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PubMed2006

Gene expression profiling of single cells on large-scale oligonucleotide arrays.

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells.

Animals↗

PubMed2025

Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.

Despite the widespread availability of genome sequencing pipelines, many genes remain part of the genome's "dark matter," where existing inference tools cannot even begin to guess the biological function of their proteins from sequence alone. This challenge is especially pronounced in organisms that are highly evolutionarily distant from well-studied models, where homology-based methods break down. Here, we describe PHILHARMONIC, a computational method that combines deep learning-based de novo protein interaction network inference with robust unsupervised spectral clustering and remote homology to illuminate functional organization in any non-model organism. From only a sequenced proteome, we show PHILHARMONIC predicts protein functions, functional communities, and higher-order network structure with high accuracy. We validate its performance using experimental gene expression and pathway data in D. melanogaster, and we demonstrate its broad utility by analyzing temperature sensing and stress response pathways in the reef-building coral P. damicornis and its algal symbiont C. goreaui. PHILHARMONIC provides a general-purpose engine for functional discovery and biological hypothesis generation in non-model organisms, enabling systems-level insights across the full diversity of life.

Journal Article↗

PubMed2006

Font adaptive word indexing of modern printed documents.

We propose an approach for the word-level indexing of modern printed documents which are difficult to recognize using current OCR engines. By means of word-level indexing, it is possible to retrieve the position of words in a document, enabling queries involving proximity of terms. Web search engines implement this kind of indexing, allowing users to retrieve Web pages on the basis of their textual content. Nowadays, digital libraries hold collections of digitized documents that can be retrieved either by browsing the document images or relying on appropriate metadata assembled by domain experts. Word indexing tools would therefore increase the access to these collections. The proposed system is designed to index homogeneous document collections by automatically adapting to different languages and font styles without relying on OCR engines for character recognition. The approach is based on three main ideas: the use of Self Organizing Maps (SOM) to perform unsupervised character clustering, the definition of one suitable vector-based word representation whose size depends on the word aspect-ratio, and the run-time alignment of the query word with indexed words to deal with broken and touching characters. The most appropriate applications are for processing modern printed documents (17th to 19th centuries) where current OCR engines are less accurate. Our experimental analysis addresses six data sets containing documents ranging from books of the 17th century to contemporary journals.

Abstracting and Indexing↗

PubMed2006

High throughput comparative genomic hybridization array analysis of multifocal urothelial cancers.

The purpose of this study was to examine genetic alterations occur during synchronous or metachronous multifocal development of urothelial cancers on the whole genome using a comparative genomic hybridization (CGH) array. We used 10 tumor pairs (2 tumors for each patient), in which we had previously defined a clonal relationship by microsatellite analysis. For CGH array analysis, Vysis GenoSensor Array 300 kit was used. An unsupervised hierarchical cluster analysis revealed that the tumors from one patient were clustered together independent of the tumors of all other patients. On the other hand, many genetic divergences among multifocal urothelial cancers were newly found by a CGH array analysis. The concordant genetic alteration patterns of the chromosomal arm in tumor pairs were most frequently observed in 9p, 9q, 8p, 7p, 7q and 11q, while discordant patterns were most frequently found in 15q, 20q, 2q, 10p and 11q. Investigation using a CGH array showed that genetically stable multifocal tumors were less frequent, and that a large percentage of urothelial cancers accumulate genetic alterations during multifocal development by clonal evolution. We might have to consider these genetic accumulations during multifocal development when designing strategies for prevention and detection of recurrent multifocal urothelial cancers. CGH array can be a powerful tool for genetic analysis of multifocal urothelial cancer.

Chromosome Aberrations↗

PubMed2005

Children and adults with acute lymphoblastic leukaemia have similar gene expression profiles.

OBJECTIVES: To compare the gene expression pattern in children and adults with acute lymphoblastic leukaemia (ALL) in order to improve our understanding of the difference in disease biology and prognosis. METHODS: The gene expression profiles in diagnostic samples from 29 children and 15 adults with ALL were analysed using the oligonucleotide chip Hu95ver2a, produced by Affymetrix. RESULTS: Unsupervised hierarchical cluster analysis revealed that, in spite of differences in outcome, patients clustered irrespective of age, first by T-cell or B-precursor immunophenotype, and second by cytogenetic changes within the B-precursor group. The expression pattern analysis allowed the reclassification of some samples into the proper cytogenetic group. We also showed that separate clustering of samples with the BCR/ABL translocation could be explained by different breakpoint regions in the BCR. No significant difference in gene expression was observed between samples with and without CDKN2A deletion within the B-precursor group. Analysis of different age groups revealed a similarity in expression profiles when infants with the MLL translocation and adults over 40 yr of age were compared irrespective of karyotype. CONCLUSIONS: In spite of the difference in clinical outcome, the gene expression pattern in children and adults with ALL is very similar and is primarily dependent on immunophenotype and cytogenetic aberrations. However, when age groups are compared, the expression patterns of infants and adults over 40 show a remarkable similarity.

Adult↗

PubMed1995

Automatic magnetic resonance tissue characterization for three-dimensional magnetic resonance imaging of the brain.

Computer-assisted diagnostic systems enhance the information available from magnetic resonance imaging. Segmentations are the basis on which three-dimensional volume renderings are made. The application of a raw data-based, operator-independent (automatic), magnetic resonance segmentation technique for tissue differentiation is demonstrated. Segmentation images of vasogenic edema with gross and histopathological correlation are presented for demonstration of the technique. A pixel was classified into a tissue class based on a feature vector using unsupervised fuzzy clustering techniques as the pattern recognition method. Correlation of fuzzy segmentations and gross and histopathology were successfully performed. Based on the results of neuropathological correlation, the application of fuzzy magnetic resonance image segmentation to a patient with a brain tumor and extensive edema represents a viable technique for automatically displaying clinically important tissue differentiation. With this pattern recognition technique, it is possible to generate automatic segmentation images that display diagnostically relevant neuroanatomical and neuropathological tissue contrast information from raw magnetic resonance data for use in three-dimensional volume reconstructions.

Adult↗

PubMed2005

Quantitative gene expression in Budd-Chiari syndrome: a molecular approach to the pathogenesis of the disease.

BACKGROUND: Budd-Chiari syndrome (BCS) is associated with parenchymal changes leading to major architecture remodelling. In order to gain further insight into the pathogenesis of BCS, we investigated expression of a set of genes involved in the course of chronic liver diseases. METHODS: Quantitative expression of 35 selected genes involved in extracellular matrix regulation, growth factors, and angiogenesis was investigated in 13 cases of BCS and compared with 10 normal livers and 13 cirrhosis cases by real time reverse transcription-polymerase chain reaction. Differential gene expression was considered significant for genes showing at least a twofold variation, with p < 0.05. RESULTS: Expression of 14 genes was significantly increased in BCS versus normal liver, with the highest increase in superior cervical ganglion 10 (SCG10) gene. BCS cases were classified according to their evolution and morphological pattern as either acute or chronic in six and seven cases, respectively. Unsupervised hierarchical clustering of acute and chronic BCS cases on the basis of similarity in gene expression pattern led to distinction between the two groups. Expression of three genes was significantly different in acute versus chronic BCS (increase in matrix metalloproteinase 7 and SCG10, decrease in thrombospondin-1 for chronic BCS). Seventeen and 10 genes, mainly involved in extracellular matrix and vascular remodelling, were significantly deregulated in acute BCS versus normal liver and cirrhosis, respectively. CONCLUSION: These results show that BCS cases display a specific gene expression profile that is different from that of normal liver and cirrhosis; the molecular configuration of BCS can be readily distinguished by its evolution and morphological pattern.

Acute Disease↗

PubMed2004

Aberrant expression of the tyrosine kinase receptor EphA4 and the transcription factor twist in Sézary syndrome identified by gene expression analysis.

Sézary syndrome (Sz) is a malignancy of CD4+ memory skin-homing T cells and presents with erythroderma, lymphadenopathy, and peripheral blood involvement. To gain more insight into the molecular features of Sz, oligonucleotide array analysis was performed comparing gene expression patterns of CD4+ T cells from peripheral blood of patients with Sz with those of patients with erythroderma secondary to dermatitis and healthy controls. Using unsupervised hierarchical clustering gene, expression patterns of T cells from patients with Sz were classified separately from those of benign T cells. One hundred twenty-three genes were identified as significantly differentially expressed and had an average fold change exceeding 2. T cells from patients with Sz demonstrated decreased expression of the following hematopoietic malignancy-linked tumor suppressor genes: TGF-beta receptor II, Mxi1, Riz1, CREB-binding protein, BCL11a, STAT4, and Forkhead Box O1A. Moreover, the tyrosine kinase receptor EphA4 and the potentially oncogenic transcription factor Twist were highly and selectively expressed in T cells of patients with Sz. High expression of EphA4 and Twist was also observed in lesional skin biopsy specimens of a subset of patients with cutaneous T cell lymphomas related to Sz, whereas their expression was nearly undetectable in benign T cells or in skin lesions of patients with inflammatory dermatoses. Detection of EphA4 and Twist may be used in the molecular diagnosis of Sz and related cutaneous T-cell lymphomas. Furthermore, the membrane-bound EphA4 receptor may serve as a target for directed therapeutic intervention.

Female↗

PubMed2004

Gene expression profiling for molecular characterization of inflammatory breast cancer and prediction of response to chemotherapy.

Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer with a 5-year survival limited to approximately 40%. Diagnosis, based on clinical and/or pathological criteria, may be difficult. Optimal systemic neoadjuvant therapy and accurate predictors of pathological response have yet to be defined for increasing response rate and survival. Using DNA microarrrays containing approximately 8,000 genes, we profiled breast cancer samples from 81 patients, including 37 with IBC and 44 with noninflammatory breast cancer (NIBC). Global unsupervised hierarchical clustering was able to some extent to distinguish IBC and NIBC cases and revealed subclasses of IBC. Supervised analysis identified a 109-gene set the expression of which discriminated IBC from NIBC samples. This molecular signature was validated in an independent series of 26 samples, with an overall performance accuracy of 85%. Discriminator genes were associated with various cellular processes possibly related to the aggressiveness of IBC, including signal transduction, cell motility, adhesion, and angiogenesis. A similar approach, with leave-one-out cross-validation, identified an 85-gene set that divided IBC patients with significantly different pathological complete response rate (70% in one group and 0% in the other group). These results show the potential of gene expression profiling to contribute to a better understanding of IBC, and to provide new diagnostic and predictive factors for IBC, as well as for potential therapeutic targets.

Adult↗

PubMed2006

Integrative genomics identifies distinct molecular classes of neuroblastoma and shows that multiple genes are targeted by regional alterations in DNA copy number.

Neuroblastoma is remarkable for its clinical heterogeneity and is characterized by genomic alterations that are strongly correlated with tumor behavior. The specific genes that influence neuroblastoma biology and are targeted by genomic alterations remain largely unknown. We quantified mRNA expression in a highly annotated series of 101 prospectively collected diagnostic neuroblastoma primary tumors using an oligonucleotide-based microarray. Genomic copy number status at the prognostically relevant loci 1p36, 2p24 (MYCN), 11q23, and 17q23 was determined by PCR and was aberrant in 26, 20, 40, and 38 cases, respectively. In addition, 72 diagnostic neuroblastoma primary tumors assayed in a different laboratory were used as an independent validation set. Unsupervised hierarchical clustering showed that gene expression was highly correlated with genomic alterations and clinical markers of tumor behavior. The vast majority of samples with MYCN amplification and 1p36 loss of heterozygosity (LOH) clustered together on a terminal node of the sample dendrogram, whereas the majority of samples with 11q deletion clustered separately and both of these were largely distinct from the copy number neutral group of tumors. Genes involved in neurodevelopment were broadly overrepresented in the more benign tumors, whereas genes involved in RNA processing and cellular proliferation were highly represented in the most malignant cases. By combining transcriptomic and genomic data, we showed that LOH at 1p and 11q was associated with significantly decreased expression of 122 (61%) and 88 (27%) of the genes mapping to 1p35-36 and all of 11q, respectively, suggesting that multiple genes may be targeted by LOH events. A total of 71 of the 1p35-36 genes were also differentially expressed in the independent validation data set, providing a prioritized list of candidate neuroblastoma suppressor genes. Taken together, these data are consistent with the hypotheses that the neuroblastoma transcriptome is a sensitive marker of underlying tumor biology and that chromosomal deletion events in this cancer likely target multiple genes through alteration in mRNA dosage. Lead positional candidates for neuroblastoma suppressor genes can be inferred from these data, but the potential multiplicity of transcripts involved has significant implications for ongoing gene discovery strategies.

Chromosome Aberrations↗

PubMed2006

Cytosine methylation profiles as a molecular marker in non-small cell lung cancer.

Aberrant promoter methylation is frequently observed in different types of lung cancer. Epigenetic modifications are believed to occur before the clinical onset of the disease and hence hold a great promise as early detection markers. Extensive analysis of DNA methylation has been impeded by methods that are either too labor intensive to allow large-scale studies or not sufficiently quantitative to measure subtle changes in the degree of methylation. We used a novel quantitative DNA methylation analysis technology to complete a large-scale cytosine methylation profiling study involving 47 gene promoter regions in 96 lung cancer patients. Each individual contributed a lung cancer specimen and corresponding adjacent normal tissue. The study identified six genes with statistically significant differences in methylation between normal and tumor tissue (P < 10(-6)). We explored the quantitative methylation data using an unsupervised hierarchical clustering algorithm. The data analysis revealed that methylation patterns differentiate normal from tumor tissue. For validation of our approach, we divided the samples to train a classifier and test its performance. We were able to distinguish normal from lung cancer tissue with >95% sensitivity and specificity. These results show that quantitative cytosine methylation profiling can be used to identify molecular classification markers in lung cancer.

Biomarkers, Tumor↗

PubMed2005

Coexpression of beta1,6-N-acetylglucosaminyltransferase V glycoprotein substrates defines aggressive breast cancers with poor outcome.

Beta1,6-n-acetylglucosaminyltransferase-V (GnT-V) catalyzes the addition of complex oligosaccharide side chains to glycoproteins, regulating the expression and function of several proteins involved in tumor metastasis. We analyzed the expression of five cell-surface glycoprotein substrates of GnT-V, matriptase, beta1-integrin, epidermal growth factor receptor, lamp-1, and N-cadherin, on a tissue microarray cohort of 670 breast carcinomas with 30-year follow-up. Phaseolus vulgaris leukocytic phytohemagglutinin (LPHA), a lectin specific for beta1,6-branched oligosaccharides, was used to assay GnT-V activity. Our results show a high degree of correlation of the LPHA staining with matriptase, lamp-1, and N-cadherin expressions, but not with epidermal growth factor receptor or beta1-integrin expressions. In addition, many of the GnT-V substrate proteins exhibited strong coassociations. Elevated levels of GnT-V substrates were correlated with various markers of tumor progression, including positive node status, large tumor size, estrogen receptor negativity, HER2/neu overexpression, and high nuclear grade. Furthermore, LPHA and matriptase showed significant association with disease-related survival. Unsupervised hierarchical clustering of the GnT-V substrate protein expression and LPHA revealed two distinct clusters: one with higher expression of all markers and poor patient outcome and one with lower expression and good outcome. These clusters showed independent prognostic value for disease-related survival when compared with traditional markers of tumor progression. Our results indicate that GnT-V substrate proteins represent a unique subset of coexpressed tumor markers associated with aggressive disease.

Adult↗

PubMed2004

Analysis of aberrant DNA methylation and human papillomavirus DNA in cervicovaginal specimens to detect invasive cervical cancer and its precursors.

PURPOSE: Cancer of the uterine cervix is an important cause of death in women worldwide. Pap smears as a tool for screening decreased the incidence and mortality of cervical cancer dramatically. This proof of principle study aimed to develop a potential tool for cervical screening using a test that can be applied by patients without visiting a physician and to increase the coverage rate, especially of the high-risk population with low socioeconomic status. EXPERIMENTAL DESIGN: Human papillomavirus (HPV) DNA testing and methylation analysis of DNA obtained from cervicovaginal specimens of 13, 31, and 11 patients with no dysplasia/low-grade squamous intraepithelial lesion (SIL), high-grade SIL, and invasive cervical cancer, respectively, collected on a tampon, was performed using PCR-based methods to detect invasive cervical cancer and study whether these changes are already present in the precursor lesions. RESULTS: High-risk HPV DNA was present in 68 and 82% of patients with high-grade SIL and invasive cervical cancer. DNA methylation of the 11 genes tested increased with severity of the cervical lesion. Unsupervised hierarchical cluster analysis using solely information on DNA methylation of the 11 genes was able to predict the presence of invasive cervical cancers: one of the two clusters formed contained 9 of 11 invasive cervical cancers, as well as two high-grade SILs. CONCLUSIONS: HPV DNA and DNA methylation analyzed in cervicovaginal specimens are able to predict invasive cervical cancers. To detect all high-grade SILs when applying this test, genes that become methylated earlier throughout cervical carcinogenesis have to be defined.

DNA↗

PubMed2005

Bladder cancer outcome and subtype classification by gene expression.

Models of bladder tumor progression have suggested that genetic alterations may determine both phenotype and clinical course. We have applied expression microarray analysis to a divergent set of bladder tumors to further elucidate the course of disease progression and to classify tumors into more homogeneous and clinically relevant subgroups. cDNA microarrays containing 10,368 human gene elements were used to characterize the global gene expression patterns in 80 bladder tumors, 9 bladder cancer cell lines, and 3 normal bladder samples. Robust statistical approaches accounting for the multiple testing problem were used to identify differentially expressed genes. Unsupervised hierarchical clustering successfully separated the samples into two subgroups containing superficial (pT(a) and pT(1)) versus muscle-invasive (pT(2)-pT(4)) tumors. Supervised classification had a 90.5% success rate separating superficial from muscle-invasive tumors based on a limited subset of genes. Tumors could also be classified into transitional versus squamous subtypes (89% success rate) and good versus bad prognosis (78% success rate). The performance of our stage classifiers was confirmed in silico using data from an independent tumor set. Validation of differential expression was done using immunohistochemistry on tissue microarrays for cathepsin E, cyclin A2, and parathyroid hormone-related protein. Genes driving the separation between tumor subsets may prove to be important biomarkers for bladder cancer development and progression and eventually candidates for therapeutic targeting.

Aged↗

PubMed2005

Bladder cancer stage and outcome by array-based comparative genomic hybridization.

PURPOSE: Bladder carcinogenesis is believed to follow alternative pathways of disease progression driven by an accumulation of genetic alterations. The purpose of this study was to evaluate associations between measures of genomic instability and bladder cancer clinical phenotype. EXPERIMENTAL DESIGN: Genome-wide copy number profiles were obtained for 98 bladder tumors of diverse stages (29 pT(a), 14 pT1, 55 pT(2-4)) and grades (21 low-grade and 8 high-grade superficial tumors) by array-based comparative genomic hybridization (CGH). Each array contained 2,464 bacterial artificial chromosome and P1 clones, providing an average resolution of 1.5 Mb across the genome. A total of 54 muscle-invasive cases had follow-up information available. Overall outcome analysis was done for patients with muscle-invasive tumors having "good" (alive >2 years) versus "bad" (dead in <2 years) prognosis. RESULTS: Array CGH analysis showed significant increases in copy number alterations and genomic instability with increasing stage and with outcome. The fraction of genome altered (FGA) was significantly different between tumors of different stages (pT(a) versus pT1, P = 0.0003; pT(a) versus pT(2-4), P = 0.02; and pT1 versus pT(2-4), P = 0.03). Individual clones that differed significantly between different tumor stages were identified after adjustment for multiple comparisons (false discovery rate < 0.05). For muscle-invasive tumors, the FGA was associated with patient outcome (bad versus good prognosis patients, P = 0.002) and was identified as the only independent predictor of overall outcome based on a multivariate Cox proportional hazards method. Unsupervised hierarchical clustering separated "good" and "bad" prognosis muscle-invasive tumors into clusters that showed significant association with FGA and survival (Kaplan-Meier, P = 0.019). Supervised tumor classification (prediction analysis for microarrays) had a 71% classification success rate based on 102 unique clones. CONCLUSIONS: Array-based CGH identified quantitative and qualitative differences in DNA copy number alterations at high resolution according to tumor stage and grade. Fraction genome altered was associated with worse outcome in muscle-invasive tumors, independent of other clinicopathologic parameters. Measures of genomic instability add independent power to outcome prediction of bladder tumors.

Chromosome Mapping↗

PubMed2005

Genetic classification of lung adenocarcinoma based on array-based comparative genomic hybridization analysis: its association with clinicopathologic features.

The array-based comparative genomic hybridization using microarrayed bacterial artificial chromosome clones allows high-resolution analysis of genome-wide copy number changes in tumors. To analyze the genetic alterations of primary lung adenocarcinoma in a high-throughput way, we used laser-capture microdissection of cancer cells and array comparative genomic hybridization focusing on 800 chromosomal loci containing cancer-related genes. We identified a large number of chromosomal numerical alterations, including frequent amplifications on 7p12, 11q13, 12q14-15, and 17q21, and two homozygous deletions on 9p21 and one on 8p23. Unsupervised hierarchical clustering analysis of multiple alterations revealed three subgroups of lung adenocarcinoma that were characterized by the accumulation of distinct genetic alterations and associated with smoking history and gender. The mutation status of the epidermal growth factor receptor (EGFR) gene was significantly associated with specific genetic alterations and supervised clustering analysis based on EGFR gene mutations elucidated a subgroup including all EGFR gene mutated tumors, which showed significantly shorter disease-free survival. Our results suggest that there exist multiple molecular carcinogenesis pathways in lung adenocarcinoma that may associate with smoking habits and gender, and that genetic cancer profiling will reveal previously uncharacterized genetic heterogeneity of cancer and be beneficial in estimating patient prognosis and discovering novel cancer-related genes including therapeutic targets.

Adenocarcinoma↗

PubMed2006

Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from diffuse malignant peritoneal mesothelioma.

PURPOSE: Ovarian/primary peritoneal serous carcinoma (OC/PPC) and diffuse peritoneal malignant mesothelioma (DMPM) are highly aggressive tumors that are closely related morphologically and histogenetically. It remains unclear whether both tumors are molecularly distinct neoplasms. The current study compared global gene expression patterns in OC/PPC and DMPM. EXPERIMENTAL DESIGN: Ten OC/PPC and five DMPM effusions were analyzed for gene expression profiles using the Affymetrix U133 Plus 2 arrays and the dCHIP analysis program. Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry. RESULTS: Unsupervised hierarchical clustering using all 54,675 genes in the array classified the samples into two groups: DMPM specimens versus OC/PPC specimens. A total of 189 genes that were differentially expressed in these two groups were selected based on statistical significance. Genes overexpressed in DMPM (n = 68) included calretinin, vitronectin, claudin 15, alpha4 laminin, hyaluronan synthase 1, cadherin 11, RAB7, v-maf, and the epidermal growth factor-containing fibulin-like extracellular matrix protein 1. Genes overexpressed in OC/PPC (n = 121) included insulin-like growth factor II (IGF-II); IGF-II binding protein 3; cyclin E1; folate receptors 1 and 3; RAB25; MUC4; endothelin-1; CD24; kallikreins 6, 7, and 8; claudins 3, 4, and 6; Notch3; and MMP-7. Quantitative real-time PCR validated the differential expression of 13 genes, and immunohistochemistry confirmed the differences for four gene products. CONCLUSIONS: Expression profiling separates OC/PPC from DMPM and identifies a number of genes that are differentially expressed in these tumors. The molecular signatures unique to OC/PPC and DMPM should provide a molecular basis to study both tumors and new potential markers for facilitating their differential diagnosis.

Carcinoma↗

PubMed2006

Gene expression profiling separates chromophobe renal cell carcinoma from oncocytoma and identifies vesicular transport and cell junction proteins as differentially expressed genes.

PURPOSE: To compare gene expression profiles of chromophobe renal cell carcinoma (RCC) and benign oncocytoma, aiming at identifying differentially expressed genes. EXPERIMENTAL DESIGN: Nine cases each of chromophobe RCC and oncocytoma were analyzed by oligonucleotide microarray. Candidate genes that showed consistent differential expression were validated by reverse transcription-PCR using 25 fresh-frozen and 15 formalin-fixed, paraffin-embedded tumor samples. Immunohistochemical analysis was also done for two selected gene products, claudin 8 and MAL2. RESULTS: Unsupervised hierarchical clustering separated the chromophobe RCC and oncocytoma into two distinct groups. By a combination of data analysis approaches, we identified 11 candidate genes showing consistent differential expression between chromophobe RCC and oncocytoma. Five of these genes, AP1M2, MAL2, PROM2, PRSS8, and FLJ20171, were shown to effectively separate these two tumor groups by quantitative reverse transcription-PCR using fresh tissue samples, with similar trends seen on formalin-fixed tissues. Immunohistochemical analysis revealed selective expression of MAL2 and claudin 8 in distal renal tubules, with MAL2 antibody showing differential expression between chromophobe RCC and oncocytoma. Functional analyses suggest that genes encoding tight junction proteins and vesicular membrane trafficking proteins, normally expressed in distal nephrons, are retained in chromophobe RCC and lost or consistently down-regulated in oncocytoma, indicating that these two tumor types, believed to be both derived from distal tubules, are likely distinctive in their histogenesis. CONCLUSIONS: We showed that chromophobe RCC and oncocytoma are distinguishable by mRNA expression profiles and a panel of gene products potentially useful as diagnostic markers were identified.

Adaptor Protein Complex 1↗