Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis

We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient. We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression

ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis

Transcriptome microarrays have become one of the tools of choice for investigating the genes involved in tumorigenesis and tumor progression, as well as finding new biomarkers and gene expression signatures for the diagnosis and prognosis of cancer. Here, we describe a new database for Integrated Tumor Transcriptome Array and Clinical data Analysis (ITTACA). ITTACA centralizes public datasets containing both gene expression and clinical data. ITTACA currently focuses on the types of cancer that are of particular interest to research teams at Institut Curie: breast carcinoma, bladder carcinoma and uveal melanoma. A web interface allows users to carry out different class comparison analyses, including the comparison of expression distribution profiles, tests for differential expression and patient survival analyses. ITTACA is complementary to other databases, such as GEO and SMD, because it offers a better integration of clinical data and different functionalities. It also offers more options for class comparison analyses when compared with similar projects such as Oncomine. For example, users can define their own patient groups according to clinical data or gene expression levels. This added flexibility and the user-friendly web interface makes ITTACA especially useful for comparing personal results with the results in the existing literature. ITTACA is accessible online at

Spatial normalization of array-CGH data

BACKGROUND: Array-based comparative genomic hybridization (array-CGH) is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, normalization is required to correct for experimental artifacts while preserving the true biological signal. We investigated various sources of systematic variation in array-CGH data and identified two distinct types of spatial effect of no biological relevance as the predominant experimental artifacts: continuous spatial gradients and local spatial bias. Local spatial bias affects a large proportion of arrays, and has not previously been considered in array-CGH experiments. RESULTS: We show that existing normalization techniques do not correct these spatial effects properly. We therefore developed an automatic method for the spatial normalization of array-CGH data. This method makes it possible to delineate and to eliminate and/or correct areas affected by spatial bias. It is based on the combination of a spatial segmentation algorithm called NEM (Neighborhood Expectation Maximization) and spatial trend estimation. We defined quality criteria for array-CGH data, demonstrating significant improvements in data quality with our method for three data sets coming from two different platforms (198, 175 and 26 BAC-arrays). CONCLUSION: We have designed an automatic algorithm for the spatial normalization of BAC CGH-array data, preventing the misinterpretation of experimental artifacts as biologically relevant outliers in the genomic profile. This algorithm is implemented in the R package MANOR (Micro-Array NORmalization), which is described at and available from the Bioconductor site . It can also be tested on the CAPweb bioinformatics platform at

Differential transcription factor expression by human epithelial cells of buccal and urothelial derivation

Identification of transcription factors expressed by differentiated cells is informative not only of tissue-specific pathways, but to help identify master regulators for cellular reprogramming. If applied, such an approach could generate healthy autologous tissue-specific cells for clinical use where cells from the homologous tissue are unavailable due to disease. Normal human epithelial cells of buccal and urothelial derivation maintained in identical culture conditions that lacked significant instructive or permissive signalling cues were found to display inherent similarities and differences of phenotype. Investigation of transcription factors implicated in driving urothelial-type differentiation revealed buccal epithelial cells to have minimal or absent expression of PPARG, GATA3 and FOXA1 genes. Retroviral overexpression of GATA3 or PPARG1 coding sequences in buccal epithelial cells resulted in nuclear immunolocalisation of the respective proteins, with both transductions also inducing expression of the urothelial differentiation-associated claudin 3 tight junction protein. PPARγ1 overexpression alone entrained expression of nuclear FOXA1 and GATA3 proteins, providing objective evidence of its upstream positioning in a transcription factor network and identifying it as a candidate factor for urothelial-type transdifferentiation or reprogramming

Clinical and biological characteristics of cervical neoplasias with FGFR3 mutation

BACKGROUND: We have previously reported activating mutations of the gene coding for the fibroblast growth factor receptor 3 (FGFR3) in invasive cervical carcinoma. To further analyze the role of FGFR3 in cervical tumor progression, we extended our study to screen a total of 75 invasive tumors and 80 cervical intraepithelial neoplasias (40 low-grade and 40 high-grade lesions). RESULTS: Using single strand conformation polymorphism (SSCP) followed by DNA sequencing, we found FGFR3 mutation (S249C in all cases) in 5% of invasive cervical carcinomas and no mutation in intraepithelial lesions. These results suggest that, unlike in bladder carcinoma, FGFR3 mutation does not or rarely occur in non invasive lesions. Compared to patients with wildtype FGFR3 tumor, patients with S249C FGFR3 mutated tumors were older (mean age 64 vs. 49.4 years, P = 0.02), and were more likely to be associated with a non-16/18 HPV type in their tumor. Gene expression analysis demonstrated that FGFR3 mutated tumors were associated with higher FGFR3b mRNA expression levels compared to wildtype FGFR3 tumors. Supervised analysis of Affymetrix expression data identified a significant number of genes specifically differentially expressed in tumors with respect to FGFR3 mutation status. CONCLUSION: This study suggest that tumors with FGFR3 mutation appear to have distinctive clinical and biological characteristics that may help in defining a population of patients for FGFR3 mutation screening

Gene List significance at-a-glance with GeneValorization

Motivation: High-throughput technologies provide fundamental informations concerning thousands of genes. Many of the current research laboratories daily use one or more of these technologies and end-up with lists of genes. Assessing the originality of the results obtained includes being aware of the number of publications available concerning individual or multiple genes and accessing information about these publications. Faced with the exponential growth of publications avaliable and number of genes involved in a study, this task is becoming particularly difficult to achieve

Identification of a Proliferation Gene Cluster Associated with HPV E6/E7 Expression Level and Viral DNA Load in Invasive Cervical Carcinoma

Specific HPV DNA sequences are associated with more than 90% of invasive carcinomas of the uterine cervix. Viral E6 and E7 oncogenes are key mediators in cell transformation by disrupting TP53 and RB pathways. To investigate molecular mechanisms involved in the progression of invasive cervical carcinoma, we performed a gene expression study on cases selected according to viral and clinical parameters. Using Coupled Two-Way Clustering and Sorting Points Into Neighbourhoods methods, we identified a Cervical Cancer Proliferation Cluster composed of 163 highly correlated transcripts, many of which corresponded to E2F pathway genes controlling cell proliferation, whereas no primary TP53 targets were present in this cluster. The average expression level of the genes of this cluster was higher in tumours with an early relapse than in tumours with a favourable course (P=0.026). Moreover, we found that E6/E7 mRNA expression level was positively correlated with the expression level of the cluster genes and with viral DNA load. These findings suggest that HPV E6/E7 expression level plays a key role in the progression of invasive carcinoma of the uterine cervix via the deregulation of cellular genes controlling tumour cell proliferation. HPV expression level may thus correspond to a biological marker useful for prognosis assessment and specific therapy of the disease

A comprehensive modular map of molecular interactions in RB/E2F pathway

We present, here, a detailed and curated map of molecular interactions taking place in the regulation of the cell cycle by the retinoblastoma protein (RB/RB1). Deregulations and/or mutations in this pathway are observed in most human cancers. The map was created using Systems Biology Graphical Notation language with the help of CellDesigner 3.5 software and converted into BioPAX 2.0 pathway description format. In the current state the map contains 78 proteins, 176 genes, 99 protein complexes, 208 distinct chemical species and 165 chemical reactions. Overall, the map recapitulates biological facts from approximately 350 publications annotated in the diagram. The network contains more details about RB/E2F interaction network than existing large-scale pathway databases. Structural analysis of the interaction network revealed a modular organization of the network, which was used to elaborate a more summarized, higher-level representation of RB/E2F network. The simplification of complex networks opens the road for creating realistic computational models of this regulatory pathway

Activating mutations of the tyrosine kinase receptor FGFR3 are associated with benign skin tumors in mice and humans

Specific germline activating point mutations in the gene encoding the tyrosine kinase receptor FGFR3 (fibroblast growth factor receptor 3) result in autosomal dominant human skeletal dysplasias. The identification in multiple myeloma and in two epithelial cancers—bladder and cervical carcinomas—of somatic FGFR3 mutations identical to the germinal activating mutations found in skeletal dysplasias, together with functional studies, have suggested an oncogenic role for this receptor. Although acanthosis nigricans, a benign skin tumor, has been found in some syndromes associated with germinal activating mutations of FGFR3, the role of activated FGFR3 in the epidermis has never been investigated. Here, we targeted an activated receptor mutant (S249C FGFR3) to the basal cells of the epidermis of transgenic mice. Mice expressing the transgene developed benign epidermal tumors with no sign of malignancy. These skin lesions had features in common with acanthosis nigricans and other benign human skin tumors, including seborrheic keratosis, one of the most common benign epidermal tumors in humans. We therefore screened a series of 62 cases of seborrheic keratosis for FGFR3 mutations. A large proportion of these tumors (39%) harbored somatic activating FGFR3 mutations, identical to those associated with skeletal dysplasia syndromes and bladder and cervical neoplasms. Our findings directly implicate FGFR3 activation as a major cause of benign epidermal tumors in human