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Motivation: Cancer evolves through microevolution where random lesions that provide the biggest advantage to cancer stand out in their frequent occurrence in multiple samples. At the same time, a gene function can be changed by aberration of the corresponding gene or modification of microRNA (miRNA) expression, which attenuates the gene. In a large number of cancer samples, these two mechanisms might be distributed in a coordinated and almost mutually exclusive manner. Understanding this coordination may assist in identifying changes which significantly produce the same functional impact on cancer phenotype, and further identify genes that are universally required for cancer. Present methodologies for finding aberrations usually analyze single datasets, which cannot identify such pairs of coordinating genes and miRNAs. Results: We have developed MIRAGAA, a statistical approach, to assess the coordinated changes of genome copy numbers and miRNA expression. We have evaluated MIRAGAA on The Cancer Genome Atlas (TCGA) Glioblastoma Multiforme datasets. In these datasets, a number of genome regions coordinating with different miRNAs are identified. Although well known for their biological significance, these genes and miRNAs would be left undetected for being less significant if the two datasets were analyzed individually. Availability and Implementation: The source code, implemented in R and java, is available from our project web site at http://www.csse.unimelb.edu.au/∼rgaire/MIRAGAA/index.html Contact: rgaire@csse.unimelb.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Ovarian cancer is characterized by complex genetic alterations, including copy number loss and copy number-neutral loss of heterozygosity (LOH). These alterations are assumed to represent the "second hit" of the underlying tumor suppressor gene (TSG), however, relative to the number of LOH hotspots reported, few ovarian TSGs have been identified. We conducted a high-resolution LOH analysis using SNP arrays (500K and SNP6.0) of 106 primary ovarian tumors of various histological subtypes together with matching normal DNA. LOH was detected in at least 35% of samples on chromosomes 17, 19p, 22q, Xp, 13q, 8p, 6q, 4q, 5q, 1p, 16q, and 9q with a median minimal region of overlap of only 300 kb. Subtype-specific differences in LOH frequency were noted, particularly for mucinous cases. We also identified 192 somatic homozygous deletions (HDs). Recurrent HDs targeted known TSGs such as CDKN2A (eight samples), RB1 (five samples), and PTEN (three samples). Additional recurrent HDs targeted 16 candidate TSGs near minimal regions of LOH on chromosomes 17, 13, 8p, 5q, and X. Given the importance of HDs in inactivating known genes, these candidates are highly likely to be ovarian TSGs. Our data suggest that the poor success of previous LOH studies was due to the inability of previous technology to resolve complex genomic alterations and distinguish true LOH from allelic imbalance. This study shows that recurrent regions of LOH and HD frequently align with known TSGs suggesting that LOH analysis remains a valid approach to discovering new candidates.

Purpose: There is accumulating evidence that microRNAs may function like classic tumor suppressor genes but little is known about their mechanism of inactivation in cancer cells. We investigated whether somatic mutations are a common mechanism of inactivation of microRNA genes in ovarian cancer. Experimental Design: Ten cancer-implicated microRNA genes were analyzed for somatic mutations in 90 ovarian epithelial cancers and matching normal DNA. High-resolution melt analysis and bidirectional sequencing was used to detect sequence variations. Results: High-resolution melt analysis and direct sequencing did not identify any somatic mutations but did reveal numerous novel and previously reported germ line base substitutions, deletions, and insertions surrounding the mature microRNA sequences. The majority of variants were detected in the same proportion of non–cancer control individuals suggesting that they do not represent ovarian cancer–predisposing alleles. Conclusion: The absence of somatic mutations in any of the 10 cancer-implicated microRNAs in our large cohort of ovarian tumors suggests that this may be an uncommon mechanism of inactivation of microRNAs in ovarian cancer.

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (> 40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r > or =0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2.

Chromodomain, helicase, DNA binding 5 (CHD5) is a member of a subclass of the chromatin remodeling Swi/Snf proteins and has recently been proposed as a tumor suppressor in a diverse range of human cancers. We analyzed all 41 coding exons of CHD5 for somatic mutations in 123 primary ovarian cancers as well as 60 primary breast cancers using high-resolution melt analysis. We also examined methylation of the CHD5 promoter in 48 ovarian cancer samples by methylation-specific single-stranded conformation polymorphism and bisulfite sequencing. In contrast to previous studies, no mutations were identified in the breast cancers, but somatic heterozygous missense mutations were identified in 3 of 123 ovarian cancers. We identified promoter methylation in 3 of 45 samples with normal CHD5 and in 2 of 3 samples with CHD5 mutation, suggesting these tumors may have biallelic inactivation of CHD5. Hemizygous copy number loss at CHD5 occurred in 6 of 85 samples as assessed by single nucleotide polymorphism array. Tumors with CHD5 mutation or methylation were more likely to have mutation of KRAS or BRAF (P = .04). The aggregate frequency of CHD5 haploinsufficiency or inactivation is 16.2% in ovarian cancer. Thus, CHD5 may play a role as a tumor suppressor gene in ovarian cancer; however, it is likely that there is another target of the frequent copy number neutral loss of heterozygosity observed at 1p36.