ChIP-Seq Data Analysis to Define Transcriptional Regulatory Networks

Differentially Expressed Genes in Nasopharyngeal Carcinoma Tissues and Their Correlation with Recurrence and Metastasis of Nasopharyngeal Carcinoma

In this study, bioinformatics tools were used to identify key genes to study the molecular mechanism of nasopharyngeal carcinoma (NPC) development and to explore the correlation of these key genes with the recurrence and metastasis of NPC. The GSE61218 microarray dataset obtained from the Gene Expression Omnibus Database (GEO) was used. The limma R package was used to screen differentially expressed genes (DEGs) between NPC and normal nasopharyngeal (NP) tissues. KEGG functional enrichment was performed on these selected DEGs. Protein-protein interaction (PPI) networks were constructed using Cytoscape software to identify key node proteins. The NPC-metastasis microarray dataset GSE103611 was obtained from GEO to analyze the expression of DEGs in NPC metastasis. A total of 239 DEGs were identified. DEGs were mainly enriched in oocyte maturation-related pathways, cytokine-related pathways, cell cycle-related pathways, cancer-related pathways, and homologous recombination-related pathways. In addition, the top 10 nodes with the higher degree in the DEG PPI network were as follows: CDK1, CCNB2, BUB1, CCNA2, AURKB, BUB1B, MAD2L1, NDC80, BIRC5, and CENPF. The results indicated that DEGs may be involved in the pathogenesis of NPC by regulating cell cycle and mitosis, which can be used as molecular biomarkers for the diagnosis of NPC. In addition, we identified 87 DEGs with $\text{FC}>2$ and $P<0.01$ from the metastasis spectrum of NPC. The intersection gene between DEGs of NPC and normal NP tissue samples and those of the metastatic spectrum of NPC was identified to be VRK2. The expression of VRK2 in NPC samples was significantly higher than that in normal NP tissue, and similarly, VRK2 expression was significantly upregulated in metastatic samples compared with nonmetastatic samples ( $P<0.05$ ). Therefore, VRK2 may be a biomarker for predicting the metastasis of NPC patients after treatment.

Identification and Functional Evaluation of a Novel TBX4 Mutation Underlies Small Patella Syndrome

Small patella syndrome (SPS) is a rare autosomal dominant disorder caused by mutations in TBX4 gene which encodes a transcription factor of FGF10. However, how TBX4 mutations result in SPS is poorly understood. Here, a novel TBX4 mutation c.1241C>T (p.P414L) was identified in a SPS family and series of studies were performed to evaluate the influences of TBX4 mutations (including c.1241C>T and two known mutations c.256G>C and c.743G>T). Results showed that mesenchymal stem cells (MSCs) with stable overexpression of either TBX4 wild-type (TBX4^wt) or mutants (TBX4^mt) were successfully generated. Immunofluorescence study revealed that both the overexpressed TBX4 wild-type and mutants were evenly expressed in the nucleus suggesting that these mutations do not alter the translocation of TBX4 into the nucleus. Interestingly, MSCs overexpression of TBX4^mt exhibited reduced differentiation activities and decreased FGF10 expression. Chromatin immunoprecipitation (ChIP) study demonstrated that TBX4 mutants still could bind to the promoter of FGF10. However, dual luciferase reporter assay clarified that the binding efficiencies of TBX4 mutants to FGF10 promoter were reduced. Taken together, MSCs were firstly used to study the function of TBX4 mutations in this study and the results indicate that the reduced binding efficiencies of TBX4 mutants (TBX4^mt) to the promoter of FGF10 result in the abnormal biological processes which provide important information for the pathogenesis of SPS.

Identification of a novel strong promoter from the anhydrobiotic midge, Polypedilum vanderplanki, with conserved function in various insect cell lines

Larvae of the African midge Polypedilum vanderplanki (Diptera: Chironomidae) show a form of extreme desiccation tolerance known as anhydrobiosis. The cell line Pv11 was recently established from the species, and these cells can also survive under desiccated conditions, and proliferate normally after rehydration. Here we report the identification of a new promoter, 121, which has strong constitutive transcriptional activity in Pv11 cells and promotes effective expression of exogenous genes. Using a luciferase reporter assay, this strong transcriptional activity was shown to be conserved in cell lines from various insect species, including S2 (Drosophila melanogaster, Diptera), SaPe-4 (Sarcophaga peregrina, Diptera), Sf9 (Spodoptera frugiperda, Lepidoptera) and Tc81 (Tribolium castaneum, Coleoptera) cells. In conjunction with an appropriate selection maker gene, the 121 promoter was able to confer zeocin resistance on SaPe-4 cells and allowed the establishment of stable SaPe-4 cell lines expressing the fluorescent protein AcGFP1; this is the first report of heterologous gene expression in this cell line. These results show the 121 promoter to be a versatile tool for exogenous gene expression in a wide range of insect cell lines, particularly useful to those from non-model insect species.

The High-Throughput Analyses Era: Are We Ready for the Data Struggle?

Recent and rapid technological advances in molecular sciences have dramatically increased the ability to carry out high-throughput studies characterized by big data production. This, in turn, led to the consequent negative effect of highlighting the presence of a gap between data yield and their analysis. Indeed, big data management is becoming an increasingly important aspect of many fields of molecular research including the study of human diseases. Now, the challenge is to identify, within the huge amount of data obtained, that which is of clinical relevance. In this context, issues related to data interpretation, sharing and storage need to be assessed and standardized. Once this is achieved, the integration of data from different -omic approaches will improve the diagnosis, monitoring and therapy of diseases by allowing the identification of novel, potentially actionably biomarkers in view of personalized medicine.