ABSTRACT
Background: Epithelial-to-mesenchymal transition (EMT) is a key step in the transformation of epithelial cells into migratory and invasive tumour cells. Intricate positive and negative regulatory processes regulate EMT. Many oncogenic signalling pathways can induce EMT, but the specific mechanisms of how this occurs, and how this process is controlled are not fully understood. Methods: RNA-Seq analysis, computational analysis of protein networks and large-scale cancer genomics datasets were used to identify ELF3 as a negative regulator of the expression of EMT markers. Western blotting coupled to siRNA as well as analysis of tumour/normal colorectal cancer panels was used to investigate the expression and function of ELF3. Results: RNA-Seq analysis of colorectal cancer cells expressing mutant and wild-type ß-catenin and analysis of colorectal cancer cells expressing inducible mutant RAS showed that ELF3 expression is reduced in response to oncogenic signalling and antagonizes Wnt and RAS oncogenic signalling pathways. Analysis of gene-expression patterns across The Cancer Genome Atlas (TCGA) and protein localization in colorectal cancer tumour panels showed that ELF3 expression is anti-correlated with ß-catenin and markers of EMT and correlates with better clinical prognosis. Conclusions: ELF3 is a negative regulator of the EMT transcription factor (EMT-TF) ZEB1 through its function as an antagonist of oncogenic signalling.
Subject(s)
Adenocarcinoma/genetics , Colorectal Neoplasms/genetics , DNA-Binding Proteins/metabolism , Epithelial-Mesenchymal Transition/genetics , Proto-Oncogene Proteins c-ets/metabolism , Transcription Factors/metabolism , Zinc Finger E-box-Binding Homeobox 1/genetics , Adenocarcinoma/mortality , Adenocarcinoma/pathology , Cell Line, Tumor , Cell Transformation, Neoplastic/genetics , Colorectal Neoplasms/mortality , Colorectal Neoplasms/pathology , Datasets as Topic , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Humans , Prognosis , RNA-Seq , Survival Analysis , Tissue Array Analysis , Wnt Signaling Pathway/genetics , ras Proteins/metabolismABSTRACT
In this study, the effect of a combination of vitamin C, vitamin E and selenium on ethanol-induced duodenal mucosal damage in rats was investigated morphologically and biochemically. The duodenal mucosal injury was produced by oral administration of 1 mL of absolute ethanol to each rat. Animals received vitamin C (250 mg/ kg), vitamin E (250 mg/kg) and selenium (0.5 mg/kg) for 3 days and absolute ethanol 1 hour after last antioxidant administration and were sacrificed 1 hour after absolute ethanol. Extreme degeneration in intestinal mucosa of rats given ethanol was observed morphologically. In addition, an increase in neuronal nitric oxide synthase immunoreactive areas was observed in the rats of the group given ethanol. On the other hand, a normal morphological appearance and a decrease in neuronal nitric oxide synthase immunoreactive areas were detected in the rats given ethanol+vitamin C+vitamin E+ selenium. In the group to which ethanol was administered, an increase in serum cholesterol and a decrease in serum albumin levels were determined. On the other hand, in the group to which ethanol+vitamin C+vitamin E+selenium were administered, serum cholesterol value decreased, and the serum albumin level increased. As a result, we can say that the combination of vitamin C, vitamin E and selenium has a protective effect on ethanol-induced duodenal mucosal injury.
Subject(s)
Antioxidants/pharmacology , Ascorbic Acid/pharmacology , Central Nervous System Depressants/toxicity , Ethanol/toxicity , Intestinal Mucosa/drug effects , Selenium/pharmacology , Vitamin E/pharmacology , Animals , Cholesterol/blood , Duodenum/pathology , Female , Intestinal Mucosa/pathology , Nitric Oxide Synthase/pharmacology , Rats , Rats, Sprague-DawleyABSTRACT
In polyacrylamide gel electrophoresis (PAGE) image analysis, it is important to determine the percentage of the protein of interest of a protein mixture. This study presents reliable computer software to determine this percentage. The region of interest containing the protein band is detected using the snake algorithm. The iterative snake algorithm is implemented in a multi-resolutional framework. The snake is initialized on a low-resolution image. Then, the final position of the snake at the low resolution is used as the initial position in the higher-resolution image. Finally, the area of the protein is estimated as the area enclosed by the final position of the snake.
