AIM: To evaluate the association of known copy number variations (CNVs) in ulcerative colitis (UC) progressing to colorectal cancer.

METHODS: Microsatellite instability analysis using the National Cancer Institute’s panel of markers, and CNV association studies using Agilent 2 × 105 k arrays were done in tissue samples from four patient groups with UC: those at low risk (LR) or high risk of developing colorectal cancer, those with premalignant dysplastic lesions, and those with colitis-associated colorectal cancer (CAC). DNA from tissue samples of these groups were independently hybridized on arrays and analyzed. The data obtained were further subjected to downstream bioinformatics enrichment analysis to examine the correlation with CAC progression.

RESULTS: Microarray analysis highlighted a progressive increase in the total number of CNVs [LR (n = 178) vs CAC (n = 958), 5.3-fold], gains and losses [LR (n = 37 and 141) vs CAC (n = 495 and 463), 13.4- and 3.3-fold, respectively], size [LR (964.2 kb) vs CAC (10540 kb), 10.9-fold] and the number of genes in such regions [LR (n = 119) vs CAC (n = 455), 3.8-fold]. Chromosome-wise analysis of CNVs also showed an increase in the number of CNVs across each chromosome. There were 38 genes common to all four groups in the study; 13 of these were common to cancer genes from the Genetic Disease Association dataset. The gene set enrichment analysis and ontology analysis highlighted many cancer-associated genes. All the samples in the different groups were microsatellite stable.

CONCLUSION: Increasing numbers of CNVs are associated with the progression of UC to CAC, and warrant further detailed exploration.

Longstanding ulcerative colitis (UC) confers an increased risk of colorectal cancer (CRC)[1-6]. The frequency of colitis-associated colorectal cancer (CAC) in the Asia-Pacific region has been variously reported to be similar to or lower than that reported from the West, mostly based on retrospective studies[6-12]. Recent data from this low prevalence region suggest that premalignant lesions may not be uncommon in patients with longstanding UC, if dysplasia is methodically looked for[13].

The inflammation-dysplasia-carcinoma sequence defines carcinogenesis in UC and is accompanied by a series of molecular changes[14]. The major molecular pathways in the development of CRC involve chromosomal instability (CIN) and microsatellite instability (MSI), which are associated with an increase in the range of gene expression and phenotypic changes[15,16]. Studies have found that around 80% of the tumors with MSI have a near-diploid karyotype and a distinct genetic alteration distinguishable from those of microsatellite stable cancers[17].

Copy number variations (CNVs), a source of genetic diversity in humans under CIN and affecting gene dosage, are also believed to play a major role in human health and disease. CNVs can lead to altered expression of genes thereby contributing to cancer development. Profiling these can help in identifying tumor suppressor genes and oncogenes[18]. In the past decade, studies have established that even though common CNVs with low penetrance levels contribute only minimally or modestly to the causation of cancer, their collective impact on the predisposition to cancer must be considered while estimating the cancer risk[19]. CNVs constitute important genetic changes in various cancers including sporadic CRC, but their association with neoplasia in UC is not well described[20-23].

Copy number alterations detected by array-based Comparative Genomic Hybridization (aCGH) can be directly related to discovery of the underlying genes and/or molecular mechanisms involved with tumorigenesis, especially so with high or moderate penetrant CNVs[24,25]. Such discovery of altered regions associated with cancer may help in classifying the cancer patient at the molecular level along with the clinico-pathological features. With this background, the present study was aimed at elucidating the CNVs associated with the pathogenesis of CAC, a complex disease.

The major aim of this study was to analyze the comprehensive association of known CNVs during various stages of UC progressing to CRC and thereby to understand the role of CNVs in inflammation-associated cancer development. The study, one of the first of its kind using 2 × 105 k CNV association arrays on DNA extracted from tissue samples has shown a progressive involvement of CNVs at different levels as the disease progresses from UC to CAC. Increasing numbers of CNVs were found to be associated with the progression of the disease from earlier stages to cancer. Other factors such as the size of CNVs and number of genes from these CNV regions were similarly found to be correlated with neoplastic progression. Bioinformatics enrichment analysis of CNV genes also enumerated putative functionally important cancer-associated genes. Hence, the study highlights the importance of classifying UC patients into subgroups at various stages of progression using clinical details in the evaluation of molecular patho-mechanisms involved in CAC.

The 2 × 105 k array has been successfully used in large sample-based studies for CNV association in common diseases[28]. A population-specific array (2 × 105 k CNV association array) with a target of analyzing the association of CNVs has shown promising results albeit with a limited number of inflammation-related and cancer-coordinating genes in the study. Being a tissue based study, the cells, and the CNVs therein being heterogeneous because of the pooling of the samples, could probably have affected the assessment of CNVs[29]. In this aspect, our results from tissue DNA samples have identified the CNV regions and the important genes situated in them that are associated with various stages of progression of UC to CAC. Unlike the present report, earlier studies on colitis-associated neoplasia used conventional methods (chromosomal genomic hybridization or bacterial artificial chromosome arrays) and were limited to only one stage of progression[21-23].

In another important observation, the genes encompassing these CNV regions matched with the cancer gene sets from various databases such as GAD or GSEA, and highlight the importance of these CNVs in carcinogenesis. Genes from amplified or gain CNV regions may act as oncogenes while the loss regions are likely to be embedded with tumor suppressor regions[18]. Gene ontology analysis further highlighted the significant number of genes involved in various molecular and biological functions from these CNV regions, increasing as the disease progressed to CAC. Thus, our data can also be used in future research to determine their definitive contribution to colorectal carcinogenesis, upon functional validation of genes from these CNV regions.

MSI is believed to play a role in the pathways of UC-associated and sporadic CRCs, contributing at a frequency of approximately 15%-20% compared to 80% CIN in the case of CRC[14]. The present study using the NCI panel of Bethesda markers found no instability in any of the samples. One reason for this difference could be the use of a cancer-specific panel and recruiting only 2 patients with CAC in the study[26]. Reports suggest that CIN is greater in microsatellite stable samples[17,30].

The study of CNVs and cancer is in its infancy, but recent advancements in and the availability of technology is ensuring that more studies are being reported in this area. There is tremendous scope for further studies considering the effect of this form of genetic variation on cancer predisposition and the association with cancer genes. To our knowledge, this is the only study available till now on the association of CNVs with UC stratified into different stages of evolution to CAC. In a first study of its kind, using the association arrays of higher resolution on tissue samples we have demonstrated the progressive changes in CNVs as UC advances to cancer, establishing the importance of such genomic alterations in the pathogenesis of CAC. These results clearly indicate a major role for CNVs in the pathogenesis of CAC, warranting further focused studies on the regions and genes identified.

The authors thank Agilent Corp (India) for their generosity in providing 2 × 105 k CNV association arrays.