Rengul Cetin Atalay

Synthesis and biological evaluation of novel pyrazolic chalcone derivatives as novel hepatocellular carcinoma therapeutics

Despite having the second highest mortality associated with cancer, currently Sorafenib is the only FDA-approved chemotherapeutic agent available for liver cancer patients which can only improve survival for few months. In this study, various pyrazolic chalcone analogous compounds were synthesized and evaluated as potential chemotherapeutic agents for the treatment of hepatocellular carcinoma (HCC). Modifying the central pyrazole ring at the C(3)-position with different heteroaryl rings and substituting the C(4)-position of pyrazole with differently substituted chalcone moiety produced fouthy two variant compounds. For all these compounds, cytotoxicity was evaluated using sulforhodamine B assay and real time cell growth tracking, respectively. Based on 50% inhibitory concentration (IC50) values, compounds 39, 42, 49, and 52 were shown to exhibit potent cytotoxic activity against all the cancer cell lines tested, and had better cytotoxic activities than the well-known chemotherapeutic drug 5-FU. Therefore, these compounds were chosen to be further evaluated in a panel of HCC cell lines. Flow cytometric analysis of HCC cells treated with compounds 39, 42, 49, and 52 demonstrated that these compounds caused cell cycle arrest at G2/M phase followed by the apoptotic cell death and impaired cell growth as shown by real-time cell growth surveillance. Consistent with these results, western blotting of HCC cells treated with the compounds resulted in molecular changes for cell cycle proteins, where p21 levels were increased independent of p53 and the levels of the key initiators of mitosis Cyclin B1 and CDK1 were shown to decrease upon treatment. In conclusion, chalcone derivatives 42 and 52 show potent bioactivities by modulating the expression of cell-cycle related proteins and resulting in cell-cycle arrest in the HCC cell lines tested here, indicating that the compounds can be considered as preclinical candidates.

PATZ1 Is a DNA Damage-Responsive Transcription Factor That Inhibits p53 Function

ABSTRACT Insults to cellular health cause p53 protein accumulation, and loss of p53 function leads to tumorigenesis. Thus, p53 has to be tightly controlled. Here we report that the BTB/POZ domain transcription factor PATZ1 (MAZR), previously known for its transcriptional suppressor functions in T lymphocytes, is a crucial regulator of p53. The novel role of PATZ1 as an inhibitor of the p53 protein marks its gene as a proto-oncogene. PATZ1-deficient cells have reduced proliferative capacity, which we assessed by transcriptome sequencing (RNA-Seq) and real-time cell growth rate analysis. PATZ1 modifies the expression of p53 target genes associated with cell proliferation gene ontology terms. Moreover, PATZ1 regulates several genes involved in cellular adhesion and morphogenesis. Significantly, treatment with the DNA damage-inducing drug doxorubicin results in the loss of the PATZ1 transcription factor as p53 accumulates. We find that PATZ1 binds to p53 and inhibits p53-dependent transcription activation. We examine the mechanism of this functional inhibitory interaction and demonstrate that PATZ1 excludes p53 from DNA binding. This study documents PATZ1 as a novel player in the p53 pathway.

Mixture of learners for cancer stem cell detection using CD13 and H and E stained images

In this article, algorithms for cancer stem cell (CSC) detection in liver cancer tissue images are developed. Conventionally, a pathologist examines of cancer cell morphologies under microscope. Computer aided diagnosis systems (CAD) aims to help pathologists in this tedious and repetitive work. The first algorithm locates CSCs in CD13 stained liver tissue images. The method has also an online learning algorithm to improve the accuracy of detection. The second family of algorithms classify the cancer tissues stained with H and E which is clinically routine and cost effective than immunohistochemistry (IHC) procedure. The algorithms utilize 1D-SIFT and Eigen-analysis based feature sets as descriptors. Normal and cancerous tissues can be classified with 92.1% accuracy in H and E stained images. Classification accuracy of low and high-grade cancerous tissue images is 70.4%. Therefore, this study paves the way for diagnosing the cancerous tissue and grading the level of it using H and E stained microscopic tissue images.

Development of a novel zebrafish xenograft model in ache mutants using liver cancer cell lines

Acetylcholinesterase (AChE), an enzyme responsible for degradation of acetylcholine, has been identified as a prognostic marker in liver cancer. Although in vivo Ache tumorigenicity assays in mouse are present, no established liver cancer xenograft model in zebrafish using an ache mutant background exists. Herein, we developed an embryonic zebrafish xenograft model using epithelial (Hep3B) and mesenchymal (SKHep1) liver cancer cell lines in wild-type and achesb55 sibling mutant larvae after characterization of cholinesterase expression and activity in cell lines and zebrafish larvae. The comparison of fluorescent signal reflecting tumor size at 3-days post-injection (dpi) revealed an enhanced tumorigenic potential and a reduced migration capacity in cancer cells injected into homozygous achesb55 mutants when compared with the wild-type. Increased tumor load was confirmed using an ALU based tumor DNA quantification method modified for use in genotyped xenotransplanted zebrafish embryos. Confocal microscopy using the Huh7 cells stably expressing GFP helped identify the distribution of tumor cells in larvae. Our results imply that acetylcholine accumulation in the microenvironment directly or indirectly supports tumor growth in liver cancer. Use of this model system for drug screening studies holds potential in discovering new cholinergic targets for treatment of liver cancers.

Cardiac Glycosides and Oxidative Stress in Liver Cancer

Abstract Hepatocellular carcinoma is the second most-deadly and the sixth most common cancer worldwide. Hence, it is essential to develop novel therapeutic or chemopreventive agents against liver cancer. Cardiac glycosides have been used to treat cardiovascular disorders for centuries, they have been also shown to possess anticancer activities. It is also known that they increase the contractility of cardiac muscles by acting on Na+/K+-ATPase ion pumps. Many cell-signaling mechanisms have been described for the anticancer apoptotic activities of cardiac glycosides due to oxidative stress induced by the variations in intracellular Ca+2 levels and Ras signaling as a result of Na+/K+-ATPase inhibition. Due to the involvement of diverse and distinct cellular pathway inductions by ROS as demonstrated by the actions of Lanatoside C on different liver cancer cell lines, cardiac glycosides can be considered as versatile cell death signaling activators and can be contemplated in clinics for chemoprevention during chronic liver disease and for liver cancer therapeutics.

Synthesis and cellular bioactivities of novel isoxazole derivatives incorporating an arylpiperazine moiety as anticancer agents

Abstract In our endeavour towards the development of effective anticancer therapeutics, a novel series of isoxazole-piperazine hybrids were synthesized and evaluated for their cytotoxic activities against human liver (Huh7 and Mahlavu) and breast (MCF-7) cancer cell lines. Within series, compounds 5l-o showed the most potent cytotoxicity on all cell lines with IC50 values in the range of 0.3–3.7 μM. To explore the mechanistic aspects fundamental to the observed activity, further biological studies with 5m and 5o in liver cancer cells were carried out. We have demonstrated that 5m and 5o induce oxidative stress in PTEN adequate Huh7 and PTEN deficient Mahlavu human liver cancer cells leading to apoptosis and cell cycle arrest at different phases. Further analysis of the proteins involved in apoptosis and cell cycle revealed that 5m and 5o caused an inhibition of cell survival pathway through Akt hyperphosphorylation and apoptosis and cell cycle arrest through p53 protein activation.

Synthesis of Novel Benzothiazole-Piperazine Derivatives and Their Biological Evaluation as Acetylcholinesterase Inhibitors and Cytotoxic Agents

OBJECTIVE AND METHOD A new series of benzothiazole-piperazine derivatives was synthesized and a complete chemical characterization of the novel compounds was provided. In vitro cytotoxic activities were screened against colorectal (HCT-116), breast (MCF-7) and hepatocellular (Huh7) cancer cell lines by Sulforhodamine B assay. RESULT AND DISCUSSION All compounds showed cytotoxic activity against hepatocellular (Huh7) and breast (MCF-7) cancer cell lines. Dihalo substituted benzylpiperazine derivatives (2a, 2e) had the highest cytotoxic activities in all the tested cell lines. In addition, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitory activities of synthesized compounds were investigated by in vitro Ellmans method. Compound 2j led to moderate and selective inhibition against AChE. Docking study was utilized to understand the binding mode of compound 2j in comparision with donepezil on AChE. The other tested compounds showed weak or no inhibition against AChE as promising anticancer agents.

Wavelet merged multi-resolution super-pixels and their applications on fluorescent MSC images

A new multi-resolution super-pixel based algorithm is proposed to track cell size, count and motion in Mesenchymal Stem Cells (MSCs) images. Multi-resolution super-pixels are obtained by placing varying density seeds on the image. The density of the seeds are determined according to the local high frequency components of the MSCs image. In this way a multi-resolution super-pixels decomposition of the image is obtained. A second contribution of the paper is novel decision rule for merging similar neighboring super-pixels. An algorithm based on well known wavelet decomposition is developed and applied to the histograms of neighboring super pixels to exploit similarity. The proposed algorithm is experimentally shown to be successful in segmenting and tracking cells in MSCs images.

Detection of Cancer Stem Cells in microscopic images by using region covariance and codifference method

This paper presents a cancer stem cell detection method using region covariance and codifference method. It focuses on detection of Cancer Stem Cell (CSC) in microscopic images which are stained with CD13 marker. Features of CSC images are extracted by using both covariance method and its multiplication free version codifference method and these features are fed into a Support Vector Machine (SVM) for classification. Experimental results are presented.