Visualizing Chromosomes as Transcriptome Correlation Maps: Evidence of Chromosomal Domains Containing Co-expressed Genes—A Study of 130 Invasive Ductal Breast Carcinomas

A CTCF-Binding Element and Histone Deacetylation Cooperatively Maintain Chromatin Loops, Linking to Long-Range Gene Regulation in Cancer Genomes

Background

Genes spanning long chromosomal domains are coordinately regulated in human genome, which contribute to global gene dysregulation and carcinogenesis in cancer. It has been noticed that epigenetic modification and chromatin architecture may participate in the regulation process. However, the regulation patterns and functional elements of long-range gene regulation are unclear.

Methods

Based on the clinical transcriptome data from different tumor sets, a novel expressional correlation analysis pipeline was performed to classify the co-regulated regions and subsets of intercorrelated regions. The GLAM2 program was used to predict conserved DNA elements that enriched in regions. Two conserved elements were selected to delete in Ishikawa and HeLa cells by CRISPR-Cas9. SAHA treatment and HDAC knockdown were used to change the histone acetylation status. Using qPCR, MTT, and scratch healing assay, we evaluate the effect on gene expression and cancer cell phenotype. By DNA pull-down and ChIP, the element-binding proteins were testified. 3C and 3D-FISH were performed to depict the alteration in chromatin architecture.

Results

In multiple cancer genomes, we classified subsets of coordinately regulated regions (sub-CRRs) that possibly shared the same regulatory mechanisms and exhibited similar expression patterns. A new conserved DNA element (CRE30) was enriched in sub-CRRs and associated with cancer patient survival. CRE30 could restrict gene regulation in sub-CRRs and affect cancer cell phenotypes. DNA pull-down showed that multiple proteins including CTCF were recruited on the CRE30 locus, and ChIP assay confirmed the CTCF-binding signals. Subsequent results uncovered that as an essential element, CRE30 maintained chromatin loops and mediated a compact chromatin architecture. Moreover, we found that blocking global histone deacetylation induced chromatin loop disruption and CTCF dropping in the region containing CRE30, linked to promoted gene regulation. Additionally, similar effects were observed with CRE30 deletion in another locus of chromosome 8.

Conclusions

Our research clarified a new functional element that recruits CTCF and collaborates with histone deacetylation to maintain high-order chromatin organizations, linking to long-range gene regulation in cancer genomes. The findings highlight a close relationship among conserved DNA element, epigenetic modification, and chromatin architecture in long-range gene regulation process.

Gravitational Force-Induced 3D Chromosomal Conformational Changes Are Associated with Rapid Transcriptional Response in Human T Cells

The mechanisms underlying gravity perception in mammalian cells are unknown. We have recently discovered that the transcriptome of cells in the immune system, which is the most affected system during a spaceflight, responds rapidly and broadly to altered gravity. To pinpoint potential underlying mechanisms, we compared gene expression and three-dimensional (3D) chromosomal conformational changes in human Jurkat T cells during the short-term gravitational changes in parabolic flight and suborbital ballistic rocket flight experiments. We found that differential gene expression in gravity-responsive chromosomal regions, but not differentially regulated single genes, are highly conserved between different real altered gravity comparisons. These coupled gene expression effects in chromosomal regions could be explained by underlying chromatin structures. Based on a high-throughput chromatin conformation capture (Hi-C) analysis in altered gravity, we found that small chromosomes (chr16–22, with the exception of chr18) showed increased intra- and interchromosomal interactions in altered gravity, whereby large chromosomes showed decreased interactions. Finally, we detected a nonrandom overlap between Hi-C-identified chromosomal interacting regions and gravity-responsive chromosomal regions (GRCRs). We therefore demonstrate the first evidence that gravitational force-induced 3D chromosomal conformational changes are associated with rapid transcriptional response in human T cells. We propose a general model of cellular sensitivity to gravitational forces, where gravitational forces acting on the cellular membrane are rapidly and mechanically transduced through the cytoskeleton into the nucleus, moving chromosome territories to new conformation states and their genes into more expressive or repressive environments, finally resulting in region-specific differential gene expression.

The “Gene Cube”: A Novel Approach to Three-dimensional Clustering of Gene Expression Data

Background:

A very popular technique for isolating significant genes from cancerous tissues is the application of various clustering algorithms on data obtained by DNA microarray experiments.

Aim:

The objective of the present work is to take into consideration the chromosomal identity of every gene before the clustering, by creating a three-dimensional structure of the form Chromosomes×Genes×Samples. Further on, the k-Means algorithm and a triclustering technique called δ- TRIMAX, are applied independently on the structure.

Materials and Methods:

The present algorithm was developed using the Python programming language (v. 3.5.1). For this work, we used two distinct public datasets containing healthy control samples and tissue samples from bladder cancer patients. Background correction was performed by subtracting the median global background from the median local Background from the signal intensity. The quantile normalization method has been applied for sample normalization. Three known algorithms have been applied for testing the “gene cube”, a classical k-means, a transformed 3D k-means and the δ-TRIMAX.

Results:

Our proposed data structure consists of a 3D matrix of the form Chromosomes×Genes×Samples. Clustering analysis of that structure manifested very good results as we were able to identify gene expression patterns among samples, genes and chromosomes. Discussion: to the best of our knowledge, this is the first time that such a structure is reported and it consists of a useful tool towards gene classification from high-throughput gene expression experiments.

Conclusion:

Such approaches could prove useful towards the understanding of disease mechanics and tumors in particular.

WoPPER: Web server for Position Related data analysis of gene Expression in Prokaryotes

The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it

Combinatorial expression of microtubule-associated EB1 and ATIP3 biomarkers improves breast cancer prognosis

PURPOSE

The identification of molecular biomarkers for classification of breast cancer is needed to better stratify the patients and guide therapeutic decisions. The aim of this study was to investigate the value of MAPRE1 gene encoding microtubule-end binding proteins EB1 as a biomarker in breast cancer and evaluate whether combinatorial expression of MAPRE1 and MTUS1 gene encoding EB1-negative regulator ATIP3 may improve breast cancer diagnosis and prognosis.

METHODS

Probeset intensities for MAPRE1 and MTUS1 genes were retrieved from Exonhit splice array analyses of 45 benign and 120 malignant breast tumors for diagnostic purposes. Transcriptomic analyses (U133 Affymetrix array) of one exploratory cohort of 150 invasive breast cancer patients and two independent series of 130 and 155 samples were compared with clinical data of the patients for prognostic studies. A tissue microarray from an independent cohort of 212 invasive breast tumors was immunostained with anti-EB1 and anti-ATIP3 antibodies.

RESULTS

We show that MAPRE1 gene is a diagnostic and prognostic biomarker in breast cancer. High MAPRE1 levels correlate with tumor malignancy, high histological grade and poor clinical outcome. Combination of high-MAPRE1 and low-MTUS1 levels in tumors is significantly associated with tumor aggressiveness and reduced patient survival. IHC studies of combined EB1/ATIP3 protein expression confirmed these results.

CONCLUSIONS

These studies emphasize the importance of studying combinatorial expression of EB1 and ATIP3 genes and proteins rather than each biomarker alone. A population of highly aggressive breast tumors expressing high-EB1/low-ATIP3 may be considered for the development of new molecular therapies.

SegCorr a statistical procedure for the detection of genomic regions of correlated expression

BACKGROUND

Detecting local correlations in expression between neighboring genes along the genome has proved to be an effective strategy to identify possible causes of transcriptional deregulation in cancer. It has been successfully used to illustrate the role of mechanisms such as copy number variation (CNV) or epigenetic alterations as factors that may significantly alter expression in large chromosomal regions (gene silencing or gene activation).

RESULTS

The identification of correlated regions requires segmenting the gene expression correlation matrix into regions of homogeneously correlated genes and assessing whether the observed local correlation is significantly higher than the background chromosomal correlation. A unified statistical framework is proposed to achieve these two tasks, where optimal segmentation is efficiently performed using dynamic programming algorithm, and detection of highly correlated regions is then achieved using an exact test procedure. We also propose a simple and efficient procedure to correct the expression signal for mechanisms already known to impact expression correlation. The performance and robustness of the proposed procedure, called SegCorr, are evaluated on simulated data. The procedure is illustrated on cancer data, where the signal is corrected for correlations caused by copy number variation. It permitted the detection of regions with high correlations linked to epigenetic marks like DNA methylation.

CONCLUSIONS

SegCorr is a novel method that performs correlation matrix segmentation and applies a test procedure in order to detect highly correlated regions in gene expression.

Regulation of miR-200c/141 expression by intergenic DNA-looping and transcriptional read-through

The miR-200 family members have been implicated in stress responses and ovarian tumorigenesis. Here, we find that miR-200c/141 transcription is intimately linked to the transcription of the proximal upstream gene PTPN6 (SHP1) in all physiological conditions tested. PTPN6 and miR-200c/141 are transcriptionally co-regulated by two complementary mechanisms. First, a bypass of the regular PTPN6 polyadenylation signal allows the transcription of the downstream miR-200c/141. Second, the promoters of the PTPN6 and miR-200c/141 transcription units physically interact through a 3-dimensional DNA loop and exhibit similar epigenetic regulation. Our findings highlight that transcription of intergenic miRNAs is a novel outcome of transcriptional read-through and reveal a yet unexplored type of DNA loop associating two closely located promoters. These mechanisms have significant relevance in ovarian cancers and stress response, pathophysiological conditions in which miR-200c/141 exert key functions.

The miR-141/200 familly of micro RNAs control oxidative stress and impact on ovarian tumorigenesis. Here the authors show that the transcription of miR-200c/141 is regulated through transcriptional read-through of the upstream gene PTPN6, and DNA looping linking the PTPN6 and miR-200c/141 promoters.

Breast cancer prognosis risk estimation using integrated gene expression and clinical data

BACKGROUND

Novel prognostic markers are needed so newly diagnosed breast cancer patients do not undergo any unnecessary therapy. Various microarray gene expression datasets based studies have generated gene signatures to predict the prognosis outcomes, while ignoring the large amount of information contained in established clinical markers. Nevertheless, small sample sizes in individual microarray datasets remain a bottleneck in generating robust gene signatures that show limited predictive power. The aim of this study is to achieve high classification accuracy for the good prognosis group and then achieve high classification accuracy for the poor prognosis group.

METHODS

We propose a novel algorithm called the IPRE (integrated prognosis risk estimation) algorithm. We used integrated microarray datasets from multiple studies to increase the sample sizes (∼ 2,700 samples). The IPRE algorithm consists of a virtual chromosome for the extraction of the prognostic gene signature that has 79 genes, and a multivariate logistic regression model that incorporates clinical data along with expression data to generate the risk score formula that accurately categorizes breast cancer patients into two prognosis groups.

RESULTS

The evaluation on two testing datasets showed that the IPRE algorithm achieved high classification accuracies of 82% and 87%, which was far greater than any existing algorithms.

RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

Background. Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification. Methods. We propose a novel method to measure and extract the reliable (biologically true or valid) interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples. Results. The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.

Detection of driver protein complexes in breast cancer metastasis by large-scale transcriptome-interactome integration

With the development of high-throughput gene expression profiling technologies came the opportunity to define genomic signatures predicting clinical condition or cancer patient outcome. However, such signatures show dependency on training set, lack of generalization, and instability, partly due to microarray data topology. Additional issues for analyzing tumor gene expression are that subtle molecular perturbations in driver genes leading to cancer and metastasis (masked in typical differential expression analysis) may provoke expression changes of greater amplitude in downstream genes (easily detected). In this chapter, we are describing an interactome-based algorithm, Interactome-Transcriptome Integration (ITI) that is used to find a generalizable signature for prediction of breast cancer relapse by superimposition of a large-scale protein-protein interaction data (human interactome) over several gene expression datasets. ITI extracts regions in the interactome whose expression is discriminating for predicting relapse-free survival in cancer and allow detection of subnetworks that constitutes a generalizable and stable genomic signature. In this chapter, we describe the practical aspects of running the full ITI pipeline (subnetwork detection and classification) on six microarray datasets.

A siRNA screen identifies RAD21, EIF3H, CHRAC1 and TANC2 as driver genes within the 8q23, 8q24.3 and 17q23 amplicons in breast cancer with effects on cell growth, survival and transformation

RNA interference has boosted the field of functional genomics, by making it possible to carry out 'loss-of-function' screens in cultured cells. Here, we performed a small interfering RNA screening, in three breast cancer cell lines, for 101 candidate driver genes overexpressed in amplified breast tumors and belonging to eight amplicons on chromosomes 8q and 17q, investigating their role in cell survival/proliferation. This screening identified eight driver genes that were amplified, overexpressed and critical for breast tumor cell proliferation or survival. They included the well-described oncogenic driver genes for the 17q12 amplicon, ERBB2 and GRB7. Four of six other candidate driver genes-RAD21 and EIF3H, both on chromosome 8q23, CHRAC1 on chromosome 8q24.3 and TANC2 on chromosome 17q23-were confirmed to be driver genes regulating the proliferation/survival of clonogenic breast cancer cells presenting an amplification of the corresponding region. Indeed, knockdown of the expression of these genes decreased cell viability, through both cell cycle arrest and apoptosis induction, and inhibited the formation of colonies in anchorage-independent conditions, in soft agar. Strategies for inhibiting the expression of these genes or the function of the proteins they encode are therefore of potential value for the treatment of breast cancers presenting amplifications of the corresponding genomic region.

Linking Interactome to Disease

The introduction of high-throughput gene expression profiling technologies (DNA microarrays) in molecular biology and their expected applications to the clinic have allowed the design of predictive signatures linked to a particular clinical condition or patient outcome in a given clinical setting. However, it has been shown that such signatures are prone to several problems: (i) they are heavily unstable and linked to the set of patients chosen for training; (ii) data topology is problematic with regard to the data dimensionality (too many variables for too few samples); (iii) diseases such as cancer are provoked by subtle misregulations which cannot be readily detected by current analysis methods. To find a predictive signature generalizable for multiple datasets, a strategy of superimposition of a large scale of protein-protein interaction data (human interactome) was devised over several gene expression datasets (a total of 2,464 breast cancer tumors were integrated), to find discriminative regions in the interactome (subnetworks) predicting metastatic relapse in breast cancer. This method, Interactome-Transcriptome Integration (ITI), was applied to several breast cancer DNA microarray datasets and allowed the extraction of a signature constituted by 119 subnetworks. All subnetworks have been stored in a relational database and linked to Gene Ontology and NCBI EntrezGene annotation databases for analysis. Exploration of annotations has shown that this set of subnetworks reflects several biological processes linked to cancer and is a good candidate for establishing a network-based signature for prediction of metastatic relapse in breast cancer.

ATIP3, a novel prognostic marker of breast cancer patient survival, limits cancer cell migration and slows metastatic progression by regulating microtubule dynamics

Metastasis, a fatal complication of breast cancer, does not fully benefit from available therapies. In this study, we investigated whether ATIP3, the major product of 8p22 MTUS1 gene, may be a novel biomarker and therapeutic target for metastatic breast tumors. We show that ATIP3 is a prognostic marker for overall survival among patients with breast cancer. Notably, among metastatic tumors, low ATIP3 levels associate with decreased survival of the patients. By using a well-defined experimental mouse model of cancer metastasis, we show that ATIP3 expression delays the time-course of metastatic progression and limits the number and size of metastases in vivo. In functional studies, ATIP3 silencing increases breast cancer cell migration, whereas ATIP3 expression significantly reduces cell motility and directionality. We report here that ATIP3 is a potent microtubule-stabilizing protein whose depletion increases microtubule dynamics. Our data support the notion that by decreasing microtubule dynamics, ATIP3 controls the ability of microtubule tips to reach the cell cortex during migration, a mechanism that may account for reduced cancer cell motility and metastasis. Of interest, we identify a functional ATIP3 domain that associates with microtubules and recapitulates the effects of ATIP3 on microtubule dynamics, cell proliferation, and migration. Our study is a major step toward the development of new personalized treatments against metastatic breast tumors that have lost ATIP3 expression.

Interactome-transcriptome integration for predicting distant metastasis in breast cancer

MOTIVATION

High-throughput gene expression profiling yields genomic signatures that allow the prediction of clinical conditions including patient outcome. However, these signatures have limitations, such as dependency on the training set, and worse, lack of generalization.

RESULTS

We propose a novel algorithm called ITI (interactome-transcriptome integration), to extract a genomic signature predicting distant metastasis in breast cancer by superimposition of large-scale protein-protein interaction data over a compendium of several gene expression datasets. Training on two different compendia showed that the estrogen receptor-specific signatures obtained are more stable (11-35% stability), can be generalized on independent data and performs better than previously published methods (53-74% accuracy).

AVAILABILITY

The ITI algorithm source code from analysis are available under CeCILL from the ITI companion website: http://bioinformatique.marseille.inserm.fr/iti.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of common differentially expressed genes in urinary bladder cancer

Background

Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays.

Purpose

Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays.

Methodology/Principal Findings

BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways.

Conclusions/Significance

The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers.

High PTP4A3 phosphatase expression correlates with metastatic risk in uveal melanoma patients

A high percentage of uveal melanoma patients develop metastatic tumors predominantly in the liver. We studied the molecular profiles derived from gene expression microarrays and comparative genomic hybridization microarrays, to identify genes associated with metastasis in this aggressive cancer. We compared 28 uveal melanomas from patients who developed liver metastases within three years of enucleation with 35 tumors from patients without metastases or who developed metastases more than 3 years after enucleation. Protein tyrosine phosphatase type IV A member 3 (PTP4A3/PRL3), was identified as a strong predictor of metastasis occurrence. We demonstrated that the differential expression of this gene, which maps to 8q24.3, was not merely a consequence of 8q chromosome overrepresentation. PTP4A3 overexpression in uveal melanoma cell lines significantly increased cell migration and invasiveness in vivo, suggesting a direct role for this protein in metastasis. Our findings suggest that PTP4A3 or its cellular substrates could constitute attractive therapeutic targets to treat metastatic uveal melanomas.

Proteomic changes resulting from gene copy number variations in cancer cells

Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts.

In the course of cancer development, cells lose regulation of the cell cycle and quality control of DNA replication. As a result, many genomic alterations accumulate, among them amplifications and deletions of chromosomal regions of varying sizes. Oncogenes that drive transformation often reside in amplified regions, while tumor suppressors are deleted, yet for thousands of genes the effect of altering gene copy number is unknown. Since only genomic alterations that ultimately affect protein levels can have functional importance, a global proteomic approach that directly measures such changes is desirable. Here, we examined output of chromosomal alterations on the proteins in a system-wide manner. We analyzed the global protein expression of cancer cells compared to normal cells using mass-spectrometry–based quantitative proteomics and quantified a large part of the expressed proteome. We compared the protein data to genomic data and matched changes in gene copy number to protein expression level changes for each gene. Overall, gene copy number changes explain only a few percent of observed protein expression changes. Knowledge of when genomic and proteomic changes correlate may help in a better understanding of regulatory mechanisms in tumor development.

Enumerating the gene sets in breast cancer, a "direct" alternative to hierarchical clustering

Background

Two-way hierarchical clustering, with results visualized as heatmaps, has served as the method of choice for exploring structure in large matrices of expression data since the advent of microarrays. While it has delivered important insights, including a typology of breast cancer subtypes, it suffers from instability in the face of gene or sample selection, and an inability to detect small sets that may be dominated by larger sets such as the estrogen-related genes in breast cancer. The rank-based partitioning algorithm introduced in this paper addresses several of these limitations. It delivers results comparable to two-way hierarchical clustering, and much more. Applied systematically across a range of parameter settings, it enumerates all the partition-inducing gene sets in a matrix of expression values.

Results

Applied to four large breast cancer datasets, this alternative exploratory method detects more than thirty sets of co-regulated genes, many of which are conserved across experiments and across platforms. Many of these sets are readily identified in biological terms, e.g., "estrogen", "erbb2", and 8p11-12, and several are clinically significant as prognostic of either increased survival ("adipose", "stromal"...) or diminished survival ("proliferation", "immune/interferon", "histone",...). Of special interest are the sets that effectively factor "immune response" and "stromal signalling".

Conclusion

The gene sets induced by the enumeration include many of the sets reported in the literature. In this regard these inventories confirm and consolidate findings from microarray-based work on breast cancer over the last decade. But, the enumerations also identify gene sets that have not been studied as of yet, some of which are prognostic of survival. The sets induced are robust, biologically meaningful, and serve to reveal a finer structure in existing breast cancer microarrays.

Clinical implications of gene dosage and gene expression patterns in diploid breast carcinoma

PURPOSE

Deregulation of key cellular pathways is fundamental for the survival and expansion of neoplastic cells. In cancer, regulation of gene transcription can be mediated in a variety of ways. The purpose of this study was to assess the impact of gene dosage on gene expression patterns and the effect of other mechanisms on transcriptional levels, and to associate these genomic changes with clinicopathologic parameters.

EXPERIMENTAL DESIGN

We screened 97 invasive diploid breast tumors for DNA copy number alterations and changes in transcriptional levels using array comparative genomic hybridization and expression microarrays, respectively.

RESULTS

The integrative analysis identified an increase in the overall number of genetic alterations during tumor progression and 15 specific genomic regions with aberrant DNA copy numbers in at least 25% of the patient population, i.e., 1q22, 1q22-q23.1, 1q25.3, 1q32.1, 1q32.1-q32.2, 8q21.2-q21.3, 8q22.3, 8q24.3, and 16p11.2 were recurrently gained, whereas 11q25, 16q21, 16q23.3, and 17p12 were frequently lost (P < 0.01). An examination of the expression patterns of genes mapping within the detected genetic aberrations identified 47 unique genes and 1 Unigene cluster significantly correlated between the DNA and relative mRNA levels. In addition, more malignant tumors with normal gene dosage levels displayed a recurrent overexpression of UBE2C, S100A8, and CBX2, and downregulation of LOC389033, STC2, DNALI1, SCUBE2, NME5, SUSD3, SERPINA11, AZGP1, and PIP.

CONCLUSIONS

Taken together, our findings suggest that the dysregulated genes identified here are critical for breast cancer initiation and progression, and could be used as novel therapeutic targets for drug development to complement classical clinicopathologic features.

Coherent expression chromosome cluster analysis reveals differential regulatory functions of amino-terminal and distal parathyroid hormone-related protein domains in prostate carcinoma

Parathyroid hormone-related protein (PTHrP) has a number of cancer-related actions. While best known for causing hypercalcemia of malignancy, it also has effects on cancer cell growth, apoptosis, and angiogenesis. Studying the actions of PTHrP in human cancer is complicated because there are three isoforms and many derived peptides. Several peptides are biologically active at known or presumed cell surface receptors; in addition, the PTHrP-derived molecules can exert effects at the cell nucleus. To address this complexity, we studied gene expression in a DU 145 prostate cancer cell line that was stably transfected with control vector, PTHrP 1-173 and PTHrP 33-173. With this model, regulatory effects of the amino-terminal portion of PTHrP would result only from transduction with the full-length molecule, while effects pertaining to distal sequences would be evident with either construct. Analysis of the expression profiles by microarrays demonstrated nonoverlapping groups of differentially expressed genes. Amino-terminal PTHrP affected groups of genes involved in apoptosis, prostaglandin and sex steroid metabolism, cell-matrix interactions, and cell differentiation, while PTHrP 33-173 caused substantial increases in MHC class I antigen expression. This work demonstrates the distinct biological actions of the amino-terminus compared to distal mid-molecule or carboxy-terminal sequences of PTHrP in prostate carcinoma cells and provides targets for further study of the malignant process.

Complex sense-antisense architecture of TNFAIP1/POLDIP2 on 17q11.2 represents a novel transcriptional structural-functional gene module involved in breast cancer progression

Background

A sense-antisense gene pair (SAGP) is a gene pair where two oppositely transcribed genes share a common nucleotide sequence region. In eukaryotic genomes, SAGPs can be organized in complex sense-antisense architectures (CSAGAs) in which at least one sense gene shares loci with two or more antisense partners. As shown in several case studies, SAGPs may be involved in cancers, neurological diseases and complex syndromes. However, CSAGAs have not yet been characterized in the context of human disease or cancer.

Results

We characterize five genes (TMEM97, IFT20, TNFAIP1, POLDIP2 and TMEM199) organized in a CSAGA on 17q11.2 (we term this the TNFAIP1/POLDIP2 CSAGA) and demonstrate their strong and reproducible co-regulatory transcription pattern in breast cancer tumours. Genes of the TNFAIP1/POLDIP2 CSAGA are located inside the smallest region of recurrent amplification on 17q11.2 and their expression profile correlates with the DNA copy number of the region. Survival analysis of a group of 410 breast cancer patients revealed significant survival-associated individual genes and gene pairs in the TNFAIP1/POLDIP2 CSAGA. Moreover, several of the gene pairs associated with survival, demonstrated synergistic effects. Expression of genes-members of the TNFAIP1/POLDIP2 CSAGA also strongly correlated with expression of genes of ERBB2 core region of recurrent amplification on 17q12. We clearly demonstrate that the observed co-regulatory transcription profile of the TNFAIP1/POLDIP2 CSAGA is maintained not only by a DNA amplification mechanism, but also by chromatin remodelling and local transcription activation.

Conclusion

We have identified a novel TNFAIP1/POLDIP2 CSAGA and characterized its co-regulatory transcription profile in cancerous breast tissues. We suggest that the TNFAIP1/POLDIP2 CSAGA represents a clinically significant transcriptional structural-functional gene module associated with amplification of the genomic region on 17q11.2 and correlated with expression ERBB2 amplicon core genes in breast cancer. Co-expression pattern of this module correlates with histological grades and a poor prognosis in breast cancer when over-expressed. TNFAIP1/POLDIP2 CSAGA maps the risks of breast cancer relapse onto the complex genomic locus on 17q11.2.

Cancer genome analysis informatics

The analysis of cancer genomes has benefited from the advances in technology that enable data to be generated on an unprecedented scale, describing a tumour genome's sequence and composition at increasingly high resolution and reducing cost. This progress is likely to increase further over the coming years as next-generation sequencing approaches are applied to the study of cancer genomes, in tandem with large-scale efforts such as the Cancer Genome Atlas and recently announced International Cancer Genome Consortium efforts to complement those already established such as the Sanger Institute Cancer Genome Project. This presents challenges for the cancer researcher and the research community in general, in terms of analysing the data generated in one's own projects and also in coordinating and interrogating data that are publicly available. This review aims to provide a brief overview of some of the main informatics resources currently available and their use, and some of the informatics approaches that may be applied in the study of cancer genomes.

8p22 MTUS1 gene product ATIP3 is a novel anti-mitotic protein underexpressed in invasive breast carcinoma of poor prognosis

BACKGROUND

Breast cancer is a heterogeneous disease that is not totally eradicated by current therapies. The classification of breast tumors into distinct molecular subtypes by gene profiling and immunodetection of surrogate markers has proven useful for tumor prognosis and prediction of effective targeted treatments. The challenge now is to identify molecular biomarkers that may be of functional relevance for personalized therapy of breast tumors with poor outcome that do not respond to available treatments. The Mitochondrial Tumor Suppressor (MTUS1) gene is an interesting candidate whose expression is reduced in colon, pancreas, ovary and oral cancers. The present study investigates the expression and functional effects of MTUS1 gene products in breast cancer.

METHODS AND FINDINGS

By means of gene array analysis, real-time RT-PCR and immunohistochemistry, we show here that MTUS1/ATIP3 is significantly down-regulated in a series of 151 infiltrating breast cancer carcinomas as compared to normal breast tissue. Low levels of ATIP3 correlate with high grade of the tumor and the occurrence of distant metastasis. ATIP3 levels are also significantly reduced in triple negative (ER- PR- HER2-) breast carcinomas, a subgroup of highly proliferative tumors with poor outcome and no available targeted therapy. Functional studies indicate that silencing ATIP3 expression by siRNA increases breast cancer cell proliferation. Conversely, restoring endogenous levels of ATIP3 expression leads to reduced cancer cell proliferation, clonogenicity, anchorage-independent growth, and reduces the incidence and size of xenografts grown in vivo. We provide evidence that ATIP3 associates with the microtubule cytoskeleton and localizes at the centrosomes, mitotic spindle and intercellular bridge during cell division. Accordingly, live cell imaging indicates that ATIP3 expression alters the progression of cell division by promoting prolonged metaphase, thereby leading to a reduced number of cells ungergoing active mitosis.

CONCLUSIONS

Our results identify for the first time ATIP3 as a novel microtubule-associated protein whose expression is significantly reduced in highly proliferative breast carcinomas of poor clinical outcome. ATIP3 re-expression limits tumor cell proliferation in vitro and in vivo, suggesting that this protein may represent a novel useful biomarker and an interesting candidate for future targeted therapies of aggressive breast cancer.

RCP is a human breast cancer-promoting gene with Ras-activating function

Aggressive forms of cancer are often defined by recurrent chromosomal alterations, yet in most cases, the causal or contributing genetic components remain poorly understood. Here, we utilized microarray informatics to identify candidate oncogenes potentially contributing to aggressive breast cancer behavior. We identified the Rab-coupling protein RCP (also known as RAB11FIP1), which is located at a chromosomal region frequently amplified in breast cancer (8p11-12) as a potential candidate. Overexpression of RCP in MCF10A normal human mammary epithelial cells resulted in acquisition of tumorigenic properties such as loss of contact inhibition, growth-factor independence, and anchorage-independent growth. Conversely, knockdown of RCP in human breast cancer cell lines inhibited colony formation, invasion, and migration in vitro and markedly reduced tumor formation and metastasis in mouse xenograft models. Overexpression of RCP enhanced ERK phosphorylation and increased Ras activation in vitro. As these results indicate that RCP is a multifunctional gene frequently amplified in breast cancer that encodes a protein with Ras-activating function, we suggest it has potential importance as a therapeutic target. Furthermore, these studies provide new insight into the emerging role of the Rab family of small G proteins and their interacting partners in carcinogenesis.

Prednisolone exerts late mitogenic and biphasic effects on resistant acute lymphoblastic leukemia cells: Relation to early gene expression

Resistance or sensitivity to glucocorticoids is considered to be of crucial importance for disease prognosis in childhood acute lymphoblastic leukemia. Prednisolone exerted a delayed biphasic effect on the resistant CCRF-CEM leukemic cell line, necrotic at low doses and apoptotic at higher doses. At low doses, prednisolone exerted a pre-dominant mitogenic effect despite its induction on total cell death, while at higher doses, prednisolone's mitogenic and cell death effects were counterbalanced. Early gene microarray analysis revealed notable differences in 40 genes. The mitogenic/biphasic effects of prednisolone are of clinical importance in the case of resistant leukemic cells. This approach might lead to the identification of gene candidates for future molecular drug targets in combination therapy with glucocorticoids, along with early markers for glucocorticoid resistance.

Genomic imbalances in rhabdomyosarcoma cell lines affect expression of genes frequently altered in primary tumors: an approach to identify candidate genes involved in tumor development

Rhabdomyosarcomas (RMS) are the most common pediatric soft tissue sarcomas. They resemble developing skeletal muscle and are histologically divided into two main subtypes; alveolar and embryonal RMS. Characteristic genomic aberrations, including the PAX3- and PAX7-FOXO1 fusion genes in alveolar cases, have led to increased understanding of their molecular biology. Here, we determined the effect of genomic copy number on gene expression levels through array comparative genomic hybridization (CGH) analysis of 13 RMS cell lines, confirmed by multiplex ligation-dependent probe amplification copy number analyses, combined with their corresponding expression profiles. Genes altered at the transcriptional level by genomic imbalances were identified and the effect on expression was proportional to the level of genomic imbalance. Extrapolating to a public expression profiling dataset for 132 primary RMS identified features common to the cell lines and primary samples and associations with subtypes and fusion gene status. Genes identified such as CDK4 and MYCN are known to be amplified, overexpressed, and involved in RMS tumorigenesis. Of the many genes identified, those with likely functional relevance included CENPF, DTL, MYC, EYA2, and FGFR1. Copy number and expression of FGFR1 was validated in additional primary material and found amplified in 6 out of 196 cases and overexpressed relative to skeletal muscle and myoblasts, with significantly higher expression levels in the embryonal compared with alveolar subtypes. This illustrates the ability to identify genes of potential significance in tumor development through combining genomic and transcriptomic profiles from representative cell lines with publicly available expression profiling data from primary tumors.

Genome-wide analysis identifies a tumor suppressor role for aminoacylase 1 in iron-induced rat renal cell carcinoma

A growing number of studies indicate a link between oxidative stress and cancer. We previously developed a rat model of renal cell carcinoma (RCC) induced by ferric nitrilotriacetate (Fe-NTA). Here, we performed a genome-wide analysis to study characteristics of genomic alteration and identify putative genes involved in the development of Fe-NTA-induced RCCs. Array-based comparative genomic hybridization analyses revealed a chromosomal loss spanning chromosome 8 in most of the RCCs studied, with a common deletion at 8q31-32, which was confirmed by loss of heterozygosity (LOH) analysis. Studies of gene expression in RCCs or following Fe-NTA treatment revealed globally decreased transcription levels of 34 genes derived from chromosome 8 that are expressed in the kidney. Among them, the aminoacylase 1 (Acy1) gene, which maps to 8q32 and is highly expressed in the kidney, displayed a significantly decreased level of expression in RCCs. Significant amounts of the Acy1 protein were detected in the cytoplasm as well as in the nuclei of renal proximal tubular cells of untreated rats. Transfection of Acy1 into RCC cell lines inhibited proliferation and colony formation on soft agar. An increased number of apoptotic cells were observed following Acy1 transfection. The rat 8q31-32 chromosomal region corresponds to human 3p21.31-24.1, a hot spot where LOH is frequently found in various human cancers. Thus, Fe-NTA-induced renal tumor model is ideal for studying the link between deletions within this region and tumor formation. Our data demonstrate that Acy1 functions as a tumor suppressor in this rat RCC model.

Re-expression of transcription factor ATF5 in hepatocellular carcinoma induces G2-M arrest

Transcription factors represent an important class of genes that play key roles in controlling cellular proliferation, cell cycle modulation, and attractive targets for cancer therapy. Here, we report on the novel finding of common ATF5 down-regulations in hepatocellular carcinoma (HCC), a highly malignant tumor with a dismal clinical course. Array-based mapping in HCC highlighted a high and consistent incidence of transcription factor ATF5 repressions on regional chr.19q13. By quantitative reverse transcription-PCR, profound down-regulations of ATF5 were further suggested in 78% of HCC tumors (60 of 77 cases) compared to their adjacent nontumoral liver (P = 0.0004). Restoration of ATF5 expression in 3 nonexpressing HCC cell lines demonstrated a consistent growth inhibitory effect (P < 0.029) but minimal induction on cellular apoptosis. Subsequent flow cytometric investigations revealed a G(2)-M cell cycle arrest in HCC cells that were ectopically transfected with ATF5 (P < 0.002). The differential expressed genes from the functional effects of ATF5 were examined by array profiling. Over a hundred genes were identified, among which ID1 contains the ATF/CREB target binding sequences within its promoter region. An inverse relationship between ATF5 expressions with ID1 transcriptions was verified in HCC (P = 0.019), and a direct interaction of ATF5 on the promoter of ID1 was further demonstrated from electromobility shift assay. Examination of causal events underlying the silencing of ATF5 in HCC suggested copy number losses, promoter hypermethylation, histone deacetylation, and DNA mutations to be the likely inactivating mechanisms. In conclusion, our finding supports a tumor suppressive role for ATF5 in HCC, and highlighted ID1 as a potential downstream target.

Characterization of the recurrent 8p11-12 amplicon identifies PPAPDC1B, a phosphatase protein, as a new therapeutic target in breast cancer

The 8p11-12 chromosome region is one of the regions most frequently amplified in breast carcinoma (10-15% of cases). Several genes within this region have been identified as candidate oncogenes, as they are both amplified and overexpressed. However, very few studies have explored the role of these genes in cell transformation, with the aim of identifying valuable therapeutic targets. An analysis of comparative genomic hybridization array and expression profiling data for a series of 152 ductal breast carcinomas and 21 cell lines identified five genes (LSM1, BAG4, DDHD2, PPAPDC1B, and WHSC1L1) within the amplified region as consistently overexpressed due to an increased gene copy number. The use of small interfering RNA to knock down the expression of each of these genes showed the major role played by two genes, PPAPDC1B and WHSC1L1, in regulating the survival and transformation of two different cell lines harboring the 8p amplicon. The role of these two genes in cell survival and cell transformation was also confirmed by long-term knockdown expression studies using short hairpin RNAs. The potential of PPAPDC1B, which encodes a transmembrane phosphatase, as a therapeutic target was further shown by the strong inhibition of growth of breast tumor xenografts displaying 8p11-12 amplification induced by the silencing of PPAPDC1B. The oncogenic properties of PPAPDC1B were further shown by its ability to transform NIH-3T3 fibroblasts, inducing their anchorage-independent growth. Finally, microarray experiments on PPAPDC1B knockdown indicated that this gene interfered with multiple cell signaling pathways, including the Janus-activated kinase-signal transducer and activator of transcription, mitogen-activated protein kinase, and protein kinase C pathways. PPAPDC1B may also potentiate the estrogen receptor pathway by down-regulating DUSP22.

Integrated genomic and transcriptomic analysis of ductal carcinoma in situ of the breast

PURPOSE

To gain insight into genomic and transcriptomic subtypes of ductal carcinomas in situ of the breast (DCIS).

EXPERIMENTAL DESIGN

We did a combined phenotypic and genomic analysis of a series of 57 DCIS integrated with gene expression profile analysis for 26 of the 57 cases.

RESULTS

Thirty-two DCIS exhibited a luminal phenotype; 21 were ERBB2 positive, and 4 were ERBB2/estrogen receptor (ER) negative with 1 harboring a bona fide basal-like phenotype. Based on a CGH analysis, genomic types were identified in this series of DCIS with the 1q gain/16q loss combination observed in 3 luminal DCIS, the mixed amplifier pattern including all ERBB2, 12 luminal and 2 ERBB2(-)/ER(-) DCIS, and the complex copy number alteration profile encompassing 14 luminal and 1 ERBB2(-)/ER(-) DCIS. Eight cases (8 of 57; 14%) presented a TP53 mutation, all being amplifiers. Unsupervised analysis of gene expression profiles of 26 of the 57 DCIS showed that luminal and ERBB2-amplified, ER-negative cases clustered separately. We further investigated the effect of high and low copy number changes on gene expression. Strikingly, amplicons but also low copy number changes especially on 1q, 8q, and 16q in DCIS regulated the expression of a subset of genes in a very similar way to that recently described in invasive ductal carcinomas.

CONCLUSIONS

These combined approaches show that the molecular heterogeneity of breast ductal carcinomas exists already in in situ lesions and further indicate that DCIS and invasive ductal carcinomas share genomic alterations with a similar effect on gene expression profile.

How basal are triple-negative breast cancers?

The basal molecular subtype of breast cancer (BC) is defined by the mRNA expression pattern of an intrinsic approximately 500-gene set. It is the most homogeneous subtype in transcriptional terms, and one of the most aggressive in prognostic terms. Clinical trials testing new systemic therapeutic strategies have been launched in basal BCs. Although no proof of evidence has yet been reported, basal tumors are currently assimilated to and selected as triple-negative (TN) BCs in these trials because of their frequent immunohistochemical (IHC) negativity for hormone and ERBB2 receptors. Here, we have assessed the degrees of correlation and of homogeneity of the TN phenotype (IHC-based definition) and the basal subtype (gene expression-based definition). We analyzed 172 TN BCs defined by gene expression profile as basal (123 cases) and nonbasal (49 cases). Conversely, 160 tumors were defined as basal by their gene expression profile and included 123 TN and 37 non-TN samples. Uni- and multivariate analyses revealed that TN BCs represent a more heterogeneous group than basal BCs, including basal and nonbasal tumors very different both at the histoclinical and molecular level, notably for mRNA expression of molecules targeted by specific therapies under evaluation in clinical trials. These results call for caution in the interpretation of ongoing trials and selection of patients in future trials. They also warrant the identification of molecular markers for basal BCs more clinically applicable than gene expression profiles.

A future of cancer prevention and cures: highlights of the Centennial Meeting of the American Association for Cancer Research

The Centennial Meeting of the American Association for Cancer Research (AACR) was held from 14-18 April 2007 at the Los Angeles Convention Center. This meeting brought together a diverse group of over 18 000 researchers working in the fields of basic and applied cancer sciences, and explored how cancer research could be used most effectively to prevent and cure cancer at the earliest possible stage. The goal of the AACR Annual Meeting was to stimulate the dialog between basic and clinical researchers so that the translation of new discoveries might be speeded up for the benefit of cancer patients. Advances in the clinical application of genomics, epigenomics and proteomics to diagnose, monitor and prognosticate cancer development led to a dramatic increase in the number of presentations with a translational focus at this year's meeting. Several remarkable areas were particularly highlighted in this report, including The Cancer Genome Atlas, cancer stem cells, microRNA and siRNA, targeted therapy and individualized treatment. This article tries to bring attention to some hot topics in the program that are both new and noteworthy. For those who did not attend the meeting, this report may serve as a highlight of this important international cancer research meeting.

An improved method for detecting and delineating genomic regions with altered gene expression in cancer

A method is presented for identifying genomic regions with altered gene expression in gene expression maps.

Genomic regions with altered gene expression are a characteristic feature of cancer cells. We present a novel method for identifying such regions in gene expression maps. This method is based on total variation minimization, a classical signal restoration technique. In systematic evaluations, we show that our method combines top-notch detection performance with an ability to delineate relevant regions without excessive over-segmentation, making it a significant advance over existing methods. Software (Rendersome) is provided.

Prognosis and gene expression profiling of 20q13-amplified breast cancers

PURPOSE

Amplification of chromosomal region 20q13 occurs in breast cancer but remains poorly characterized.

EXPERIMENTAL DESIGN

To establish the frequency of 20q13 amplification and select the amplified cases to be studied, we used fluorescence in situ hybridization of bacterial artificial chromosome probes for three 20q13 loci (MYBL2, STK6, ZNF217) on sections of tissue microarrays containing 466 primary carcinoma samples. We used Affymetryx whole-genome DNA microarrays to establish the gene expression profiles of 20q13-amplified tumors and quantitative reverse transcription-PCR to validate the results.

RESULTS

We found 36 (8%) 20q13-amplified samples. They were distributed in two types: type 1 tumors showed ZNF217 amplification only, whereas type 2 tumors showed amplification at two or three loci. Examination of the histoclinical features of the amplified tumors showed two strikingly opposite data. First, type 1 tumors were more frequently lymph node-negative tumors but were paradoxically associated with a poor prognosis. Second, type 2 tumors were more frequently lymph node-positive tumors but were paradoxically associated with a good prognosis. Type 1 and type 2 showed different gene expression profiles. No 20q13 gene could be associated with type 1 amplification, whereas several 20q13 genes were overexpressed in type 2 tumors.

CONCLUSIONS

Our results suggest that amplified tumors of types 1 and 2 are two distinct entities resulting from two different mechanisms and associated to different prognosis.

SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets

Background

Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.

Results

We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.

Conclusion

We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.

Genomic expression during human myelopoiesis

Background

Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where multipotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally differentiated cells. This study aimed at investigating the genomic expression during myeloid differentiation through a computational approach that integrates gene expression profiles with functional information and genome organization.

Results

Gene expression data from 24 experiments for 8 different cell types of the human myelopoietic lineage were used to generate an integrated myelopoiesis dataset of 9,425 genes, each reliably associated to a unique genomic position and chromosomal coordinate. Lists of genes constitutively expressed or silent during myelopoiesis and of genes differentially expressed in commitment phase of myelopoiesis were first identified using a classical data analysis procedure. Then, the genomic distribution of myelopoiesis genes was investigated integrating transcriptional and functional characteristics of genes. This approach allowed identifying specific chromosomal regions significantly highly or weakly expressed, and clusters of differentially expressed genes and of transcripts related to specific functional modules.

Conclusion

The analysis of genomic expression during human myelopoiesis using an integrative computational approach allowed discovering important relationships between genomic position, biological function and expression patterns and highlighting chromatin domains, including genes with coordinated expression and lineage-specific functions.

Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes

We have investigated the relationship between gene expression and chromosomal positions in 402 breast cancer patients. Using an overrepresentation approach based on Fisher's exact test, we identified disproportionate contributions of specific chromosomal positions to genes associated with survival. Our major finding is that the gene expression in the long arm of chromosome 16 stands out in its relationship to survival. This arm contributes 36 (18%) and 55 (11%) genes to lists negatively associated with recurrence-free survival (set to sizes 200 and 500). This is a highly disproportionate contribution from the 313 (2%) genes in this arm represented on the used Affymetrix U133A and B microarray platforms (Bonferroni corrected Fisher test: P < 2.2 x 10(-16)). We also demonstrate differential expression in 16q across tumor subtypes, which suggests that the ERBB2, basal, and luminal B tumors progress along a high grade-poor prognosis path, while luminal A and normal-like tumors progress along a low grade-good prognosis path, in accordance with a previously proposed model of tumor progression. We conclude that important biological information can be extracted from gene expression data in breast cancer by studying non-random connections between chromosomal positions and gene expression. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Genomic and transcriptional aberrations linked to breast cancer pathophysiologies

This study explores the roles of genome copy number abnormalities (CNAs) in breast cancer pathophysiology by identifying associations between recurrent CNAs, gene expression, and clinical outcome in a set of aggressively treated early-stage breast tumors. It shows that the recurrent CNAs differ between tumor subtypes defined by expression pattern and that stratification of patients according to outcome can be improved by measuring both expression and copy number, especially high-level amplification. Sixty-six genes deregulated by the high-level amplifications are potential therapeutic targets. Nine of these (FGFR1, IKBKB, ERBB2, PROCC, ADAM9, FNTA, ACACA, PNMT, and NR1D1) are considered druggable. Low-level CNAs appear to contribute to cancer progression by altering RNA and cellular metabolism.

Regional copy number–independent deregulation of transcription in cancer

Genetic and epigenetic alterations have been identified that lead to transcriptional deregulation in cancers. Genetic mechanisms may affect single genes or regions containing several neighboring genes, as has been shown for DNA copy number changes. It was recently reported that epigenetic suppression of gene expression can also extend to a whole region; this is known as long-range epigenetic silencing. Various techniques are available for identifying regional genetic alterations, but no large-scale analysis has yet been carried out to obtain an overview of regional epigenetic alterations. We carried out an exhaustive search for regions susceptible to such mechanisms using a combination of transcriptome correlation map analysis and array CGH data for a series of bladder carcinomas. We validated one candidate region experimentally, demonstrating histone methylation leading to the loss of expression of neighboring genes without DNA methylation.

A genome-wide screen reveals functional gene clusters in the cancer genome and identifies EphA2 as a mitogen in glioblastoma

A novel genome-wide screen that combines patient outcome analysis with array comparative genomic hybridization and mRNA expression profiling was developed to identify genes with copy number alterations, aberrant mRNA expression, and relevance to survival in glioblastoma. The method led to the discovery of physical gene clusters within the cancer genome with boundaries defined by physical proximity, correlated mRNA expression patterns, and survival relatedness. These boundaries delineate a novel genomic interval called the functional common region (FCR). Many FCRs contained genes of high biological relevance to cancer and were used to pinpoint functionally significant DNA alterations that were too small or infrequent to be reliably identified using standard algorithms. One such FCR contained the EphA2 receptor tyrosine kinase. Validation experiments showed that EphA2 mRNA overexpression correlated inversely with patient survival in a panel of 21 glioblastomas, and ligand-mediated EphA2 receptor activation increased glioblastoma proliferation and tumor growth via a mitogen-activated protein kinase-dependent pathway. This novel genome-wide approach greatly expanded the list of target genes in glioblastoma and represents a powerful new strategy to identify the upstream determinants of tumor phenotype in a range of human cancers.

Genetic profiling of chromosome 1 in breast cancer: mapping of regions of gains and losses and identification of candidate genes on 1q

Chromosome 1 is involved in quantitative anomalies in 50-60% of breast tumours. However, the structure of these anomalies and the identity of the affected genes remain to be determined. To characterise these anomalies and define their consequences on gene expression, we undertook a study combining array-CGH analysis and expression profiling using specialised arrays. Array-CGH data showed that 1p was predominantly involved in losses and 1q almost exclusively in gains. Noticeably, high magnitude amplification was infrequent. In an attempt to fine map regions of copy number changes, we defined 19 shortest regions of overlap (SROs) for gains (one at 1p and 18 at 1q) and of 20 SROs for losses (all at 1p). These SROs, whose sizes ranged from 170 kb to 3.2 Mb, represented the smallest genomic intervals possible based on the resolution of our array. The elevated incidence of gains at 1q, added to the well-established concordance between DNA copy increase and augmented RNA expression, made us focus on gene expression changes at this chromosomal arm. To identify candidate oncogenes, we studied the RNA expression profiles of 307 genes located at 1q using a home-made built cDNA array. We identified 30 candidate genes showing significant overexpression correlated to copy number increase. In order to substantiate their involvement, RNA expression levels of these candidate genes were measured by quantitative (Q)-RT-PCR in a panel of 25 breast cancer cell lines previously typed by array-CGH. Q-PCR showed that 11 genes were significantly overexpressed in the presence of a genomic gain in these cell lines, and 20 overexpressed when compared to normal breast.

Using array-comparative genomic hybridization to define molecular portraits of primary breast cancers

We analysed 148 primary breast cancers using BAC-arrays containing 287 clones representing cancer-related gene/loci to obtain genomic molecular portraits. Gains were detected in 136 tumors (91.9%) and losses in 123 tumors (83.1%). Eight tumors (5.4%) did not have any genomic aberrations in the 281 clones analysed. Common (more than 15% of the samples) gains were observed at 8q11-qtel, 1q21-qtel, 17q11-q12 and 11q13, whereas common losses were observed at 16q12-qtel, 11ptel-p15.5, 1p36-ptel, 17p11.2-p12 and 8ptel-p22. Patients with tumors registering either less than 5% (median value) or less than 11% (third quartile) total copy number changes had a better overall survival (log-rank test: P=0.0417 and P=0.0375, respectively). Unsupervised hierarchical clustering based on copy number changes identified four clusters. Women with tumors from the cluster with amplification of three regions containing known breast oncogenes (11q13, 17q12 and 20q13) had a worse prognosis. The good prognosis group (Nottingham Prognostic Index (NPI) <or=3.4) tumors had frequent loss of 16q24-qtel. Genes significantly associated with estrogen receptor (ER), Grade and NPI were used to build k-nearest neighbor (KNN) classifiers that predicted ER, Grade and NPI status in the test set with an average misclassification rate of 24.7, 25.7 and 35.7%, respectively. These data raise the prospect of generating a molecular taxonomy of breast cancer based on copy number profiling using tumor DNA, which may be more generally applicable than expression microarray analysis.

A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions

MOTIVATION

The systematic integration of expression profiles and other types of gene information, such as chromosomal localization, ontological annotations and sequence characteristics, still represents a challenge in the gene expression arena. In particular, the analysis of transcriptional data in context of the physical location of genes in a genome appears promising in detecting chromosomal regions with transcriptional imbalances often characterizing cancer.

RESULTS

A computational tool named locally adaptive statistical procedure (LAP), which incorporates transcriptional data and structural information for the identification of differentially expressed chromosomal regions, is described. LAP accounts for variations in the distance between genes and in gene density by smoothing standard statistics on gene position before testing the significance of their differential levels of gene expression. The procedure smooths parameters and computes p-values locally to account for the complex structure of the genome and to more precisely estimate the differential expression of chromosomal regions. The application of LAP to three independent sets of raw expression data allowed identifying differentially expressed regions that are directly involved in known chromosomal aberrations characteristic of tumors.

AVAILABILITY

Functions in R for implementing the LAP method are available at http://www.dpci.unipd.it/Bioeng/Publications/LAP.htm

Regional activation of chromosomal arm 7q with and without gene amplification in taxane-selected human ovarian cancer cell lines

Taxanes are important drugs in the treatment of ovarian and other cancers, but their efficacy is limited by intrinsic and acquired drug resistance. Expression of the multidrug transporter P-glycoprotein, encoded by the MDR1 (ABCB1) gene, is one of the causes of clinical drug resistance to taxanes. To study the mechanisms of MDR1 activation related to taxanes, we established 11 multidrug-resistant variants from six ovarian cancer cell lines by continuous exposure to either paclitaxel or docetaxel. We profiled gene expression and gene copy number alterations in these cell lines using cDNA microarrays and identified a cluster of genes coactivated with MDR1 in 7q21.11-13. Regional activation was evident in nine resistant variants displaying a coexpression pattern of up to 22 genes over an 8-Mb area, including SRI, MGC4175, CLDN12, CROT, and CDK6. In six of these variants, regional activation was driven by gene copy number alterations, with low-level gains or high-level amplifications spanning the involved region. However, three variants displayed regional increases in gene expression even without concomitant gene copy number changes. These results suggest that regional gene activation may be a fundamental mechanism for acquired drug resistance, with or without changes in gene dosage. In addition to numerical and structural chromosomal changes driven by genome instability in cancer cells, other mechanisms might be involved in MDR1 regional activation, such as chromatin remodeling and DNA or histone modifications of the 7q21 region.

Correlation between genomic DNA copy number alterations and transcriptional expression in hepatitis B virus-associated hepatocellular carcinoma

Human hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, in which the genetic mechanisms of oncogenesis are still unclear. To investigate whether the genomic DNA copy number alterations may contribute to primary HCC, the cDNA microarray-based comparative genomic hybridization (CGH) analysis was here performed in 41 primary HCC infected by hepatitis B virus and 12 HCC cell lines. The resulting data showed that, on average, 7.25% of genome-wide DNA copy numbers was significantly altered in those samples (4.61+/-2.49% gained and 2.64+/-1.78% lost). Gains involving 1q, 6p, 8q and 9p were frequently observed in these cases; and whilst, losses involving Ip, 16q and 19p occurred in most patients. To address the correlation between the alteration of genomic DNA copy numbers and transcriptional expression, the same cDNA microarray was further applied in 20 HCC specimens and all available cell lines to figure out the gene expression profiles of those samples. Interestingly, the genomic DNA copy number alterations of most genes appeared not to be in generally parallel with the corresponding transcriptional expression. However, the transcriptional deregulation of a few genes, such as osteopontin (SPP1), transgelin 2 (TAGLN2) and PEG10, could be ascribed partially to their genomic aberrations, although the many alternative mechanisms could be involved in the deregulation of these genes. In general, this work would provide new insights into the genetic mechanisms in hepatocarcinogenesis associated with hepatitis B virus through the comprehensive survey on correlation between genomic DNA copy number alterations and transcriptional expression.

Transcriptome coexpression map of human embryonic stem cells

Background

Human embryonic stem (ES) cells hold great promise for medicine and science. The transcriptome of human ES cells has been studied in detail in recent years. However, no systematic analysis has yet addressed whether gene expression in human ES cells may be regulated in chromosomal domains, and no chromosomal domains of coexpression have been identified.

Results

We report the first transcriptome coexpression map of the human ES cell and the earliest stage of ES differentiation, the embryoid body (EB), for the analysis of how transcriptional regulation interacts with genomic structure during ES self-renewal and differentiation. We determined the gene expression profiles from multiple ES and EB samples and identified chromosomal domains showing coexpression of adjacent genes on the genome. The coexpression domains were not random, with significant enrichment in chromosomes 8, 11, 16, 17, 19, and Y in the ES state, and 6, 11, 17, 19 and 20 in the EB state. The domains were significantly associated with Giemsa-negative bands in EB, yet showed little correlation with known cytogenetic structures in ES cells. Different patterns of coexpression were revealed by comparative transcriptome mapping between ES and EB.

Conclusion

The findings and methods reported in this investigation advance our understanding of how genome organization affects gene expression in human ES cells and help to identify new mechanisms and pathways controlling ES self-renewal or differentiation.

Comprehensive Profiling of 8p11-12 Amplification in Breast Cancer

In human carcinomas, especially breast cancer, chromosome arm 8p is frequently involved in complex chromosomal rearrangements that combine amplification at 8p11-12, break in the 8p12-21 region, and loss of 8p21-ter. Several studies have identified putative oncogenes in the 8p11-12 amplicon. However, discrepancies and the lack of knowledge on the structure of this amplification lead us to think that the actual identity of the oncogenes is not definitively established. We present here a comprehensive study combining genomic, expression, and chromosome break analyses of the 8p11-12 region in breast cell lines and primary breast tumors. We show the existence of four amplicons at 8p11-12 using array comparative genomic hybridization. Gene expression analysis of 123 samples using DNA microarrays identified 14 genes significantly overexpressed in relation to amplification. Using fluorescence in situ hybridization analysis on tissue microarrays, we show the existence of a cluster of breakpoints spanning a region just telomeric to and associated with the amplification. Finally, we show that 8p11-12 amplification has a pejorative effect on survival in breast cancer.

A role for the scaffolding adapter GAB2 in breast cancer

The scaffolding adapter GAB2 maps to a region (11q13-14) commonly amplified in human breast cancer, and is overexpressed in breast cancer cell lines and primary tumors, but its functional role in mammary carcinogenesis has remained unexplored. We found that overexpression of GAB2 (Grb2-associated binding protein 2) increases proliferation of MCF10A mammary cells in three-dimensional culture. Coexpression of GAB2 with antiapoptotic oncogenes causes lumenal filling, whereas coexpression with Neu (also known as ErbB2 and HER2) results in an invasive phenotype. These effects of GAB2 are mediated by hyperactivation of the Shp2-Erk pathway. Furthermore, overexpression of Gab2 potentiates, whereas deficiency of Gab2 ameliorates, Neu-evoked breast carcinogenesis in mice. Finally, GAB2 is amplified in some GAB2-overexpressing human breast tumors. Our data suggest that GAB2 may be a key gene within an 11q13 amplicon in human breast cancer and propose a role for overexpression of GAB2 in mammary carcinogenesis. Agents that target GAB2 or GAB2-dependent pathways may be useful for treating breast tumors that overexpress GAB2 or HER2 or both.