FAT, E-cadherin, β catenin, HER 2/neu, Ki67 immunoexpression, and histological grade in intrahepatic cholangiocarcinoma

Aim: To identify surrogate prognostic markers in intrahepatic cholangiocarcinoma (IHCC). Methods: Thirty one cases of IHCC were graded and immunostained for FAT, Ki67, E-cadherin, β catenin, and HER 2/neu. Results: Twenty two cases were high grade and 27 had high Ki67 counts. Strong membranous staining of HER 2/neu was found in 10 tumours and reduced membranous E-cadherin and β catenin in 19 and 18 tumours, respectively. Nuclear localisation of β catenin was identified in five tumours and 22 showed weak cytoplasmic staining of FAT. Strong HER 2/neu and weak FAT immunoexpression were significantly correlated with high histological grade (p  =  0.01) and high Ki67 index (p  =  0.03). Upregulation of HER 2/neu was also significantly associated with nuclear localisation of β catenin (p  =  0.01). Reduced membranous β catenin was significantly related to reduced membranous E-cadherin (p  =  0.03), weak staining for FAT (p  =  0.01), and nuclear translocation of β catenin (p  =  0.04). Conclusions: Reduced immunoexpression of E-cadherin and FAT at their normal membranous location may be potential prognostic markers, and the overexpression of HER 2/neu and β catenin nuclear translocation may have a role in cholangiocarcinogenesis

Exploring targeted therapy of osteosarcoma using proteomics data

Parunya Chaiyawat,1 Jongkolnee Settakorn,2 Apiruk Sangsin,1 Pimpisa Teeyakasem,1 Jeerawan Klangjorhor,1 Aungsumalee Soongkhaw,2 Dumnoensun Pruksakorn1,3 1Orthopedic Laboratory and Research Netting Center, Department of Orthopedics, 2Department of Pathology, Faculty of Medicine, 3Excellence Center in Osteology Research and Training Center, Chiang Mai University, Chiang Mai, Thailand Abstract: Despite multimodal therapeutic treatments of osteosarcoma (OS), some patients develop resistance to currently available regimens and eventually end up with recurrent or metastatic outcomes. Many attempts have been made to discover effective drugs for improving outcome; however, due to the heterogeneity of the disease, new therapeutic options have not yet been identified. This study aims to explore potential targeted therapy related to protein profiles of OS. In this review of proteomics studies, we extracted data on differentially expressed proteins (DEPs) from archived literature in PubMed and our in-house repository. The data were divided into three experimental groups, DEPs in 1) OS/OB: OS vs osteoblastic (OB) cells, 2) metastasis: metastatic vs non-metastatic sublines plus fresh tissues from primary OS with and without pulmonary metastasis, and 3) chemoresistance: spheroid (higher chemoresistance) vs monolayer cells plus fresh tissues from biopsies from good and poor responders. All up-regulated protein entities in the list of DEPs were sorted and cross-referenced with identifiers of targets of US Food and Drug Administration (FDA)-approved agents and chemical inhibitors. We found that many targets of FDA-approved antineoplastic agents, mainly a group of epigenetic regulators, kinases, and proteasomes, were highly expressed in OS cells. Additionally, some overexpressed proteins were targets of FDA-approved non-cancer drugs, including immunosuppressive and antiarrhythmic drugs. The resulting list of chemical agents showed that some transferase enzyme inhibitors might have anticancer activity. We also explored common targets of OS/OB and metastasis groups, including amidophosphoribosyltransferase (PPAT), l-lactate dehydrogenase B chain (LDHB), and pyruvate kinase M2 (PKM2) as well as the common target of all categories, cathepsin D (CTSD). This study demonstrates the benefits of a text mining approach to exploring therapeutic targets related to protein expression patterns. These results suggest possible repurposing of some FDA-approved medicines for the treatment of OS and using chemical inhibitors in drug screening tests. Keywords: osteosarcoma, proteomics, targeted therapy, text mining, FDA-approved drug

Genotypic distribution of multidrug-resistant and extensively drug-resistant tuberculosis in northern Thailand

Risara Jaksuwan,1 Prasit Tharavichikul,2 Jayanton Patumanond,3 Charoen Chuchottaworn,4 Sakarin Chanwong,5 Saijai Smithtikarn,6 Jongkolnee Settakorn7 1Clinical Epidemiology Unit, 2Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 3Division of Clinical Epidemiology, Faculty of Medicine, Thammasat University, Pathum Thani, 4Division of Respiratory Medicine, Chest Disease Institute, Nonthaburi, 5Office of Disease Prevention and Control Region 10, Chiang Mai, 6Bureau of Tuberculosis, Department of Disease Control, Ministry of Public Health, Bangkok, 7Department of Pathology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand Background: Multidrug/extensively drug-resistant tuberculosis (M/XDR-TB) is a major public health problem, and early detection is important for preventing its spread. This study aimed to demonstrate the distribution of genetic site mutation associated with drug resistance in M/XDR-TB in the northern Thai population. Methods: Thirty-four clinical MTB isolates from M/XDR-TB patients in the upper northern region of Thailand, who had been identified for drug susceptibility using the indirect agar proportion method from 2005 to 2012, were examined for genetic site mutations of katG, inhA, and ahpC for isoniazid (INH) drug resistance and rpoB for rifampicin (RIF) drug resistance. The variables included the baseline characteristics of the resistant gene, genetic site mutations, and drug susceptibility test results. Results: All 34 isolates resisted both INH and RIF. Thirty-two isolates (94.1%) showed a mutation of at least 1 codon for katG, inhA, and ahpC genes. Twenty-eight isolates (82.4%) had a mutation of at least 1 codon of rpoB gene. The katG, inhA, ahpC, and rpoB mutations were detected in 20 (58.7%), 27 (79.4%), 13 (38.2%), and 28 (82.3%) of 34 isolates. The 3 most common mutation codons were katG 315 (11/34, 35.3%), inhA 14 (11/34, 32.4%), and inhA 114 (11/34, 32.4%). For this population, the best genetic mutation test panels for INH resistance included 8 codons (katG 310, katG 340, katG 343, inhA 14, inhA 84, inhA 86, inhA 114, and ahpC 75), and for RIF resistance included 6 codons (rpoB 445, rpoB 450, rpoB 464, rpoB 490, rpoB 507, and rpoB 508) with a sensitivity of 94.1% and 82.4%, respectively. Conclusion: The genetic mutation sites for drug resistance in M/XDR-TB are quite variable. The distribution of these mutations in a certain population must be studied before developing the specific mutation test panels for each area. The results of this study can be applied for further molecular M/XDR-TB diagnosis in the upper northern region of Thailand. Keywords: tuberculosis, drug resistance, MDR-TB, XDR-TB, genotype, mutatio