Nuclear exclusion of p33ING1b tumor suppressor protein: explored in HCC cells using a new highly specific antibody

Image classification of human carcinoma cells using complex wavelet-based covariance descriptors

Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-[Formula: see text]WT) coefficients and several morphological attributes are computed. Directionally selective DT-[Formula: see text]WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html.

Inhibition of Akt signaling in hepatoma cells induces apoptotic cell death independent of Akt activation status

The serine/threonine kinase Akt, a downstream effector of phosphatidylinositol 3-kinase (PI3K), is involved in cell survival and anti-apoptotic signaling. Akt has been shown to be constitutively expressed in a variety of human tumors including hepatocellular carcinoma (HCC). In this report we analyzed the status of Akt pathway in three HCC cell lines, and tested cytotoxic effects of Akt pathway inhibitors LY294002, Wortmannin and Inhibitor VIII. In Mahlavu human hepatoma cells Akt was constitutively activated, as demonstrated by its Ser473 phosphorylation, downstream hyperphosphorylation of BAD on Ser136, and by a specific cell-free kinase assay. In contrast, Huh7 and HepG2 did not show hyperactivation when tested by the same criteria. Akt enzyme hyperactivation in Mahlavu was associated with a loss of PTEN protein expression. Akt signaling was inhibited by the upstream kinase inhibitors, LY294002, Wortmannin, as well as by the specific Akt Inhibitor VIII in all three hepatoma cell lines. Cytotoxicity assays with Akt inhibitors in the same cell lines indicated that they were all sensitive, but with different IC50 values as assayed by RT-CES. We also demonstrated that the cytotoxic effect was through apoptotic cell death. Our findings provide evidence for its constitutive activation in one HCC cell line, and that HCC cell lines, independent of their Akt activation status respond to Akt inhibitors by apoptotic cell death. Thus, Akt inhibition may be considered as an attractive therapeutic intervention in liver cancer.