Correlation analysis between single-nucleotide polymorphism and expression arrays in gliomas identifies potentially relevant target genes

Comprehensive bioinformatics analysis of the characterization and determination underlying mechanisms of over-expression and co-expression of genes residing on 20q in colorectal cancer

The Long arm of chromosome 20 (20q) is closely related to the development of colorectal cancer, so identifying the expression profile of genes on 20q through a comprehensive overview is indispensable. In this article, preliminar experimental data, several available databases and bioinformatics tools such as the Cancer Genome Atlas, the Encyclopedia of DNA Elements, the JASPAR database and starBase were combined to analyze the correlation between genes and chromosomal aberrations, microRNA and transcription factors, as well as to explore the expression feature and potential regulative mechanism. The results showed that the most frequently unregulated genes in colorectal cancer arelocated on chromosome 20q, present a significant CNA–mRNA correlation.Furthermore, the genes with mRNA overexpression showed co-expression features and tended to be clustered within the same genomic neighborhoods. Then, several genes were selected to carry out further analysis and demonstrated that shared transcription factors, a conserved bidirectional promoter, and competition for a limited pool of microRNAin the 3’UTR of mRNA may be the underlying mechanisms behind the co-expression of physically adjacent genes.Finally, the databases, Lentivirus shRNA, and qPCR were used to find that these adjacent genes with co-expression cooperatively participated in the same biological pathways associated with the pathogenesis and development of colorectal cancer.

Atrazine exposure elicits copy number alterations in the zebrafish genome

Atrazine is an agricultural herbicide used throughout the Midwestern United States that frequently contaminates potable water supplies resulting in human exposure. Using the zebrafish model system, an embryonic atrazine exposure was previously reported to decrease spawning rates with an increase in progesterone and ovarian follicular atresia in adult females. In addition, alterations in genes associated with distinct molecular pathways of the endocrine system were observed in brain and gonad tissue of the adult females and males. Current hypotheses for mechanistic changes in the developmental origins of health and disease include genetic (e.g., copy number alterations) or epigenetic (e.g., DNA methylation) mechanisms. As such, in the current study we investigated whether an atrazine exposure would generate copy number alterations (CNAs) in the zebrafish genome. A zebrafish fibroblast cell line was used to limit detection to CNAs caused by the chemical exposure. First, cells were exposed to a range of atrazine concentrations and a crystal violet assay was completed, showing confluency decreased by ~60% at 46.3μM. Cells were then exposed to 0, 0.463, 4.63, or 46.3μM atrazine and array comparative genomic hybridization completed. Results showed 34, 21, and 44 CNAs in the 0.463, 4.63, and 46.3μM treatments, respectively. Furthermore, CNAs were associated with previously reported gene expression alterations in adult male and female zebrafish. This study demonstrates that atrazine exposure can generate CNAs that are linked to gene expression alterations observed in adult zebrafish exposed to atrazine during embryogenesis providing a mechanism of the developmental origins of atrazine endocrine disruption.

Chromosome 17p Homodisomy Is Associated With Better Outcome in 1p19q Non-Codeleted and IDH-Mutated Gliomas

BACKGROUND

The 1p19q non-codeleted gliomas with IDH mutation, defined as "molecular astrocytomas," display frequent TP53 mutations and have an intermediate prognosis. We investigated the prognostic impact of copy number-neutral loss of heterozygosity (CNLOH) in 17p in this population.

METHODS

We analyzed 793 gliomas (206 grade II, 377 grade III, and 210 grade IV) by single nucleotide polymorphism array and for TP53 mutations.

RESULTS

Homodisomy revealed by CNLOH was observed in 156 cases (19.7%). It was more frequent in astrocytomas and oligoastrocytomas (98/256, 38%) than oligodendrogliomas (28/327, 8.6%; p < .0001) or glioblastoma multiforme (30/210, 14.3%; p < .0001), tightly associated with TP53 mutation (69/71 vs. 20/79; p = 2 × 10(-16)), and mutually exclusive with 1p19q codeletion (1/156 vs. 249/556; p < .0001). In the group of IDH-mutated 1p19q non-codeleted gliomas, CNLOH 17p was associated with longer survival (86.3 vs. 46.2 months; p = .004), particularly in grade III gliomas (overall survival >100 vs. 37.9 months; p = .007). These data were confirmed in an independent dataset from the Cancer Genome Atlas.

CONCLUSION

CNLOH 17p is a prognostic marker and further refines the molecular classification of gliomas.

IMPLICATIONS FOR PRACTICE

Homodisomy of chromosome 17p (CNLOH 17p) is a frequent feature in IDH-mutated 1p19q non-codeleted gliomas (group 2). It is constantly associated with TP53 mutation. It was found, within this specific molecular group of gliomas (corresponding to molecular astrocytomas), that CNLOH 17p is associated with a much better outcome and may therefore represent an additional prognostic marker to refine the prognostic classification of gliomas.

An Integrated Approach for RNA-seq Data Normalization

BACKGROUND

DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization.

RESULTS

In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression.

CONCLUSIONS

Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.

Chromosomal Aberrations in Canine Gliomas Define Candidate Genes and Common Pathways in Dogs and Humans

Spontaneous gliomas in dogs occur at a frequency similar to that in humans and may provide a translational model for therapeutic development and comparative biological investigations. Copy number alterations in 38 canine gliomas, including diffuse astrocytomas, glioblastomas, oligodendrogliomas, and mixed oligoastrocytomas, were defined using an Illumina 170K single nucleotide polymorphism array. Highly recurrent alterations were seen in up to 85% of some tumor types, most notably involving chromosomes 13, 22, and 38, and gliomas clustered into 2 major groups consisting of high-grade IV astrocytomas, or oligodendrogliomas and other tumors. Tumor types were characterized by specific broad and focal chromosomal events including focal loss of the INK4A/B locus in glioblastoma and loss of the RB1 gene and amplification of the PDGFRA gene in oligodendrogliomas. Genes associated with the 3 critical pathways in human high-grade gliomas (TP53, RB1, and RTK/RAS/PI3K) were frequently associated with canine aberrations. Analysis of oligodendrogliomas revealed regions of chromosomal losses syntenic to human 1p involving tumor suppressor genes, such as CDKN2C, as well as genes associated with apoptosis, autophagy, and response to chemotherapy and radiation. Analysis of high frequency chromosomal aberrations with respect to human orthologues may provide insight into both novel and common pathways in gliomagenesis and response to therapy.

Identification of differentially expressed genes regulated by transcription factors in glioblastomas by bioinformatics analysis

The present study aimed to identify differentially expressed genes (DEGs) regulated by transcription factors (TFs) in glioblastoma, by conducting a bioinformatics analysis. The results of the present study may provide potential therapeutic targets that are involved in the development of glioblastoma. The GSE4290 raw data set was downloaded from the Gene Expression Omnibus database, and consisted of 23 non‑tumor samples and 77 glioblastoma (grade 4) tumor samples. Robust Multichip Averaging was used to identify DEGs between the glioblastoma and non‑tumor samples. Functional enrichment analysis of the DEGs was also performed. Based on the TRANSFAC® database, TFs associated with the glioblastoma gene expression profile were used to construct a regulatory network. Furthermore, trimmed subnets were identified according to calculated Z‑scores. A total of 676 DEGs were identified, of which 190 were upregulated and 496 were downregulated. Gene Ontology analysis demonstrated that the majority of these DEGs were functionally enriched in synaptic transmission, regulation of vesicle‑mediated transport and ion‑gated channel activity. In addition, the enriched Kyoto Encyclopedia of Genes and Genomes pathway included neuroactive ligand‑receptor interaction, calcium signaling pathway, p53 signaling pathway and cell cycle. Based on the TRANSFAC® database, transcriptional regulatory networks with 2,246 nodes and 4,515 regulatory pairs were constructed. According to the Z‑scores, the following candidate TFs were identified: TP53, SP1, JUN, STAT3 and SPI1; alongside their downstream DEGs. TP53 was the only differentially expressed TF. These candidate TFs and their downstream DEGs may have important roles in the progression of glioblastoma, and could be potential biomarkers for clinical treatment.

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis

Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

Integrated analysis of copy number variation and genome-wide expression profiling in colorectal cancer tissues

Integrative analyses of multiple genomic datasets for selected samples can provide better insight into the overall data and can enhance our knowledge of cancer. The objective of this study was to elucidate the association between copy number variation (CNV) and gene expression in colorectal cancer (CRC) samples and their corresponding non-cancerous tissues. Sixty-four paired CRC samples from the same patients were subjected to CNV profiling using the Illumina HumanOmni1-Quad assay, and validation was performed using multiplex ligation probe amplification method. Genome-wide expression profiling was performed on 15 paired samples from the same group of patients using the Affymetrix Human Gene 1.0 ST array. Significant genes obtained from both array results were then overlapped. To identify molecular pathways, the data were mapped to the KEGG database. Whole genome CNV analysis that compared primary tumor and non-cancerous epithelium revealed gains in 1638 genes and losses in 36 genes. Significant gains were mostly found in chromosome 20 at position 20q12 with a frequency of 45.31% in tumor samples. Examples of genes that were associated at this cytoband were PTPRT, EMILIN3 and CHD6. The highest number of losses was detected at chromosome 8, position 8p23.2 with 17.19% occurrence in all tumor samples. Among the genes found at this cytoband were CSMD1 and DLC1. Genome-wide expression profiling showed 709 genes to be up-regulated and 699 genes to be down-regulated in CRC compared to non-cancerous samples. Integration of these two datasets identified 56 overlapping genes, which were located in chromosomes 8, 20 and 22. MLPA confirmed that the CRC samples had the highest gains in chromosome 20 compared to the reference samples. Interpretation of the CNV data in the context of the transcriptome via integrative analyses may provide more in-depth knowledge of the genomic landscape of CRC.

Vitamin D receptor expression is associated with improved overall survival in human glioblastoma multiforme

Vitamin D and its analogs have been shown to display anti-proliferative effects in a wide variety of cancer types including glioblastoma multiforme (GBM). These anticancer effects are mediated by its active metabolite, 1α, 25-dihydroxyvitamin D3 (calcitriol) acting mainly through vitamin D receptor (VDR) signaling. In addition to its involvement in calcitriol action, VDR has also been demonstrated to be useful as a prognostic factor for some types of cancer. However, to our knowledge, there are no studies evaluating the expression of VDR protein and its association with outcome in gliomas. Therefore, we investigated VDR expression by using immunohistochemical analysis in human glioma tissue microarrays, and analyzed the association between VDR expression and clinico-pathological parameters. We further investigated the effects of genetic and pharmacologic modulation of VDR on survival and migration of glioma cell lines. Our data demonstrate that VDR is increased in tumor tissues when compared with VDR in non-malignant brains, and that VDR expression is associated with an improved outcome in patients with GBM. We also show that both genetic and pharmacologic modulation of VDR modulates GBM cellular migration and survival and that VDR is necessary for calcitriol-mediated effects on migration. Altogether these results provide some limited evidence supporting a role for VDR in glioma progression.

Integrated high-resolution array CGH and SKY analysis of homozygous deletions and other genomic alterations present in malignant mesothelioma cell lines

High-resolution oligonucleotide array comparative genomic hybridization (aCGH) and spectral karyotyping (SKY) were applied to a panel of malignant mesothelioma (MMt) cell lines. SKY has not been applied to MMt before, and complete karyotypes are reported based on the integration of SKY and aCGH results. A whole genome search for homozygous deletions (HDs) produced the largest set of recurrent and non-recurrent HDs for MMt (52 recurrent HDs in 10 genomic regions; 36 non-recurrent HDs). For the first time, LINGO2, RBFOX1/A2BP1, RPL29, DUSP7, and CCSER1/FAM190A were found to be homozygously deleted in MMt, and some of these genes could be new tumor suppressor genes for MMt. Integration of SKY and aCGH data allowed reconstruction of chromosomal rearrangements that led to the formation of HDs. Our data imply that only with acquisition of structural and/or numerical karyotypic instability can MMt cells attain a complete loss of tumor suppressor genes located in 9p21.3, which is the most frequently homozygously deleted region. Tetraploidization is a late event in the karyotypic progression of MMt cells, after HDs in the 9p21.3 region have already been acquired.

Genome-wide associations of signaling pathways in glioblastoma multiforme

BACKGROUND

eQTL analysis is a powerful method that allows the identification of causal genomic alterations, providing an explanation of expression changes of single genes. However, genes mediate their biological roles in groups rather than in isolation, prompting us to extend the concept of eQTLs to whole gene pathways.

METHODS

We combined matched genomic alteration and gene expression data of glioblastoma patients and determined associations between the expression of signaling pathways and genomic copy number alterations with a non-linear machine learning approach.

RESULTS

Expectedly, over-expressed pathways were largely associated to tag-loci on chromosomes with signature alterations. Surprisingly, tag-loci that were associated to under-expressed pathways were largely placed on other chromosomes, an observation that held for composite effects between chromosomes as well. Indicating their biological relevance, identified genomic regions were highly enriched with genes having a reported driving role in gliomas. Furthermore, we found pathways that were significantly enriched with such driver genes.

CONCLUSIONS

Driver genes and their associated pathways may represent a functional core that drive the tumor emergence and govern the signaling apparatus in GBMs. In addition, such associations may be indicative of drug combinations for the treatment of brain tumors that follow similar patterns of common and diverging alterations.

Distinct genomic aberrations between low-grade and high-grade gliomas of Chinese patients

Background

Glioma is a type of tumor that develops in the central nerve system, mainly the brain. Alterations of genomic sequence and sequence segments (such as copy number variations or CNV and copy neutral loss of heterozygosities or cnLOH) are thought to be a major determinant of the tumor grade.

Methods

We mapped genomic variations between low-grade and high-grade gliomas (LGG and HGG) in Chinese population based on Illumina’s Beadchip and validated the results using real-time qPCR.

Results

At the cytoband level, we discovered: (1) unique losses in LGG on 5q, 8p and 11q, and in HGG on 6q, 11p, 13q and 19q; (2) unique gains in the LGG on 1p and in HGG at 5p, 7p, 7q and 20q; and (3) cnLOH in HGG only on 3q, 8q, 10p, 14q, 15q, 17p, 17q, 18q and 21q. Subsequently, we confirmed well-characterized oncogenes among tumor-related loci (such as EGFR and KIT) and detected novel genes that gained chromosome sequences (such as AASS, HYAL4, NDUFA5 and SPAM1) in both LGG and HGG. In addition, we found gains, losses, and cnLOH in several genes, including VN1R2, VN1R4, and ZNF677, in multiple samples. Mapping grade-associated pathways and their related gene ontology (GO) terms, we classified LGG-associated functions as “arachidonic acid metabolism”, “DNA binding” and “regulation of DNA-dependent transcription” and the HGG-associated as “neuroactive ligand-receptor interaction”, “neuronal cell body” and “defense response to bacterium”.

Conclusion

LGG and HGG appear to have different molecular signatures in genomic variations and our results provide invaluable information for the diagnosis and treatment of gliomas in patients with variable duration or diverse tumor differentiation.

Combined analysis of genome-wide expression and copy number profiles to identify key altered genomic regions in cancer

BACKGROUND

Analysis of DNA copy number alterations and gene expression changes in human samples have been used to find potential target genes in complex diseases. Recent studies have combined these two types of data using different strategies, but focusing on finding gene-based relationships. However, it has been proposed that these data can be used to identify key genomic regions, which may enclose causal genes under the assumption that disease-associated gene expression changes are caused by genomic alterations.

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.

A global view of the oncogenic landscape in nasopharyngeal carcinoma: an integrated analysis at the genetic and expression levels

Previous studies have reported that the tumour cells of nasopharyngeal carcinoma (NPC) exhibit recurrent chromosome abnormalities. These genetic changes are broadly assumed to lead to changes in gene expression which are important for the pathogenesis of this tumour. However, this assumption has yet to be formally tested at a global level. Therefore a genome wide analysis of chromosome copy number and gene expression was performed in tumour cells micro-dissected from the same NPC biopsies. Cellular tumour suppressor and tumour-promoting genes (TSG, TPG) and Epstein-Barr Virus (EBV)-encoded oncogenes were examined. The EBV-encoded genome maintenance protein EBNA1, along with the putative oncogenes LMP1, LMP2 and BARF1 were expressed in the majority of NPCs that were analysed. Significant downregulation of expression in an average of 76 cellular TSGs per tumour was found, whilst a per-tumour average of 88 significantly upregulated, TPGs occurred. The expression of around 60% of putative TPGs and TSGs was both up-and down-regulated in different types of cancer, suggesting that the simplistic classification of genes as TSGs or TPGs may not be entirely appropriate and that the concept of context-dependent onco-suppressors may be more extensive than previously recognised. No significant enrichment of TPGs within regions of frequent genomic gain was seen but TSGs were significantly enriched within regions of frequent genomic loss. It is suggested that loss of the FHIT gene may be a driver of NPC tumourigenesis. Notwithstanding the association of TSGs with regions of genomic loss, on a gene by gene basis and excepting homozygous deletions and high-level amplification, there is very little correlation between chromosomal copy number aberrations and expression levels of TSGs and TPGs in NPC.

Microarray-based comparative genomic hybridization of cancer targets reveals novel, recurrent genetic aberrations in the myelodysplastic syndromes

The myelodysplastic syndromes (MDS) are a heterogeneous group of clonal disorders characterized by ineffective hematopoiesis, cytopenias, and a risk of transformation to acute myeloid leukemia (AML). However, only approximately 50% of primary MDS patients show clonal cytogenetic aberrations. To determine whether high-resolution microarray analysis would reveal new or additional aberrations, we analyzed 35 samples derived from patients with a diagnosis or suspicion of MDS and abnormal karyotypes. We used a whole-genome oligonucleotide microarray with targeted coverage of approximately 1900 genes associated with hematologic and other cancers. Clinically relevant copy number aberrations (CNAs) were identified by microarray-based comparative genomic hybridization (aCGH) in all samples (range 1-31, median 5). In 28 of 35 samples (80%), aCGH revealed new cytogenetic aberrations not seen by karyotype or fluorescence in situ hybridization (FISH). Furthermore, 132 cryptic aberrations (≤5 Mb) were identified in 25 cases (71.4%) including deletions of NF1, RUNX1, RASSF1, CCND1, TET2, DNMT3A, HRAS, PDGFRA and FIP1L1. Additionally, aCGH clarified known complex aberrations in 17 of 35 samples (48.6%). Finally, our results using whole-genome arrays with higher density coverage targeted to cancer features demonstrate the usefulness of arrays to identify rare and cryptic recurring imbalances that may prove to be significant in disease progression or transformation to AML and may improve the suitability or efficacy of molecularly targeted therapy.

Lessons from a decade of integrating cancer copy number alterations with gene expression profiles

Over the last decade, multiple functional genomic datasets studying chromosomal aberrations and their downstream effects on gene expression have accumulated for several cancer types. A vast majority of them are in the form of paired gene expression profiles and somatic copy number alterations (CNA) information on the same patients identified using microarray platforms. In response, many algorithms and software packages are available for integrating these paired data. Surprisingly, there has been no serious attempt to review the currently available methodologies or the novel insights brought using them. In this work, we discuss the quantitative relationships observed between CNA and gene expression in multiple cancer types and biological milestones achieved using the available methodologies. We discuss the conceptual evolution of both, the step-wise and the joint data integration methodologies over the last decade. We conclude by providing suggestions for building efficient data integration methodologies and asking further biological questions.

Integrated analyses of copy number variations and gene expression in lung adenocarcinoma

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10(-5)). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis.

Integration and analysis of genome-scale data from gliomas

Primary brain tumors are a leading cause of cancer-related mortality among young adults and children. The most common primary malignant brain tumor, glioma, carries a median survival of only 14 months. Two major multi-institutional programs, the Glioma Molecular Diagnostic Initiative and The Cancer Genome Atlas, have pursued a comprehensive genomic characterization of a large number of clinical glioma samples using a variety of technologies to measure gene expression, chromosomal copy number alterations, somatic and germline mutations, DNA methylation, microRNA, and proteomic changes. Classification of gliomas on the basis of gene expression has revealed six major subtypes and provided insights into the underlying biology of each subtype. Integration of genome-wide data from different technologies has been used to identify many potential protein targets in this disease, while increasing the reliability and biological interpretability of results. Mapping genomic changes onto both known and inferred cellular networks represents the next level of analysis, and has yielded proteins with key roles in tumorigenesis. Ultimately, the information gained from these approaches will be used to create customized therapeutic regimens for each patient based on the unique genomic signature of the individual tumor. In this Review, we describe efforts to characterize gliomas using genomic data, and consider how insights gained from these analyses promise to increase understanding of the biological underpinnings of the disease and lead the way to new therapeutic strategies.

Gene pathways and subnetworks distinguish between major glioma subtypes and elucidate potential underlying biology

Molecular diagnostic tools are increasingly being used in an attempt to classify primary human brain tumors more accurately. While methods that are based on the analysis of individual gene expression prove to be useful for diagnostic purposes, they are devoid of biological significance since tumorgenesis is a concerted deregulation of multiple pathways rather than single genes. In a proof of concept, we utilize two large clinical data sets and show that the elucidation of enriched pathways and small differentially expressed sub-networks of protein interactions allow a reliable classification of glioblastomas and oligodendrogliomas. Applying a feature selection method, we observe that an optimized subset of pathways and subnetworks significantly improves the prediction accuracy. By determining the enrichment of altered genes in pathways and subnetworks we show that optimized subsets of genes rarely seem to be a target of genomic alteration. Our results suggest that groups of genes play a decisive role for the phenotype of the underlying tumor samples that can be utilized to reliably distinguish tumor types. In the absence of enrichment of genes that are genomically altered we assume that genetic changes largely exert an indirect rather than direct regulatory influence on a number of tumor-defining regulatory networks.

Selenium derivatization of nucleic acids for X-ray crystal-structure and function studies

It is estimated that over two thirds of all new crystal structures of proteins are determined via the protein selenium derivatization (selenomethionine (Se-Met) strategy). This selenium derivatization strategy via MAD (multi-wavelength anomalous dispersion) phasing has revolutionized protein X-ray crystallography. Through our pioneer research, similarly, Se has also been successfully incorporated into nucleic acids to facilitate the X-ray crystal-structure and function studies of nucleic acids. Currently, Se has been stably introduced into nucleic acids by replacing nucleotide O-atom at the positions 2', 4', 5', and in nucleobases and non-bridging phosphates. The Se derivatization of nucleic acids can be achieved through solid-phase chemical synthesis and enzymatic methods, and the Se-derivatized nucleic acids (SeNA) can be easily purified by HPLC, FPLC, and gel electrophoresis to obtain high purity. It has also been demonstrated that the Se derivatization of nucleic acids facilitates the phase determination via MAD phasing without significant perturbation. A growing number of structures of DNAs, RNAs, and protein-nucleic acid complexes have been determined by the Se derivatization and MAD phasing. Furthermore, it was observed that the Se derivatization can facilitate crystallization, especially when it is introduced to the 2'-position. In addition, this novel derivatization strategy has many advantages over the conventional halogen derivatization, such as more choices of the modification sites via the atom-specific substitution of the nucleotide O-atom, better stability under X-ray radiation, and structure isomorphism. Therefore, our Se-derivatization strategy has great potentials to provide rational solutions for both phase determination and high-quality crystal growth in nucleic-acid crystallography. Moreover, the Se derivatization generates the nucleic acids with many new properties and creates a new paradigm of nucleic acids. This review summarizes the recent developments of the atomic site-specific Se derivatization of nucleic acids for structure determination and function study. Several applications of this Se-derivatization strategy in nucleic acid and protein research are also described in this review.

Integrative analysis of DNA copy number and gene expression in metastatic oral squamous cell carcinoma identifies genes associated with poor survival

Background

Lymphotropism in oral squamous cell carcinoma (OSCC) is one of the most important prognostic factors of 5-year survival. In an effort to identify genes that may be responsible for the initiation of OSCC lymphotropism, we examined DNA copy number gains and losses and corresponding gene expression changes from tumor cells in metastatic lymph nodes of patients with OSCC.

Results

We performed integrative analysis of DNA copy number alterations (CNA) and corresponding mRNA expression from OSCC cells isolated from metastatic lymph nodes of 20 patients using Affymetrix 250 K Nsp I SNP and U133 Plus 2.0 arrays, respectively. Overall, genome CNA accounted for expression changes in 31% of the transcripts studied. Genome region 11q13.2-11q13.3 shows the highest correlation between DNA CNA and expression. With a false discovery rate < 1%, 530 transcripts (461 genes) demonstrated a correlation between CNA and expression. Among these, we found two subsets that were significantly associated with OSCC (n = 122) when compared to controls, and with survival (n = 27), as tested using an independent dataset with genome-wide expression profiles for 148 primary OSCC and 45 normal oral mucosa. We fit Cox models to calculate a principal component analysis-derived risk-score for these two gene sets ('122-' or '27-transcript PC'). The models combining the 122- or 27-transcript PC with stage outperformed the model using stage alone in terms of the Area Under the Curve (AUC = 0.82 or 0.86 vs. 0.72, with p = 0.044 or 0.011, respectively).

Conclusions

Genes exhibiting CNA-correlated expression may have biological impact on carcinogenesis and cancer progression in OSCC. Determination of copy number-associated transcripts associated with clinical outcomes in tumor cells with an aggressive phenotype (i.e., cells metastasized to the lymph nodes) can help prioritize candidate transcripts from high-throughput data for further studies.

Integrated analysis of copy number alterations and gene expression: a bivariate assessment of equally directed abnormalities

MOTIVATION

The analysis of a number of different genetic features like copy number (CN) variation, gene expression (GE) or loss of heterocygosity has considerably increased in recent years, as well as the number of available datasets. This is particularly due to the success of microarray technology. Thus, to understand mechanisms of disease pathogenesis on a molecular basis, e.g. in cancer research, the challenge of analyzing such different data types in an integrated way has become increasingly important. In order to tackle this problem, we propose a new procedure for an integrated analysis of two different data types that searches for genes and genetic regions which for both inputs display strong equally directed deviations from the reference median. We employ this approach, based on a modified correlation coefficient and an explorative Wilcoxon test, to find DNA regions of such abnormalities in GE and CN (e.g. underexpressed genes accompanied by a loss of DNA material).

RESULTS

In an application to acute myeloid leukemia, our procedure is able to identify various regions on different chromosomes with characteristic abnormalities in GE and CN data and shows a higher sensitivity to differences in abnormalities than standard approaches. While the results support various findings of previous studies, some new interesting DNA regions can be identified. In a simulation study, our procedure also shows more reliable results than standard approaches.

AVAILABILITY

Code and data available as R packages edira and ediraAMLdata from http://www.statistik.tu-dortmund.de/~schaefer/

CONTACT

martin.schaefer@udo.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.