112 research outputs found

    DataSheet_1_In-depth analysis of the expression and functions of signal transducers and activators of transcription in human ovarian cancer.docx

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    BackgroundSignal transducers and activators of transcription (STAT) transcription factors, a family of genes encoding transcription factors, have been linked to the development of numerous types of tumors. However, there is a relative paucity of a comprehensive investigation of the expression and functional analysis of STATs in ovarian cancer (OV).MethodGene expression profile interaction analysis (GEPI2A), Metascape, The Cancer Genome Atlas (TCGA), Kaplan-Meier Plotter, Linkedomics, and CancerSEA databases were used for expression analysis and functional enrichment of STATs in ovarian cancer patients. We screened potential predictive genes and evaluated their prognostic value by constructing the minor absolute shrinkage and selection operator (LASSO) Cox proportional risk regression model. We explored STAT5A expression and its effects on cell invasion using ovarian cancer cells and a tissue microarray.ResultsThe expression level of STAT1 was higher, but that of STAT2-6 was lower in cancerous ovarian tissues compared to normal tissues, which were closely associated with the clinicopathological features. Low STAT1, high STAT4, and 6 mRNA levels indicated high overall survival. STAT1, 3, 4, and 5A were collectively constructed as prognostic risk models. STAT3, and 5A, up-regulating in the high-risk group, were regarded as risk genes. In subsequent validation, OV patients with a low level of P-STAT5A but not low STAT5A had a longer survival time (P=0.0042). Besides, a negative correlation was found between the expression of STAT5A and invasion of ovarian cancer cells (R= -0.38, p ConclusionIt is suggested that STAT1, STAT4, and STAT6 may be potential targets for the proper treatment of ovarian cancer. STAT5A and P-STAT5A, biomarkers identified in ovarian cancer, may offer new perspectives for predicting prognosis and assessing therapeutic effects.</p

    Secondary structure prediction of hic31.

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    <p>Based on the protein sequence of hic22, the secondary structure prediction is performed by Phyre<sup>2</sup>. The amino acids are colored based on the physiochemical properties of the side chains. The regions adopting putative α-helix and β-sheet conformations are represented as green spiral and blue arrow, respectively. The degrees of confidence 0.9 are also indicated by a rainbow color gradient.</p

    The relative expression level of hic31 in the pearl sac during the early stages of pearl formation after implantation.

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    <p>The relative expression level of hic31 in the pearl sac during the early stages of pearl formation after implantation.</p

    Amino acid composition (mole percent) of Hic31.

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    <p>Amino acid composition (mole percent) of Hic31.</p

    Comparisons of simulated and measured SSA under different cultivars and N rates.

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    <p>Comparisons of simulated and measured SSA under different cultivars and N rates.</p

    Changes of SSA in the 5<sup>th</sup> leaf rank on main stem in YD6 under different N rates with TT.

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    <p>Changes of SSA in the 5<sup>th</sup> leaf rank on main stem in YD6 under different N rates with TT.</p

    cDNA and deduced amino acid sequence of hic31.

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    <p>The putative signal peptide is shown underlined. The putative polyadenylation signal (AATATA) is shown underlined boxed. The cDNA sequence of hic31 has been submitted to Genebank (Accession No. KR534872).</p

    Changes of SSA in the 1<sup>th</sup>-8<sup>th</sup> leaf ranks on main stem with TT in YD6 under N3 rate.

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    <p>Changes of SSA in the 1<sup>th</sup>-8<sup>th</sup> leaf ranks on main stem with TT in YD6 under N3 rate.</p

    Detailed information about template in the secondary structure prediction.

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    <p>Detailed information about template in the secondary structure prediction.</p
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