Establishment of experimental angiogenic models with applications of quantitative digital image analysis / 中华病理学杂志

<p><b>OBJECTIVE</b>To establish experimental models for tumor neovascularization and to apply quantitative digital imaging analysis in the study.</p><p><b>METHODS</b>An endothelial tube formation model was established by human umbilical vein endothelial cells (HUVECs). A vasculogenic mimicry model was established by SGC-7901 gastric cancer cell line. Fertilized eggs were used to establish a chorioallantoic membrane angiogenesis model. Using gene transfection experiment, IRX1 tumor suppressor gene was chosen as a therapeutic target. Image Pro Plus (IPP) analysis software was used for digital vascular images analysis with parameters including points, lines, angles and integral absorbance (IA) for the tubular formation or vasculogenic mimicry.</p><p><b>RESULTS</b>Digital image analysis by IPP showed that HUVEC tubular formation was significantly inhibited in IRX1 transfectant, compared with controls. The tubular numbers in three groups were 12.80 +/- 3.83, 29.00 +/- 5.34 and 28.20 +/- 4.32 (P<0.01). The connection points of tubules in three groups were 13.20 +/- 2.59, 25.00 +/- 2.24 and 24.60 +/- 3.21 (P<0.01). The tubular lengths of three groups were (821.5 +/- 12.5), (930.9 +/- 13.5) and (948.4 +/- 18.1) microm (P=0.022). The IA values of PAS stain in three groups were 3606 +/- 363, 14 200 +/- 1251 and 15 043 +/- 1220 (P<0.01). In chick chorioallantoic membrane model, the angular numbers of tubules in three groups were 6.41 +/- 2.60, 10.27 +/- 2.65 and 9.18 +/- 1.99 (P<0.01).</p><p><b>CONCLUSIONS</b>The endothelial tube formation model, vasculogenic mimicry model and chorioallantoic membrane angiogenesis model are useful for gene therapy and drug screening with targeting neoplastic vascularization. Professional image analysis software may greatly facilitate the quantitative analysis of tumor neovascularization.</p>

Discovery and verification of matrix gla protein, a TNM staging and prognosis-related biomarker for gastric cancer / 中华病理学杂志

<p><b>OBJECTIVE</b>To analyze microarray datasets deposited in the public database and to identify TNM associated genes in gastric cancers.</p><p><b>METHODS</b>Microarray datasets of gastric cancer were selected from GEO database. Differentially expressed genes related to TNM staging were evaluated by significant analysis of the microarray using MultiExperiment Viewer (MEV) platform. Candidate gene expressions in gastric cancer tissues and cell lines were verified by reverse transcriptase polymerase chain reaction (RT-PCR), quantitative RT-PCR, Western blot and immunohistochemistry.</p><p><b>RESULTS</b>GES4007 dataset was re-analyzed leading to the identification of 14 genes associated with TNM staging. Over-expression of matrix gla protein (MGP) was confirmed in gastric cancer cell lines and tumor tissues by quantitative RT-PCR, Western blot and immunohistochemistry. Increased MGP expression was found in 22 of 54 cases of (40.7%) gastric cancer specimens compared to the normal gastric tissues. The up-regulation of MGP mRNA expression closely correlated with TNM stage (P = 0.001) and prognosis (P = 0.006).</p><p><b>CONCLUSIONS</b>Public databases of microarray studies are the valuable resources for data mining. MGP has been identified and confirmed as a novel biomarker for the TNM stage and prognosis of gastric cancer.</p>