Identification of Tumor-Specific Molecular Signatures in Intracranial Ependymoma and Association With Clinical Characteristics

2006 ◽  
Vol 24 (33) ◽  
pp. 5223-5233 ◽  
Author(s):  
Piergiorgio Modena ◽  
Elena Lualdi ◽  
Federica Facchinetti ◽  
Joris Veltman ◽  
James F. Reid ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Hedgehog Signaling ◽  
Clinical Characteristics ◽  
Disease Onset ◽  
Gene Expression Signature ◽  
Comparative Genomic ◽  
Specific Gene ◽  
Molecular Signatures ◽  
Intracranial Ependymoma

Purpose To delineate clinically relevant molecular signatures of intracranial ependymoma. Materials and Methods We analyzed 24 primary intracranial ependymomas. For genomic profiling, microarray-based comparative genomic hybridization (CGH) was used and results were validated by fluorescent in situ hybridization and loss of heterozygosity mapping. We performed gene expression profiling using microarrays, real-time quantitative reverse transcriptase polymerase chain reaction, and methylation analysis of selected genes. We applied class comparison analyses to compare both genomic and expression profiling data with clinical characteristics. Results A variable number of genomic imbalances were detected by array CGH, revealing multiple regions of recurrent gain (including 2q23, 7p21, 12p, 13q21.1, and 20p12) and loss (including 5q31, 6q26, 7q36, 15q21.1, 16q24, 17p13.3, 19p13.2, and 22q13.3). An ependymoma-specific gene expression signature was characterized by the concurrent abnormal expression of developmental and differentiation pathways, including NOTCH and sonic hedgehog signaling. We identified specific differentially imbalanced genomic clones and gene expression signatures significantly associated with tumor location, patient age at disease onset, and retrospective risk for relapse. Integrated genomic and expression profiling allowed us to identify genes of which the expression is deregulated in intracranial ependymoma, such as overexpression of the putative proto-oncogene YAP1 (located at 11q22) and downregulation of the SULT4A1 gene (at 22q13.3). Conclusion The present exploratory molecular profiling study allowed us to refine previously reported intervals of genomic imbalance, to identify novel restricted regions of gain and loss, and to identify molecular signatures correlating with various clinical variables. Validation of these results on independent data sets represents the next step before translation into the clinical setting.

scholarly journals The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

2021 ◽  
Author(s):  
Ekaterina Bourova-Flin ◽  
Samira Derakhshan ◽  
Afsaneh Goudarzi ◽  
Tao Wang ◽  
Anne-Laure Vitte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Specific Gene ◽  
Specific Expression ◽  
Intrinsic Nature ◽  
Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

scholarly journals Gene Expression Profiling on Global cDNA Arrays Gives Hints Concerning Potential Signal Transduction Pathways Involved in Cardiac Fibrosis of Renal Failure

2003 ◽  
Vol 4 (6) ◽  
pp. 571-583 ◽  
Author(s):  
Kerstin Amann ◽  
Heidrun Ridinger ◽  
Christiane Rutenberg ◽  
Eberhard Ritz ◽  
Gerhard Mall ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Failure ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cardiac Remodelling ◽  
Cardiomyocyte Hypertrophy ◽  
Specific Gene ◽  
Interstitial Tissue ◽  
Sham Operation ◽  
Cdna Arrays

Cardiac remodelling with interstitial fibrosis in renal failure, which so far is only poorly understood on the molecular level, was investigated in the rat model by a global gene expression profiling analysis. Sprague–Dawley rats were subjected to subtotal nephrectomy (SNX) or sham operation (sham) and followed for 2 and 12 weeks, respectively. Heart-specific gene expression profiling, with RZPD Rat Unigene-1 cDNA arrays containing about 27 000 gene and EST sequences revealed substantial changes in gene expression in SNX compared to sham animals. Motor protein genes, growth and differentiation markers, and extracellular matrix genes were upregulated in SNX rats. Obviously, not only genes involved in cardiomyocyte hypertrophy, but also genes involved in the expansion of non-vascular interstitial tissue are activated very early in animals with renal failure. Together with earlier findings in the SNX model, the present data suggest the hypothesis that the local renin–angiotensin system (RAS) may be activated by at least two pathways: (a) via second messengers and Gproteins (short-term signalling); and (b) via motor proteins, actins and integrins (longterm signalling). The study documents that complex hybridization analysis yields reproducible and promising results of patterns of gene activation pointing to signalling pathways involved in cardiac remodelling in renal failure. The complete array data are available via http://www.rzpd.de/cgi-bin/services/exp/viewExpressionData.pl.cgi

scholarly journals Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

2012 ◽  
Vol 1 (2S) ◽  
Author(s):  
Kyle A. Furge ◽  
Karl Dykema ◽  
David Petillo ◽  
Michael Westphal ◽  
Zhongfa Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Cancer Cells ◽  
Expression Profiling ◽  
Renal Cell ◽  
Molecular Signatures ◽  
Genetic Makeup ◽  
Papillary Rcc

Using high-throughput gene-expression profiling technology, we can now gaina better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup ofthe cancer cells. This abnormal genetic makeup can have profound effectson cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeuticagents and radiation. These approaches will lead to better molecularsubclassification of tumours, the basis of personalized medicine. We have, todate, done whole-genome microarray gene-expression profiling on several hundredsof kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used toidentify both cytogenetic abnormalities and molecular pathways that are deregulatedin renal cell carcinoma (RCC). For example, we have identified the deregulationof the VHL-hypoxia pathway in clear-cell RCC, as previously known,and the c-Myc pathway in aggressive papillary RCC. Besides the more commonclear-cell, papillary and chromophobe RCCs, we are currently characterizingthe molecular signatures of rarer forms of renal neoplasia such ascarcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosomeXp11 translocations associated with papillary RCC, renal medullarycarcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response.

scholarly journals Gene Expression Profiling of the Hedgehog Signaling Pathway in Human Meningiomas

2010 ◽  
Vol 16 (7-8) ◽  
pp. 262-270 ◽  
Author(s):  
Ingrid Laurendeau ◽  
Marcela Ferrer ◽  
Delia Garrido ◽  
Nicky D’Haene ◽  
Patricia Ciavarelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Signaling Pathway ◽  
Expression Profiling ◽  
Hedgehog Signaling ◽  
Hedgehog Signaling Pathway ◽  
Human Meningiomas

FOXA1 in breast cancer

2009 ◽  
Vol 11 ◽  
Author(s):  
Harikrishna Nakshatri ◽  
Sunil Badve
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Signature ◽  
Specific Gene ◽  
Breast Cancers ◽  
Transcription Factor Network ◽  
Histopathological Classification

Breast cancer is a heterogeneous disease and classification is important for clinical management. At least five subtypes can be identified based on unique gene expression patterns; this subtype classification is distinct from the histopathological classification. The transcription factor network(s) required for the specific gene expression signature in each of these subtypes is currently being elucidated. The transcription factor network composed of the oestrogen (estrogen) receptor α (ERα), FOXA1 and GATA3 may control the gene expression pattern in luminal subtype A breast cancers. Breast cancers that are dependent on this network correspond to well-differentiated and hormone-therapy-responsive tumours with good prognosis. In this review, we discuss the interplay between these transcription factors with a particular emphasis on FOXA1 structure and function, and its ability to control ERα function. Additionally, we discuss modulators of FOXA1 function, ERα–FOXA1–GATA3 downstream targets, and potential therapeutic agents that may increase differentiation through FOXA1.

scholarly journals Specific Secondary Genetic Alterations in Mantle Cell Lymphoma Provide Prognostic Information Independent of the Gene Expression–Based Proliferation Signature

2007 ◽  
Vol 25 (10) ◽  
pp. 1216-1222 ◽  
Author(s):  
Itziar Salaverria ◽  
Andreas Zettl ◽  
Sílvia Beà ◽  
Victor Moreno ◽  
Joan Valls ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cyclin D1 ◽  
Expression Profiles ◽  
Genetic Alterations ◽  
Comparative Genomic ◽  
Survival Prediction ◽  
Specific Gene ◽  
Prognostic Information ◽  
Substantial Impact ◽  
Mantle Cell

Purpose To compare the genetic relationship between cyclin D1–positive and cyclin D1–negative mantle cell lymphomas (MCLs) and to determine whether specific genetic alterations may add prognostic information to survival prediction based on the proliferation signature of MCLs. Patients and Methods Seventy-one cyclin D1–positive and six cyclin D1–negative MCLs previously characterized by gene expression profiling were examined by comparative genomic hybridization (CGH). Results Cyclin D1–negative MCLs were genetically characterized by gains of 3q, 8q, and 15q, and losses of 1p, 8p23-pter, 9p21-pter, 11q21-q23, and 13q that were also the most common alterations in conventional MCLs. Parallel analysis of CGH aberrations and locus-specific gene expression profiles in cyclin D1–positive patients showed that chromosomal imbalances had a substantial impact on the expression levels of the genes located in the altered regions. The analysis of prognostic factors revealed that the proliferation signature, the number of chromosomal aberrations, gains of 3q, and losses of 8p, 9p, and 9q predicted survival of MCL patients. A multivariate analysis showed that the gene expression-based proliferation signature was the strongest predictor for shorter survival. However, 3q gains and 9q losses provided prognostic information that was independent of the proliferative activity. Conclusion Cyclin D1–positive and –negative MCLs share the same secondary genetic aberrations, supporting the concept that they correspond to the same genetic entity. The integration of genetic information on chromosome 3q and 9q alterations into a proliferation signature-based model may improve the ability to predict survival in patients with MCL.

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