Oligoclonal band status in Scandinavian multiple sclerosis patients is associated with specific genetic risk alleles.

The presence of oligoclonal bands (OCB) in cerebrospinal fluid (CSF) is a typical finding in multiple sclerosis (MS). We applied data from Norwegian, Swedish and Danish (i.e. Scandinavian) MS patients from a genome-wide association study (GWAS) to search for genetic differences in MS relating to OCB status. GWAS data was compared in 1367 OCB positive and 161 OCB negative Scandinavian MS patients, and nine of the most associated SNPs were genotyped for replication in 3403 Scandinavian MS patients. HLA-DRB1 genotypes were analyzed in a subset of the OCB positive (n = 2781) and OCB negative (n = 292) MS patients and compared to 890 healthy controls. Results from the genome-wide analyses showed that single nucleotide polymorphisms (SNPs) from the HLA complex and six other loci were associated to OCB status. In SNPs selected for replication, combined analyses showed genome-wide significant association for two SNPs in the HLA complex; rs3129871 (p = 5.7×10(-15)) and rs3817963 (p = 5.7×10(-10)) correlating with the HLA-DRB1*15 and the HLA-DRB1*04 alleles, respectively. We also found suggestive association to one SNP in the Calsyntenin-2 gene (p = 8.83×10(-7)). In HLA-DRB1 analyses HLA-DRB1*15∶01 was a stronger risk factor for OCB positive than OCB negative MS, whereas HLA-DRB1*04∶04 was associated with increased risk of OCB negative MS and reduced risk of OCB positive MS. Protective effects of HLA-DRB1*01∶01 and HLA-DRB1*07∶01 were detected in both groups. The groups were different with regard to age at onset (AAO), MS outcome measures and gender. This study confirms both shared and distinct genetic risk for MS subtypes in the Scandinavian population defined by OCB status and indicates different clinical characteristics between the groups. This suggests differences in disease mechanisms between OCB negative and OCB positive MS with implications for patient management, which need to be further studied.

Molecular diversity in ductal carcinoma in situ (DCIS) and early invasive breast cancer.

Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer where cells restricted to the ducts exhibit an atypical phenotype. Some DCIS lesions are believed to rapidly transit to invasive ductal carcinomas (IDCs), while others remain unchanged. Existing classification systems for DCIS fail to identify those lesions that transit to IDC. We studied gene expression patterns of 31 pure DCIS, 36 pure invasive cancers and 42 cases of mixed diagnosis (invasive cancer with an in situ component) using Agilent Whole Human Genome Oligo Microarrays 44k. Six normal breast tissue samples were also included as controls. qRT-PCR was used for validation. All DCIS and invasive samples could be classified into the "intrinsic" molecular subtypes defined for invasive breast cancer. Hierarchical clustering establishes that samples group by intrinsic subtype, and not by diagnosis. We observed heterogeneity in the transcriptomes among DCIS of high histological grade and identified a distinct subgroup containing seven of the 31 DCIS samples with gene expression characteristics more similar to advanced tumours. A set of genes independent of grade, ER-status and HER2-status was identified by logistic regression that univariately classified a sample as belonging to this distinct DCIS subgroup. qRT-PCR of single markers clearly separated this DCIS subgroup from the other DCIS, and contains samples from several histopathological and intrinsic molecular subtypes. The genes that differentiate between these two types of DCIS suggest several processes related to the re-organisation of the microenvironment. This raises interesting possibilities for identification of DCIS lesions both with and without invasive characteristics, which potentially could be used in clinical assessment of a woman's risk of progression, and lead to improved management that would avoid the current over- and under-treatment of patients.

Frequent aberrant DNA methylation of ABCB1, FOXC1, PPP2R2B and PTEN in ductal carcinoma in situ and early invasive breast cancer.

INTRODUCTION: Ductal carcinoma in situ (DCIS) is a non-invasive lesion of the breast that is frequently detected by mammography and subsequently removed by surgery. However, it is estimated that about half of the detected lesions would never have progressed into invasive cancer. Identifying DCIS and invasive cancer specific epigenetic lesions and understanding how these epigenetic changes are involved in triggering tumour progression is important for a better understanding of which lesions are at risk of becoming invasive. METHODS: Quantitative DNA methylation analysis of ABCB1, CDKN2A/p16INK4a, ESR1, FOXC1, GSTP1, IGF2, MGMT, MLH1, PPP2R2B, PTEN and RASSF1A was performed by pyrosequencing in a series of 27 pure DCIS, 28 small invasive ductal carcinomas (IDCs), 34 IDCs with a DCIS component and 5 normal breast tissue samples. FOXC1, ABCB1, PPP2R2B and PTEN were analyzed in 23 additional normal breast tissue samples. Real-Time PCR expression analysis was performed for FOXC1. RESULTS: Aberrant DNA methylation was observed in all three diagnosis groups for the following genes: ABCB1, FOXC1, GSTP1, MGMT, MLH1, PPP2R2B, PTEN and RASSF1A. For most of these genes, methylation was already present at the DCIS level with the same frequency as within IDCs. For FOXC1 significant differences in methylation levels were observed between normal breast tissue and invasive tumours (P < 0.001). The average DNA methylation levels were significantly higher in the pure IDCs and IDCs with DCIS compared to pure DCIS (P = 0.007 and P = 0.001, respectively). Real-time PCR analysis of FOXC1 expression from 25 DCIS, 23 IDCs and 28 normal tissue samples showed lower gene expression levels of FOXC1 in both methylated and unmethylated tumours compared to normal tissue (P < 0.001). DNA methylation levels of FOXC1, GSTP1, ABCB1 and RASSF1A were higher in oestrogen receptor (ER) positive vs. ER negative tumours; whereas methylation levels of FOXC1, ABCB1, PPP2R2B and PTEN were lower in tumours with a TP53 mutation. CONCLUSIONS: Quantitative methylation analysis identified ABCB1, FOXC1, PPP2R2B and PTEN as novel genes to be methylated in DCIS. In particular, FOXC1 showed a significant increase in the methylation frequency in invasive tumours. Low FOXC1 gene expression in both methylated and unmethylated DCIS and IDCs indicates that the loss of its expression is an early event during breast cancer progression.

Data integration from two microarray platforms identifies bi-allelic genetic inactivation of RIC8A in a breast cancer cell line.

BACKGROUND: Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. METHODS: We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. RESULTS: This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. qRT-PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P = 0.006). CONCLUSION: We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers.

Full sequencing of TP53 identifies identical mutations within in situ and invasive components in breast cancer suggesting clonal evolution.

In breast cancer, previous studies have suggested that somatic TP53 mutations are likely to be an early event. However, there are controversies regarding the cellular origin and linear course of breast cancer. The purpose of this study was to investigate tumor evolution in breast cancer by analyzing TP53 mutation status in tumors from various stages of the disease. The entire coding sequence of TP53 was sequenced in a cohort of pure ductal carcinoma in situ (DCIS), pure invasive cancer (≤15mm) and mixed lesions (i.e. invasive cancer with an in situ component). Of 118 tumor samples, 19 were found to harbor a TP53 mutation; 5 (15.6%) of the pure DCIS, 4 (10.5%) of the pure invasive cancers and 10 (20.8%) of the mixed lesions. In the mixed lesions, both the invasive and the DCIS components showed the same mutation in all 5 cases where the two components were successfully microdissected. Presence of the same mutation in both DCIS and invasive components from the same tumor indicates same cellular origin. The role of mutant TP53 in the progression of breast cancer is less clear and may vary between subtypes.

Evaluation of MetriGenix custom 4D arrays applied for detection of breast cancer subtypes.

BACKGROUND: Previously, a total of five breast cancer subtypes have been identified based on variation in gene expression patterns. These expression profiles were also shown to be associated with different prognostic value. In this study tumour samples from 27 breast cancer patients, previously subtyped by expression analysis using DNA microarrays, and four controls from normal breast tissue were included. A new MetriGenix 4D array proposed for diagnostic use was evaluated. METHODS: We applied MetriGenix custom 4D arrays for the detection of previously defined molecular subtypes of breast cancer. MetriGenix 4D arrays have special features including probe immobilization in microchannels with chemiluminescence detection that enable shorter hybridization time. RESULTS: The MetriGenix 4D array platform was evaluated with respect to both the accuracy in classifying the samples as well as the performance of the system itself. In a cross validation analysis using "Nearest Shrunken Centroid classifier" and the PAM software, 77% of the samples were classified correctly according to earlier classification results. CONCLUSION: The system shows potential for fast screening; however, improvements are needed.

NMD microarray analysis for rapid genome-wide screen of mutated genes in cancer.

Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD) inhibition and microarray analysis (NMD microarrays) in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization) in order to identify inactivation of tumor suppressor genes in cancer. Such a "mutatomics" screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.