Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees

Background. Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0). Methods. Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. Results. The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. Conclusion. We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC

Clinicopathologic Factors Related to the Histological Tumor Grade of Breast Cancer in Western China: An Epidemiological Multicenter Study of 8619 Female Patients

BACKGROUND AND PURPOSE: Breast cancer is now recognized as a clinically heterogeneous disease with a wide spectrum of epidemiological and clinicopathologic features. We aimed to evaluate whether epidemiological and clinicopathologic features are associated with the histological tumor grade of breast carcinomas in Western China. METHODS: We retrospectively collected data from the Western China Clinical Cooperation Group and assessed associations between clinicopathologic factors and histological tumor grade in 8619 female breast cancer patients. Patients were divided into two groups: Group I (tumor grade I/II) and Group II (tumor grade III). Univariable analysis and multivariable logistic regression models were used to analyze the relationships between clinicopathologic factors and tumor grade. RESULTS: Patients presenting with positive axillary lymph nodes, large tumor size (>2 cm), lymphovascular invasion, hormone receptor negativity, human epidermal growth factor receptor 2 (HER-2) positivity, and triple negativity tended to have an increased risk of a high tumor grade. However, the number of pregnancies or births was inversely correlated with the risk of a high tumor grade. In addition, patients presenting with grade III tumors were more likely to receive aggressive treatment, such as adjuvant chemotherapy, anti–HER-2 therapy, and level III axillary lymph node dissection. CONCLUSIONS: Our results suggested that several clinicopathologic factors were associated with high tumor grade of breast cancer patients in Western China

Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees

Background. Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0). Methods. Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. Results. The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. Conclusion. We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC

Obesity disproportionately impacts lung volumes, airflow and exhaled nitric oxide in children

<div><p>Background</p><p>The current literature focusing on the effect of obesity and overweight on lung function and fraction of exhaled nitric oxide (FeNO) in children, particularly among healthy children of non-European descent, remains controversial. Furthermore, whether the relationship of obesity and overweight with lung function and FeNO in children is modified by atopy is unclear. The objective of this study was to examine the effect of excess weight on lung function parameters and FeNO among Asian children, with a particular focus on exploring the potential effect modification by atopy.</p><p>Methods</p><p>We investigated the effect of excess weight on lung function and FeNO in a population sample of 1,717 children aged 5 to 18 years and explored the potential modifying effect of atopy.</p><p>Results</p><p>There were positive associations of body mass index (BMI) z-score with forced vital capacity (FVC), forced expiratory volume in 1 second (FEV₁), peak expiratory flow (PEF), and forced expiratory flow at 25–75% (FEF_25-75) (all <i>P</i><0.001), after controlling for confounders. The beta coefficient for FEV₁ (0.084) was smaller than that for FVC (0.111). In contrast, a negative association was found between BMI z-score and FEV₁/FVC ratio (<i>P</i><0.001) and FeNO (<i>P</i> = 0.03). A consistent pattern of association for lung function variables was observed when stratifying by atopy. There was a negative association of BMI z-score with FeNO in atopic subjects (<i>P</i> = 0.006), but not in non-atopic subjects (<i>P</i> = 0.46).</p><p>Conclusions</p><p>Excess weight disproportionately impacts lung volumes and airflow in children from the general population, independent of atopic status. Excess weight inversely affects FeNO in atopic but not in non-atopic children.</p></div

Multivariable analysis of associations of BMI z-scores with lung function variables and FeNO^*.

<p>Multivariable analysis of associations of BMI z-scores with lung function variables and FeNO^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0174691#t004fn002" target="_blank">*</a>}.</p

Association of BMI categories with sex, age and asthma, respectively^*.

<p>Association of BMI categories with sex, age and asthma, respectively^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0174691#t002fn002" target="_blank">*</a>}.</p

Box plots showing median and interquartile ranges of lung function parameters by BMI category.

<p>(A) FVC and (B) FEV₁, (C) FEV₁/FVC ratio, (D) PEF, (E) FEF_25-75, (F) FeNO. <i>P</i> values refer to the comparisons using the ANCOVA model.</p