Homeobox gene expression profile indicates HOXA5 as a candidate prognostic marker in oral squamous cell carcinoma

The search for molecular markers to improve diagnosis, individualize treatment and predict behavior of tumors has been the focus of several studies. This study aimed to analyze homeobox gene expression profile in oral squamous cell carcinoma (OSCC) as well as to investigate whether some of these genes are relevant molecular markers of prognosis and/or tumor aggressiveness. Homeobox gene expression levels were assessed by microarrays and qRT-PCR in OSCC tissues and adjacent non-cancerous matched tissues (margin), as well as in OSCC cell lines. Analysis of microarray data revealed the expression of 147 homeobox genes, including one set of six at least 2-fold up-regulated, and another set of 34 at least 2-fold down-regulated homeobox genes in OSCC. After qRT-PCR assays, the three most up-regulated homeobox genes (HOXA5, HOXD10 and HOXD11) revealed higher and statistically significant expression levels in OSCC samples when compared to margins. Patients presenting lower expression of HOXA5 had poorer prognosis compared to those with higher expression (P=0.03). Additionally, the status of HOXA5, HOXD10 and HOXD11 expression levels in OSCC cell lines also showed a significant up-regulation when compared to normal oral keratinocytes. Results confirm the presence of three significantly upregulated (>4-fold) homeobox genes (HOXA5, HOXD10 and HOXD11) in OSCC that may play a significant role in the pathogenesis of these tumors. Moreover, since lower levels of HOXA5 predict poor prognosis, this gene may be a novel candidate for development of therapeutic strategies in OSCC.

MSX2 copy number increase and craniosynostosis: copy number variation detected by array comparative genomic hybridization

Fleury Group

HOXB7 mRNA is overexpressed in pancreatic ductal adenocarcinomas and its knockdown induces cell cycle arrest and apoptosis

Background Human homeobox genes encode nuclear proteins that act as transcription factors involved in the control of differentiation and proliferation. Currently, the role of these genes in development and tumor progression has been extensively studied. Recently, increased expression of HOXB7 homeobox gene (HOXB7) in pancreatic ductal adenocarcinomas (PDAC) was shown to correlate with an invasive phenotype, lymph node metastasis and worse survival outcomes, but no influence on cell proliferation or viability was detected. In the present study, the effects arising from the knockdown of HOXB7 in PDAC cell lines was investigated. Methods Real time quantitative PCR (qRT-PCR) (Taqman) was employed to assess HOXB7 mRNA expression in 29 PDAC, 6 metastatic tissues, 24 peritumoral tissues and two PDAC cell lines. siRNA was used to knockdown HOXB7 mRNA in the cell lines and its consequences on apoptosis rate and cell proliferation were measured by flow cytometry and MTT assay respectively. Results Overexpression of HOXB7 mRNA was observed in the tumoral tissues and in the cell lines MIA PaCa-2 and Capan-1. HOXB7 knockdown elicited (1) an increase in the expression of the pro-apoptotic proteins BAX and BAD in both cell lines; (2) a decrease in the expression of the anti-apoptotic protein BCL-2 and in cyclin D1 and an increase in the number of apoptotic cells in the MIA PaCa-2 cell line; (3) accumulation of cell in sub-G1 phase in both cell lines; (4) the modulation of several biological processes, especially in MIA PaCa-2, such as proteasomal ubiquitin-dependent catabolic process and cell cycle. Conclusion The present study confirms the overexpression of HOXB7 mRNA expression in PDAC and demonstrates that decreasing its protein level by siRNA could significantly increase apoptosis and modulate several biological processes. HOXB7 might be a promising target for future therapies.

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.