Dental management in head and neck cancers: from intensity-modulated radiotherapy with photons to proton therapy.

INTRODUCTION: Despite reduction of xerostomia with intensity-modulated compared to conformal X-ray radiotherapy, radiation-induced dental complications continue to occur. Proton therapy is promising in head and neck cancers to further reduce radiation-induced side-effects, but the optimal dental management has not been defined. MATERIAL AND METHODS: Dental management before proton therapy was assessed compared to intensity-modulated radiotherapy based on a bicentric experience, a literature review and illustrative cases. RESULTS: Preserved teeth frequently contain metallic dental restorations (amalgams, crowns, implants). Metals blur CT images, introducing errors in tumour and organ contour during radiotherapy planning. Due to their physical interactions with matter, protons are more sensitive than photons to tissue composition. The composition of restorative materials is rarely documented during radiotherapy planning, introducing dose errors. Manual artefact recontouring, metal artefact-reduction CT algorithms, dual or multi-energy CT and appropriate dose calculation algorithms insufficiently compensate for contour and dose errors during proton therapy. Physical uncertainties may be associated with lower tumour control probability and more side-effects after proton therapy. Metal-induced errors should be quantified and removal of metal restorations discussed on a case by case basis between dental care specialists, radiation oncologists and physicists. Metallic amalgams can be replaced with water-equivalent materials and crowns temporarily removed depending on rehabilitation potential, dental condition and cost. Implants might contraindicate proton therapy if they are in the proton beam path. CONCLUSION: Metallic restorations may more severely affect proton than photon radiotherapy quality. Personalized dental care prior to proton therapy requires multidisciplinary assessment of metal-induced errors before choice of conservation/removal of dental metals and optimal radiotherapy.

Identification of candidate genes and gene networks specifically associated with analgesic tolerance to morphine.

Chronic morphine administration may alter the expression of hundreds to thousands of genes. However, only a subset of these genes is likely involved in analgesic tolerance. In this report, we used a behavior genetics strategy to identify candidate genes specifically linked to the development of morphine tolerance. Two inbred genotypes [C57BL/6J (B6), DBA2/J (D2)] and two reciprocal congenic genotypes (B6D2, D2B6) with the proximal region of chromosome 10 (Chr10) introgressed into opposing backgrounds served as the behavior genetic filter. Tolerance after therapeutically relevant doses of morphine developed most rapidly in the B6 followed by the B6D2 genotype and did not develop in the D2 mice and only slightly in the D2B6 animals indicating a strong influence of the proximal region of Chr10 in the development of tolerance. Gene expression profiling and pattern matching identified 64, 53, 86, and 123 predisposition genes and 81, 96, 106, and 82 tolerance genes in the periaqueductal gray (PAG), prefrontal cortex, temporal lobe, and ventral striatum, respectively. A potential gene network was identified in the PAG in which 19 of the 34 genes were strongly associated with tolerance. Eleven of the network genes were found to reside in quantitative trait loci previously associated with morphine-related behaviors, whereas seven were predictive of tolerance (morphine-naive condition). Overall, the genes modified by chronic morphine administration show a strong presence in canonical pathways representative of neuroadaptation. A potentially significant role for the micro-RNA and epigenetic mechanisms in response to chronic administration of pharmacologically relevant doses of morphine was highlighted by candidate genes Dicer and H19.

Cross-talk of expression quantitative trait loci within 2 interacting blood pressure quantitative trait loci.

Genetic dissection of the S rat genome has provided strong evidence for the presence of 2 interacting blood pressure quantitative trait loci (QTLs), termed QTL1 and QTL2, on rat chromosome 5. However, the identities of the underlying interacting genetic factors remain unknown. Further experiments targeted to identify the interacting genetic factors by the substitution mapping approach alone are difficult because of the interdependency of natural recombinations to occur at the 2 QTLs. We hypothesized that the interacting genetic factors underlying these 2 QTLs may interact at the level of gene transcription and thereby represent expression QTLs or eQTLs. To detect these interacting expression QTLs, a custom QTL chip containing the annotated genes within QTL1 and QTL2 was developed and used to conduct a transcriptional profiling study of S and 2 congenic strains that retain either 1 or both of the QTLs. The results uncovered an interaction between 2 transcription factor genes, Dmrta2 and Nfia. Furthermore, the "biological signature" elicited by these 2 transcription factors was differential between the congenic strain that retained Lewis alleles at both QTL1 and QTL2 compared with the congenic strain that retained Lewis alleles at QTL1 alone. A network of transcription factors potentially affecting blood pressure could be traced, lending support to our hypothesis.

Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay.

UNLABELLED: Gene expression and phenotypic functionality can best be associated when they are measured quantitatively within the same experiment. The analysis of such a complex experiment is presented, searching for associations between measures of exploratory behavior in mice and gene expression in brain regions. The analysis of such experiments raises several methodological problems. First and foremost, the size of the pool of potential discoveries being screened is enormous yet only few biologically relevant findings are expected, making the problem of multiple testing especially severe. We present solutions based on screening by testing related hypotheses, then testing the hypotheses of interest. In one variant the subset is selected directly, in the other one a tree of hypotheses is tested hierarchical; both variants control the False Discovery Rate (FDR). Other problems in such experiments are in the fact that the level of data aggregation may be different for the quantitative traits (one per animal) and gene expression measurements (pooled across animals); in that the association may not be linear; and in the resolution of interest only few replications exist. We offer solutions to these problems as well. The hierarchical FDR testing strategies presented here can serve beyond the structure of our motivating example study to any complex microarray study. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Combined application of behavior genetics and microarray analysis to identify regional expression themes and gene-behavior associations.

In this report we link candidate genes to complex behavioral phenotypes by using a behavior genetics approach. Gene expression signatures were generated for the prefrontal cortex, ventral striatum, temporal lobe, periaqueductal gray, and cerebellum in eight inbred strains from priority group A of the Mouse Phenome Project. Bioinformatic analysis of regionally enriched genes that were conserved across all strains revealed both functional and structural specialization of particular brain regions. For example, genes encoding proteins with demonstrated anti-apoptotic function were over-represented in the cerebellum, whereas genes coding for proteins associated with learning and memory were enriched in the ventral striatum, as defined by the Expression Analysis Systematic Explorer (EASE) application. Association of regional gene expression with behavioral phenotypes was exploited to identify candidate behavioral genes. Phenotypes that were investigated included anxiety, drug-naive and ethanol-induced distance traveled across a grid floor, and seizure susceptibility. Several genes within the glutamatergic signaling pathway (i.e., NMDA/glutamate receptor subunit 2C, calmodulin, solute carrier family 1 member 2, and glutamine synthetase) were identified in a phenotype-dependent and region-specific manner. In addition to supporting evidence in the literature, many of the genes that were identified could be mapped in silico to surrogate behavior-related quantitative trait loci. The approaches and data set described herein serve as a valuable resource to investigate the genetic underpinning of complex behaviors.

Physiogenomic resources for rat models of heart, lung and blood disorders.

Cardiovascular disorders are influenced by genetic and environmental factors. The TIGR rodent expression web-based resource (TREX) contains over 2,200 microarray hybridizations, involving over 800 animals from 18 different rat strains. These strains comprise genetically diverse parental animals and a panel of chromosomal substitution strains derived by introgressing individual chromosomes from normotensive Brown Norway (BN/NHsdMcwi) rats into the background of Dahl salt sensitive (SS/JrHsdMcwi) rats. The profiles document gene-expression changes in both genders, four tissues (heart, lung, liver, kidney) and two environmental conditions (normoxia, hypoxia). This translates into almost 400 high-quality direct comparisons (not including replicates) and over 100,000 pairwise comparisons. As each individual chromosomal substitution strain represents on average less than a 5% change from the parental genome, consomic strains provide a useful mechanism to dissect complex traits and identify causative genes. We performed a variety of data-mining manipulations on the profiles and used complementary physiological data from the PhysGen resource to demonstrate how TREX can be used by the cardiovascular community for hypothesis generation.

Transcriptional profiling with a blood pressure QTL interval-specific oligonucleotide array.

Although the evidence for a genetic predisposition to human essential hypertension is compelling, the genetic control of blood pressure (BP) is poorly understood. The Dahl salt-sensitive (S) rat is a model for studying the genetic component of BP. Using this model, we previously reported the identification of 16 different genomic regions that contain one or more BP quantitative trait loci (QTLs). The proximal region of rat chromosome 1 contains multiple BP QTLs. Of these, we have localized the BP QTL1b region to a 13.5-cM (20.92 Mb) region. Interestingly, five additional independent studies in rats and four independent studies in humans have reported genetic linkage for BP control by regions homologous to QTL1b. To view the overall renal transcriptional topography of the positional candidate genes for this QTL, we sought a comparative gene expression profiling between a congenic strain containing QTL1b and control S rats by employing 1) a saturated QTL1b interval-specific oligonucleotide array and 2) a whole genome cDNA microarray representing 20,465 unique genes that are positioned outside the QTL. Results indicated that 17 of the 231 positional candidate genes for this QTL are differentially expressed between the two strains tested. Surprisingly, >1,500 genes outside of QTL1b were differentially expressed between the two rat strains. Integrating the results from the two approaches revealed at least one complex network of transcriptional control initiated by the positional candidate Nr2f2. This network appears to account for the majority of gene expression differences occurring outside of the QTL interval. Further substitution mapping is currently underway to test the validity of each of these differentially expressed positional candidate genes. These results demonstrate the importance of using a saturated oligonucleotide array for identifying and prioritizing differentially expressed positional candidate genes of a BP QTL.

Iterative microarray and RNA interference-based interrogation of the SRC-induced invasive phenotype.

Src kinase has long been recognized as a factor in the progression of colorectal cancer and seems to play a specific role in the development of the metastatic phenotype. In spite of numerous studies conducted to elucidate the exact role of Src in cancer progression, downstream targets of Src remain poorly understood. Gene expression profiling has permitted the identification of large sets of genes that may be functionally interrelated but it is often unclear as to which molecular pathways they belong. Here we have developed an iterative approach to experimentally reconstruct a network of gene activity regulated by Src and contributing to the invasive phenotype. Our strategy uses a combination of phenotypic anchoring of gene expression profiles and loss-of-function screening by way of RNA-mediated interference. Using a panel of human colon cancer cell lines exhibiting differential Src-specific activity and invasivity, we identify the first two levels of gene transcription responsible for the invasive phenotype, where first-tier genes are controlled by Src activity and the second-tier genes are under the influence of the first tier. Specifically, perturbation of first-tier gene activity by either pharmacologic inhibition of Src or RNA-mediated interference-directed knockdown leads to a loss of invasivity and decline of second-tier gene activity. The targeting of first-tier genes may be bypassed altogether because knockdown of second-tier genes led to a similar loss of invasive potential. In this manner, numerous members of a "transcriptional cascade" pathway for metastatic activity have been identified and functionally validated.

Autocrine activation of an osteopontin-CD44-Rac pathway enhances invasion and transformation by H-RasV12.

Activated forms of Ras family members are prevalent in many cancers where Ras mutants transduce signals essential for transformation, angiogenesis, invasion and metastasis. As a cancer progression model, we used NIH3T3 cells to explore the mechanism of Ras-induced tumorigenesis. Ras family mutants H-RasV12 and Rit79L strongly induced foci formation, while Rho family mutants RhoA-QL, Rac1-QL and Cdc42-QL were less effective. A comparison of downstream transcriptional targets of Ras and Rho family members using a 26 383 element cDNA microarray revealed that the osteopontin (OPN) gene exhibited the best correlation between magnitude of gene expression change and level of foci formation (r=0.96, P<0.001). In association with H-RasV12- and Rit79L-mediated transformation, foci secreted OPN protein and upregulated the OPN receptor CD44, suggesting the novel initiation of an aberrant OPN-CD44-Rac autocrine pathway. In support of this were the following observations. First, RGD-deficient OPN protein-binding activity was present in H-RasV12-transformed cells but not in control cells, and binding activity was inhibited by the CD44 blocking antibody. Second, foci formation, cell invasion and Rac activity were induced by H-RasV12 and inhibited by the CD44 blocking antibody. Third, foci formation by H-RasV12 was substantially reduced by a short interfering RNA (siRNA) specifically targeting OPN expression for knockdown. Fourth, H-RasV12-mediated transformation was not blocked by the GRGDS peptide, suggesting that OPN effects were not mediated by the integrins. Lastly, OPN knockdown affected the downstream expression of 160 '2nd tier' genes, and at least a subset of these genes appears to be involved in transformation. Indeed, four genes were selected for knockdown, each resulting in a disruption of foci formation and/or invasion. These results underscore the role of aberrant autocrine signaling and transcriptional networking during tumorigenesis.