ABSTRACT
Immunohistochemistry for vascular network analysis plays a fundamental role in basic science, translational research and clinical practice. However, identifying vascularization in histological tissue images is time consuming and markedly depends on the operator's experience. In this study, we present "blood vessel detection-BVD", an automatic algorithm for quantitative analysis of blood vessels in immunohistochemical images. BVD is based on extraction and analysis of low-level image features and spatial filtering techniques, which do not require a training phase. BVD algorithm performance was comparatively evaluated on histological sections from three different in vivo experiments. Collectively, 173 independent images were analyzed, and the algorithm's results were compared to those obtained by human operators. The developed BVD algorithm proved to be a robust and versatile tool, being able to quantify number, area, and spatial distribution of blood vessels within all three considered histologic datasets. BVD is provided as an open-source application working on different operating systems. BVD is supported by a user-friendly graphical interface designed to facilitate large-scale analysis.
Subject(s)
Algorithms , Tissue Engineering , Humans , Image Processing, Computer-Assisted/methods , Immunohistochemistry , Neovascularization, PathologicABSTRACT
Authors have only now noticed that in the Figure 3a, the immunohistochemical analysis of IL-4Rα on paraffin-embedded sections from breast is incorrect: IL-4 from breast was duplicated and used for the IL-4Rα staining. The correct Figure 3a has been included in the amendment to this paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.
ABSTRACT
We investigated the mechanisms involved in the resistance to cell death observed in epithelial cancers. Here, we identify that primary epithelial cancer cells from colon, breast and lung carcinomas express high levels of the antiapoptotic proteins PED, cFLIP, Bcl-xL and Bcl-2. These cancer cells produced interleukin-4 (IL-4), which amplified the expression levels of these antiapoptotic proteins and prevented cell death induced upon exposure to TRAIL or other drug agents. IL-4 blockade resulted in a significant decrease in the growth rate of epithelial cancer cells and sensitized them, both in vitro and in vivo, to apoptosis induction by TRAIL and chemotherapy via downregulation of the antiapoptotic factors PED, cFLIP, Bcl-xL and Bcl-2. Furthermore, we provide evidence that exogenous IL-4 was able to upregulate the expression levels of these antiapoptotic proteins and potently stabilized the growth of normal epithelial cells rendering them apoptosis resistant. In conclusion, IL-4 acts as an autocrine survival factor in epithelial cells. Our results indicate that inhibition of IL-4/IL-4R signaling may serve as a novel treatment for epithelial cancers.
