identify tissue- and tumor-specific alternative splicing, we used the GeneChip Human Exon 1.0 ST Array to measure whole-genome exon expression in 102 normal and cancer tissue samples of different stages from colon, urinary bladder, and prostate. We identified 2069 candidate alternative splicing events between normal tissue samples from colon, bladder, and prostate and selected 15 splicing events for RT-PCR validation, 10 of which were successfully validated by RT-PCR and sequencing. Furthermore 23, 19, and 18 candidate tumor-specific splicing alterations in colon, bladder, and prostate, respectively, were selected for RT-PCR validation on an independent set of 81 normal and tumor tissue samples. In total, seven genes with tumor-specific splice variants were identified (ACTN1, CALD1, COL6A3, LRRFIP2, PIK4CB, TPM1, and VCL). The validated tumor-specific splicing alterations were highly consistent, enabling clear separation of normal and cancer samples and in some cases even of different tumor stages. A subset of the tumor-specific splicing alterations (ACTN1, CALD1, and VCL) was found in all three organs and may represent general cancer-related splicing events. In silico protein predictions suggest that the identified cancer-specific splice variants encode proteins with potentially altered functions, indicating that they may be involved in pathogenesis and hence represent novel therapeutic targets. In conclusion, we identified and validated alternative splicing between normal tissue samples from colon, bladder, and prostate in addition to cancer-specific splicing events in colon, bladder, and prostate cancer that may have diagnostic and prognostic implications.
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                Author and article information

                Journal
                J Oncol
                J Oncol
                JO
                Journal of Oncology
                Hindawi Publishing Corporation
                1687-8450
                1687-8469
                2012
                16 August 2012
                : 2012
                : 541353
                Affiliations
                Department of Research and Development, GenomeDx Biosciences Inc., Vancouver, BC, Canada V6J 1J8
                Author notes
                *Elai Davicioni: elai@ 123456genomedx.com

                Academic Editor: Anirban P. Mitra

                Article
                10.1155/2012/541353
                3431106
                22956952
                99bbe6fb-d5cf-4d12-9603-af309995bab5
                Copyright © 2012 Nicholas Erho et al.

                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
                : 1 June 2012
                : 30 June 2012
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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