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Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray.

ABSTRACT: Colorectal cancer (CRC), which has high prevalence in Saudi Arabia and worldwide, needs better understanding by exploiting the latest available cytogenetic microarrays. We used biopsy tissue from consenting colorectal cancer patients to extract DNA and carry out microarray analysis using a CytoScan HD platform from Affymetrix. Patient specific comparisons of tumor-normal pairs were carried out. To find out the high probability key players, we performed Genomic Identification of Significant Targets in Cancer analysis and found 144 genes to form the list of driver genes. Of these, 24 genes attained high GISTIC scores and suggest being significantly associated with CRC. Loss of heterozygosity and uniparental disomy were found to affect 9 genes and suggest different mechanisms associated with CRC in every patient. Here we present the details of the methods used in carrying out the above analyses. Also, we provide some additional data on biomarker analysis that would complement the findings.

SUBMITTER: Aziz MA

PROVIDER: S-EPMC4535873 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray.

Aziz Mohammad Azhar MA Periyasamy Sathish S Yousef Zeyad Z Deeb Ahmad A AlOtaibi Majed M

Genomics data 20140313

Colorectal cancer (CRC), which has high prevalence in Saudi Arabia and worldwide, needs better understanding by exploiting the latest available cytogenetic microarrays. We used biopsy tissue from consenting colorectal cancer patients to extract DNA and carry out microarray analysis using a CytoScan HD platform from Affymetrix. Patient specific comparisons of tumor-normal pairs were carried out. To find out the high probability key players, we performed Genomic Identification of Significant Targe ...[more]

PMID: 26484062

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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: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.

Project description:Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity.We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results.Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes.Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

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Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray.

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Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray.

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