A transcriptomic computational analysis of mastic oil-treated Lewis lung carcinomas reveals molecular mechanisms targeting tumor cell growth and survival

Background

DNA copy number alterations are frequently observed in ovarian cancer, but it remains a challenge to identify the most relevant alterations and the specific causal genes in those regions.

Methods

We obtained high-resolution 500K SNP array data for 52 ovarian tumors and identified the most statistically significant minimal genomic regions with the most prevalent and highest-level copy number alterations (recurrent CNAs). Within a region of recurrent CNA, comparison of expression levels in tumors with a given CNA to tumors lacking that CNA and to whole normal ovary samples was used to select genes with CNA-specific expression patterns. A public expression array data set of laser capture micro-dissected (LCM) non-malignant fallopian tube epithelia and LCM ovarian serous adenocarcinoma was used to evaluate the effect of cell-type mixture biases.

Results

Fourteen recurrent deletions were detected on chromosomes 4, 6, 9, 12, 13, 15, 16, 17, 18, 22 and most prevalently on X and 8. Copy number and expression data suggest several apoptosis mediators as candidate drivers of the 8p deletions. Sixteen recurrent gains were identified on chromosomes 1, 2, 3, 5, 8, 10, 12, 15, 17, 19, and 20, with the most prevalent gains localized to 8q and 3q. Within the 8q amplicon, PVT1, but not MYC, was strongly over-expressed relative to tumors lacking this CNA and showed over-expression relative to normal ovary. Likewise, the cell polarity regulators PRKCI and ECT2 were identified as putative drivers of two distinct amplicons on 3q. Co-occurrence analyses suggested potential synergistic or antagonistic relationships between recurrent CNAs. Genes within regions of recurrent CNA showed an enrichment of Cancer Census genes, particularly when filtered for CNA-specific expression.

Conclusion

These analyses provide detailed views of ovarian cancer genomic changes and highlight the benefits of using multiple reference sample types for the evaluation of CNA-specific expression changes.     

Assessment of RainDrop BS-seq as a method for large-scale,targeted bisulfite sequencing

We present a systematic assessment of RainDrop BS-seq, a novel method for large-scale, targeted bisulfite sequencing using microdroplet-based PCR amplification coupled with next-generation sequencing. We compared DNA methylation levels at 498 target loci (1001 PCR amplicons) in human whole blood, osteosarcoma cells and an archived tumor tissue sample. We assessed the ability of RainDrop BS-seq to accurately measure DNA methylation over a range of DNA quantities (from 10 to 1500 ng), both with and without whole-genome amplification (WGA) following bisulfite conversion. DNA methylation profiles generated using at least 100 ng correlated well (median R = 0.92) with those generated on Illumina Infinium HumanMethylation450 BeadChips, currently the platform of choice for epigenome-wide association studies (EWAS). WGA allowed for testing of samples with a starting DNA amount of 10 and 50 ng, although a reduced correlation was observed (median R = 0.79). We conclude that RainDrop BS-seq is suitable for measuring DNA methylation levels using nanogram quantities of DNA, and can be used to study candidate epigenetic biomarker loci in an accurate and high-throughput manner, paving the way for its application to routine clinical diagnostics.     

Identification of Novel Genomic Aberrations in AML-M5 in a Level of Array CGH

To assess the possible existence of unbalanced chromosomal abnormalities and delineate the characterization of copy number alterations (CNAs) of acute myeloid leukemia-M5 (AML-M5), R-banding karyotype, oligonucelotide array CGH and FISH were performed in 24 patients with AML-M5. A total of 117 CNAs with size ranging from 0.004 to 146.263 Mb was recognized in 12 of 24 cases, involving all chromosomes other than chromosome 1, 4, X and Y. Cryptic CNAs with size less than 5 Mb accounted for 59.8% of all the CNAs. 12 recurrent chromosomal alterations were mapped. Seven out of them were described in the previous AML studies and five were new candidate AML-M5 associated CNAs, including gains of 3q26.2-qter and 13q31.3 as well as losses of 2q24.2, 8p12 and 14q32. Amplication of 3q26.2-qter was the sole large recurrent chromosomal anomaly and the pathogenic mechanism in AML-M5 was possibly different from the classical recurrent 3q21q26 abnormality in AML. As a tumor suppressor gene, FOXN3, was singled out from the small recurrent CNA of 14q32, however, it is proved that deletion of FOXN3 is a common marker of myeloid leukemia rather than a specific marker for AML-M5 subtype. Moreover, the concurrent amplication of MLL and deletion of CDKN2A were noted and it might be associated with AML-M5. The number of CNA did not show a significant association with clinico-biological parameters and CR number of the 22 patients received chemotherapy. This study provided the evidence that array CGH served as a complementary platform for routine cytogenetic analysis to identify those cryptic alterations in the patients with AML-M5. As a subtype of AML, AML-M5 carries both common recurrent CNAs and unique CNAs, which may harbor novel oncogenes or tumor suppressor genes. Clarifying the role of these genes will contribute to the understanding of leukemogenic network of AML-M5.     

Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

SUMMARY: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs. AVAILABILITY: Source code and sample data are available at http://bioinfo-out.curie.fr/projects/freec/.     

A comprehensive characterization of genome-wide copy number aberrations in colorectal cancer reveals novel oncogenes and patterns of alterations

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p<0.01). Focal aberrations identified by the GISTIC method confirmed amplifications of oncogenes including EGFR, ERBB2, CCND1, MET, and MYC, and deletions of tumor suppressors including TP53, APC, and SMAD4, and gene expression was highly concordant with copy number aberration for these genes. Novel amplicons included putative oncogenes such as WNK1 and HNF4A, which also showed high concordance between copy number and expression. Survival analysis associated a specific patient segment featured by chromosome 20 q gains to an improved overall survival, which might be due to higher expression of genes such as EEF1B2 and PTK6. The CNA clustering also grouped tumors characterized by a poor prognosis BRAF-mutant-like signature derived from mRNA data from this cohort. We further revealed non-random correlation between CNAs among unlinked loci, including positive correlation between 20 q gain and 8 q gain, and 20 q gain and chromosome 18 loss, consistent with co-selection of these CNAs. These results reinforce the non-random nature of somatic CNAs in stage-II/III CRC and highlight loci and genes that may play an important role in driving the development and outcome of this disease.     

Assessment of RainDrop BS-seq as a method for large-scale,targeted bisulfite sequencing

We present a systematic assessment of RainDrop BS-seq, a novel method for large-scale, targeted bisulfite sequencing using microdroplet-based PCR amplification coupled with next-generation sequencing. We compared DNA methylation levels at 498 target loci (1001 PCR amplicons) in human whole blood, osteosarcoma cells and an archived tumor tissue sample. We assessed the ability of RainDrop BS-seq to accurately measure DNA methylation over a range of DNA quantities (from 10 to 1500 ng), both with and without whole-genome amplification (WGA) following bisulfite conversion. DNA methylation profiles generated using at least 100 ng correlated well (median R = 0.92) with those generated on Illumina Infinium HumanMethylation450 BeadChips, currently the platform of choice for epigenome-wide association studies (EWAS). WGA allowed for testing of samples with a starting DNA amount of 10 and 50 ng, although a reduced correlation was observed (median R = 0.79). We conclude that RainDrop BS-seq is suitable for measuring DNA methylation levels using nanogram quantities of DNA, and can be used to study candidate epigenetic biomarker loci in an accurate and high-throughput manner, paving the way for its application to routine clinical diagnostics.     

Illumina WG-6 BeadChip strips should be normalized separately

Background  

Illumina Sentrix-6 Whole-Genome Expression BeadChips are relatively new microarray platforms which have been used in many microarray studies in the past few years. These Chips have a unique design in which each Chip contains six microarrays and each microarray consists of two separate physical strips, posing special challenges for precise between-array normalization of expression values.     

Germline DNA Copy Number Aberrations Identified as Potential Prognostic Factors for Breast Cancer Recurrence

Breast cancer recurrence (BCR) is a common treatment outcome despite curative-intent primary treatment of non-metastatic breast cancer. Currently used prognostic and predictive factors utilize tumor-based markers, and are not optimal determinants of risk of BCR. Germline-based copy number aberrations (CNAs) have not been evaluated as determinants of predisposition to experience BCR. In this study, we accessed germline DNA from 369 female breast cancer subjects who received curative-intent primary treatment following diagnosis. Of these, 155 experienced BCR and 214 did not, after a median duration of follow up after breast cancer diagnosis of 6.35 years (range = 0.60–21.78) and 8.60 years (range = 3.08–13.57), respectively. Whole genome CNA genotyping was performed on the Affymetrix SNP array 6.0 platform. CNAs were identified using the SNP-Fast Adaptive States Segmentation Technique 2 algorithm implemented in Nexus Copy Number 6.0. Six samples were removed due to poor quality scores, leaving 363 samples for further analysis. We identified 18,561 CNAs with ≥1 kb as a predefined cut-off for observed aberrations. Univariate survival analyses (log-rank tests) identified seven CNAs (two copy number gains and five copy neutral-loss of heterozygosities, CN-LOHs) showing significant differences (P<2.01×10⁻⁵) in recurrence-free survival (RFS) probabilities with and without CNAs.We also observed three additional but distinct CN-LOHs showing significant differences in RFS probabilities (P<2.86×10⁻⁵) when analyses were restricted to stratified cases (luminal A, n = 208) only. After adjusting for tumor stage and grade in multivariate analyses (Cox proportional hazards models), all the CNAs remained strongly associated with the phenotype of BCR. Of these, we confirmed three CNAs at 17q11.2, 11q13.1 and 6q24.1 in representative samples using independent genotyping platforms. Our results suggest further investigations on the potential use of germline DNA variations as prognostic markers in cancer-associated phenotypes.     

Integrated study of copy number states and genotype calls using high-density SNP arrays

We propose a statistical framework, named genoCN, to simultaneously dissect copy number states and genotypes using high-density SNP (single nucleotide polymorphism) arrays. There are at least two types of genomic DNA copy number differences: copy number variations (CNVs) and copy number aberrations (CNAs). While CNVs are naturally occurring and inheritable, CNAs are acquired somatic alterations most often observed in tumor tissues only. CNVs tend to be short and more sparsely located in the genome compared with CNAs. GenoCN consists of two components, genoCNV and genoCNA, designed for CNV and CNA studies, respectively. In contrast to most existing methods, genoCN is more flexible in that the model parameters are estimated from the data instead of being decided a priori. GenoCNA also incorporates two important strategies for CNA studies. First, the effects of tissue contamination are explicitly modeled. Second, if SNP arrays are performed for both tumor and normal tissues of one individual, the genotype calls from normal tissue are used to study CNAs in tumor tissue. We evaluated genoCN by applications to 162 HapMap individuals and a brain tumor (glioblastoma) dataset and showed that our method can successfully identify both types of copy number differences and produce high-quality genotype calls.     

Recurrent patterns of DNA copy number alterations in tumors reflect metabolic selection pressures

Copy number alteration (CNA) profiling of human tumors has revealed recurrent patterns of DNA amplifications and deletions across diverse cancer types. These patterns are suggestive of conserved selection pressures during tumor evolution but cannot be fully explained by known oncogenes and tumor suppressor genes. Using a pan‐cancer analysis of CNA data from patient tumors and experimental systems, here we show that principal component analysis‐defined CNA signatures are predictive of glycolytic phenotypes, including ¹⁸F‐fluorodeoxy‐glucose (FDG) avidity of patient tumors, and increased proliferation. The primary CNA signature is enriched for p53 mutations and is associated with glycolysis through coordinate amplification of glycolytic genes and other cancer‐linked metabolic enzymes. A pan‐cancer and cross‐species comparison of CNAs highlighted 26 consistently altered DNA regions, containing 11 enzymes in the glycolysis pathway in addition to known cancer‐driving genes. Furthermore, exogenous expression of hexokinase and enolase enzymes in an experimental immortalization system altered the subsequent copy number status of the corresponding endogenous loci, supporting the hypothesis that these metabolic genes act as drivers within the conserved CNA amplification regions. Taken together, these results demonstrate that metabolic stress acts as a selective pressure underlying the recurrent CNAs observed in human tumors, and further cast genomic instability as an enabling event in tumorigenesis and metabolic evolution.     

Genomic profiling of submucosal-invasive gastric cancer by array-based comparative genomic hybridization

Genomic copy number aberrations (CNAs) in gastric cancer have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis. However, involvement of genomic CNAs in the process of submucosal invasion and lymph node metastasis in early gastric cancer is still poorly understood. In this study, to address this issue, we collected a total of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC), analyzed their genomic profiles by array CGH, and compared them between paired samples of mucosal (MU) and submucosal (SM) invasion (23 pairs), and SM invasion and lymph node (LN) metastasis (9 pairs). Initially, we hypothesized that acquisition of specific CNA(s) is important for these processes. However, we observed no significant difference in the number of genomic CNAs between paired MU and SM, and between paired SM and LN. Furthermore, we were unable to find any CNAs specifically associated with SM invasion or LN metastasis. Among the 23 cases analyzed, 15 had some similar pattern of genomic profiling between SM and MU. Interestingly, 13 of the 15 cases also showed some differences in genomic profiles. These results suggest that the majority of SMGCs are composed of heterogeneous subpopulations derived from the same clonal origin. Comparison of genomic CNAs between SMGCs with and without LN metastasis revealed that gain of 11q13, 11q14, 11q22, 14q32 and amplification of 17q21 were more frequent in metastatic SMGCs, suggesting that these CNAs are related to LN metastasis of early gastric cancer. In conclusion, our data suggest that generation of genetically distinct subclones, rather than acquisition of specific CNA at MU, is integral to the process of submucosal invasion, and that subclones that acquire gain of 11q13, 11q14, 11q22, 14q32 or amplification of 17q21 are likely to become metastatic.     

Genome-wide DNA methylation profiling of chronic lymphocytic leukemia allows identification of epigenetically repressed molecular pathways with clinical impact

We performed a genome-wide analysis of aberrant DNA methylation in chronic lymphocytic leukemia (CLL) using methylated CpG island amplification (MCA) coupled with a promoter microarray. We identified 280 potential targets of aberrant DNA methylation in CLL. These genes were located more frequently in chromosomes 19 (16%, p = 0.001), 16 (11%, p = 0.001), 17 (10%, p = 0.02) and 11 (9%, p = 0.02) and could be grouped in several functional networks. Methylation status was confirmed for 22 of these genes (SOX11, DLX1, FAM62C, SOX14, RSPO1, ADCY5, HAND2, SPOCK, MLL, ING1, PRIMA1, BCL11B, LTBP2, BNC1, NR2F2, SALL1, GALGT2, LHX1, DLX4, KLK10, TFAP2 and APP) in 78 CLL patients by pyrosequencing. As a proof of principle, we analyzed the expression of 2 genes, PRIMA1 and APP, in primary cells and of GALGT2, TFAP2C and PRIMA1 in leukemia cells. There was an inverse association between methylation and gene expression. This could be reversed by treatment with 5-aza-2′-deoxycytidine in cell lines. Treatment in a clinical trial with 5-azacitidine resulted in decreased methylation of LINE, DLX4 and SALL1 in the peripheral blood B-cells of patients with CLL. IgV_H mutational status or ZAP-70 expression were not associated with specific methylation profiles. By multivariate analysis, methylation of LINE and APP was associated with shorter overall survival (p = 0.045 and 0.0035, respectively). This study demonstrates that aberrant DNA methylation is common and has potential prognostic and therapeutic value in CLL.Key words: chronic lymphocytic leukemia, DNA methylation, MCA/promoter microarray, epigenetics     

Assessing combined methylation-sensitive high resolution melting and pyrosequencing for the analysis of heterogeneous DNA methylation

Heterogeneous DNA methylation leads to difficulties in accurate detection and quantification of methylation. Methylation-sensitive high resolution melting (MS-HRM) is unique among regularly used methods for DNA methylation analysis in that heterogeneous methylation can be readily identified, although not quantified, by inspection of the melting curves. Bisulfite pyrosequencing has been used to estimate the level of heterogeneous methylation by quantifying methylation levels present at individual CpG dinucleotides. Sequentially combining the two methodologies using MS-HRM to screen the amplification products prior to bisulfite pyrosequencing would be advantageous. This would not only replace the quality control step using agarose gel analysis prior to the pyrosequencing step but would also provide important qualitative information in its own right. We chose to analyze DAPK1 as it is an important tumor suppressor gene frequently heterogeneously methylated in a number of malignancies, including chronic lymphocytic leukemia (CLL). A region of the DAPK1 promoter was analyzed in ten CLL samples by MS-HRM. By using a biotinylated primer, bisulfite pyrosequencing could be used to directly analyze the samples. MS-HRM revealed the presence of various extents of heterogeneous DAPK1 methylation in all CLL samples. Further analysis of the biotinylated MS-HRM products by bisulfite pyrosequencing provided quantitative information for each CpG dinucleotide analyzed, and confirmed the presence of heterogeneous DNA methylation. Whereas each method could be used individually, MS-HRM and bisulfite pyrosequencing provided complementary information for the assessment of heterogeneous methylation.Key words: MS-HRM, pyrosequencing, digital PCR, heterogeneous DNA methylation, DAPK1, chronic lymphocytic leukemia     

Detection of DNA copy number abnormality by microarray expression analysis

Gene copy-number abnormalities (CNAs) are characteristic of solid tumors and are found in association with developmental abnormalities and/or mental retardation. The ultimate impact of CNAs is exerted by the altered expression of encoded genes. We have utilized high-density oligonucleotide arrays from Affymetrix to identify DNA CNAs via their impact on mRNA expression levels. In these studies, we have used three different trisomic cell lines (trisomy 9, trisomy 18, trisomy 21) as models of CNAs and have compared mRNA expression in those trisomic cells with that observed in diploid cell lines of matched tissue origin. Our data clearly show that genes from CNA chromosome regions are substantially over-represented (P<0.000001 by chi-square analysis) in the differentially expressed subset from comparisons of all three trisomic cell lines with normal matching cells. In addition, we have been able to detect the origin of the duplication by a statistical scan for over-expressed genes. These data show that microarray detection of differential mRNA expression can be used to identify significant DNA CNAs.     

microRNA-34b/c on chromosome 11q23 is aberrantly methylated in chronic lymphocytic leukemia

A commonly deleted region in chronic lymphocytic leukemia (CLL) is the 11q22–23 region, which encompasses the ATM gene. Evidence suggests that tumor suppressor genes other than ATM are likely to be involved in CLL with del(11q). A microRNA (miR) cluster including the miR-34b and miR-34c genes is located, among other genes, within the commonly deleted region (CDR) at 11q. Interestingly, these miRs are part of the TP53 network and have been shown to be epigenetically regulated. In this study, we investigated the expression and methylation status of these miRs in a well-characterized cohort of CLL, including cases with/without 11q-deletion. We show that the miR-34b/c promoter was aberrantly hypermethylated in a large proportion of CLL cases (48%, 25/52 cases). miR-34b/c expression correlated inversely to DNA methylation (P = 0.003), and presence of high H3K37me3 further suppressed expression regardless of methylation status. Furthermore, increased miR-34b/c methylation inversely correlated with the presence of 11q-deletion, indicating that methylation and del(11q) independently silence these miRs. Finally, 5-azacytidine and trichostatin A exposure synergistically increased the expression of miR-34b/c in CLL cells, and transfection of miR-34b or miR-34c into HG3 CLL cells significantly increased apoptosis. Altogether, our novel data suggest that miR-34b/c is a candidate tumor suppressor that is epigenetically silenced in CLL.     

lumi: a pipeline for processing Illumina microarray

Illumina microarray is becoming a popular microarray platform. The BeadArray technology from Illumina makes its preprocessing and quality control different from other microarray technologies. Unfortunately, most other analyses have not taken advantage of the unique properties of the BeadArray system, and have just incorporated preprocessing methods originally designed for Affymetrix microarrays. lumi is a Bioconductor package especially designed to process the Illumina microarray data. It includes data input, quality control, variance stabilization, normalization and gene annotation portions. In specific, the lumi package includes a variance-stabilizing transformation (VST) algorithm that takes advantage of the technical replicates available on every Illumina microarray. Different normalization method options and multiple quality control plots are provided in the package. To better annotate the Illumina data, a vendor independent nucleotide universal identifier (nuID) was devised to identify the probes of Illumina microarray. The nuID annotation packages and output of lumi processed results can be easily integrated with other Bioconductor packages to construct a statistical data analysis pipeline for Illumina data. Availability: The lumi Bioconductor package, www.bioconductor.org     

Latent Factor Analysis to Discover Pathway-Associated Putative Segmental Aneuploidies in Human Cancers

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of “trans”-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1α protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage.     

Copy Number Gains at 8q24 and 20q11-q13 in Gastric Cancer Are More Common in Intestinal-Type than Diffuse-Type

The present study was aimed at discovering DNA copy number alterations (CNAs) involved in the carcinogenesis of stomach and at understanding their clinicopathological significances in the Korean population. DNA copy numbers were analyzed using Agilent 244K or 400K array comparative genomic hybridization (aCGH) in fresh-frozen tumor and matched normal tissues from 40 gastric cancer patients. Some of the detected CNA regions were validated using multiplex ligation-dependent probe amplification (MLPA) in six of the 40 patients and customized Agilent 60K aCGH in an independent set of 48 gastric cancers. The mRNA levels of genes at common CNA regions were analyzed using quantitative real-time PCR. Copy number gains were more common than losses across the entire genome in tumor tissues compared to matched normal tissues. The mean number of alterations per case was 64 for gains and 40 for losses, and the median aberration length was 44016 bp for gains and 4732 bp for losses. Copy number gains were frequently detected at 7p22.1 (20%), 8q24.21 (27%–30%), 8q24.3 (22%–48%), 13q34 (20%–31%), and 20q11-q13 (25%–30%), and losses at 3p14.2 (43%), 4q35.2 (27%), 6q26 (23%), and 17p13.3 (20%–23%). CNAs at 7p22.1, 13q34, and 17p13.3 have not been reported in other populations. Most of the copy number losses were associated with down-regulation of mRNA levels, but the correlation between copy number gains and mRNA expression levels varied in a gene-dependent manner. In addition, copy number gains tended to occur more commonly in intestinal-type cancers than in diffuse-type cancers. In conclusion, the present study suggests that copy number gains at 8q24 and 20q11-q13 and losses at 3p14.2 may be common events in gastric cancer but CNAs at 7p22.1, 13q34, and 17p13.3 may be Korean-specific.     

Amplified and Homozygously Deleted Genes in Glioblastoma: Impact on Gene Expression Levels

Background

Glioblastoma multiforme (GBM) displays multiple amplicons and homozygous deletions that involve relevant pathogenic genes and other genes whose role remains unknown.

Methodology

Single-nucleotide polymorphism (SNP)-arrays were used to determine the frequency of recurrent amplicons and homozygous deletions in GBM (n = 46), and to evaluate the impact of copy number alterations (CNA) on mRNA levels of the genes involved.

Principal Findings

Recurrent amplicons were detected for chromosomes 7 (50%), 12 (22%), 1 (11%), 4 (9%), 11 (4%), and 17 (4%), whereas homozygous deletions involved chromosomes 9p21 (52%) and 10q (22%). Most genes that displayed a high correlation between DNA CNA and mRNA levels were coded in the amplified chromosomes. For some amplicons the impact of DNA CNA on mRNA expression was restricted to a single gene (e.g., EGFR at 7p11.2), while for others it involved multiple genes (e.g., 11 and 5 genes at 12q14.1–q15 and 4q12, respectively). Despite homozygous del(9p21) and del(10q23.31) included multiple genes, association between these DNA CNA and RNA expression was restricted to the MTAP gene.

Conclusions

Overall, our results showed a high frequency of amplicons and homozygous deletions in GBM with variable impact on the expression of the genes involved, and they contributed to the identification of other potentially relevant genes.     

MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.