Background: Dendritic cells (DCs) are a complex group of cells that play a critical role in vertebrate immunity. Lymph-node resident DCs (LN-DCs) are subdivided into conventional DC (cDC) subsets (CD11b and CD8α in mouse; BDCA1 and BDCA3 in human) and plasmacytoid DCs (pDCs). It is currently unclear if these various DC populations belong to a unique hematopoietic lineage and if the subsets identified in the mouse and human systems are evolutionary homologs. To gain novel insights into these questions, we sought conserved genetic signatures for LN-DCs and in vitro derived granulocyte-macrophage colony stimulating factor (GM-CSF) DCs through the analysis of a compendium of genome-wide expression profiles of mouse or human leukocytes. Results: We show through clustering analysis that all LN-DC subsets form a distinct branch within the leukocyte family tree, and reveal a transcriptomal signature evolutionarily conserved in all LN-DC subsets. Moreover, we identify a large gene expression program shared between mouse and human pDCs, and smaller conserved profiles shared between mouse and human LN-cDC subsets. Importantly, most of these genes have not been previously associated with DC function and many have unknown functions. Finally, we use compendium analysis to re-evaluate the classification of interferon-producing killer DCs, lin^-CD16⁺HLA-DR⁺ cells and in vitro derived GM-CSF DCs, and show that these cells are more closely linked to natural killer and myeloid cells, respectively. Conclusion: Our study provides a unique database resource for future investigation of the evolutionarily conserved molecular pathways governing the ontogeny and functions of leukocyte subsets, especially DCs.

Motivation: Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. Results: A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Availability: Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/ Contact: doulaye@titus.u-strasbg.fr

Squamous cell carcinoma (SCC) of the lung is a frequent and aggressive cancer type. Gene amplifications, a known activating mechanism of oncogenes, target the 3q26-qter region as one of the most frequently gained/amplified genomic sites in SCC of various types. Here, we used array comparative genomic hybridization to delineate the consensus region of 3q26.3 amplifications in lung SCC. Recurrent amplifications occur in 20% of lung SCC (136 tumors in total) and map to a core region of 2 Mb (Megabases) that encompasses SOX2, a transcription factor gene. Intense SOX2 immunostaining is frequent in nuclei of lung SCC, indicating potential active transcriptional regulation by SOX2. Analyses of the transcriptome of lung SCC, SOX2-overexpressing lung epithelial cells and embryonic stem cells (ESCs) reveal that SOX2 contributes to activate ESC-like phenotypes and provide clues pertaining to the deregulated genes involved in the malignant phenotype. In cell culture experiments, overexpression of SOX2 stimulates cellular migration and anchorage-independent growth while SOX2 knockdown impairs cell growth. Finally, SOX2 over-expression in non-tumorigenic human lung bronchial epithelial cells is tumorigenic in immunocompromised mice. These results indicate that the SOX2 transcription factor, a major regulator of stem cell function, is also an oncogene and a driver gene for the recurrent 3q26.33 amplifications in lung SCC.