Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.orgComment: PDF file including supplementary material. 9 pages. Preprin

Primary familial brain calcification linked to deletion of 5' noncoding region of SLC20A2

OBJECTIVES: Primary familial brain calcification (PFBC) is a rare neurological disease often inherited as a dominant trait. Mutations in four genes (SLC20A2, PDGFB, PDGFRB, and XPR1) have been reported in patients with PFBC. Of these, point mutations or small deletions in SLC20A2 are most common. Thus far, only one large deletion covering entire SLC20A2 and several smaller, exonic deletions of SLC20A2 have been reported. The aim of this study was to identify the causative gene defect in a Finnish PFBC family with three affected patients. MATERIALS AND METHODS: A Finnish family with three PFBC patients and five unaffected subjects was studied. Sanger sequencing was used to exclude mutations in the coding and splice site regions of SLC20A2, PDGFRB, and PDGFB. Whole-exome (WES) and whole-genome sequencing (WGS) were performed to identify the causative mutation. A SNP array was used in segregation analysis. RESULTS: Copy number analysis of the WGS data revealed a heterozygous deletion of ~578 kb on chromosome 8. The deletion removes the 5' UTR region, the noncoding exon 1 and the putative promoter region of SLC20A2 as well as the coding regions of six other genes. CONCLUSIONS: Our results support haploinsufficiency of SLC20A2 as a pathogenetic mechanism in PFBC. Analysis of copy number variations (CNVs) is emerging as a crucial step in the molecular genetic diagnostics of PFBC, and it should not be limited to coding regions, as causative variants may reside in the noncoding parts of known disease-associated genes

CAIDE Dementia Risk Score, Alzheimer and cerebrovascular pathology : a population-based autopsy study

Background. CAIDE Dementia Risk Score is a tool for estimating dementia risk in the general population. Its longitudinal associations with Alzheimer or vascular neuropathology in the oldest old are not known. Aim. To explore the relationship between CAIDE Dementia Risk Score at baseline and neuritic plaques, neurofibrillary tangles, cerebral infarcts and cerebral amyloid angiopathy (CAA) after up to 10-year follow-up in the Vantaa 85+ population. Methods. Study population included 149 participants aged 85 years, without dementia at baseline, and with available clinical and autopsy data. Methenamine silver staining was used for beta-amyloid and modified Bielschowsky method for neurofibrillary tangles and neuritic plaques. Macroscopic infarcts were identified from cerebral hemispheres, brain-stem and cerebellum slices. Standardized methods were used to determine microscopic infarcts, CAA and alpha-synuclein pathologies. The CAIDE Dementia Risk Score was calculated based on scores for age, sex, BMI, total cholesterol, systolic blood pressure, physical activity and APOE epsilon 4 carrier status (range 0-18 points). Results. A CAIDE Dementia Risk Score above 11 points was associated with more cerebral infarctions up to 10 years later: OR (95% CI) was 2.10 (1.06-4.16). No associations were found with other neuropathologies. Conclusion. In a population of elderly aged 85 years, higher CAIDE Dementia Risk Score was associated with increased risk of cerebral infarcts.Peer reviewe

An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

<p>Abstract</p> <p>Background</p> <p>Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.</p> <p>Method</p> <p>To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.</p> <p>Result</p> <p>We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.</p> <p>Conclusions</p> <p>We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.</p

Genetics of dementia in a Finnish cohort.

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the two most common neurodegenerative dementias. Variants in APP, PSEN1 and PSEN2 are typically linked to early-onset AD, and several genetic risk loci are associated with late-onset AD. Inherited FTD can be caused by hexanucleotide expansions in C9orf72, or variants in GRN, MAPT or CHMP2B. Several other genes have also been linked to FTD or FTD with motor neuron disease. Here we describe a cohort of 60 Finnish families with possible inherited dementia. Our aim was to clarify the genetic background of dementia in this cohort by analysing both known dementia-associated genes (APOE, APP, C9ORF72, GRN, PSEN1 and PSEN2) and searching for rare or novel segregating variants with exome sequencing. C9orf72 repeat expansions were detected in 12 (20%) of the 60 families, including, in addition to FTD, a family with neuropathologically verified AD. Twelve families (10 with AD and 2 with FTD) with representative samples from affected and unaffected subjects and without C9orf72 expansions were selected for whole-exome sequencing. Exome sequencing did not reveal any variants that could be regarded unequivocally causative, but revealed potentially damaging variants in UNC13C and MARCH4

Relationships Linking Amplification Level to Gene Over-Expression in Gliomas

Background: Gene amplification is thought to promote over-expression of genes favouring tumour development. Because amplified regions are usually megabase-long, amplification often concerns numerous syntenic or non-syntenic genes, among which only a subset is over-expressed. The rationale for these differences remains poorly understood. Methodology/Principal Finding: To address this question, we used quantitative RT-PCR to determine the expression level of a series of co-amplified genes in five xenografted and one fresh human gliomas. These gliomas were chosen because we have previously characterised in detail the genetic content of their amplicons. In all the cases, the amplified sequences lie on extra-chromosomal DNA molecules, as commonly observed in gliomas. We show here that genes transcribed in nonamplified gliomas are over-expressed when amplified, roughly in proportion to their copy number, while non-expressed genes remain inactive. When specific antibodies were available, we also compared protein expression in amplified and nonamplified tumours. We found that protein accumulation barely correlates with the level of mRNA expression in some of these tumours. Conclusions/Significance: Here we show that the tissue-specific pattern of gene expression is maintained upon amplification in gliomas. Our study relies on a single type of tumour and a limited number of cases. However, it strongly suggests that, even when amplified, genes that are normally silent in a given cell type play no role in tumour progression

CDCOCA: a statistical method to define complexity dependent co-occurring chromosomal aberrations

<p>Abstract</p> <p>Background</p> <p>Copy number alterations (CNA) play a key role in cancer development and progression. Since more than one CNA can be detected in most tumors, frequently co-occurring genetic CNA may point to cooperating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNA per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association due to the high genetic instability of many samples.</p> <p>Method</p> <p>We hypothesize that in cancer some linkage-independent CNA may display a non-random co-occurrence, and that these CNA could be of pathogenetic relevance for the respective cancer. We also hypothesize that the statistical relevance of co-occurring CNA may depend on the sample specific CNA complexity. We verify our hypotheses with a simulation based algorithm CDCOCA (complexity dependence of co-occurring chromosomal aberrations).</p> <p>Results</p> <p>Application of CDCOCA to example data sets identified co-occurring CNA from low complex background which otherwise went unnoticed. Identification of cancer associated genes in these co-occurring changes can provide insights of cooperative genes involved in oncogenesis.</p> <p>Conclusions</p> <p>We have developed a method to detect associations of regional copy number abnormalities in cancer data. Along with finding statistically relevant CNA co-occurrences, our algorithm points towards a generally low specificity for co-occurrence of regional imbalances in CNA rich samples, which may have negative impact on pathway modeling approaches relying on frequent CNA events.</p

Genome-Wide Data-Mining of Candidate Human Splice Translational Efficiency Polymorphisms (STEPs) and an Online Database

Variation in pre-mRNA splicing is common and in some cases caused by genetic variants in intronic splicing motifs. Recent studies into the insulin gene (INS) discovered a polymorphism in a 5' non-coding intron that influences the likelihood of intron retention in the final mRNA, extending the 5' untranslated region and maintaining protein quality. Retention was also associated with increased insulin levels, suggesting that such variants--splice translational efficiency polymorphisms (STEPs)--may relate to disease phenotypes through differential protein expression. We set out to explore the prevalence of STEPs in the human genome and validate this new category of protein quantitative trait loci (pQTL) using publicly available data.Gene transcript and variant data were collected and mined for candidate STEPs in motif regions. Sequences from transcripts containing potential STEPs were analysed for evidence of splice site recognition and an effect in expressed sequence tags (ESTs). 16 publicly released genome-wide association data sets of common diseases were searched for association to candidate polymorphisms with HapMap frequency data. Our study found 3324 candidate STEPs lying in motif sequences of 5' non-coding introns and further mining revealed 170 with transcript evidence of intron retention. 21 potential STEPs had EST evidence of intron retention or exon extension, as well as population frequency data for comparison.Results suggest that the insulin STEP was not a unique example and that many STEPs may occur genome-wide with potentially causal effects in complex disease. An online database of STEPs is freely accessible at http://dbstep.genes.org.uk/

A comprehensive screening of copy number variability in dementia with Lewy bodies

The role of genetic variability in dementia with Lewy bodies (DLB) is now indisputable; however, data regarding copy number variation (CNV) in this disease has been lacking. Here, we used whole-genome genotyping of 1454 DLB cases and 1525 controls to assess copy number variability. We used 2 algorithms to confidently detect CNVs, performed a case-control association analysis, screened for candidate CNVs previously associated with DLB-related diseases, and performed a candidate gene approach to fully explore the data. We identified 5 CNV regions with a significant genome-wide association to DLB; 2 of these were only present in cases and absent from publicly available databases: one of the regions overlapped LAPTM4B, a known lysosomal protein, whereas the other overlapped the NME1 locus and SPAG9. We also identified DLB cases presenting rare CNVs in genes previously associated with DLB or related neurodegenerative diseases, such as SNCA, APP, and MAPT. To our knowledge, this is the first study reporting genome-wide CNVs in a large DLB cohort. These results provide preliminary evidence for the contribution of CNVs in DLB risk.info:eu-repo/semantics/publishedVersio

MAL2 and tumor protein D52 (TPD52) are frequently overexpressed in ovarian carcinoma, but differentially associated with histological subtype and patient outcome

Background: The four-transmembrane MAL2 protein is frequently overexpressed in breast carcinoma, and MAL2 overexpression is associated with gain of the corresponding locus at chromosome 8q24.12. Independent expression microarray studies predict MAL2 overexpression in ovarian carcinoma, but these had remained unconfirmed. MAL2 binds tumor protein D52 (TPD52), which is frequently overexpressed in ovarian carcinoma, but the clinical significance of MAL2 and TPD52 overexpression was unknown. Methods: Immunohistochemical analyses of MAL2 and TPD52 expression were performed using tissue microarray sections including benign, borderline and malignant epithelial ovarian tumours. Inmmunohistochemical staining intensity and distribution was assessed both visually and digitally. Results: MAL2 and TPD52 were significantly overexpressed in high-grade serous carcinomas compared with serous borderline tumours. MAL2 expression was highest in serous carcinomas relative to other histological subtypes, whereas TPD52 expression was highest in clear cell carcinomas. MAL2 expression was not related to patient survival, however high-level TPD52 staining was significantly associated with improved overall survival in patients with stage III serous ovarian carcinoma (log-rank test, p < 0.001; n = 124) and was an independent predictor of survival in the overall carcinoma cohort (hazard ratio (HR), 0.498; 95% confidence interval (CI), 0.34-0.728; p < 0.001; n = 221), and in serous carcinomas (HR, 0.440; 95% CI, 0.294-0.658; p < 0.001; n = 182). Conclusions: MAL2 is frequently overexpressed in ovarian carcinoma, and TPD52 overexpression is a favourable independent prognostic marker of potential value in the management of ovarian carcinoma patients.11 page(s