Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P10636 (tau protein)
 5,110 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Koolen de Vries syndrome (KDVS; MIM 610443) is a genomic disorder caused by a recurrent microdeletion derived from nonallelic homologous recombination mediated by flanking segmental duplications. Clinical manifestations of this syndrome are characterized by intellectual disability, hypotonia, a friendly behavior, distinctive facial features, and epilepsy. Herein, we report a case of 2 girls who revealed global developmental delay, mild facial dysmorphisms, friendly behavior, and epileptic seizure with a de novo 17q21.31 microdeletion detected by chromosomal microarray analysis (CMA). Conventional cytogenetics analysis by GTG-banding showed a female karyotype 46,XX for both girls. CMA revealed a microdeletion spanning approximately 500 kb in 17q21.31 in both girls, encompassing the following genes: CRHR1, MGC57346, CRHR1-IT1, MAPT-AS1, SPPL2C, MAPT, MAPT-IT1, STH, and KANSL1. Haploinsufficiency of one or more of these genes within the deleted region is the most probable cause of the probands' phenotype and is responsible for the phenotype seen in KDVS. CMA is a powerful diagnostic tool and an effective method to identify the de novo 17q21.31 microdeletion associated with KDVS in our probands.
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PMID:Molecular Characterization of Koolen De Vries Syndrome in Two Girls with Idiopathic Intellectual Disability from Central Brazil. 2858 37

Long noncoding RNA (lncRNA) plays a critical role in the development of tumors. The aim of our study was construction of a lncRNA signature model to predict breast cancer (BRCA) patient survival. We downloaded RNA-seq data and relevant clinical information from the Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNA were computed using the "edgeR" package and subjected to the univariate and multivariate Cox regression analysis. Corresponding protein-coding genes were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis. Finally, 521 differentially expression lncRNA were obtained. We constructed a ten-lncRNA signature model (LINC01208, RP5-1011O1.3, LINC01234, LINC00989, RP11-696F12.1, RP11-909N17.2, CTC-297N7.9, CTA-384D8.34, CTC-276P9.4, and MAPT-IT1) to predict BRCA patient survival using the multivariate Cox proportional hazard regression model. The C-index was 0.712, and AUC scores of training, test, and entire sets were 0.746, 0.717, and 0.732, respectively. Univariate Cox regression analysis indicated that age, tumor status, N status, M status, and risk score were significantly related to overall survival in patients with BRCA. Further, the multivariate analysis showed that risk score and M status had outstanding independent prognostic values, both with p < 0.001. The Gene Ontology (GO) function and KEEG pathway analysis was primarily enriched in immune response, receptor binding, external surface of plasma membrane, signal transduction, cytokine-cytokine receptor interaction, and cell adhesion molecules (CAMs). Finally, we constructed a ten-lncRNA signature model that can serve as an independent prognostic model to predict BRCA patient survival.
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PMID:Development of a Ten-lncRNA Signature Prognostic Model for Breast Cancer Survival: A Study with the TCGA Database. 3290 14