Increasing expression of extracellular matrix metalloprotease inducer in renal cell carcinoma: Tissue microarray analysis of immunostaining score with clinicopathological parameters

2006 ◽  
Vol 13 (5) ◽  
pp. 573-580 ◽  
Author(s):  
JONG-SHIAW JIN ◽  
DAR-SHIH HSIEH ◽  
YEH-FENG LIN ◽  
JIA-YI WANG ◽  
LAI-FA SHEU ◽  
...  
2005 ◽  
Vol 4 (6) ◽  
pp. 2117-2125 ◽  
Author(s):  
Slobodan Poznanović ◽  
Wojciech Wozny ◽  
Gerhard P. Schwall ◽  
Chaturvedula Sastri ◽  
Christian Hunzinger ◽  
...  

Author(s):  
Martin Thurnher ◽  
Christian Radmayr ◽  
Reinhold Ramoner ◽  
Susanne Ebner ◽  
Günther Böck ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Tae-Yun Kim ◽  
Nam-Hoon Cho ◽  
Goo-Bo Jeong ◽  
Ewert Bengtsson ◽  
Heung-Kook Choi

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.


2012 ◽  
Vol 61 (2) ◽  
pp. 385-394 ◽  
Author(s):  
Kimberley A. Oldham ◽  
Greg Parsonage ◽  
Rupesh I. Bhatt ◽  
D. Michael A. Wallace ◽  
Nayneeta Deshmukh ◽  
...  

Tumor Biology ◽  
2017 ◽  
Vol 39 (2) ◽  
pp. 101042831769118 ◽  
Author(s):  
Zijie Wang ◽  
Chao Qin ◽  
Jing Zhang ◽  
Zhijian Han ◽  
Jun Tao ◽  
...  

MicroRNAs are short non-coding RNAs, which have been implicated in several biological processes. Aberrant expression of the microRNA miR-122 has frequently been reported in malignant cancers. However, the mechanism underlying the effects of miR-122 in renal cell carcinoma remains unknown. The aim of this study was to determine the biological function of miR-122 in renal cell carcinoma and to identify a novel molecular target regulated by miR-122. We measured the expression levels of Sprouty2 in six renal cell carcinoma tissue samples and adjacent non-tumor tissues by western blot analysis. We then used reverse transcription polymerase chain reaction to measure miR-122 levels in 40 primary renal cell carcinoma and adjacent non-malignant tissue samples. The effects of miR-122 down-regulation or Sprouty2 knockdown were evaluated via Cell Counting Kit-8 assay, flow cytometry, and western blot analysis. The relationship between miR-122 and Sprouty2 was determined using dual-luciferase reporter assays. Sprouty2 was down-regulated in renal cell carcinoma tissue samples compared with adjacent normal tissue. In contrast, miR-122 was up-regulated in primary renal cell carcinoma tissue samples compared with adjacent normal tissue samples. Down-regulation of miR-122 substantially weakened the proliferative ability of renal cell carcinoma cell lines in vitro. In contrast, Sprouty2 knockdown promoted the in vitro proliferation of renal cell carcinoma cell lines. The spry2 gene could therefore be a direct target of miR-122. In conclusion, miR-122 could act as a tumor promoter and potentially target Sprouty2. MiR-122 promotes renal cell carcinoma cell proliferation, migration, and invasion and could be a molecular target in novel therapies for renal cell carcinoma.


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