Systematic analysis of secreted proteins reveals synergism between IL6 and other proteins in soft agar growth of MCF10A cells

<p>Abstract</p> <p>Introduction</p> <p>Breast cancer, the most common malignancy in women, still holds many secrets. The causes for non-hereditary breast cancer are still unknown. To elucidate any role for circulating naturally secreted proteins, a screen of secreted proteins' influence of MCF10A cell anchorage independent growth was set up.</p> <p>Methods</p> <p>To systematically screen secreted proteins for their capacity to transform mammalian breast epithelial cells, a soft agar screen of MCF10A cells was performed using a library of ~ 470 secreted proteins. A high concentration of infecting viral particles was used to obtain multiple infections in individual cells to specifically study the combined effect of multiple secreted proteins.</p> <p>Results</p> <p>Several known breast cancer factors, such as Wnt, FGF and IL were retained, as well as factors that were previously unknown to have a role in breast cancer, such as paraoxonase 1 and fibroblast growth factor binding protein 2. Additionally, a combinatory role of Interleukin 6 with other factors in MCF10A anchorage-independent growth is demonstrated.</p> <p>Conclusion</p> <p>The transforming effect of combinations of IL6 with other secreted proteins allows studying the transformation of mammary epithelial cells <it>in vitro</it>, and may also have implications in <it>in vivo </it>studies where secreted proteins are upregulated or overexpressed.</p

Number of People Blind or Visually Impaired by Glaucoma Worldwide and in World Regions 1990 – 2010: A Meta-Analysis

Objective: To assess the number of individuals visually impaired or blind due to glaucoma and to examine regional differences and temporal changes in this parameter for the period from 1990 to 2012. Methods: As part of the Global Burden of Diseases (GBD) Study 2010, we performed a systematic literature review for the period from 1980 to 2012. We primarily identified 14,908 relevant manuscripts, out of which 243 high-quality, population-based studies remained after review by an expert panel that involved application of selection criteria that dwelt on population representativeness and clarity of visual acuity methods used. Sixty-six specified the proportion attributable to glaucoma. The software tool DisMod-MR (Disease Modeling–Metaregression) of the GBD was used to calculate fraction of vision impairment due to glaucoma. Results: In 2010, 2.1 million (95% Uncertainty Interval (UI):1.9,2.6) people were blind, and 4.2 (95% UI:3.7,5.8) million were visually impaired due to glaucoma. Glaucoma caused worldwide 6.6% (95% UI:5.9,7.9) of all blindness in 2010 and 2.2% (95% UI:2.0,2.8) of all moderate and severe visual impairment (MSVI). These figures were lower in regions with younger populations (10%). From 1990 to 2010, the number of blind or visually impaired due to glaucoma increased by 0.8 million (95%UI:0.7, 1.1) or 62% and by 2.3 million (95%UI:2.1,3.5) or 83%, respectively. Percentage of global blindness caused by glaucoma increased between 1990 and 2010 from 4.4% (4.0,5.1) to 6.6%. Age-standardized prevalence of glaucoma related blindness and MSVI did not differ markedly between world regions nor between women. Significance: By 2010, one out of 15 blind people was blind due to glaucoma, and one of 45 visually impaired people was visually impaired, highlighting the increasing global burden of glaucoma

The prognostic significance of <i>ANO1</i> and <i>SQLE</i> mRNA expression in colon cancer patients stratified by their TAZ-AXL-CTGF mRNA expression.

<p>Kaplan-Meier analyses for <i>ANO1</i> mRNA expression in patients overexpressing (A) none, (B) one, (C) two and (D) three of the three genes (TAZ, <i>AXL</i> and <i>CTGF</i>) in the GSE14333 colon cancer patient datasets. Kaplan-Meier analyses for <i>SQLE</i> mRNA expression in patients overexpressing (E) none, (F) one, (G) two and (H) three of the three genes in the GSE14333 colon cancer patient datasets. Kaplan-Meier analyses for <i>ANO1</i> mRNA expression in patients overexpressing (I) none, (J) one, (K) two and (L) three of the three genes in the GSE17538 colon cancer patient datasets. Kaplan-Meier analyses for <i>SQLE</i> mRNA expression in patients overexpressed in the GSE17538 colon cancer patient datasets.</p

The associations between TAZ-AXL-CTGF expression and survival in colon cancer patients.

<p>Patients were divided into 4 groups according to the number of genes that they overexpressed (expressed at above the Median level) among TAZ, <i>AXL</i> and <i>CTGF</i>. Kaplan-Meier analyses for TAZ-AXL-CTGF mRNA expression in (A) GSE14333 and (B) GSE17538 colon cancer patient datasets. Univariate and Multivariate Cox regression analyses for TAZ-AXL-CTGF mRNA expression, age, tumor stage and tumor grade in (C) GSE14333 and (D) GSE17538 colon cancer patient datasets.</p

In vitro and in vivo assays for colon cancer cells expressing scramble shRNA or TAZ shRNA.

<p>(A) Western blot showing that shTAZ specifically knockdown TAZ, but not YAP, and that AXL was down-regulated in shTAZ cells compared to shScr cells. (B) The clonogenicity and non-adherent growth of HCT116 cells expressing shScr or shTAZ were assessed and the number of colonies formed from three repeats was recorded (C) The clonogenicity and non-adherent growth of SW620 cells expressing shScr or shTAZ were assessed and the number of colonies formed from three repeats was recorded. (D) The in vivo tumorigenicity of HCT116 cells expressing shScr or shTAZ was assessed in nude nice, and the tumor formed was excised and weighted (n = 3 in each group). (E) The in vivo tumorigenicity of SW620 cells expressing shScr or shTAZ was assessed in nude nice, and the tumor formed was excised and weighted (n = 3 in each group).</p

Genes that are co-regulated with TAZ-AXL-CTGF expression in GSE14333 colon cancer patient cohort.

<p>Genes that are co-regulated with TAZ-AXL-CTGF expression in GSE14333 colon cancer patient cohort.</p

Genes that are co-regulated with TAZ-AXL-CTGF expression in GSE17538 colon cancer patient cohort.

<p>Genes that are co-regulated with TAZ-AXL-CTGF expression in GSE17538 colon cancer patient cohort.</p

The associations between TAZ or YAP, and survival in colon cancer patients.

<p>Kaplan-Meier analyses for TAZ mRNA expression in (A) GSE14333 and (B) GSE17538 colon cancer patient datasets. Univariate and Multivariate Cox regression analyses for TAZ mRNA expression, age, tumor stage and tumor grade in (C) GSE14333 and (D) GSE17538 colon cancer patient datasets. Kaplan-Meier analyses for YAP mRNA expression in (E) GSE14333 and (F) GSE17538 colon cancer patient datasets. Univariate and Multivariate Cox regression analyses for TAZ mRNA expression, age, tumor stage and tumor grade in (G) GSE14333 and (H) GSE17538 colon cancer patient datasets.</p