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Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

ABSTRACT: BACKGROUND: Colorectal cancer (CRC) is a heterogeneous disease that, on the molecular level, can be characterized by inherent genomic instabilities; chromosome instability and microsatellite instability. In the present study we analyze genome-wide disruption of pre-mRNA splicing, and propose transcriptome instability as a characteristic that is analogous to genomic instability on the transcriptome level. METHODS: Exon microarray profiles from two independent series including a total of 160 CRCs were investigated for their relative amounts of exon usage differences. Each exon in each sample was assigned an alternative splicing score calculated by the FIRMA algorithm. Amounts of deviating exon usage per sample were derived from exons with extreme splicing scores. RESULTS: There was great heterogeneity within both series in terms of sample-wise amounts of deviating exon usage. This was strongly associated with the expression levels of approximately half of 280 splicing factors (54% and 48% of splicing factors were significantly correlated to deviating exon usage amounts in the two series). Samples with high or low amounts of deviating exon usage, associated with overall transcriptome instability, were almost completely separated into their respective groups by hierarchical clustering analysis of splicing factor expression levels in both sample series. Samples showing a preferential tendency towards deviating exon skipping or inclusion were associated with skewed transcriptome instability. There were significant associations between transcriptome instability and reduced patient survival in both sample series. In the test series, patients with skewed transcriptome instability showed the strongest prognostic association (P = 0.001), while a combination of the two characteristics showed the strongest association with poor survival in the validation series (P = 0.03). CONCLUSIONS: We have described transcriptome instability as a characteristic of CRC. This transcriptome instability has associations with splicing factor expression levels and poor patient survival.

SUBMITTER: Sveen A

PROVIDER: S-EPMC3219073 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

Sveen Anita A Agesen Trude H TH Nesbakken Arild A Rognum Torleiv O TO Lothe Ragnhild A RA Skotheim Rolf I RI

Genome medicine 20110527 5

<h4>Background</h4>Colorectal cancer (CRC) is a heterogeneous disease that, on the molecular level, can be characterized by inherent genomic instabilities; chromosome instability and microsatellite instability. In the present study we analyze genome-wide disruption of pre-mRNA splicing, and propose transcriptome instability as a characteristic that is analogous to genomic instability on the transcriptome level.<h4>Methods</h4>Exon microarray profiles from two independent series including a total ...[more]

PMID: 21619627

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Project description:DNA hypermethylation is a common epigenetic abnormality in colorectal cancers (CRCs) and a promising class of CRC screening biomarkers. We conducted a genome-wide search for novel neoplasia-specific hypermethylation events in the colon. We applied methylation microarray analysis to identify loci hypermethylated in 17 primary CRCs relative to eight non-neoplastic colonic mucosae (NCs) from neoplasia-free subjects. These CRC-associated hypermethylation events were then individually evaluated for their ability to discriminate neoplastic from non-neoplastic cases, based on real-time quantitative methylation-specific PCR (qMSP) assays in 113 colonic tissues: 51 CRCs, nine adenomas, 19 NCs from CRC patients (CRC-NCs), and 34 NCs from neoplasia-free subjects (control NCs). A strict microarray data filtering identified 169 candidate CRC-associated hypermethylation events. Fourteen of these 169 loci were evaluated using qMSP assays. Ten of these 14 methylation events significantly distinguished CRCs from age-matched control NCs (P<0.05 by receiver operator characteristic curve analysis); methylation of visual system homeobox 2 (VSX2) achieved the highest discriminative accuracy (83.3% sensitivity and 92.3% specificity, P<1×10(-6)), followed by BEN domain containing 4 (BEND4), neuronal pentraxin I (NPTX1), ALX homeobox 3 (ALX3), miR-34b, glucagon-like peptide 1 receptor (GLP1R), BTG4, homer homolog 2 (HOMER2), zinc finger protein 583 (ZNF583), and gap junction protein, gamma 1 (GJC1). Adenomas were significantly discriminated from control NCs by hypermethylation of VSX2, BEND4, NPTX1, miR-34b, GLP1R, and HOMER2 (P<0.05). CRC-NCs were significantly distinguished from control NCs by methylation of ALX3 (P<1×10(-4)). In conclusion, systematic methylome-wide analysis has identified ten novel methylation events in neoplastic and non-neoplastic colonic mucosae from CRC patients. These potential biomarkers significantly discriminate CRC patients from controls. Thus, they merit further evaluation in stool- and circulating DNA-based CRC detection studies.

Project description:Colorectal cancer is the second leading cause of cancer death worldwide, and the incidence of this disease is expected to increase as global socioeconomic changes occur. Immune checkpoint inhibition therapy is effective in treating a minority of colorectal cancer tumors; however, microsatellite stable tumors do not respond well to this treatment. Emerging cancer immunotherapeutic strategies aim to activate a cytotoxic T cell response against tumor-specific antigens, presented exclusively at the cell surface of cancer cells. These antigens are rare and are most effectively identified with a mass spectrometry-based approach, which allows the direct sampling and sequencing of these peptides. Although the few tumor-specific antigens identified to date are derived from coding regions of the genome, recent findings indicate that a large proportion of tumor-specific antigens originate from allegedly noncoding regions. Here, we employed a novel proteogenomic approach to identify tumor antigens in a collection of colorectal cancer-derived cell lines and biopsy samples consisting of matched tumor and normal adjacent tissue. The generation of personalized cancer databases paired with mass spectrometry analyses permitted the identification of more than 30,000 unique MHC I-associated peptides. We identified 19 tumor-specific antigens in both microsatellite stable and unstable tumors, over two-thirds of which were derived from noncoding regions. Many of these peptides were derived from source genes known to be involved in colorectal cancer progression, suggesting that antigens from these genes could have therapeutic potential in a wide range of tumors. These findings could benefit the development of T cell-based vaccines, in which T cells are primed against these antigens to target and eradicate tumors. Such a vaccine could be used in tandem with existing immune checkpoint inhibition therapies, to bridge the gap in treatment efficacy across subtypes of colorectal cancer with varying prognoses. Data are available via ProteomeXchange with identifier PXD028309.

Dataset Information

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

Publications

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

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