Systematic Tracking of Disrupted Modules Identifies Altered Pathways Associated with Congenital Heart Defects in Down Syndrome

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.

Mature miR-99a Upregulation in the Amniotic Fluid Samples from Female Fetus Down Syndrome Pregnancies: A Pilot Study

Background and Objective: Although Down syndrome is the most frequent aneuploidy, its pathogenic molecular mechanisms are not yet fully understood. The aim of our study is to quantify-by qRT-PCR-the expression levels of both the mature forms and the pri-miRNAs of the microRNAs resident on chromosome 21 (miR(21)) in the amniotic fluid samples from Down syndrome singleton pregnancies and to estimate the impact of the differentially expressed microRNAs on Down syndrome fetal heart and amniocytes transcriptomes. Materials and methods: We collected amniotic fluid samples harvested by trained obstetricians as part of the second trimester screening/diagnostic procedure for aneuploidies to assess the trisomy 21 status by QF-PCR and karyotyping. Next, we evaluated-by Taqman qRT-PCR-the expression levels of both the mature forms and the pri-miRNA precursors of the microRNAs resident on chromosome 21 in amniotic fluid samples from singleton Down syndrome and euploid pregnancies. Further, we combined miRWalk 3.0 microRNA target prediction with GEO DataSets analysis to estimate the impact of hsa-miR-99a abnormal expression on Down syndrome heart and amniocytes transcriptome. Results: We found a statistically significant up-regulation of the mature form of miR-99a, but not pri-miR-99a, in the amniotic fluid samples from Down syndrome pregnancies with female fetuses. GATHER functional enrichment analysis of miRWalk3.0-predicted targets from Down syndrome amniocytes and fetal hearts transcriptome GEODataSets outlined both focal adhesion and cytokine-cytokine receptor interaction signaling as novel signaling pathways impacted by miR-99a and associated with cardiac defects in female Down syndrome patients. Conclusions: The significant overexpression of miR-99a, but not pri-miR-99a, points towards an alteration of the post-transcriptional mechanisms of hsa-miR-99a maturation and/or stability in the female trisomic milieu, with a potential impact on signaling pathways important for proper development of the heart.