Maxime Tarabichi

Profiling of olfactory receptor gene expression in whole human olfactory mucosa.

Olfactory perception is mediated by a large array of olfactory receptor genes. The human genome contains 851 olfactory receptor gene loci. More than 50% of the loci are annotated as nonfunctional due to frame-disrupting mutations. Furthermore haplotypic missense alleles can be nonfunctional resulting from substitution of key amino acids governing protein folding or interactions with signal transduction components. Beyond their role in odor recognition, functional olfactory receptors are also required for a proper targeting of olfactory neuron axons to their corresponding glomeruli in the olfactory bulb. Therefore, we anticipate that profiling of olfactory receptor gene expression in whole human olfactory mucosa and analysis in the human population of their expression should provide an opportunity to select the frequently expressed and potentially functional olfactory receptors in view of a systematic deorphanization. To address this issue, we designed a TaqMan Low Density Array (Applied Biosystems), containing probes for 356 predicted human olfactory receptor loci to investigate their expression in whole human olfactory mucosa tissues from 26 individuals (13 women, 13 men; aged from 39 to 81 years, with an average of 67±11 years for women and 63±12 years for men). Total RNA isolation, DNase treatment, RNA integrity evaluation and reverse transcription were performed for these 26 samples. Then 384 targeted genes (including endogenous control genes and reference genes specifically expressed in olfactory epithelium for normalization purpose) were analyzed using the same real-time reverse transcription PCR platform. On average, the expression of 273 human olfactory receptor genes was observed in the 26 selected whole human olfactory mucosa analyzed, of which 90 were expressed in all 26 individuals. Most of the olfactory receptors deorphanized to date on the basis of sensitivity to known odorant molecules, which are described in the literature, were found in the expressed olfactory receptors gene set.

Thyroid cancer cell lines: an overview

Human thyroid cancer cell lines are the most used models for thyroid cancer studies. They must be used with detailed knowledge of their characteristics. These in vitro cell lines originate from differentiated and dedifferentiated in vivo human thyroid tumors. However, it has been shown that mRNA expression profiles of these cell lines were closer to dedifferentiated in vivo thyroid tumors (anaplastic thyroid carcinoma, ATC) than to differentiated ones. Here an overview of the knowledge of these models was made. The mutational status of six human thyroid cancer cell lines (WRO, FTC133, BCPAP, TPC1, K1, and 8505C) was in line with previously reported findings for 10 genes frequently mutated in thyroid cancer. However, the presence of a BRAF mutation (T1799A: V600E) in WRO questions the use of this cell line as a model for follicular thyroid carcinoma (FTC). Next, to investigate the biological meaning of the modulated mRNAs in these cells, a pathway analysis on previously obtained mRNA profiles was performed on five cell lines. In five cell lines, the MHC class II pathway was down-regulated and in four of them, ribosome biosynthesis and translation pathways were up-regulated. mRNA expression profiles of the cell lines were also compared to those of the different types of thyroid cancers. Three datasets originating from different microarray platforms and derived from distinct laboratories were used. This meta-analysis showed a significant higher correlation between the profiles of the thyroid cancer cell lines and ATC, than to differentiated thyroid tumors (i.e., PTC or FTC) specifically for DNA replication. This already observed higher correlation was obtained here with an increased number of in vivo tumors and using different platforms. In summary, this would suggest that some papillary thyroid carcinoma or follicular thyroid carcinoma (PTC or FTC) cell lines (i.e., TPC-1) might have partially lost their original DNA synthesis/replication regulation mechanisms during their in vitro cell adaptation/evolution.

A gene expression signature distinguishes normal tissues of sporadic and radiation-induced papillary thyroid carcinomas

Background:Papillary thyroid cancer (PTC) incidence increased dramatically in children after the Chernobyl accident, providing a unique opportunity to investigate the molecular features of radiation-induced thyroid cancer. In contrast to the previous studies that included age-related confounding factors, we investigated mRNA expression in PTC and in the normal contralateral tissues of patients exposed and non-exposed to the Chernobyl fallout, using age- and ethnicity-matched non-irradiated cohorts.Methods:Forty-five patients were analysed by full-genome mRNA microarrays. Twenty-two patients have been exposed to the Chernobyl fallout; 23 others were age-matched and resident in the same regions of Ukraine, but were born after 1 March 1987, that is, were not exposed to 131I.Results:A gene expression signature of 793 probes corresponding to 403 genes that permitted differentiation between normal tissues from patients exposed and from those who were not exposed to radiation was identified. The differences were confirmed by quantitative RT-PCR. Many deregulated pathways in the exposed normal tissues are related to cell proliferation.Conclusion:Our results suggest that a higher proliferation rate in normal thyroid could be related to radiation-induced cancer either as a predisposition or as a consequence of radiation. The signature allows the identification of radiation-induced thyroid cancers.

Systems biology of cancer: entropy, disorder, and selection-driven evolution to independence, invasion and "swarm intelligence"

Our knowledge of the biology of solid cancer has greatly progressed during the last few years, and many excellent reviews dealing with the various aspects of this biology have appeared. In the present review, we attempt to bring together these subjects in a general systems biology narrative. It starts from the roles of what we term entropy of signaling and noise in the initial oncogenic events, to the first major transition of tumorigenesis: the independence of the tumor cell and the switch in its physiology, i.e., from subservience to the organism to its own independent Darwinian evolution. The development after independence involves a constant dynamic reprogramming of the cells and the emergence of a sort of collective intelligence leading to invasion and metastasis and seldom to the ultimate acquisition of immortality through inter-individual infection. At each step, the probability of success is minimal to infinitesimal, but the number of cells possibly involved and the time scale account for the relatively high occurrence of tumorigenesis and metastasis in multicellular organisms.

A general method to derive robust organ-specific gene expression-based differentiation indices: application to thyroid cancer diagnostic

Differentiation is central to development, while dedifferentiation is central to cancer progression. Hence, a quantitative assessment of differentiation would be most useful. We propose an unbiased method to derive organ-specific differentiation indices from gene expression data and demonstrate its usefulness in thyroid cancer diagnosis. We derived a list of thyroid-specific genes by selecting automatically those genes that are expressed at higher level in the thyroid than in any other organ in a normal tissues genome-wide gene expression compendium. The thyroid index of a tissue was defined as the median expression of these thyroid-specific genes in that tissue. As expected, the thyroid index was inversely correlated with meta-PCNA, a proliferation metagene, across a wide range of thyroid tumors. By contrast, the two indices were positively correlated in a time course of thyroid-stimulating hormone (TSH) activation of primary thyrocytes. Thus, the thyroid index captures biological information not integrated by proliferation rates. The differential diagnostic of follicular thyroid adenomas and follicular thyroid carcinoma is a notorious challenge for pathologists. The thyroid index discriminated them as accurately as did machine-learning classifiers trained on the genome-wide cancer data. Hence, although it was established exclusively from normal tissue data, the thyroid index integrates the relevant diagnostic information contained in tumoral transcriptomes. Similar results were obtained for the classification of the follicular vs classical variants of papillary thyroid cancers, that is, tumors dedifferentiating along a different route. The automated procedures demonstrated in the thyroid are applicable to other organs.

Comparative analysis of the thyrocytes and T cells: responses to H2O2 and radiation reveals an H2O2-induced antioxidant transcriptional program in thyrocytes.

CONTEXT Radiation is an established cause of thyroid cancer, and growing evidence supports a role for hydrogen peroxide (H2O2) in spontaneous thyroid carcinogenesis. Little is known about the molecular programs activated by these agents in thyrocytes. OBJECTIVE The purpose of this study was to compare the responses of thyrocytes and T cells to H2O2 and radiation. METHODS We profiled the DNA damage and cell death induced by γ-radiation (0.1-5 Gy) and H2O2 (0.0025-0.3 mM) in primary human thyrocytes and T cells. We next prepared thyroid and T-cell primary cultures from 8 donors operated for noncancerous thyroid pathological conditions and profiled their genome-wide transcriptional response 4 hours after (1) exposure to 1-Gy radiation, (2) treatment with H2O2 and (3) no treatment. Two H2O2 concentrations were investigated, calibrated in each cell type to elicit levels of single- and double-strand breaks equivalent to 1-Gy γ-radiation. RESULTS Although thyrocytes and T cells had comparable radiation responses, 3- to 10-fold more H2O2 was needed to induce detectable DNA damage in thyrocytes. At H2O2 and radiation doses inducing double-strand breaks, cell death occurred after 24 hours in T cells but not in thyrocytes. The transcriptional responses of thyrocytes and T cells to radiation were similar, involving DNA repair and cell death genes. In addition to this transcriptional program, H2O2 also up-regulated antioxidant genes in thyrocytes, including glutathione peroxidases and heme oxygenase at the double-strand breaks-inducing concentration. In contrast, a transcriptional storm involving thousands of genes was raised in T cells. Finally, we showed that inhibiting glutathione peroxidases activity increased the DNA damaging effect of H2O2 in thyrocytes. CONCLUSION We propose that high H2O2 production in thyrocytes is matched with specific transcriptionally regulated antioxidant protection.

The human bitter taste receptor T2R38 is broadly tuned for bacterial compounds.

T2R38 has been shown to be a specific bacterial detector implicated in innate immune defense mechanism of human upper airway. Several clinical studies have demonstrated that this receptor is associated with the development of chronic rhinosinusitis (CRS). T2R38 was previously reported to bind to homoserine lactones (HSL), quorum sensing molecules specific of Pseudomonas Aeruginosa and other gram negative species. Nevertheless, these bacteria are not the major pathogens found in CRS. Here we report on the identification of bacterial metabolites acting as new agonists of T2R38 based on a single cell calcium imaging study. Two quorum sensing molecules (Agr D1 thiolactone from Staphylococcus Aureus and CSP-1 from Streptococcus Pneumoniae) and a list of 32 bacterial metabolites from pathogens frequently implicated in CRS were tested. First, we observed that HSL failed to activate T2R38 in our experimental system, but that the dimethylsulfoxide (DMSO), used as a solvent for these lactones may, by itself, account for the agonistic effect previously described. Secondly, we showed that both Agr D1 thiolactone and CSP-1 are inactive but that at least 7 bacterial metabolites (acetone, 2-butanone, 2-pentanone, 2-methylpropanal, dimethyl disulfide, methylmercaptan, γ-butyrolactone) are able to specifically trigger this receptor. T2R38 is thus much more broadly tuned for bacterial compounds than previously thought.

miRNA expression and function in thyroid carcinomas: a comparative and critical analysis and a model for other cancers.

As in many cancer types, miRNA expression profiles and functions have become an important field of research on non-medullary thyroid carcinomas, the most common endocrine cancers. This could lead to the establishment of new diagnostic tests and new cancer therapies. However, different studies showed important variations in their research strategies and results. In addition, the action of miRNAs is poorly considered as a whole because of the use of underlying dogmatic truncated concepts. These lead to discrepancies and limits rarely considered. Recently, this field has been enlarged by new miRNA functional and expression studies. Moreover, studies using next generation sequencing give a new view of general miRNA differential expression profiles of papillary thyroid carcinoma. We analyzed in detail this literature from both physiological and differential expression points of view. Based on explicit examples, we reviewed the progresses but also the discrepancies and limits trying to provide a critical approach of where this literature may lead. We also provide recommendations for future studies. The conclusions of this systematic analysis could be extended to other cancer types.

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer

Background:Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities.Methods:We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We also included patient-matched non-cancerous thyroid and lymph node samples as controls to address some limits of previous studies.Results:The transcriptomes of patient-matched primary tumours and metastases were more similar than those of unrelated metastases/primary pairs, as previously reported in other organ systems. This similarity partly reflected patient background. Lymphoid tissues in the metastases confounded the comparison of patient-matched primary tumours and metastases. We circumvented this with an original data adjustment, revealing a differential expression of stroma-related gene signatures also regulated in other organs. The comparison of N0 vs N+ primary tumours uncovered a signal irreproducible across independent data sets. This signal was also detectable when comparing the non-cancerous thyroid tissues adjacent to N0 and N+ tumours, suggesting a cohort-specific bias also likely present in previous similarly sized studies. Classification of N0 vs N+ yielded an accuracy of 63%, but additional statistical controls absent in previous studies revealed that this is explainable by chance alone. We used large data sets from The Cancer Genome Atlas: N0 vs N+ classification was not better than random for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.Conclusions:The clinical potential of gene expression to predict nodal metastases seems limited for most cancers.

Piecewise polynomial representations of genomic tracks.

Genomic data from micro-array and sequencing projects consist of associations of measured values to chromosomal coordinates. These associations can be thought of as functions in one dimension and can thus be stored, analyzed, and interpreted as piecewise-polynomial curves. We present a general framework for building piecewise polynomial representations of genome-scale signals and illustrate some of its applications via examples. We show that piecewise constant segmentation, a typical step in copy-number analyses, can be carried out within this framework for both array and (DNA) sequencing data offering advantages over existing methods in each case. Higher-order polynomial curves can be used, for example, to detect trends and/or discontinuities in transcription levels from RNA-seq data. We give a concrete application of piecewise linear functions to diagnose and quantify alignment quality at exon borders (splice sites). Our software (source and object code) for building piecewise polynomial models is available at http://sourceforge.net/projects/locsmoc/.