RESUMO
Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.
Assuntos
Algoritmos , Neoplasias Encefálicas/genética , Genes Neoplásicos , Estudos de Associação Genética/métodos , Glioma/genética , Ontologia Genética , Humanos , Transdução de Sinais/genéticaRESUMO
Cognitive deficits in neurofibromatosis Type 1 (NF-1) have been documented in both the verbal and visuospatial domains. Previous investigations from our laboratory have determined a specific pattern of "spared" (Picture Arrangement, Picture Completion, and Rapid Automatized Naming) and "impaired" (Judgment of Line Orientation, Vocabulary, and Block Design) performance on cognitive measures in this population when compared to sibling-matched controls in pairwise designs. Growth curve analyses were conducted on these repeated measures in 19 patients with NF-1 and their siblings to investigate the longitudinal course and growth pattern of these spared and impaired measures. Results indicated that over time children with NF-1 do not catch up to their siblings on impaired measures, and they continue to perform similarly to their siblings on the spared measures. With respect to growth rates, on average across the 6 cognitive measures there was no significant difference between the groups. However, the variation among families for level of performance was estimated to be larger than variation among siblings within a family for 2 out of 6 cognitive measures (i.e., providing for these 2, Vocabulary and Rapid Automatized Naming, evidence of substantial familial correlation), suggesting that there is need to consider NF-1 associated deficits within a familial context.