Quantitative linkage of physiology and gene expression through empirical model construction: an investigation of diabetes

A methodology for the construction of predictive empirical models of physiological characteristics from microarray data is presented. The method, applied here to the study of the development of diabetes and insulin resistance, can be further expanded to other cases and to also include a variety of other data, such as protein expression, or metabolic flux data. The importance of several of the genes identified by the modeling methodology can be verified by comparison with results from prior literature. This implies potentially significant roles in diabetes for several of the uncharacterized genes discovered during the modeling procedure.Singapore-MIT Alliance (SMA

Expressing Confidence in Models and in Model Transformation Elements.

The expression and management of uncertainty, both in the information and in the operations that manipulate it, is a critical issue in those systems that work with physical environments. Measurement uncertainty can be due to several factors, such as unreliable data sources, tolerance in the measurements, or the inability to determine if a certain event has actually happened or not. In particular, this contribution focuses on the expression of one kind of uncertainty, namely the confidence on the model elements, i.e., the degree of belief that we have on their occurrence, and on how such an uncertainty can be managed and propagated through model transformations, whose rules can also be subject to uncertainty

Food choices and practices during pregnancy of immigrant women with high-risk pregnancies in Canada: a pilot study

Background: Immigrant women may be regarded as a vulnerable population with respect to access and navigation of maternity care services. They may encounter difficulties when accessing culturally safe and appropriate maternity care, which may be further exacerbated by language difficulties and discriminatory practices or attitudes. The project aimed to understand ethnocultural food and health practices and how these intersect in a particular social context of cultural adaptation and adjustment in order to improve the care-giving capacities of health practitioners working in multicultural perinatal clinics. Methods: This four-phase study employed a case study design allowing for multiple means of data collection and different units of analysis. Phase one consists of a scoping review of the literature. Phases two and three incorporate pictorial representations of food choices with semi-structured photo-elicited interviews. This study was undertaken at a Prenatal and Obstetric Clinic, in an urban Canadian city. In phase four, the research team will inform the development of culturally appropriate visual tools for health promotion. Results: Five themes were identified: (a) Perceptions of Health, (b) Social Support (c) Antenatal Foods (d) Postnatal Foods and (e) Role of Health Education. These themes provide practitioners with an understanding of the cultural differences that affect women’s dietary choices during pregnancy. The project identified building collaborations between practitioners and families of pregnant immigrant women to be of utmost importance in supporting healthy pregnancies, along with facilitating social support for pregnant and breastfeeding mothers. Conclusion: In a multicultural society that contemporary Canada is, it is challenging for health practitioners to understand various ethnocultural dietary norms and practices. Practitioners need to be aware of customary practices of the ethnocultural groups that they work with, while simultaneously recognizing the variation within—not everyone follows customary practices, individuals may pick and choose which customary guidelines they follow. What women choose to eat is also influenced by their own experiences, access to particular foods, socioeconomic status, family context, and so on. The pilot study demonstrated the efficacy of the employed research strategies and we subsequently acquired funding for a national study

Oral tongue cancer gene expression profiling: Identification of novel potential prognosticators by oligonucleotide microarray analysis

<p>Abstract</p> <p>Background</p> <p>The present study is aimed at identifying potential candidate genes as prognostic markers in human oral tongue squamous cell carcinoma (SCC) by large scale gene expression profiling.</p> <p>Methods</p> <p>The gene expression profile of patients (n=37) with oral tongue SCC were analyzed using Affymetrix HG_U95Av2 high-density oligonucleotide arrays. Patients (n=20) from which there were available tumor and matched normal mucosa were grouped into stage (early vs. late) and nodal disease (node positive vs. node negative) subgroups and genes differentially expressed in tumor vs. normal and between the subgroups were identified. Three genes, <it>GLUT3</it>, <it>HSAL2</it>, and <it>PACE4</it>, were selected for their potential biological significance in a larger cohort of 49 patients via quantitative real-time RT-PCR.</p> <p>Results</p> <p>Hierarchical clustering analyses failed to show significant segregation of patients. In patients (n=20) with available tumor and matched normal mucosa, 77 genes were found to be differentially expressed (P< 0.05) in the tongue tumor samples compared to their matched normal controls. Among the 45 over-expressed genes, <it>MMP-1</it> encoding interstitial collagenase showed the highest level of increase (average: 34.18 folds). Using the criterion of two-fold or greater as overexpression, 30.6%, 24.5% and 26.5% of patients showed high levels of <it>GLUT3</it>, <it>HSAL2</it> and <it>PACE4</it>, respectively. Univariate analyses demonstrated that <it>GLUT3</it> over-expression correlated with depth of invasion (P<0.0001), tumor size (P=0.024), pathological stage (P=0.009) and recurrence (P=0.038). <it>HSAL2</it> was positively associated with depth of invasion (P=0.015) and advanced T stage (P=0.047). In survival studies, only <it>GLUT3</it> showed a prognostic value with disease-free (P=0.049), relapse-free (P=0.002) and overall survival (P=0.003). <it>PACE4</it> mRNA expression failed to show correlation with any of the relevant parameters. </p> <p>Conclusion</p> <p>The characterization of genes identified to be significant predictors of prognosis by oligonucleotide microarray and further validation by real-time RT-PCR offers a powerful strategy for identification of novel targets for prognostication and treatment of oral tongue carcinoma.</p

Aberrant expression of RAB1A in human tongue cancer

This study was designed to identify specific gene expression changes in tongue squamous cell carcinomas (TSCCs) compared with normal tissues using in-house cDNA microarray that comprised of 2304 full-length cDNAs from a cDNA library prepared from normal oral tissues, primary oral cancers, and oral cancer cell lines. The genes identified by our microarray system were further analysed at the mRNA or protein expression level in a series of clinical samples by real-time quantitative reverse transcriptase–polymerase chain reaction (qRT–PCR) analysis and imuunohositochemistry. The microarray analysis identified a total of 16 genes that were significantly upregulated in common among four TSCC specimens. Consistent with the results of the microarray, increased mRNA levels of selected genes with known molecular functions were found in the four TSCCs. Among genes identified, Rab1a, a member of the Ras oncogene family, was further analysed for its protein expression in 54 TSCCs and 13 premalignant lesions. We found a high prevalence of Rab1A-overexpression not only in TSCCs (98%) but also in premalignant lesions (93%). Thus, our results suggest that rapid characterisation of the target gene(s) for TSCCs can be accomplished using our in-house cDNA microarray analysis combined with the qRT–PCR and immunohistochemistry, and that the Rab1A is a potential biomarker of tongue carcinogenesis

Clinical relevance of nine transcriptional molecular markers for the diagnosis of head and neck squamous cell carcinoma in tissue and saliva rinse

<p>Abstract</p> <p>Background</p> <p>Analysis of 23 published transcriptome studies allowed us to identify nine genes displaying frequent alterations in HNSCC (<it>FN1, MMP1, PLAU, SPARC</it>, <it>IL1RN, KRT4, KRT13, MAL</it>, and <it>TGM3</it>). We aimed to independently confirm these dysregulations and to identify potential relationships with clinical data for diagnostic, staging and prognostic purposes either at the tissue level or in saliva rinse.</p> <p>Methods</p> <p>For a period of two years, we systematically collected tumor tissue, normal matched mucosa and saliva of patients diagnosed with primary untreated HNSCC. Expression levels of the nine genes of interest were measured by RT-qPCR in tumor and healthy matched mucosa from 46 patients. <it>MMP1 </it>expression level was measured by RT-qPCR in the salivary rinse of 51 HNSCC patients and 18 control cases.</p> <p>Results</p> <p>Dysregulation of the nine genes was confirmed by the Wilcoxon test. <it>IL1RN, MAL </it>and <it>MMP1 </it>were the most efficient diagnostic markers of HNSCC, with ROC AUC > 0.95 and both sensitivity and specificity above 91%. No clinically relevant correlation was found between gene expression level in tumor and T stage, N stage, tumor grade, global survival or disease-free survival. Our preliminary results suggests that with 100% specificity, <it>MMP1 </it>detection in saliva rinse is potentially useful for non invasive diagnosis of HNSCC of the oral cavity or oropharynx, but technical improvement is needed since sensitivity was only 20%.</p> <p>Conclusion</p> <p><it>IL1RN, MAL </it>and <it>MMP1 </it>are prospective tumor diagnostic markers for HNSCC. <it>MMP1 </it>overexpression is the most promising marker, and its detection could help identify tumor cells in tissue or saliva.</p

Circulating microRNAs as novel biomarkers for diabetes mellitus.

Diabetes mellitus is characterized by insulin secretion from pancreatic β cells that is insufficient to maintain blood glucose homeostasis. Autoimmune destruction of β cells results in type 1 diabetes mellitus, whereas conditions that reduce insulin sensitivity and negatively affect β-cell activities result in type 2 diabetes mellitus. Without proper management, patients with diabetes mellitus develop serious complications that reduce their quality of life and life expectancy. Biomarkers for early detection of the disease and identification of individuals at risk of developing complications would greatly improve the care of these patients. Small non-coding RNAs called microRNAs (miRNAs) control gene expression and participate in many physiopathological processes. Hundreds of miRNAs are actively or passively released in the circulation and can be used to evaluate health status and disease progression. Both type 1 diabetes mellitus and type 2 diabetes mellitus are associated with distinct modifications in the profile of miRNAs in the blood, which are sometimes detectable several years before the disease manifests. Moreover, circulating levels of certain miRNAs seem to be predictive of long-term complications. Technical and scientific obstacles still exist that need to be overcome, but circulating miRNAs might soon become part of the diagnostic arsenal to identify individuals at risk of developing diabetes mellitus and its devastating complications