Nonparametric network design and analysis of disease genes in oral cancer progression.

Biological networks in living organisms can be seen as the ultimate means of understanding the underlying mechanisms in complex diseases, such as oral cancer. During the last decade, many algorithms based on high-throughput genomic data have been developed to unravel the complexity of gene network construction and their progression in time. However, the small size of samples compared to the number of observed genes makes the inference of the network structure quite challenging. In this study, we propose a framework for constructing and analyzing gene networks from sparse experimental temporal data and investigate its potential in oral cancer. We use two network models based on partial correlations and kernel density estimation, in order to capture the genetic interactions. Using this network construction framework on real clinical data of the tissue and blood at different time stages, we identified common disease-related structures that may decipher the association between disease state and biological processes in oral cancer. Our study emphasizes an altered MET (hepatocyte growth factor receptor) network during oral cancer progression. In addition, we demonstrate that the functional changes of gene interactions during oral cancer progression might be particularly useful for patient categorization at the time of diagnosis and/or at follow-up periods.

Identification of altered MET network in oral cancer progression based on nonparametric network design.

Oral cancer is characterized by multiple genetic events such as alterations of a number of oncogenes and tumour suppressor genes. The aim of this study is to identify genes and their functional interactions that may play a crucial role on a specific disease-state, especially during oral cancer progression. We examine gene interaction networks on blood genomic data, obtained from twenty three oral cancer patients at four different time stages. We generate the gene-gene networks from sparse experimental temporal data using two methods, Partial Correlations and Kernel Density Estimation, in order to capture genetic interactions. The network study reveals an altered MET (hepatocyte growth factor receptor) network during oral cancer progression, which is further analyzed in relation to other studies.

Anomalous cerebral structure in dyslexia revealed with magnetic resonance imaging.

OBJECTIVE: To develop quantitative methods for identifying cerebral anomalies on magnetic resonance images of subjects with language disorders and other learning disabilities. DESIGN: Partially blinded comparison of subjects with dyslexia, unaffected relatives, and a control group balanced for age and socioeconomic status. Criterion standard: clinical diagnosis of dyslexia by physician or learning disabilities specialist on the basis of clinical assessment and family history. SETTINGS: Hospital pediatric neurology clinic and private reading clinic. VOLUNTEERS: individuals with dyslexia (seven male and two female, aged 15 to 65 years) from professional families; unaffected first- and second-degree relatives (four male and six female, aged 6 to 63 years) available in the geographical area; and controls (five male and seven female, aged 14 to 52 years). INTERVENTIONS: Gradient echo three-dimensional scan in Seimens 1-Tesla Magnetom; 128 1.25-mm consecutive sagittal images. MAIN OUTCOME MEASURES: (1) Average length of the temporal (T) and parietal (P) banks of the planum temporale; (2) interhemispheric coefficients of asymmetry for T and P banks: Left-Right interhemispheric coefficients of asymmetry = (L-R)/[(L+R)/2]; (3) intrahemispheric coefficients of asymmetry = (T-P)/[(T+P)/2]; and (4) qualitative assessment of gyral variants in the parietotemporal operculum. RESULTS: All groups had left-sided asymmetry for the temporal bank and right-sided asymmetry for the parietal bank. The group with dyslexia had exaggerated asymmetries, owing to a significant shift of right planar tissue from the temporal to parietal bank. They also had a higher incidence of cerebral anomalies bilaterally (subjects with dyslexia, six of nine; relatives, two of 10; and controls, zero of 12). CONCLUSIONS: Quantitative assessment of high-resolution magnetic resonance images can reveal functionally relevant variations and anomalies in cerebral structure. Further refinement of these measurement techniques should improve the diagnosis, classification, and treatment of language disorders and other learning disabilities.