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The amino acid transporter SLC6A14 in cancer and its potential use in chemotherapy

Asian Journal of Pharmaceutical Sciences 2014年第6期9卷 293-303页

作者： Yangzom D.Bhutia ellappan babu Puttur D.Prasad Vadivel Ganapathy Department of Biochemistry and Molecular Biology Medical College of GeorgiaGeorgia Regents UniversityAugustaGA 30912USA

Tumor cells have an increased demand for glucose and amino acids to support their rapid growth,and also exhibit alterations in biochemical pathways that metabolize these nutrients.Transport across the plasma membrane is essential to feed glucose and amino acids into these tumor cell-selective metabolic pathways.Transfer of amino acids across biological membranes occurs via a multitude of transporters;tumor cells must upregulate one or more of these transporters to satisfy their increased demand for amino acids.Among the amino acid transporters,SLC6A14 stands out with specific functional features uniquely suited for the biological needs of the tumor cells.This transporter is indeed upregulated in tumors of epithelial origin,including colon cancer,cervical cancer,breast cancer,and pancreatic cancer.Since normal cells express this transporter only at low levels,blockade of this transporter should lead to amino acid starvation selectively in tumor cells,thus having little effect on normal cells.This offers a novel,yet logical,strategy for the treatment of cancers that are associated with upregulation of SLC6A14.In addition,a variety of amino acid-based prodrugs are recognized as substrates by SLC6A14,thus raising the possibility that anticancer drugs can be delivered into tumor cells selectively via this transporter in the form of amino acid prodrugs.This strategy allows exposure of SLC6A14-positive tumor cells to chemotherapy with minimal off-target effects.In conclusion,the amino acid transporter SLC6A14 holds great potential not only as a direct drug target for cancer therapy but also for tumor cell-selective delivery of anticancer drugs.

关键词： Essential amino acids Glutamine addiction Amino acid transporters SLC6A14 Prodrugs Cancer therapy

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Chronic exposure to excess iron promotes EMT and cancer via p53 loss in pancreatic cancer

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Asian Journal of Pharmaceutical Sciences 2020年第2期15卷 237-251页

作者： Yangzom D.Bhutia Jiro Ogura Paul J.Grippo Carolina Torres Toshihiro Sato Mitchell Wachtel Sabarish Ramachandran ellappan babu Sathish Sivaprakasam Devaraja Rajasekaran Bradley Schniers Nhu On Logan Smoot Muthusamy Thangaraju Jaya P.Gnana-Prakasam Vadivel Ganapathy Department of Cell Biology and Biochemistry Texas Tech University Health Sciences CenterLubbockTX 79430USA Department of Pharmaceutical Sciences Tohoku University Hospital1-1 Seiryo-machiAoba-kuSendaiMiyagi 980-8574Japan Department of Medicine University of Illinois at ChicagoChicagoIL 60607USA Department of Surgical Pathology Texas Tech University Health Sciences CenterLubbockTX 79430USA Department of Biological Sciences Texas Tech UniversityLubbockTX 79410USA Department of Chemistry and Biochemistry Texas Tech UniversityLubbockTX 79410USA Department of Biochemistry and Molecular Biology Augusta UniversityAugustaGA 30912USA Department of Ophthalmology St.Louis UniversitySt.LouisMO 63104USA

Based on the evidence that hemochromatosis, an iron-overload disease, drives hepatocellular carcinoma, we hypothesized that chronic exposure to excess iron, either due to genetic or environmental causes, predisposes an individual to cancer. Using pancreatic cancer as our primary focus, we employed cell culture studies to interrogate the connection between excess iron and cancer, and combined in vitro and in vivo studies to explore the connection further. Ferric ammonium citrate was used as an exogenous iron source. Chronic exposure to excess iron induced epithelial-mesenchymal transition(EMT) in normal and cancer cell lines, loss of p53, and suppression of p53 transcriptional activity evidenced from decreased expression of p53 target genes(p21, cyclin D1, Bax, SLC7A11). To further extrapolate our cell culture data, we generated EL-KrasG12D( EL-Kras) mouse(pancreatic neoplastic mouse model) expressing Hfe+/+ and Hfe-/- genetic background. p53 target gene expression decreased in EL-Kras/Hfe-/- mouse pancreas compared to EL-Kras/Hfe+/+ mouse pancreas. Interestingly, the incidence of acinar-to-ductal metaplasia and cystic pancreatic neoplasms(CPN) decreased in EL-Kras/Hfe-/- mice, but the CPNs that did develop were larger in these mice than in EL-Kras/Hfe+/+ mice. In conclusion, these in vitro and in vivo studies support a potential role for chronic exposure to excess iron as a promoter of more aggressive disease via p53 loss and SLC7A11 upregulation within pancreatic epithelial cells.

关键词： SLC7A11 p53 Iron Heme Epithelial-mesenchymal transition

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Suicide Ideation Detection of Covid Patients Using Machine Learning Algorithm

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Computer Systems Science & Engineering 2023年第4期45卷 247-261页

作者： R.Punithavathi S.Thenmozhi R.Jothilakshmi V.ellappan Islam Md Tahzib Ul M Kumarasamy College of Engineering KarucrTamil NaduIndia Dayananda Sagar College of Engineering BangaloreKarnatakaIndia R.M.D Engineering College KavaraipettaiTamil NaduIndia Adama Science and Technology University AdamaEthiopia Dhaka International University DhakaBangaladesh

During Covid pandemic,many individuals are suffering from suicidal ideation in the world.Social distancing and quarantining,affects the patient emotionally.Affective computing is the study of recognizing human feelings and emotions.This technology can be used effectively during pandemic for facial expression recognition which automatically extracts the features from the human face.Monitoring system plays a very important role to detect the patient condition and to recognize the patterns of expression from the safest distance.In this paper,a new method is proposed for emotion recognition and suicide ideation detection in COVID patients.This helps to alert the nurse,when patient emotion is fear,cry or sad.The research presented in this paper has introduced Image Processing technology for emotional analysis of patients using Machine learning algorithm.The proposed Convolution Neural Networks(CNN)architecture with DnCNN preprocessing enhances the performance of recognition.The system can analyze the mood of patients either in real time or in the form of video files from CCTV cameras.The proposed method accuracy is more when compared to other methods.It detects the chances of suicide attempt based on stress level and emotional recognition.

关键词： HOG ACO-CS optimizedKNN PCA emotion detection covid face recognition

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