Microarray analyses reveal strong influence of DNA copy number alterations on the transcriptional patterns in pancreatic cancer: implications for the interpretation of genomic amplifications

Exploring the role of TLK2 mutation in tropical calcific pancreatitis: an in silico and molecular dynamics simulation study

Tropical calcific pancreatitis (TCP) is a juvenile form of non-alcoholic chronic pancreatitis seen exclusively in tropical countries. The disease poses a high risk of complications, including pancreatic diabetes and cancer, leading to significant mortality due to poor diagnosis and ineffective treatments. This study employed whole exome sequencing (WES) of 5 TCP patient samples to identify genetic variants associated with TCP. Advanced computational techniques were used to gain atomic-level insights into disease progression, including microsecond-scale long MD simulations and essential dynamics. In silico virtual screening was performed to identify potential therapeutic compounds targeting the mutant protein using the Asinex and DrugBank compound library. WES analysis predicted several single nucleotide variants (SNVs) associated with TCP, including a novel missense variant (c.T1802A or p.V601E) in the TLK2 gene. Computational analysis revealed that the p.V601E mutation significantly affected the structure of the TLK2 kinase domain and its conformational dynamics, altering the interaction profile between ATP and the binding pocket. These changes could impact TLK2's kinase activity and functions, potentially correlating with TCP progression. Promising lead compounds that selectively bind to the TLK2 mutant protein were identified, offering potential for therapeutic interventions in TCP. These findings hold great potential for future research.

Benchmark Dose Modeling Approaches for Volatile Organic Chemicals using a Novel Air-Liquid Interface In Vitro Exposure System

Inhalation is the most relevant route of volatile organic chemical (VOC) exposure; however, due to unique challenges posed by their chemical properties and poor solubility in aqueous solutions, in vitro chemical safety testing is predominantly performed using direct application dosing/submerged exposures. To address the difficulties in screening toxic effects of VOCs, our cell culture exposure system permits cells to be exposed to multiple concentrations at air-liquid interface (ALI) in a 24-well format. ALI exposure methods permit direct chemical-to-cell interaction with the test article at physiological conditions. In the present study, BEAS-2B and primary normal human bronchial epithelial cells (pHBEC) are used to assess gene expression, cytotoxicity, and cell viability responses to a variety of volatile chemicals including acrolein, formaldehyde, 1,3-butadiene, acetaldehyde, 1-bromopropane, carbon tetrachloride, dichloromethane, and trichloroethylene. BEAS-2B cells were exposed to all the test agents, while pHBECs were only exposed to the latter four listed above. The VOC concentrations tested elicited only slight cell viability changes in both cell types. Gene expression changes were analyzed using benchmark dose (BMD) modeling. The BMD for the most sensitive gene set was within one order of magnitude of the threshold-limit value reported by the American Conference of Governmental Industrial Hygienists, and the most sensitive gene sets impacted by exposure correlate to known adverse health effects recorded in epidemiologic and in vivo exposure studies. Overall, our study outlines a novel in vitro approach for evaluating molecular-based points-of-departure in human airway epithelial cell exposure to volatile chemicals.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors

BACKGROUND

Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes.

METHODS

Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data.

RESULTS

The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes.

CONCLUSIONS

The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

A comprehensive molecular characterization of the 8q22.2 region reveals the prognostic relevance of OSR2 mRNA in muscle invasive bladder cancer

Technological advances in molecular profiling have enabled the comprehensive identification of common regions of gene amplification on chromosomes (amplicons) in muscle invasive bladder cancer (MIBC). One such region is 8q22.2, which is largely unexplored in MIBC and could harbor genes with potential for outcome prediction or targeted therapy. To investigate the prognostic role of 8q22.2 and to compare different amplicon definitions, an in-silico analysis of 357 patients from The Cancer Genome Atlas, who underwent radical cystectomy for MIBC, was performed. Amplicons were generated using the GISTIC2.0 algorithm for copy number alterations (DNA_Amplicon) and z-score normalization for mRNA gene overexpression (RNA_Amplicon). Kaplan-Meier survival analysis, univariable, and multivariable Cox proportional hazard ratios were used to relate amplicons, genes, and clinical parameters to overall (OS) and disease-free survival (DFS). Analyses of the biological functions of 8q22.2 genes and genomic events in MIBC were performed to identify potential targets. Genes with prognostic significance from the in silico analysis were validated using RT-qPCR of MIBC tumor samples (n = 46). High 8q22.2 mRNA expression (RNA-AMP) was associated with lymph node metastases. Furthermore, 8q22.2 DNA and RNA amplified patients were more likely to show a luminal subtype (DNA_Amplicon_core: p = 0.029; RNA_Amplicon_core: p = 0.01). Overexpression of the 8q22.2 gene OSR2 predicted shortened DFS in univariable (HR [CI] 1.97 [1.2; 3.22]; p = 0.01) and multivariable in silico analysis (HR [CI] 1.91 [1.15; 3.16]; p = 0.01) and decreased OS (HR [CI] 6.25 [1.37; 28.38]; p = 0.0177) in RT-qPCR data analysis. Alterations in different levels of the 8q22.2 region are associated with manifestation of different clinical characteristics in MIBC. An in-depth comprehensive molecular characterization of genomic regions involved in cancer should include multiple genetic levels, such as DNA copy number alterations and mRNA gene expression, and could lead to a better molecular understanding. In this study, OSR2 is identified as a potential biomarker for survival prognosis.

Inhibiting MARSs reduces hyperhomocysteinemia-associated neural tube and congenital heart defects

Hyperhomocysteinemia is a common metabolic disorder that imposes major adverse health consequences. Reducing homocysteine levels, however, is not always effective against hyperhomocysteinemia-associated pathologies. Herein, we report the potential roles of methionyl-tRNA synthetase (MARS)-generated homocysteine signals in neural tube defects (NTDs) and congenital heart defects (CHDs). Increased copy numbers of MARS and/or MARS2 were detected in NTD and CHD patients. MARSs sense homocysteine and transmit its signal by inducing protein lysine (N)-homocysteinylation. Here, we identified hundreds of novel N-homocysteinylated proteins. N-homocysteinylation of superoxide dismutases (SOD1/2) provided new mechanistic insights for homocysteine-induced oxidative stress, apoptosis and Wnt signalling deregulation. Elevated MARS expression in developing and proliferating cells sensitizes them to the effects of homocysteine. Targeting MARSs using the homocysteine analogue acetyl homocysteine thioether (AHT) reversed MARS efficacy. AHT lowered NTD and CHD onsets in retinoic acid-induced and hyperhomocysteinemia-induced animal models without affecting homocysteine levels. We provide genetic and biochemical evidence to show that MARSs are previously overlooked genetic determinants and key pathological factors of hyperhomocysteinemia, and suggest that MARS inhibition represents an important medicinal approach for controlling hyperhomocysteinemia-associated diseases.

STK38L kinase ablation promotes loss of cell viability in a subset of KRAS-dependent pancreatic cancer cell lines

Pancreatic ductal adenocarcinomas (PDACs) are highly aggressive malignancies, associated with poor clinical prognosis and limited therapeutic options. Oncogenic KRAS mutations are found in over 90% of PDACs, playing a central role in tumor progression. Global gene expression profiling of PDAC reveals 3-4 major molecular subtypes with distinct phenotypic traits and pharmacological vulnerabilities, including variations in oncogenic KRAS pathway dependencies. PDAC cell lines of the aberrantly differentiated endocrine exocrine (ADEX) subtype are robustly KRAS-dependent for survival. The KRAS gene is located on chromosome 12p11-12p12, a region amplified in 5-10% of primary PDACs. Within this amplicon, we identified co-amplification of KRAS with the STK38L gene in a subset of primary human PDACs and PDAC cell lines. Therefore, we determined whether PDAC cell lines are dependent on STK38L expression for proliferation and viability. STK38L encodes a serine/threonine kinase, which shares homology with Hippo pathway kinases LATS1/2. We show that STK38L expression is elevated in a subset of primary PDACs and PDAC cell lines displaying ADEX subtype characteristics, including overexpression of mutant KRAS. RNAi-mediated depletion of STK38L in a subset of ADEX subtype cell lines inhibits cellular proliferation and induces apoptosis. Concomitant with these effects, STK38L depletion causes increased expression of the LATS2 kinase and the cell cycle regulator p21. LATS2 depletion partially rescues the cytostatic and cytotoxic effects of STK38L depletion. Lastly, high STK38L mRNA expression is associated with decreased overall patient survival in PDACs. Collectively, our findings implicate STK38L as a candidate targetable vulnerability in a subset of molecularly-defined PDACs.

The four-transmembrane protein MAL2 and tumor protein D52 (TPD52) are highly expressed in colorectal cancer and correlated with poor prognosis

The four-transmembrane protein MAL2 and tumor protein D52 (TPD52) have been shown to be involved in tumorigenesis of various cancers. However, their roles in colorectal cancer (CRC) remain unclear. In this study, we explored the expressions of MAL2 and TPD52 in tumor specimens resected from 123 CRC patients and the prognostic values of the two proteins in CRC. Immunohistochemical analyses showed that MAL2 (P<0.001) and TPD52 (P<0.001) were significantly highly expressed in primary carcinoma tissues compared with adjacent non-cancerous mucosa tissues. And TPD52 exhibited frequent overexpression in liver metastasis tissues relative to primary carcinoma tissues (P = 0.042), while MAL2 in lymphnode and liver metastasis tissues showed no significant elevation. Real-time quantitative PCR (RT-qPCR) showed the identical results. Correlation analyses by Pearson's chi-square test demonstrated that MAL2 in tumors was positively correlated with tumor status (pathological assessment of regional lymph nodes (pN, P = 0.024)), and clinic stage (P = 0.017). Additionally, the expression of TPD52 was detected under the same condition and was shown to be positively correlated withtumor status (pathological assessment of the primary tumor (pT, P = 0.035), distant metastasis (pM, P = 0.001)) and CRC clinicopathology(P = 0.024). Kaplan-Meier survival curves indicated that positive MAL2 (P<0.001) and TPD52 (P<0.001) expressions were associated with poor overall survival (OS) in CRC patients. Multivariate analysis showed that MAL2 and TPD52 expression was an independent prognostic factor for reduced OS of CRC patients. Moreover, overexpression of TPD52 in CRC SW480 cells showed an increased cell migration (P = 0.023) and invasion (P = 0.012) through inducing occurrence of epithelial-mesenchymal transition (EMT) and activating focal adhesion kinase (FAK)-mediated integrin signalling and PI3K⁄Akt signalling.Whereas TPD52-depleted cells showed the reverse effect. These data suggested that MAL2 and TPD52 might be potential biomarkers for clinical prognosis and might be a promising therapeutic target for CRC.

PAK4 interacts with p85 alpha: implications for pancreatic cancer cell migration

It has been reported that p21-activated kinase 4 (PAK4) is amplified in pancreatic cancer tissue. PAK4 is a member of the PAK family of serine/threonine kinases, which act as effectors for several small GTPases, and has been specifically identified to function downstream of HGF-mediated c-Met activation in a PI3K dependent manner. However, the functionality of PAK4 in pancreatic cancer and the contribution made by HGF signalling to pancreatic cancer cell motility remain to be elucidated. We now find that elevated PAK4 expression is coincident with increased expression levels of c-Met and the p85α subunit of PI3K. Furthermore, we demonstrate that pancreatic cancer cells have a specific motility response to HGF both in 2D and 3D physiomimetic organotypic assays; which can be suppressed by inhibition of PI3K. Significantly, we report a specific interaction between PAK4 and p85α and find that PAK4 deficient cells exhibit a reduction in Akt phosphorylation downstream of HGF signalling. These results implicate a novel role for PAK4 within the PI3K pathway via interaction with p85α. Thus, PAK4 could be an essential player in PDAC progression representing an interesting therapeutic opportunity.

Identification and characterization of the gene expression profiles for protein coding and non-coding RNAs of pancreatic ductal adenocarcinomas

Significant advances have been achieved in recent years in the identification of the genetic and the molecular alterations of pancreatic ductal adenocarcinoma (PDAC). Despite this, at present the understanding of the precise mechanisms involved in the development and malignant transformation of PDAC remain relatively limited. Here, we evaluated for the first time, the molecular heterogeneity of PDAC tumors, through simultaneous assessment of the gene expression profile (GEP) for both coding and non-coding genes of tumor samples from 27 consecutive PDAC patients. Overall, we identified a common GEP for all PDAC tumors, characterized by an increased expression of genes involved in PDAC cell proliferation, local invasion and metastatic capacity, together with a significant alteration of the early steps of the cellular immune response. At the same time, we confirm and extend on previous observations about the genetic complexity of PDAC tumors as revealed by the demonstration of two clearly distinct and unique GEPs (e.g. epithelial-like vs. mesenchymal-like) reflecting the alteration of different signaling pathways involved in the oncogenesis and progression of these tumors. Our results also highlight the potential role of the immune system microenvironment in these tumors, with potential diagnostic and therapeutic implications.

Consequences of Aneuploidy in Cancer: Transcriptome and Beyond

Cancer cells differ from normal healthy cells in multiple aspects ranging from altered cellular signaling through metabolic changes to aberrant chromosome content, so called aneuploidy. The large-scale changes in copy numbers of chromosomes or large chromosomal regions due to aneuploidy alter significantly the gene expression, as several hundreds of genes are gained or lost. Comparison of quantitative genome, transcriptome and proteome data enables dissection of the molecular causes that underlie the gene expression changes observed in cancer cells and provides a new perspective on the molecular consequences of aneuploidy. Here, we will map to what degree aneuploidy affects the expression of genes located on the affected chromosomes. We will also address the effects of aneuploidy on global gene expression in cancer cells as well as whether and how it may contribute to the physiology of cancer cells.

Mesenchymal-like pancreatic cancer cells harbor specific genomic alterations more frequently than their epithelial-like counterparts

The aggressiveness of pancreatic cancer is associated with the acquisition of mesenchymal characteristics by a subset of pancreatic cancer cells. The factors driving the development of this subset are not well understood. In this study, we tested the hypothesis that acquisition of a mesenchymal phenotype occurs selectively in tumor cells that harbor specific enabling genetic alterations. We obtained whole-genome comparative genomic hybridization (CGH) measurements on pancreatic cancer cell lines that have either an epithelial-like (17 cell lines) or a mesenchymal-like (9 cell lines) phenotype in vitro. The total amounts of amplifications and deletions were equivalent between the epithelial and mesenchymal groups, but 20 genes showed a major difference between the groups in prevalence of alterations. All 20 alterations (18 deletions and 2 amplifications) were more prevalent in the mesenchymal group, confirming the advanced nature of this cellular subtype. CDKN2A was altered in more than 50% of both groups, but co-deletions in neighboring genes, and concomitant loss of gene expression, were more prevalent in the mesenchymal group, suggesting that the size of the loss around CDKN2A affects cell phenotype. Whole-genome CGH on 11 primary cancer tissues revealed that the 20 genes were altered at a higher prevalence (up to 55% of the cases for certain genes) than randomly selected sets of 20 genes, with the same direction of alteration as in the cell lines. These findings support the concept that specific genetic alterations enable phenotype plasticity and provide promising candidate genes for further research.

Autoregressive higher-order hidden Markov models: exploiting local chromosomal dependencies in the analysis of tumor expression profiles

Changes in gene expression programs play a central role in cancer. Chromosomal aberrations such as deletions, duplications and translocations of DNA segments can lead to highly significant positive correlations of gene expression levels of neighboring genes. This should be utilized to improve the analysis of tumor expression profiles. Here, we develop a novel model class of autoregressive higher-order Hidden Markov Models (HMMs) that carefully exploit local data-dependent chromosomal dependencies to improve the identification of differentially expressed genes in tumor. Autoregressive higher-order HMMs overcome generally existing limitations of standard first-order HMMs in the modeling of dependencies between genes in close chromosomal proximity by the simultaneous usage of higher-order state-transitions and autoregressive emissions as novel model features. We apply autoregressive higher-order HMMs to the analysis of breast cancer and glioma gene expression data and perform in-depth model evaluation studies. We find that autoregressive higher-order HMMs clearly improve the identification of overexpressed genes with underlying gene copy number duplications in breast cancer in comparison to mixture models, standard first- and higher-order HMMs, and other related methods. The performance benefit is attributed to the simultaneous usage of higher-order state-transitions in combination with autoregressive emissions. This benefit could not be reached by using each of these two features independently. We also find that autoregressive higher-order HMMs are better able to identify differentially expressed genes in tumors independent of the underlying gene copy number status in comparison to the majority of related methods. This is further supported by the identification of well-known and of previously unreported hotspots of differential expression in glioblastomas demonstrating the efficacy of autoregressive higher-order HMMs for the analysis of individual tumor expression profiles. Moreover, we reveal interesting novel details of systematic alterations of gene expression levels in known cancer signaling pathways distinguishing oligodendrogliomas, astrocytomas and glioblastomas. An implementation is available under www.jstacs.de/index.php/ARHMM.

Purification, crystallization and preliminary X-ray diffraction analysis of the kinase domain of human tousled-like kinase 2

Tousled-like kinases (TLKs) are an evolutionarily conserved family of serine/threonine protein kinases involved in chromatin dynamics, including DNA replication and repair, transcription and chromosome segregation. The two members of the family reported in humans, namely TLK1 and TLK2, localize to the cell nucleus and are capable of forming homo- or hetero-oligomers by themselves. To characterize the role of TLK2, its C-terminal kinase domain was cloned and overexpressed in Escherichia coli followed by purification to homogeneity. Crystallization experiments in the presence of ATP-γ-S yielded crystals suitable for X-ray diffraction analysis belonging to two different space groups: tetragonal I4122 and cubic P213. The latter produced the best diffracting crystal (3.4 Å resolution using synchrotron radiation), with unit-cell parameters a = b = c = 126.05 Å, α = β = γ = 90°. The asymmetric unit contained one protein molecule, with a Matthews coefficient of 4.59 Å(3) Da(-1) and a solvent content of 73.23%.

Detection of candidate tumor driver genes using a fully integrated Bayesian approach

DNA copy number alterations (CNAs), including amplifications and deletions, can result in significant changes in gene expression and are closely related to the development and progression of many diseases, especially cancer. For example, CNA-associated expression changes in certain genes (called candidate tumor driver genes) can alter the expression levels of many downstream genes through transcription regulation and cause cancer. Identification of such candidate tumor driver genes leads to discovery of novel therapeutic targets for personalized treatment of cancers. Several approaches have been developed for this purpose by using both copy number and gene expression data. In this study, we propose a Bayesian approach to identify candidate tumor driver genes, in which the copy number and gene expression data are modeled together, and the dependency between the two data types is modeled through conditional probabilities. The proposed joint modeling approach can identify CNA and differentially expressed genes simultaneously, leading to improved detection of candidate tumor driver genes and comprehensive understanding of underlying biological processes. We evaluated the proposed method in simulation studies, and then applied to a head and neck squamous cell carcinoma data set. Both simulation studies and data application show that the joint modeling approach can significantly improve the performance in identifying candidate tumor driver genes, when compared with other existing approaches.

Intra- and inter-individual variance of gene expression in clinical studies

Background

Variance in microarray studies has been widely discussed as a critical topic on the identification of differentially expressed genes; however, few studies have addressed the influence of estimating variance.

Methodology/Principal Findings

To break intra- and inter-individual variance in clinical studies down to three levels–technical, anatomic, and individual–we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of “inter-individual variable genes” were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduces/eliminates the effects of underestimated variance.

Conclusions/Significance

Our data demonstrated that correct variance evaluation is critical in selecting significant genes. If the degree of variance is underestimated, “noisy” genes are falsely identified as differentially expressed genes. These genes are the noise associated with biological interpretation, reducing the biological significance of the gene set. Our results also indicate that applying a higher number of fold change as the selection criteria reduces/eliminates the differences between distinct estimations of variance.

Integration of DNA copy number alterations and transcriptional expression analysis in human gastric cancer

Background

Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level.

Principal Findings

We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12–20q13.1 (12/72), 20q13.1–20q13.2 (11/72) and 20q13.2–20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis.

Conclusions

This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets.

Segmental chromosome aberrations converge on overexpression of mitotic spindle regulatory genes in high-risk neuroblastoma

Integration of genome-wide profiles of DNA copy number alterations (CNAs) and gene expression variations (GEVs) could provide combined power to the identification of driver genes and gene networks in tumors. Here we merge matched genome and transcriptome microarray analyses from neuroblastoma samples to derive correlation patterns of CNAs and GEVs, irrespective of their genomic location. Neuroblastoma correlation patterns are strongly asymmetrical, being on average 10 CNAs linked to 1 GEV, and show the widespread prevalence of long range covariance. Functional enrichment and network analysis of the genes covarying with CNAs consistently point to a major cell function, the regulation of mitotic spindle assembly. Moreover, elevated expression of 14 key genes promoting this function is strongly associated to high-risk neuroblastomas with 1p loss and MYCN amplification in a set of 410 tumor samples (P < 0.00001). Independent CNA/GEV profiling on neuroblastoma cell lines shows that increased levels of expression of these genes are linked to 1p loss. By this approach, we reveal a convergence of clustered neuroblastoma CNAs toward increased expression of a group of prognostic and functionally cooperating genes. We therefore propose gain of function of the spindle assembly machinery as a lesion potentially offering new targets for therapy of high-risk neuroblastoma.

GSVD comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival

Despite recent large-scale profiling efforts, the best prognostic predictor of glioblastoma multiforme (GBM) remains the patient's age at diagnosis. We describe a global pattern of tumor-exclusive co-occurring copy-number alterations (CNAs) that is correlated, possibly coordinated with GBM patients' survival and response to chemotherapy. The pattern is revealed by GSVD comparison of patient-matched but probe-independent GBM and normal aCGH datasets from The Cancer Genome Atlas (TCGA). We find that, first, the GSVD, formulated as a framework for comparatively modeling two composite datasets, removes from the pattern copy-number variations (CNVs) that occur in the normal human genome (e.g., female-specific X chromosome amplification) and experimental variations (e.g., in tissue batch, genomic center, hybridization date and scanner), without a-priori knowledge of these variations. Second, the pattern includes most known GBM-associated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in >3% of the patients. These include the biochemically putative drug target, cell cycle-regulated serine/threonine kinase-encoding TLK2, the cyclin E1-encoding CCNE1, and the Rb-binding histone demethylase-encoding KDM5A. Third, the pattern provides a better prognostic predictor than the chromosome numbers or any one focal CNA that it identifies, suggesting that the GBM survival phenotype is an outcome of its global genotype. The pattern is independent of age, and combined with age, makes a better predictor than age alone. GSVD comparison of matched profiles of a larger set of TCGA patients, inclusive of the initial set, confirms the global pattern. GSVD classification of the GBM profiles of an independent set of patients validates the prognostic contribution of the pattern.

Parsimonious higher-order hidden Markov models for improved array-CGH analysis with applications to Arabidopsis thaliana

Array-based comparative genomic hybridization (Array-CGH) is an important technology in molecular biology for the detection of DNA copy number polymorphisms between closely related genomes. Hidden Markov Models (HMMs) are popular tools for the analysis of Array-CGH data, but current methods are only based on first-order HMMs having constrained abilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. Here, we develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling spatial dependencies. We apply parsimonious higher-order HMMs to the analysis of Array-CGH data of the accessions C24 and Col-0 of the model plant Arabidopsis thaliana. We compare these models against first-order HMMs and other existing methods using a reference of known deletions and sequence deviations. We find that parsimonious higher-order HMMs clearly improve the identification of these polymorphisms. Moreover, we perform a functional analysis of identified polymorphisms revealing novel details of genomic differences between C24 and Col-0. Additional model evaluations are done on widely considered Array-CGH data of human cell lines indicating that parsimonious HMMs are also well-suited for the analysis of non-plant specific data. All these results indicate that parsimonious higher-order HMMs are useful for Array-CGH analyses. An implementation of parsimonious higher-order HMMs is available as part of the open source Java library Jstacs (www.jstacs.de/index.php/PHHMM).

Array-based comparative genomics is a standard approach for the identification of DNA copy number polymorphisms between closely related genomes. The huge amounts of data produced by these experiments require efficient and accurate bioinformatics tools for the identification of copy number polymorphisms. Hidden Markov Models (HMMs) are frequently used for analyzing such data sets, but current models are based on first-order HMMs only having limited capabilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. We develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling these dependencies to overcome this limitation. In an in-depth case study with Arabidopsis thaliana, we find that parsimonious higher-order HMMs clearly improve the identification of copy number polymorphisms in comparison to standard first-order HMMs and other frequently used methods. Functional analysis of identified polymorphisms revealed details of genomic differences between the accessions C24 and Col-0 of Arabidopsis thaliana. An additional study on human cell lines further indicates that parsimonious HMMs are well-suited for the analysis of Array-CGH data.

Segmented regression, a versatile tool to analyze mRNA levels in relation to DNA copy number aberrations

DNA copy number aberrations (CNA) and subsequent altered gene expression profiles (mRNA levels) are characteristic features of cancerous cells. Integrative genomic analysis aims to identify recurrent CNA that may have a potential role in cancer development, assuming that gene amplification is accompanied by overexpression, while deletions give rise to downregulation of gene expression. We propose a segmented regression-based approach to identify CNA-driven alteration of gene expression profiles. Segmented regression allows to fit piecewise linear models in different domains of CNA joined by a change-point, where the mRNA-CNA relationship undergoes structural changes. Here, we illustrate the implementation and applicability of the proposed model using 1,161 chromosome fragments detected as DNA CNA in primary tumors from 97 breast cancer patients. We identified significant CNA-driven changes in gene expression levels for 341 chromosome fragments, of which 72 showed a nonlinear relationship to CNA. For 59 of 72 chromosome fragments (82%), we observed an initial increase in mRNA levels due to changes in CNA. After the change-point was passed, the mRNA levels reached a plateau, and a further increase in DNA copy numbers did not induce further elevation in mRNA levels. In contrast, for 13 chromosome fragments, the change-point marked the point where mRNA production accelerated. We conclude that segmented regression modeling may provide valuable insights into the impact CNA have on gene expression in cancer cells.

Inferring causal genomic alterations in breast cancer using gene expression data

BACKGROUND

One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies.

RESULTS

We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments.

CONCLUSIONS

To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data.

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.

The ARF tumor suppressor inhibits tumor cell colonization independent of p53 in a novel mouse model of pancreatic ductal adenocarcinoma metastasis

Pancreatic ductal adenocarcinoma (PDAC) is an incurable, highly metastatic disease that is largely resistant to existing treatments. A better understanding of the genetic basis of PDAC metastasis should facilitate development of improved therapies. To that end, we developed a novel mouse xenograft model of PDAC metastasis to expedite testing of candidate genes associated with the disease. Human PDAC cell lines BxPC-3, MiaPaCa-2, and Panc-1 stably expressing luciferase were generated and introduced by intracardiac injections into immunodeficient mice to model hematogenous dissemination of cancer cells. Tumor development was monitored by bioluminescence imaging. Bioluminescent MiaPaCa-2 cells most effectively recapitulated PDAC tumor development and metastatic distribution in vivo. Tumors formed in nearly 90% of mice and in multiple tissues, including normal sites of PDAC metastasis. Effects of p14ARF, a known suppressor of PDAC, were tested to validate the model. In vitro, p14ARF acted through a CtBP2-dependent, p53-independent pathway to inhibit MiaPaCa-2-invasive phenotypes, which correlated with reduced tumor cell colonization in vivo. These findings establish a new bioluminescent mouse tumor model for rapidly assessing the biological significance of suspected PDAC metastasis genes. This system may also provide a valuable platform for testing innovative therapies.

Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models

MOTIVATION

Changes in gene expression levels play a central role in tumors. Additional information about the distribution of gene expression levels and distances between adjacent genes on chromosomes should be integrated into the analysis of tumor expression profiles.

RESULTS

We use a Hidden Markov Model with distance-scaled transition matrices (DSHMM) to incorporate chromosomal distances of adjacent genes on chromosomes into the identification of differentially expressed genes in breast cancer. We train the DSHMM by integrating prior knowledge about potential distributions of expression levels of differentially expressed and unchanged genes in tumor. We find that especially the combination of these data and to a lesser extent the modeling of distances between adjacent genes contribute to a substantial improvement of the identification of differentially expressed genes in comparison to other existing methods. This performance benefit is also supported by the identification of genes well known to be associated with breast cancer. That suggests applications of DSHMMs for screening of other tumor expression profiles.

AVAILABILITY

The DSHMM is available as part of the open-source Java library Jstacs (www.jstacs.de/index.php/DSHMM).

LY6K is a novel molecular target in bladder cancer on basis of integrate genome-wide profiling

Background:

The aim of this study is to find a novel molecular target based on chromosomal alteration and array-based gene expression analyses in bladder cancer (BC). We investigated a cancer testis antigen, LY6K, which is located on chromosome 8q24.3.

Methods:

Five BC cell lines were subjected to high-resolution array-comparative genomic hybridisation with 244 000 probes. The expression levels of LY6K mRNA were evaluated in BC cell lines and clinical BC specimens by real-time reverse transcription–PCR. The cell lines were subjected to fluorescence in situ hybridisation of LY6K. Cell viability was evaluated by cell growth, wound healing, and matrigel invasion assays.

Results:

Typical gained loci (P<0.0001) at 6p21.33-p21.32, 8q24.3, 9q34.13, 11q13.1-q14.1, 12q13.12-q13.13, 16p13.3, and 20q11.21-q13.33 were observed in all of the cell lines. We focused on 8q24.3 locus where LY6K gene harbours, and it was the top upregulated one in the gene profile from the BC cell line. LY6K mRNA expression was significantly higher in 91 BCs than in 37 normal bladder epitheliums (P<0.0001). Fluorescence in situ hybridisation validated that the high LY6K mRNA expression was due to gene amplification in the region where the gene harbours. Cell viability assays demonstrated that significant inhibitions of cell growth, migration, and invasion occured in LY6K knock down BC cell lines; converse phenomena were observed in a stable LY6K transfectant; and LY6K knockdown of the transfectant retrieved the original phenotype from the LY6K transfectant.

Conclusion:

Upregulation of the oncogenic LY6K gene located on the gained locus at 8q24.3 may contribute BC development.

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.

19q13 amplification is associated with high grade and stage in pancreatic cancer

Pancreatic cancer is a devastating disease with an extremely poor prognosis, and thus, there is a great need for better diagnostic and therapeutic tools. The 19q13 chromosomal locus is amplified in several cancer types, including pancreatic cancer, but the possible clinical significance of this aberration remains unclear. We used fluorescence in situ hybridization on tissue microarrays containing 357 primary pancreatic tumors, 151 metastases, and 24 local recurrences as well as 120 cancer cell lines from various tissues to establish the frequency of the 19q13 amplification and to find potential correlations to clinical parameters including patient survival. Copy number increases were found in 12.2% of the primary pancreatic tumors and 9.3% of the cell lines, including those derived from bladder, colorectal, ovarian, and thyroid carcinomas. Copy number changes were linked to high grade (P = 0.044) and stage (P = 0.025) tumors, and the average survival time of patients with 19q13 amplification was shorter than that of those without this aberration. Our findings revealed recurrent 19q13 amplification in pancreatic cancer and involvement of the same locus as in bladder, colorectal, ovarian, and thyroid carcinomas. More importantly, the 19q13 amplifications were associated with poor tumor phenotype and showed a trend toward shorter survival.

Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer

Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.

Identification of candidate growth promoting genes in ovarian cancer through integrated copy number and expression analysis

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≥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.

Selective regain of egfr gene copies in CD44+/CD24-/low breast cancer cellular model MDA-MB-468

Background

Increased transcription of oncogenes like the epidermal growth factor receptor (EGFR) is frequently caused by amplification of the whole gene or at least of regulatory sequences. Aim of this study was to pinpoint mechanistic parameters occurring during egfr copy number gains leading to a stable EGFR overexpression and high sensitivity to extracellular signalling. A deeper understanding of those marker events might improve early diagnosis of cancer in suspect lesions, early detection of cancer progression and the prediction of egfr targeted therapies.

Methods

The basal-like/stemness type breast cancer cell line subpopulation MDA-MB-468 CD44^high/CD24^-/low, carrying high egfr amplifications, was chosen as a model system in this study. Subclones of the heterogeneous cell line expressing low and high EGF receptor densities were isolated by cell sorting. Genomic profiling was carried out for these by means of SNP array profiling, qPCR and FISH. Cell cycle analysis was performed using the BrdU quenching technique.

Results

Low and high EGFR expressing MDA-MB-468 CD44⁺/CD24^-/low subpopulations separated by cell sorting showed intermediate and high copy numbers of egfr, respectively. However, during cell culture an increase solely for egfr gene copy numbers in the intermediate subpopulation occurred. This shift was based on the formation of new cells which regained egfr gene copies. By two parametric cell cycle analysis clonal effects mediated through growth advantage of cells bearing higher egfr gene copy numbers could most likely be excluded for being the driving force. Subsequently, the detection of a fragile site distal to the egfr gene, sustaining uncapped telomere-less chromosomal ends, the ladder-like structure of the intrachromosomal egfr amplification and a broader range of egfr copy numbers support the assumption that dynamic chromosomal rearrangements, like breakage-fusion-bridge-cycles other than proliferation drive the gain of egfr copies.

Conclusion

Progressive genome modulation in the CD44⁺/CD24^-/low subpopulation of the breast cancer cell line MDA-MB-468 leads to different coexisting subclones. In isolated low-copy cells asymmetric chromosomal segregation leads to new cells with regained solely egfr gene copies. Furthermore, egfr regain resulted in enhanced signal transduction of the MAP-kinase and PI3-kinase pathway. We show here for the first time a dynamic copy number regain in basal-like/stemness cell type breast cancer subpopulations which might explain genetic heterogeneity. Moreover, this process might also be involved in adaptive growth factor receptor intracellular signaling which support survival and migration during cancer development and progression.

Chromosomal and genomic changes in lung cancer

Lung cancer is a complex spectrum of diseases characterized by extensive genomic instability, which can be detected among both histological subtypes and different foci within a tumor. Conventional and cutting edge investigative technologies have uncovered scores of genomic changes in individual specimens that have been used to characterize specific molecular subtypes. Oncogenes with predominant roles in lung cancer include EGFR, MYC and RAS family members, PIK3CA, NKX2-1 and ALK; tumor suppressor genes include TP53, RB1, CDKN2, and a cluster of genes mapped at 3p. MicroRNA regulators also have been linked to lung cancer. The functional role of the recurrent genomic changes in lung tumors has been explored, which has led to a better understanding of cell growth, differentiation and apoptotic pathways. Additionally, this knowledge has supported the development of novel therapeutics and translational tools for selection of patients for personalized therapy.

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.

Integrated analysis of copy number alteration and RNA expression profiles of cancer using a high-resolution whole-genome oligonucleotide array

Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.

DNA profiling by array comparative genomic hybridization (CGH) of peripheral blood mononuclear cells (PBMC) and tumor tissue cell in non-small cell lung cancer (NSCLC)

Lung tumor cell DNA copy number alteration (CNA) was expected to display specific patterns such as a large-scale amplification or deletion of chromosomal arms, as previously published data have reported. Peripheral blood mononuclear cell (PBMC) CNA however, was expected to show normal variations in cancer patients as well as healthy individuals, and has thus been used as normal control DNA samples in various published studies. We performed array CGH to measure and compare genetic changes in terms of the CNA of PBMC samples as well as DNA isolated from tumor tissue samples, obtained from 24 non-small cell lung cancer patients. Contradictory to expectations, our studies showed that the PBMC CNA also showed chromosomal variant regions. The list included well-known tumor-associated NTRK1, FGF8, TP53, and TGFbeta1 genes and potentially novel oncogenes such as THPO (3q27.1), JMJD1B, and EGR1 (5q31.2), which was investigated in this study. The results of this study highlighted the connection between PBMC and tumor cell genomic DNA in lung cancer patients. However, the application of these studies to cancer prognosis may pose a challenge due to the large amount of information contained in genetic predisposition and family history that has to be processed for useful downstream clinical applications.

The galanin signaling cascade is a candidate pathway regulating oncogenesis in human squamous cell carcinoma

To identify putative biomarkers in squamous cell carcinoma (SCC), a survey of parallel chromosomal alterations and gene expression studies in 10 SCC cell lines were performed using array-comparative genomic hybridization (CGH) and oligo-microarray techniques. The most frequent changes were gains of 11q13.1-13.3 and losses of 18q12.1-23 in SCC. Furthermore, the expression levels of the sets of genes at both these loci in SCC were measured using microarray analysis. By combining the array-CGH with the microarray data, 10 genes at 11q13.1-13.3 and 6 genes at 18q12.1-23 whose expression correlated with chromosomal alterations were identified. To verify the expression levels of the identified genes, we used expression analysis data derived from our earlier study of clinical specimens. In clinical samples, six genes (GAL, GSTP1, MRPL11, MRPL21, SF3B2, and YIF1A) at 11q13.1-13.3 and one gene (GALR1) at 18q23 showed a significant difference between normal and tumor samples. GAL, coding for the neuropeptide galanin, and GALR1, a galanin receptor, were identified as candidate genes of oncogenesis in SCC. The expression levels of GAL, GALR1, GALR2, and GALR3 were confirmed by real-time PCR. The expression ratio between GAL and GALR1 showed a significant negative correlation. GALR1 is a G-protein-coupled receptor that activates GTP-binding proteins to trigger signaling cascades such as the mitogen-activated protein kinase pathway, and is a well-established mitogenic pathway. This further supports the hypothesis that the genes involved in the GAL signaling cascade are candidates for regulation of oncogenesis in SCC.

Genomic characterization of esophageal squamous cell carcinoma from a high-risk population in China

Genomic instability plays an important role in most human cancers. To characterize genomic instability in esophageal squamous cell carcinoma (ESCC), we examined loss of heterozygosity (LOH), copy number (CN) loss, CN gain, and gene expression using the Affymetrix GeneChip Human Mapping 500K (n = 30 cases) and Human U133A (n = 17 cases) arrays in ESCC cases from a high-risk region of China. We found that genomic instability measures varied widely among cases and separated them into two groups: a high-frequency instability group (two-thirds of all cases with one or more instability category of > or =10%) and a low-frequency instability group (one-third of cases with instability of <10%). Genomic instability also varied widely across chromosomal arms, with the highest frequency of LOH on 9p (33% of informative single nucleotide polymorphisms), CN loss on 3p (33%), and CN gain on 3q (48%). Twenty-two LOH regions were identified: four on 9p, seven on 9q, four on 13q, two on 17p, and five on 17q. Three CN loss regions-3p12.3, 4p15.1, and 9p21.3-were detected. Twelve CN gain regions were found, including six on 3q, one on 7q, four on 8q, and one on 11q. One of the most gene-rich of these CN gain regions was 11q13.1-13.4, where 26 genes also had RNA expression data available. CN gain was significantly correlated with increased RNA expression in over 80% of these genes. Our findings show the potential utility of combining CN analysis and gene expression data to identify genes involved in esophageal carcinogenesis.

A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets

The integration of high-throughput genomic data represents an opportunity for deciphering the interplay between structural and functional organization of genomes and for discovering novel biomarkers. However, the development of integrative approaches to complement gene expression (GE) data with other types of gene information, such as copy number (CN) and chromosomal localization, still represents a computational challenge in the genomic arena. This work presents a computational procedure that directly integrates CN and GE profiles at genome-wide level. When applied to DNA/RNA paired data, this approach leads to the identification of Significant Overlaps of Differentially Expressed and Genomic Imbalanced Regions (SODEGIR). This goal is accomplished in three steps. The first step extends to CN a method for detecting regional imbalances in GE. The second part provides the integration of CN and GE data and identifies chromosomal regions with concordantly altered genomic and transcriptional status in a tumor sample. The last step elevates the single-sample analysis to an entire dataset of tumor specimens. When applied to study chromosomal aberrations in a collection of astrocytoma and renal carcinoma samples, the procedure proved to be effective in identifying discrete chromosomal regions of coordinated CN alterations and changes in transcriptional levels.

The pathology and genetics of metastatic pancreatic cancer

CONTEXT

Metastatic disease is the most critical determinant of resectability of pancreatic cancer and accounts for the poor outcome of patients with this disease. Thus, a better understanding of metastatic pancreatic cancer will afford new opportunities for therapeutic intervention.

OBJECTIVE

To summarize and discuss the current understanding of the clinical and molecular features of metastatic pancreatic cancer.

DATA SOURCES

Published literature on advanced stage pancreatic cancer, pancreatic cancer metastasis, and autopsy findings in patients with pancreatic cancer.

CONCLUSIONS

In the clinical setting, it can be difficult to distinguish a metastatic pancreatic carcinoma from primary neoplasms in the liver, lung, or ovary. However, immunolabeling for DPC4 protein as part of a diagnostic panel is useful for making this distinction. Emerging data from a variety of investigators now indicate that overexpression of EphA2, loss of DPC4 and MKK4, and aberrant activation of the Hedgehog signaling pathway are associated with metastatic propensity of pancreatic cancers, providing novel therapeutic targets for the most lethal stage of this disease.

Genome-wide analysis of DNA copy number alterations and gene expression in gastric cancer

Genomic copy number aberrations (CNAs) are believed to play a major role in the development and progression of human cancers. Although many CNAs have been reported in gastric cancer, their genome-wide transcriptional consequences are poorly understood. In this study, to reveal the impact of CNAs on genome-wide expression in gastric cancer, we analysed 30 cases of gastric cancers for their CNAs by array comparative genomic hybridization (array CGH) and 24 of these 30 cases for their expression profiles by oligonucleotide-expression microarray. We found that with the application of laser microdissection, most CNAs were detected at higher frequency than in previous studies. Notably, gain at 20q13 was detected in almost all cases (97%), suggesting that this may play an important role in the pathogenesis of gastric cancer. By comparing the array CGH data with expression profiles of the same samples, we showed that both genomic amplification and deletion strongly influence the expression of genes in altered genomic regions. Furthermore, we identified 125 candidate genes, consisting of 114 up-regulated genes located in recurrent regions (>10%) of amplification and 11 down-regulated genes located in recurrent regions of deletion. Up-regulation of several candidate genes, such as CDC6, SEC61G, ANP32E, BYSL and FDFT1, was confirmed by immunohistochemistry. Interestingly, some candidate genes were localized at genomic loci adjacent to well-known genes such as EGFR, ERBB2 and SMAD4, and concordantly deregulated by genomic alterations. Based on these results, we propose that our list of candidate genes may contain novel genes involved in the pathogenesis of advanced gastric cancer.

Evolving strategies for global gene expression analysis of cancer

The advent of high throughput gene expression profiling, from microarrays to sequence based assays has yielded vast insight into the biology of tumors. New technologies are constantly being unveiled which promise to generate more accurate maps of tumor gene deregulation, and demand the development of new strategies in data analysis. This review details the challenges faced in profiling tumor transcriptomes, and highlights the emerging strategies to utilize global profiling approaches to advance our understanding of causal genetic and epigenetic events and their impact on gene expression and tumor phenotype and behavior, through high throughput profiling, and integration of multiple dimensions of genomic data.

High-resolution array-based comparative genomic hybridization of bladder cancers identifies mouse double minute 4 (MDM4) as an amplification target exclusive of MDM2 and TP53

PURPOSE

Loss of p53 function in urothelial cell carcinoma (UCC) by mutation or inactivation disrupts normal cell cycle checkpoints, generating a favorable milieu for genomic instability, a hallmark of UCC. The aim of this study was to characterize novel DNA copy number changes to identify putative therapeutic targets.

EXPERIMENTAL DESIGN

We report our findings using array comparative genomic hybridization on a whole-genome BAC/PAC/cosmid array with a median clone interval of 0.97 Mb to study a series of UCC cases. TP53 status was determined by direct sequencing, and an in-house tissue microarray was constructed to identify protein expression of target genes.

RESULTS

Array comparative genomic hybridization allowed identification of novel regions of copy number changes in addition to those already known from previous studies. A novel amplification previously unreported in UCC was identified at 1q32. A chromosome 1 tile path array was used to analyze tumors that showed gains and amplification; the mouse double minute 4 (MDM4) homologue was identified as the amplified gene. MDM4 mRNA expression correlated with copy number and tumor grade. Copy number changes of MDM4 and MDM2 occurred exclusively in tumors with wild-type p53. Overexpression of MDM4 corresponded to disruption of p53 transcriptional activity. Immunohistochemistry on an independent series by tissue microarray identified an inverse relationship between Mdm4 and Mdm2, with Mdm4 expression highest in invasive UCC.

CONCLUSION

The data indicate that gain/amplification and overexpression of MDM4 is a novel molecular mechanism by which a subset of UCC escapes p53-dependent growth control, thus providing new avenues for therapeutic intervention.

PIK3CA mutations and copy number gains in human lung cancers

We investigated the frequency and function of mutations and increased copy number of the PIK3CA gene in lung cancers. PIK3CA mutations are one of the most common gene changes present in human cancers. We analyzed the mutational status of exons 9 and 20 and gene copy number of PIK3CA using 86 non-small cell lung cancer (NSCLC) cell lines, 43 small cell lung cancer (SCLC) cell lines, 3 extrapulmonary small cell cancer (ExPuSC) cell lines, and 691 resected NSCLC tumors and studied the relationship between PIK3CA alterations and mutational status of epidermal growth factor receptor (EGFR) signaling pathway genes (EGFR, KRAS, HER2, and BRAF). We also determined PIK3CA expression and activity and correlated the findings with effects on cell growth. We identified mutations in 4.7% of NSCLC cell lines and 1.6% of tumors of all major histologic types. Mutations in cell lines of small cell origin were limited to two ExPuSC cell lines. PIK3CA copy number gains were more frequent in squamous cell carcinoma (33.1%) than in adenocarcinoma (6.2%) or SCLC lines (4.7%). Mutational status of PIK3CA was not mutually exclusive to EGFR or KRAS. PIK3CA alterations were associated with increased phosphatidylinositol 3-kinase activity and phosphorylated Akt expression. RNA interference-mediated knockdown of PIK3CA inhibited colony formation of cell lines with PIK3CA mutations or gains but was not effective in PIK3CA wild-type cells. PIK3CA mutations or gains are present in a subset of lung cancers and are of functional importance.

Human PAF complexes in endocrine tumors and pancreatic cancer

The human RNA polymerase II-associated factor (hPAF) complex is comprised of five subunits that include hPaf1, parafibromin, hLeo1, hCtr9 and hSki8. This multifaceted complex was first identified in yeast (yPAF) and subsequently in Drosophila and humans. Recent advances in the study on hPAF have revealed various functions of the complex in humans that are similar to yPAF, including efficient transcription elongation, mRNA quality control and cell cycle regulation. A major component of the hPAF complex, hPaf1, is amplified and overexpressed in pancreatic cancer. The parafibromin subunit of the hPAF complex is a product of the hereditary hyperparathyroidism type 2 (HRPT-2) tumor-suppressor gene, which is mutated in the germ line of hyperparathyroidism-jaw tumor patients. This review evaluates the role of the hPAF complex and its individual subunits in endocrine and pancreatic cancers. It focuses on the functions of the hPAF complex and its individual subunits and dysregulation of the complex, thus providing an insight into its potential involvement in the development of endocrine cancers and other tumor types.

DNA amplification is a ubiquitous mechanism of oncogene activation in lung and other cancers

Chromosomal translocation is the best-characterized genetic mechanism for oncogene activation. However, there are documented examples of activation by alternate mechanisms, for example gene dosage increase, though its prevalence is unclear. Here, we answered the fundamental question of the contribution of DNA amplification as a molecular mechanism driving oncogenesis. Comparing 104 cancer lines representing diverse tissue origins identified genes residing in amplification 'hotspots' and discovered an unexpected frequency of genes activated by this mechanism. The 3431 amplicons identified represent approximately 10 per hematological and approximately 36 per epithelial cancer genome. Many recurrently amplified oncogenes were previously known to be activated only by disease-specific translocations. The 135 hotspots identified contain 538 unique genes and are enriched for proliferation, apoptosis and linage-dependency genes, reflecting functions advantageous to tumor growth. Integrating gene dosage with expression data validated the downstream impact of the novel amplification events in both cell lines and clinical samples. For example, multiple downstream components of the EGFR-family-signaling pathway, including CDK5, AKT1 and SHC1, are overexpressed as a direct result of gene amplification in lung cancer. Our findings suggest that amplification is far more common a mechanism of oncogene activation than previously believed and that specific regions of the genome are hotspots of amplification.

Global associations between copy number and transcript mRNA microarray data: an empirical study

With an increasing number of cancer profiling studies assaying both transcript mRNA and copy number expression levels, a natural question then involves the potential to combine information across the two types of genomic data. In this article, we perform a study to assess the nature of association between the two types of data across several experiments. We report on several interesting findings: 1) global correlation between gene expression and copy number is relatively weak but consistent across studies; 2) there is strong evidence for a cis-dosage effect of copy number on gene expression; 3) segmenting the copy number levels helps to improve correlations.