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1.  Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family 
BMC Medical Genomics  2009;2:59.
Background
Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.
Methods
We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.
Results
We demonstrate that the two separately introduced ER- breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.
Conclusion
We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.
doi:10.1186/1755-8794-2-59
PMCID: PMC2753593  PMID: 19747394
2.  Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus 
BMC Medical Genomics  2009;2:72.
Background
Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prioritize single nucleotide polymorphisms (SNPs) from GWAS for further replication in different population. Several recent studies have shown that genetic variation often affects gene-expression at proximal (cis) as well as distal (trans) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability.
Methods
To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC), with genome-wide expression data from pancreas, adipose tissue, liver and skeletal muscle of individuals with or without T2DM or animal models thereof to identify T2DM susceptibility loci.
Results
We identified 1,170 SNPs associated with T2DM with P < 0.05 in both GWAS and 243 genes that were located in the vicinity of these SNPs. Out of these 243 genes, we identified 115 differentially expressed in publicly available gene expression profiling data. Notably five of them, IGF2BP2, KCNJ11, NOTCH2, TCF7L2 and TSPAN8, have subsequently been shown to be associated with T2DM in different populations. To provide further validation of our approach, we reversed the approach and started with 26 known SNPs associated with T2DM and related traits. We could show that 12 (57%) (HHEX, HNF1B, IGF2BP2, IRS1, KCNJ11, KCNQ1, NOTCH2, PPARG, TCF7L2, THADA, TSPAN8 and WFS1) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies.
Conclusions
Utilizing of gene expression profiling data from different tissues of individuals with or without T2DM or animal models thereof is a powerful tool for prioritizing SNPs from WGAS for further replication studies.
doi:10.1186/1755-8794-2-72
PMCID: PMC2815699  PMID: 20043853
3.  Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells 
BMC Medical Genomics  2009;2:71.
Background
Accumulating evidence suggests that somatic stem cells undergo mutagenic transformation into cancer initiating cells. The serous subtype of ovarian adenocarcinoma in humans has been hypothesized to arise from at least two possible classes of progenitor cells: the ovarian surface epithelia (OSE) and/or an as yet undefined class of progenitor cells residing in the distal end of the fallopian tube.
Methods
Comparative gene expression profiling analyses were carried out on OSE removed from the surface of normal human ovaries and ovarian cancer epithelial cells (CEPI) isolated by laser capture micro-dissection (LCM) from human serous papillary ovarian adenocarcinomas. The results of the gene expression analyses were randomly confirmed in paraffin embedded tissues from ovarian adenocarcinoma of serous subtype and non-neoplastic ovarian tissues using immunohistochemistry. Differentially expressed genes were analyzed using gene ontology, molecular pathway, and gene set enrichment analysis algorithms.
Results
Consistent with multipotent capacity, genes in pathways previously associated with adult stem cell maintenance are highly expressed in ovarian surface epithelia and are not expressed or expressed at very low levels in serous ovarian adenocarcinoma. Among the over 2000 genes that are significantly differentially expressed, a number of pathways and novel pathway interactions are identified that may contribute to ovarian adenocarcinoma development.
Conclusions
Our results are consistent with the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as the origin of ovarian adenocarcinoma. While our findings do not rule out the possibility that ovarian cancers may also arise from other sources, they are inconsistent with claims that ovarian surface epithelia cannot serve as the origin of ovarian cancer initiating cells.
doi:10.1186/1755-8794-2-71
PMCID: PMC2806370  PMID: 20040092
4.  Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency 
BMC Medical Genomics  2009;2:70.
Background
Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer.
Results
To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage.
Conclusions
We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.
doi:10.1186/1755-8794-2-70
PMCID: PMC2805685  PMID: 20025723
5.  A taxonomy of epithelial human cancer and their metastases 
BMC Medical Genomics  2009;2:69.
Background
Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination.
Methods
We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures.
Results
Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination.
Conclusion
Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile.
doi:10.1186/1755-8794-2-69
PMCID: PMC2806369  PMID: 20017941
6.  A transcriptomic computational analysis of mastic oil-treated Lewis lung carcinomas reveals molecular mechanisms targeting tumor cell growth and survival 
BMC Medical Genomics  2009;2:68.
Background
Mastic oil from Pistacia lentiscus variation chia, a blend of bioactive terpenes with recognized medicinal properties, has been recently shown to exert anti-tumor growth activity through inhibition of cancer cell proliferation, survival, angiogenesis and inflammatory response. However, no studies have addressed its mechanisms of action at genome-wide gene expression level.
Methods
To investigate molecular mechanisms triggered by mastic oil, Lewis Lung Carcinoma cells were treated with mastic oil or DMSO and RNA was collected at five distinct time points (3-48 h). Microarray expression profiling was performed using Illumina mouse-6 v1 beadchips, followed by computational analysis. For a number of selected genes, RT-PCR validation was performed in LLC cells as well as in three human cancer cell lines of different origin (A549, HCT116, K562). PTEN specific inhibition by a bisperovanadium compound was applied to validate its contribution to mastic oil-mediated anti-tumor growth effects.
Results
In this work we demonstrated that exposure of Lewis lung carcinomas to mastic oil caused a time-dependent alteration in the expression of 925 genes. GO analysis associated expression profiles with several biological processes and functions. Among them, modifications on cell cycle/proliferation, survival and NF-κB cascade in conjunction with concomitant regulation of genes encoding for PTEN, E2F7, HMOX1 (up-regulation) and NOD1 (down-regulation) indicated some important mechanistic links underlying the anti-proliferative, pro-apoptotic and anti-inflammatory effects of mastic oil. The expression profiles of Hmox1, Pten and E2f7 genes were similarly altered by mastic oil in the majority of test cancer cell lines. Inhibition of PTEN partially reversed mastic oil effects on tumor cell growth, indicating a multi-target mechanism of action. Finally, k-means clustering, organized the significant gene list in eight clusters demonstrating a similar expression profile. Promoter analysis in a representative cluster revealed shared putative cis-elements suggesting a common regulatory transcription mechanism.
Conclusions
Present results provide novel evidence on the molecular basis of tumor growth inhibition mediated by mastic oil and set a rational basis for application of genomics and bioinformatic methodologies in the screening of natural compounds with potential cancer chemopreventive activities.
doi:10.1186/1755-8794-2-68
PMCID: PMC2801511  PMID: 20003503
7.  DNA microarray profiling of genes differentially regulated by the histone deacetylase inhibitors vorinostat and LBH589 in colon cancer cell lines 
BMC Medical Genomics  2009;2:67.
Background
Despite the significant progress made in colon cancer chemotherapy, advanced disease remains largely incurable and novel efficacious chemotherapies are urgently needed. Histone deacetylase inhibitors (HDACi) represent a novel class of agents which have demonstrated promising preclinical activity and are undergoing clinical evaluation in colon cancer. The goal of this study was to identify genes in colon cancer cells that are differentially regulated by two clinically advanced hydroxamic acid HDACi, vorinostat and LBH589 to provide rationale for novel drug combination partners and identify a core set of HDACi-regulated genes.
Methods
HCT116 and HT29 colon cancer cells were treated with LBH589 or vorinostat and growth inhibition, acetylation status and apoptosis were analyzed in response to treatment using MTS, Western blotting and flow cytometric analyses. In addition, gene expression was analyzed using the Illumina Human-6 V2 BeadChip array and Ingenuity® Pathway Analysis.
Results
Treatment with either vorinostat or LBH589 rapidly induced histone acetylation, cell cycle arrest and inhibited the growth of both HCT116 and HT29 cells. Bioinformatic analysis of the microarray profiling revealed significant similarity in the genes altered in expression following treatment with the two HDACi tested within each cell line. However, analysis of genes that were altered in expression in the HCT116 and HT29 cells revealed cell-line-specific responses to HDACi treatment. In addition a core cassette of 11 genes modulated by both vorinostat and LBH589 were identified in both colon cancer cell lines analyzed.
Conclusion
This study identified HDACi-induced alterations in critical genes involved in nucleotide metabolism, angiogenesis, mitosis and cell survival which may represent potential intervention points for novel therapeutic combinations in colon cancer. This information will assist in the identification of novel pathways and targets that are modulated by HDACi, providing much-needed information on HDACi mechanism of action and providing rationale for novel drug combination partners. We identified a core signature of 11 genes which were modulated by both vorinostat and LBH589 in a similar manner in both cell lines. These core genes will assist in the development and validation of a common gene set which may represent a molecular signature of HDAC inhibition in colon cancer.
doi:10.1186/1755-8794-2-67
PMCID: PMC2799439  PMID: 19948057
8.  A metadata approach for clinical data management in translational genomics studies in breast cancer 
BMC Medical Genomics  2009;2:66.
Background
In molecular profiling studies of cancer patients, experimental and clinical data are combined in order to understand the clinical heterogeneity of the disease: clinical information for each subject needs to be linked to tumour samples, macromolecules extracted, and experimental results. This may involve the integration of clinical data sets from several different sources: these data sets may employ different data definitions and some may be incomplete.
Methods
In this work we employ semantic web techniques developed within the CancerGrid project, in particular the use of metadata elements and logic-based inference to annotate heterogeneous clinical information, integrate and query it.
Results
We show how this integration can be achieved automatically, following the declaration of appropriate metadata elements for each clinical data set; we demonstrate the practicality of this approach through application to experimental results and clinical data from five hospitals in the UK and Canada, undertaken as part of the METABRIC project (Molecular Taxonomy of Breast Cancer International Consortium).
Conclusion
We describe a metadata approach for managing similarities and differences in clinical datasets in a standardized way that uses Common Data Elements (CDEs). We apply and evaluate the approach by integrating the five different clinical datasets of METABRIC.
doi:10.1186/1755-8794-2-66
PMCID: PMC3225860  PMID: 19948017
9.  Gene expression profiling in sinonasal adenocarcinoma 
BMC Medical Genomics  2009;2:65.
Background
Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers.
Methods
To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and non-tumor sinusal tissue. Microarray results were validated by quantitative RT-PCR and immunohistochemistry on two additional sets of tumors.
Results
Among the genes with significant differential expression we selected LGALS4, ACS5, CLU, SRI and CCT5 for further exploration. The overexpression of LGALS4, ACS5, SRI, CCT5 and the downregulation of CLU were confirmed by quantitative RT-PCR. Immunohistochemistry was performed for LGALS4 (Galectin 4), ACS5 (Acyl-CoA synthetase) and CLU (Clusterin) proteins: LGALS4 was highly up-regulated, particularly in the most differentiated tumors, while CLU was lost in all tumors. The expression of ACS5, was more heterogeneous and no correlation was observed with the tumor type.
Conclusion
Within our microarray study in sinonasal adenocarcinoma we identified two proteins, LGALS4 and CLU, that were significantly differentially expressed in tumors compared to normal tissue. A further evaluation on a new set of tissues, including precancerous stages and low grade tumors, is necessary to evaluate the possibility of using them as diagnostic markers.
doi:10.1186/1755-8794-2-65
PMCID: PMC2780459  PMID: 19903339
10.  Accurate molecular classification of cancer using simple rules 
BMC Medical Genomics  2009;2:64.
Background
One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.
Methods
We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.
Results
We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.
Conclusion
In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.
doi:10.1186/1755-8794-2-64
PMCID: PMC2777919  PMID: 19874631
11.  Early over expression of messenger RNA for multiple genes, including insulin, in the Pancreatic Lymph Nodes of NOD mice is associated with Islet Autoimmunity 
BMC Medical Genomics  2009;2:63.
Background
Autoimmune diabetes (T1D) onset is preceded by a long inflammatory process directed against the insulin-secreting β cells of the pancreas. Deciphering the early autoimmune mechanisms represents a challenge due to the absence of clinical signs at early disease stages. The aim of this study was to identify genes implicated in the early steps of the autoimmune process, prior to inflammation, in T1D. We have previously established that insulin autoantibodies (E-IAA) predict early diabetes onset delineating an early phenotypic check point (window 1) in disease pathogenesis. We used this sub-phenotype and applied differential gene expression analysis in the pancreatic lymph nodes (PLN) of 5 weeks old Non Obese Diabetic (NOD) mice differing solely upon the presence or absence of E-IAA. Analysis of gene expression profiles has the potential to provide a global understanding of the disease and to generate novel hypothesis concerning the initiation of the autoimmune process.
Methods
Animals have been screened weekly for the presence of E-IAA between 3 and 5 weeks of age. E-IAA positive or negative NOD mice at least twice were selected and RNAs isolated from the PLN were used for microarray analysis. Comparison of transcriptional profiles between positive and negative animals and functional annotations of the resulting differentially expressed genes, using software together with manual literature data mining, have been performed.
Results
The expression of 165 genes was modulated between E-IAA positive and negative PLN. In particular, genes coding for insulin and for proteins known to be implicated in tissue remodelling and Th1 immunity have been found to be highly differentially expressed. Forty one genes showed over 5 fold differences between the two sets of samples and 30 code for extracellular proteins. This class of proteins represents potential diagnostic markers and drug targets for T1D.
Conclusion
Our data strongly suggest that the immune related mechanisms taking place at this early age in the PLN, correlate with homeostatic changes influencing tissue integrity of the adjacent pancreatic tissue. Functional analysis of the identified genes suggested that similar mechanisms might be operating during pre-inflammatory processes deployed in tissues i) hosting parasitic microorganisms and ii) experiencing unrestricted invasion by tumour cells.
doi:10.1186/1755-8794-2-63
PMCID: PMC2763872  PMID: 19799787
12.  Exon expression in lymphoblastoid cell lines from subjects with schizophrenia before and after glucose deprivation 
BMC Medical Genomics  2009;2:62.
Background
The purpose of this study was to examine the effects of glucose reduction stress on lymphoblastic cell line (LCL) gene expression in subjects with schizophrenia compared to non-psychotic relatives.
Methods
LCLs were grown under two glucose conditions to measure the effects of glucose reduction stress on exon expression in subjects with schizophrenia compared to unaffected family member controls. A second aim of this project was to identify cis-regulated transcripts associated with diagnosis.
Results
There were a total of 122 transcripts with significant diagnosis by probeset interaction effects and 328 transcripts with glucose deprivation by probeset interaction probeset effects after corrections for multiple comparisons. There were 8 transcripts with expression significantly affected by the interaction between diagnosis and glucose deprivation and probeset after correction for multiple comparisons. The overall validation rate by qPCR of 13 diagnosis effect genes identified through microarray was 62%, and all genes tested by qPCR showed concordant up- or down-regulation by qPCR and microarray. We assessed brain gene expression of five genes found to be altered by diagnosis and glucose deprivation in LCLs and found a significant decrease in expression of one gene, glutaminase, in the dorsolateral prefrontal cortex (DLPFC). One SNP with previously identified regulation by a 3' UTR SNP was found to influence IRF5 expression in both brain and lymphocytes. The relationship between the 3' UTR rs10954213 genotype and IRF5 expression was significant in LCLs (p = 0.0001), DLPFC (p = 0.007), and anterior cingulate cortex (p = 0.002).
Conclusion
Experimental manipulation of cells lines from subjects with schizophrenia may be a useful approach to explore stress related gene expression alterations in schizophrenia and to identify SNP variants associated with gene expression.
doi:10.1186/1755-8794-2-62
PMCID: PMC2760574  PMID: 19772658
13.  Discovering cancer genes by integrating network and functional properties 
BMC Medical Genomics  2009;2:61.
Background
Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes.
Methods
Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1.
Results
Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1.
Conclusion
Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.
doi:10.1186/1755-8794-2-61
PMCID: PMC2758898  PMID: 19765316
14.  Transcriptional profiling differences for articular cartilage and repair tissue in equine joint surface lesions 
BMC Medical Genomics  2009;2:60.
Background
Full-thickness articular cartilage lesions that reach to the subchondral bone yet are restricted to the chondral compartment usually fill with a fibrocartilage-like repair tissue which is structurally and biomechanically compromised relative to normal articular cartilage. The objective of this study was to evaluate transcriptional differences between chondrocytes of normal articular cartilage and repair tissue cells four months post-microfracture.
Methods
Bilateral one-cm2 full-thickness defects were made in the articular surface of both distal femurs of four adult horses followed by subchondral microfracture. Four months postoperatively, repair tissue from the lesion site and grossly normal articular cartilage from within the same femorotibial joint were collected. Total RNA was isolated from the tissue samples, linearly amplified, and applied to a 9,413-probe set equine-specific cDNA microarray. Eight paired comparisons matched by limb and horse were made with a dye-swap experimental design with validation by histological analyses and quantitative real-time polymerase chain reaction (RT-qPCR).
Results
Statistical analyses revealed 3,327 (35.3%) differentially expressed probe sets. Expression of biomarkers typically associated with normal articular cartilage and fibrocartilage repair tissue corroborate earlier studies. Other changes in gene expression previously unassociated with cartilage repair were also revealed and validated by RT-qPCR.
Conclusion
The magnitude of divergence in transcriptional profiles between normal chondrocytes and the cells that populate repair tissue reveal substantial functional differences between these two cell populations. At the four-month postoperative time point, the relative deficiency within repair tissue of gene transcripts which typically define articular cartilage indicate that while cells occupying the lesion might be of mesenchymal origin, they have not recapitulated differentiation to the chondrogenic phenotype of normal articular chondrocytes.
doi:10.1186/1755-8794-2-60
PMCID: PMC2751772  PMID: 19751507
15.  Glucocorticoids with different chemical structures but similar glucocorticoid receptor potency regulate subsets of common and unique genes in human trabecular meshwork cells 
BMC Medical Genomics  2009;2:58.
Background
In addition to their well-documented ocular therapeutic effects, glucocorticoids (GCs) can cause sight-threatening side-effects including ocular hypertension presumably via morphological and biochemical changes in trabecular meshwork (TM) cells. In the present study, we directly compared the glucocorticoid receptor (GR) potency for dexamethasone (DEX), fluocinolone acetonide (FA) and triamcinolone acetonide (TA), examined the expression of known GRα and GRβ isoforms, and used gene expression microarrays to compare the effects of DEX, FA, and TA on the complete transcriptome in two primary human TM cell lines.
Methods
GR binding affinity for DEX, FA, and TA was measured by a cell-free competitive radio-labeled GR binding assay. GR-mediated transcriptional activity was assessed using the GeneBLAzer beta-lactamase reporter gene assay. Levels of GRα and GRβ isoforms were assessed by Western blot. Total RNA was extracted from TM 86 and TM 93 cells treated with 1 μM DEX, FA, or TA for 24 hr and used for microarray gene expression analysis. The microarray experiments were repeated three times. Differentially expressed genes were identified by Rosetta Resolver Gene Expression Analysis System.
Results
The GR binding affinity (IC50) for DEX, FA, and TA was 5.4, 2.0, and 1.5 nM, respectively. These values are similar to the GR transactivation EC50 of 3.0, 0.7, and 1.5 nM for DEX, FA, and TA, respectively. All four GRα translational isoforms (A-D) were expressed in TM 86 and TM 93 total cell lysates, however, the C and D isoforms were more highly expressed relative to A and B. All four GRβ isoforms (A-D) were also detected in TM cells, although GRβ-D isoform expression was lower compared to that of the A, B, or C isoforms. Microarray analysis revealed 1,968 and 1,150 genes commonly regulated by DEX, FA, and TA in TM 86 and TM 93, respectively. These genes included RGC32, OCA2, ANGPTL7, MYOC, FKBP5, SAA1 and ZBTB16. In addition, each GC specifically regulated a unique set of genes in both TM cell lines. Using Ingenuity Pathway Analysis (IPA) software, analysis of the data from TM 86 cells showed that DEX significantly regulated transcripts associated with RNA post-transcriptional modifications, whereas FA and TA modulated genes involved in lipid metabolism and cell morphology, respectively. In TM 93 cells, DEX significantly regulated genes implicated in histone methylation, whereas FA and TA altered genes associated with cell cycle and cell adhesion, respectively.
Conclusion
Human trabecular meshwork cells in culture express all known GRα and GRβ translational isoforms, and GCs with similar potency but subtly different chemical structure are capable of regulating common and unique gene subsets and presumably biologic responses in these cells. These GC structure-dependent effects appear to be TM cell-lineage dependent.
doi:10.1186/1755-8794-2-58
PMCID: PMC2749862  PMID: 19744340
16.  Evaluation of a new high-dimensional miRNA profiling platform 
BMC Medical Genomics  2009;2:57.
Background
MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.
Methods
We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application.
Results
Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98) as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98). To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed.
Conclusion
These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.
doi:10.1186/1755-8794-2-57
PMCID: PMC2744682  PMID: 19712457
17.  Induction of the interleukin 6/ signal transducer and activator of transcription pathway in the lungs of mice sub-chronically exposed to mainstream tobacco smoke 
BMC Medical Genomics  2009;2:56.
Background
Tobacco smoking is associated with lung cancer and other respiratory diseases. However, little is known about the global molecular changes that precede the appearance of clinically detectable symptoms. In this study, the effects of mainstream tobacco smoke (MTS) on global transcription in the mouse lung were investigated.
Methods
Male C57B1/CBA mice were exposed to MTS from two cigarettes daily, 5 days/week for 6 or 12 weeks. Mice were sacrificed immediately, or 6 weeks following the last cigarette. High density DNA microarrays were used to characterize global gene expression changes in whole lung. Microarray results were validated by Quantitative real-time RT-PCR. Further analysis of protein synthesis and function was carried out for a select set of genes by ELISA and Western blotting.
Results
Globally, seventy nine genes were significantly differentially expressed following the exposure to MTS. These genes were associated with a number of biological processes including xenobiotic metabolism, redox balance, oxidative stress and inflammation. There was no differential gene expression in mice exposed to smoke and sampled 6 weeks following the last cigarette. Moreover, cluster analysis demonstrated that these samples clustered alongside their respective controls. We observed simultaneous up-regulation of interleukin 6 (IL-6) and its antagonist, suppressor of cytokine signalling (SOCS3) mRNA following 12 weeks of MTS exposure. Analysis by ELISA and Western blotting revealed a concomitant increase in total IL-6 antigen levels and its downstream targets, including phosphorylated signal transducer and activator of transcription 3 (Stat3), basal cell-lymphoma extra large (BCL-XL) and myeloid cell leukemia 1 (MCL-1) protein, in total lung tissue extracts. However, in contrast to gene expression, a subtle decrease in total SOCS3 protein was observed after 12 weeks of MTS exposure.
Conclusion
Global transcriptional analysis identified a set of genes responding to MTS exposure in mouse lung. These genes returned to basal levels following smoking cessation, providing evidence to support the benefits of smoking cessation. Detailed analyses were undertaken for IL-6 and its associated pathways. Our results provide further insight into the role of these pathways in lung injury and inflammation induced by MTS.
doi:10.1186/1755-8794-2-56
PMCID: PMC2737544  PMID: 19698101
18.  Anti-oncogenic and pro-differentiation effects of clorgyline, a monoamine oxidase A inhibitor, on high grade prostate cancer cells 
BMC Medical Genomics  2009;2:55.
Background
Monoamine oxidase A (MAO-A), a mitochondrial enzyme that degrades monoamines including neurotransmitters, is highly expressed in basal cells of the normal human prostatic epithelium and in poorly differentiated (Gleason grades 4 and 5), aggressive prostate cancer (PCa). Clorgyline, an MAO-A inhibitor, induces secretory differentiation of normal prostate cells. We examined the effects of clorgyline on the transcriptional program of epithelial cells cultured from high grade PCa (E-CA).
Methods
We systematically assessed gene expression changes induced by clorgyline in E-CA cells using high-density oligonucleotide microarrays. Genes differentially expressed in treated and control cells were identified by Significance Analysis of Microarrays. Expression of genes of interest was validated by quantitative real-time polymerase chain reaction.
Results
The expression of 156 genes was significantly increased by clorgyline at all time points over the time course of 6 – 96 hr identified by Significance Analysis of Microarrays (SAM). The list is enriched with genes repressed in 7 of 12 oncogenic pathway signatures compiled from the literature. In addition, genes downregulated ≥ 2-fold by clorgyline were significantly enriched with those upregulated by key oncogenes including beta-catenin and ERBB2, indicating an anti-oncogenic effect of clorgyline. Another striking effect of clorgyline was the induction of androgen receptor (AR) and classic AR target genes such as prostate-specific antigen together with other secretory epithelial cell-specific genes, suggesting that clorgyline promotes differentiation of cancer cells. Moreover, clorgyline downregulated EZH2, a critical component of the Polycomb Group (PcG) complex that represses the expression of differentiation-related genes. Indeed, many genes in the PcG repression signature that predicts PCa outcome were upregulated by clorgyline, suggesting that the differentiation-promoting effect of clorgyline may be mediated by its downregulation of EZH2.
Conclusion
Our results suggest that inhibitors of MAO-A, already in clinical use to treat depression, may have potential application as therapeutic PCa drugs by inhibiting oncogenic pathway activity and promoting differentiation.
doi:10.1186/1755-8794-2-55
PMCID: PMC2736984  PMID: 19691856
19.  MicroRNA-125a is over-expressed in insulin target tissues in a spontaneous rat model of Type 2 Diabetes 
BMC Medical Genomics  2009;2:54.
Background
MicroRNAs (miRNAs) are non-coding RNA molecules involved in post-transcriptional control of gene expression of a wide number of genes, including those involved in glucose homeostasis. Type 2 diabetes (T2D) is characterized by hyperglycaemia and defects in insulin secretion and action at target tissues. We sought to establish differences in global miRNA expression in two insulin-target tissues from inbred rats of spontaneously diabetic and normoglycaemic strains.
Methods
We used a miRNA microarray platform to measure global miRNA expression in two insulin-target tissues: liver and adipose tissue from inbred rats of spontaneously diabetic (Goto-Kakizaki [GK]) and normoglycaemic (Brown-Norway [BN]) strains which are extensively used in genetic studies of T2D. MiRNA data were integrated with gene expression data from the same rats to investigate how differentially expressed miRNAs affect the expression of predicted target gene transcripts.
Results
The expression of 170 miRNAs was measured in liver and adipose tissue of GK and BN rats. Based on a p-value for differential expression between GK and BN, the most significant change in expression was observed for miR-125a in liver (FC = 5.61, P = 0.001, Padjusted = 0.10); this overexpression was validated using quantitative RT-PCR (FC = 13.15, P = 0.0005). MiR-125a also showed over-expression in the GK vs. BN analysis within adipose tissue (FC = 1.97, P = 0.078, Padjusted = 0.99), as did the previously reported miR-29a (FC = 1.51, P = 0.05, Padjusted = 0.99). In-silico tools assessing the biological role of predicted miR-125a target genes suggest an over-representation of genes involved in the MAPK signaling pathway. Gene expression analysis identified 1308 genes with significantly different expression between GK and BN rats (Padjusted < 0.05): 233 in liver and 1075 in adipose tissue. Pathways related to glucose and lipid metabolism were significantly over-represented among these genes. Enrichment analysis suggested that differentially expressed genes in GK compared to BN included more predicted miR-125a target genes than would be expected by chance in adipose tissue (FDR = 0.006 for up-regulated genes; FDR = 0.036 for down-regulated genes) but not in liver (FDR = 0.074 for up-regulated genes; FDR = 0.248 for down-regulated genes).
Conclusion
MiR-125a is over-expressed in liver in hyperglycaemic GK rats relative to normoglycaemic BN rats, and our array data also suggest miR-125a is over-expressed in adipose tissue. We demonstrate the use of in-silico tools to provide the basis for further investigation of the potential role of miR-125a in T2D. In particular, the enrichment of predicted miR-125a target genes among differentially expressed genes has identified likely target genes and indicates that integrating global miRNA and mRNA expression data may give further insights into miRNA-mediated regulation of gene expression.
doi:10.1186/1755-8794-2-54
PMCID: PMC2754496  PMID: 19689793
20.  Verification of genes differentially expressed in neuroblastoma tumours: a study of potential tumour suppressor genes 
BMC Medical Genomics  2009;2:53.
Background
One of the most striking features of the childhood malignancy neuroblastoma (NB) is its clinical heterogeneity. Although there is a great need for better clinical and biological markers to distinguish between tumours with different severity and to improve treatment, no clear-cut prognostic factors have been found. Also, no major NB tumour suppressor genes have been identified.
Methods
In this study we performed expression analysis by quantitative real-time PCR (QPCR) on primary NB tumours divided into two groups, of favourable and unfavourable outcome respectively. Candidate genes were selected on basis of lower expression in unfavourable tumour types compared to favourables in our microarray expression analysis. Selected genes were studied in two steps: (1) using TaqMan Low Density Arrays (TLDA) targeting 89 genes on a set of 12 NB tumour samples, and (2) 12 genes were selected from the TLDA analysis for verification using individual TaqMan assays in a new set of 13 NB tumour samples.
Results
By TLDA analysis, 81 out of 87 genes were found to be significantly differentially expressed between groups, of which 14 have previously been reported as having an altered gene expression in NB. In the second verification round, seven out of 12 transcripts showed significantly lower expression in unfavourable NB tumours, ATBF1, CACNA2D3, CNTNAP2, FUSIP1, GNB1, SLC35E2, and TFAP2B. The gene that showed the highest fold change in the TLDA analysis, POU4F2, was investigated for epigenetic changes (CpG methylation) and mutations in order to explore the cause of the differential expression. Moreover, the fragile site gene CNTNAP2 that showed the largest fold change in verification group 2 was investigated for structural aberrations by copy number analysis. However, the analyses of POU4F2 and CNTNAP2 showed no genetic alterations that could explain a lower expression in unfavourable NB tumours.
Conclusion
Through two steps of verification, seven transcripts were found to significantly discriminate between favourable and unfavourable NB tumours. Four of the transcripts, CACNA2D3, GNB1, SLC35E2, and TFAP2B, have been observed in previous microarray studies, and are in this study independently verified. Our results suggest these transcripts to be markers of malignancy, which could have a potential usefulness in the clinic.
doi:10.1186/1755-8794-2-53
PMCID: PMC2743704  PMID: 19686582
21.  A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility 
BMC Medical Genomics  2009;2:52.
Background
Microarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.
Methods
In this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.
Results
Supervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47–0.73).
Conclusion
The developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.
doi:10.1186/1755-8794-2-52
PMCID: PMC2732639  PMID: 19674463
22.  Hepatic inflammation mediated by hepatitis C virus core protein is ameliorated by blocking complement activation 
BMC Medical Genomics  2009;2:51.
Background
The pathogenesis of inflammation and fibrosis in chronic hepatitis C virus (HCV) infection remains unclear. Transgenic mice with constitutive HCV core over-expression display steatosis only. While the reasons for this are unclear, it may be important that core protein production in these models begins during gestation, in contrast to human hepatitis C virus infection, which occurs post-natally and typically in adults. AIMS: To more realistically model the effect of core protein production in the adult liver, we developed a mouse with conditional expression of HCV core and examined the effect of core protein production in the adult liver.
Methods
Liver biopsy samples from transgenic mice with tetracycline(tet)-regulated conditional core protein expression were evaluated immunohistologically. Microarray analysis of HCV core transgenic mice with steatohepatitis pointed to a role of the complement pathway. This was further explored by blocking complement activation by in vivo administration of CD55 (decay accelerating factor for complement), which inhibits activation of C3.
Results
Transgenic mice exhibited low, intermediate, or high HCV core protein expression when fed a permissive diet of standard chow. Aside from hepatic steatosis, hepatic inflammation and fibrosis were seen in mice with intermediate levels of core protein. Microarray analyses of inflamed liver demonstrated activation of both the complement (C3 up-regulation) and coagulation pathways (fibrinogen B up-regulation). Administration of CD55 reduced hepatic inflammation.
Conclusion
Transgenic mice that conditionally express intermediate HCV core protein develop inflammation, steatosis, and fibrosis. These effects mediated by HCV core are reduced by administration of CD55, a regulator of the complement pathway. The model may be valuable in investigating the pathogenesis of liver inflammation in chronic hepatitis C.
doi:10.1186/1755-8794-2-51
PMCID: PMC2734540  PMID: 19664232
23.  Integrated microarray and multiplex cytokine analyses of Kaposi's Sarcoma Associated Herpesvirus viral FLICE Inhibitory Protein K13 affected genes and cytokines in human blood vascular endothelial cells 
BMC Medical Genomics  2009;2:50.
Background
Kaposi's sarcoma (KS) associated herpesvirus (KSHV) is the etiological agent of KS, a neoplasm characterized by proliferating spindle cells, extensive neoangiogenesis and a prominent inflammatory infiltrate. Infection of blood vascular endothelial cells with KSHV in vitro results in their spindle cell transformation, which is accompanied by increased expression of inflammatory chemokines and cytokines, and acquisition of lymphatic endothelial markers. Mimicking the effect of viral infection, ectopic expression of KSHV-encoded latent protein vFLIP K13 is sufficient to induce spindle transformation of vascular endothelial cells. However, the effect of K13 expression on global gene expression and induction of lymphatic endothelial markers in vascular endothelial cells has not been studied.
Methods
We used gene array analysis to determine change in global gene expression induced by K13 in human vascular endothelial cells (HUVECs). Results of microarray analysis were validated by quantitative RT-PCR, immunoblotting and a multiplex cytokine array.
Results
K13 affected the expression of several genes whose expression is known to be modulated by KSHV infection, including genes involved in immune and inflammatory responses, anti-apoptosis, stress response, and angiogenesis. The NF-κB pathway was the major signaling pathway affected by K13 expression, and genetic and pharmacological inhibitors of this pathway effectively blocked K13-induced transcriptional activation of the promoter of CXCL10, one of the chemokines whose expression was highly upregulated by K13. However, K13, failed to induce expression of lymphatic markers in blood vascular endothelial cells.
Conclusion
While K13 may account for change in the expression of a majority of genes observed following KSHV infection, it is not sufficient for inducing lymphatic reprogramming of blood vascular endothelial cells.
doi:10.1186/1755-8794-2-50
PMCID: PMC2732924  PMID: 19660139
24.  Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood 
BMC Medical Genomics  2009;2:49.
Background
Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization.
Methods
Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT), 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS) and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms.
Results
Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder).
Conclusion
The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.
doi:10.1186/1755-8794-2-49
PMCID: PMC2736983  PMID: 19656400
25.  Candidate pathways and genes for prostate cancer: a meta-analysis of gene expression data 
BMC Medical Genomics  2009;2:48.
Backgound
The genetic mechanisms of prostate tumorigenesis remain poorly understood, but with the advent of gene expression array capabilities, we can now produce a large amount of data that can be used to explore the molecular and genetic mechanisms of prostate tumorigenesis.
Methods
We conducted a meta-analysis of gene expression data from 18 gene array datasets targeting transition from normal to localized prostate cancer and from localized to metastatic prostate cancer. We functionally annotated the top 500 differentially expressed genes and identified several candidate pathways associated with prostate tumorigeneses.
Results
We found the top differentially expressed genes to be clustered in pathways involving integrin-based cell adhesion: integrin signaling, the actin cytoskeleton, cell death, and cell motility pathways. We also found integrins themselves to be downregulated in the transition from normal prostate tissue to primary localized prostate cancer. Based on the results of this study, we developed a collagen hypothesis of prostate tumorigenesis. According to this hypothesis, the initiating event in prostate tumorigenesis is the age-related decrease in the expression of collagen genes and other genes encoding integrin ligands. This concomitant depletion of integrin ligands leads to the accumulation of ligandless integrin and activation of integrin-associated cell death. To escape integrin-associated death, cells suppress the expression of integrins, which in turn alters the actin cytoskeleton, elevates cell motility and proliferation, and disorganizes prostate histology, contributing to the histologic progression of prostate cancer and its increased metastasizing potential.
Conclusion
The results of this study suggest that prostate tumor progression is associated with the suppression of integrin-based cell adhesion. Suppression of integrin expression driven by integrin-mediated cell death leads to increased cell proliferation and motility and increased tumor malignancy.
doi:10.1186/1755-8794-2-48
PMCID: PMC2731785  PMID: 19653896

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