9 results on '"Wan, Wei Keat"'
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2. Additional file 10 of Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma
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Jeon, Ah-Jung, Teo, Yue-Yang, Sekar, Karthik, Chong, Shay Lee, Wu, Lingyan, Chew, Sin-Chi, Chen, Jianbin, Kendarsari, Raden Indah, Lai, Hannah, Ling, Wen Huan, Kaya, Neslihan Arife, Lim, Jia Qi, Ramasamy, Adaikalavan, Oguz, Gokce, Chung, Alexander Yaw-Fui, Chan, Chung Yip, Cheow, Peng-Chung, Kam, Juinn Huar, Madhavan, Krishnakumar, Kow, Alfred, Ganpathi, Iyer Shridhar, Lim, Tony Kiat Hon, Leow, Wei-Qiang, Loong, Shihleone, Loh, Tracy Jiezhen, Wan, Wei Keat, Soon, Gwyneth Shook Ting, Pang, Yin Huei, Yoong, Boon Koon, Ong, Diana Bee-Lan, Lim, Jasmine, de Villa, Vanessa H., Cruz, Rouchelle D.dela, Chanwat, Rawisak, Thammasiri, Jidapa, Bonney, Glenn K., Goh, Brian K. P., Tucker-Kellogg, Greg, Foo, Roger Sik Yin, and Chow, Pierce K. H.
- Abstract
Additional file 10: Fig. S2. A. GSEA results for up-regulated genes in tumour tissues from all-patients (AP) analysis. B: GSEA results for down-regulated genes in tumour tissues from AP analysis. Across both panels, top chart shows results including all the up-regulated genes from the AP analysis, while the bottom chart excludes the genes also detected in PP analyses.
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- 2023
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3. Additional file 8 of Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma
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Jeon, Ah-Jung, Teo, Yue-Yang, Sekar, Karthik, Chong, Shay Lee, Wu, Lingyan, Chew, Sin-Chi, Chen, Jianbin, Kendarsari, Raden Indah, Lai, Hannah, Ling, Wen Huan, Kaya, Neslihan Arife, Lim, Jia Qi, Ramasamy, Adaikalavan, Oguz, Gokce, Chung, Alexander Yaw-Fui, Chan, Chung Yip, Cheow, Peng-Chung, Kam, Juinn Huar, Madhavan, Krishnakumar, Kow, Alfred, Ganpathi, Iyer Shridhar, Lim, Tony Kiat Hon, Leow, Wei-Qiang, Loong, Shihleone, Loh, Tracy Jiezhen, Wan, Wei Keat, Soon, Gwyneth Shook Ting, Pang, Yin Huei, Yoong, Boon Koon, Ong, Diana Bee-Lan, Lim, Jasmine, de Villa, Vanessa H., Cruz, Rouchelle D.dela, Chanwat, Rawisak, Thammasiri, Jidapa, Bonney, Glenn K., Goh, Brian K. P., Tucker-Kellogg, Greg, Foo, Roger Sik Yin, and Chow, Pierce K. H.
- Abstract
Additional file 8: Supplementary Table S10. Top 20 REACTOME gene sets from GSEA of down-regulated and up-regulated genes in PG1.
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- 2023
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4. Additional file 12 of Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma
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Jeon, Ah-Jung, Teo, Yue-Yang, Sekar, Karthik, Chong, Shay Lee, Wu, Lingyan, Chew, Sin-Chi, Chen, Jianbin, Kendarsari, Raden Indah, Lai, Hannah, Ling, Wen Huan, Kaya, Neslihan Arife, Lim, Jia Qi, Ramasamy, Adaikalavan, Oguz, Gokce, Chung, Alexander Yaw-Fui, Chan, Chung Yip, Cheow, Peng-Chung, Kam, Juinn Huar, Madhavan, Krishnakumar, Kow, Alfred, Ganpathi, Iyer Shridhar, Lim, Tony Kiat Hon, Leow, Wei-Qiang, Loong, Shihleone, Loh, Tracy Jiezhen, Wan, Wei Keat, Soon, Gwyneth Shook Ting, Pang, Yin Huei, Yoong, Boon Koon, Ong, Diana Bee-Lan, Lim, Jasmine, de Villa, Vanessa H., Cruz, Rouchelle D.dela, Chanwat, Rawisak, Thammasiri, Jidapa, Bonney, Glenn K., Goh, Brian K. P., Tucker-Kellogg, Greg, Foo, Roger Sik Yin, and Chow, Pierce K. H.
- Abstract
Additional file 12: Fig. S4. A. Schematic illustration of machine-learning based patient stratification strategy for TCGA- LIHC paired sample data. B: Patient stratification classification accuracies of PG0, PG1, PG2 and combined (Total).
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- 2023
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5. Additional file 3 of Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma
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Jeon, Ah-Jung, Teo, Yue-Yang, Sekar, Karthik, Chong, Shay Lee, Wu, Lingyan, Chew, Sin-Chi, Chen, Jianbin, Kendarsari, Raden Indah, Lai, Hannah, Ling, Wen Huan, Kaya, Neslihan Arife, Lim, Jia Qi, Ramasamy, Adaikalavan, Oguz, Gokce, Chung, Alexander Yaw-Fui, Chan, Chung Yip, Cheow, Peng-Chung, Kam, Juinn Huar, Madhavan, Krishnakumar, Kow, Alfred, Ganpathi, Iyer Shridhar, Lim, Tony Kiat Hon, Leow, Wei-Qiang, Loong, Shihleone, Loh, Tracy Jiezhen, Wan, Wei Keat, Soon, Gwyneth Shook Ting, Pang, Yin Huei, Yoong, Boon Koon, Ong, Diana Bee-Lan, Lim, Jasmine, de Villa, Vanessa H., Cruz, Rouchelle D.dela, Chanwat, Rawisak, Thammasiri, Jidapa, Bonney, Glenn K., Goh, Brian K. P., Tucker-Kellogg, Greg, Foo, Roger Sik Yin, and Chow, Pierce K. H.
- Abstract
Additional file 3: Supplementary Table S4. Top 20 gene sets from GSEA of up-regulated and down-regulated genes in all-patients analysis.
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- 2023
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6. Sedentary Behavior and Colorectal Adenoma – Is it a Risk Factor Independent of Physical Activity?
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Wan Wei Keat, Lim Kiat Hon, Wong Wai Yin, Rafay Azhar, Vikneswaran Namasivayam, Assam Nkouibert Pryseley, and John Connolly
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Cisplatin ,Hepatology ,biology ,business.industry ,medicine.medical_treatment ,Gastroenterology ,Colorectal adenoma ,Pharmacology ,Esophageal cancer ,medicine.disease ,biology.organism_classification ,In vivo ,medicine ,MTT assay ,Cytotoxicity ,business ,Adjuvant ,Andrographis paniculata ,medicine.drug - Abstract
Esophageal cancer (EC) is the sixthmost common cause of cancer-related deaths worldwide. Surgery is the main treatment option for EC, however, postoperative recurrence rate is high due to cancer metastasis. Even though surgery followed by adjuvant chemotherapy and concurrent radiation have shown favorable efficacies, searching for alternative adjuvant treatments—such as Chinese herbal medicines—for metastatic EC also get patients’ desire. Based on our previous screening among various Chinese herbs, Andrographis paniculata (AP) exhibited anti-tumor effect in human esophageal cancer cells. The present study therefore aimed to evaluate the anti-tumor and anti-metastasis activities of AP and the combined effects of such herbal extract with standard chemotherapeutics for EC, cisplatin and 5-fluorouracil (5-FU). Human squamous esophageal cancer (EC-109) xenograft-bearing mice model was employed to evaluate the in vivo antitumor activities. The absorption of AP water extract was determined in human intestinal Caco-2 cell monolayers. The absorbed AP components have been evaluated for their cytotoxicity using MTT assay. Our preliminary results of in vivo study showed that the number of tumor nodules was decreased in intraperitoneal xenograft-bearing mice treated with AP water extract (1600 mg/kg daily for 20 days). Besides, AP treatment also enhanced the inhibitory effects of cisplatin plus 5-FU on the number of tumor nodules. In view of our in vitro results, the absorbed AP components (APPC) showed significant cytotoxicity on EC-109. Furthermore, seven known chemical constituents were identified in the APPC for the first time, suggesting these absorbed AP components may be responsible for the activities. In conclusion, the AP water extract is effective on inhibiting tumor growth in vivo and the chemical constituents in the absorbed AP components were identified, which may further enhance the understanding of the therapeutic mechanisms of this herb. The anti-metastasis effects of AP will also be further investigated. ACKNOWLEDGEMENT: This work was supported by Food and Health Bureau HKSAR, Health and Medical Research Fund no. 11120981.
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- 2015
7. Liver Transplantation in an Adult with Citrullinaemia Type 2
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Tan, Hui-Hui, Chow, Wan-Cheng, Lim, Kiat-Hon, Wan, Wei-Keat, Chung, Alexander Y. F., Cheow, Peng-Chung, and Tan, Chee-Kiat
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Article Subject - Abstract
Citrullinaemia is a urea cycle defect that results from a deficiency of the enzyme arginosuccinate synthetase. Type 1 disease is diagnosed in childhood, whereas Type 2 disease is adult onset. We report the outcome of a patient with citrullinemia Type 2 who received a liver transplant at our center and the implications of this diagnosis in liver transplantation.
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- 2011
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8. Genomic and proteomic characterization of ARID1A chromatin remodeller in ampullary tumors
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Nastase, Anca, Teo, Jin Yao, Heng, Hong Lee, Ng, Cedric Chuan Young, Myint, Swe Swe, Rajasegaran, Vikneswari, Loh, Jia Liang, Lee, Ser Yee, Ooi, London Lucien, Chung, Alexander Yaw Fui, Chow, Pierce Kah Hoe, Cheow, Peng Chung, Wan, Wei Keat, Azhar, Rafy, Khoo, Avery, Xiu, Sam Xin, Alkaff, Syed Muhammad Fahmy, Cutcutache, Ioana, Lim, Jing Quan, Ong, Choon Kiat, Herlea, Vlad, Dima Simona, Duda, Dan G., Teh, Bin Tean, Popescu, Irinel, and Lim, Tony Kiat Hon
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Original Article - Abstract
AT rich interactive domain 1A (ARID1A) is one of the most commonly mutated genes in a broad variety of tumors. The mechanisms that involve ARID1A in ampullary cancer progression remains elusive. Here, we evaluated the frequency of ARID1A and KRAS mutations in ampullary adenomas and adenocarcinomas and in duodenal adenocarcinomas from two cohorts of patients from Singapore and Romania, correlated with clinical and pathological tumor features, and assessed the functional role of ARID1A. In the ampullary adenocarcinomas, the frequency of KRAS and ARID1A mutations was 34.7% and 8.2% respectively, with a loss or reduction of ARID1A protein in 17.2% of the cases. ARID1A mutational status was significantly correlated with ARID1A protein expression level (P=0.023). There was a significant difference in frequency of ARID1A mutation between Romania and Singapore (2.7% versus 25%, P=0.04), suggestive of different etiologies. One somatic mutation was detected in the ampullary adenoma group. In vitro studies indicated the tumor suppressive role of ARID1A. Our results warrant further investigation of this chromatin remodeller as a potential early biomarker of the disease, as well as identification of therapeutic targets in ARID1A mutated ampullary cancers.
9. qFIBS: A Novel Automated Technique for Quantitative Evaluation of Fibrosis, Inflammation, Ballooning, and Steatosis in Patients With Nonalcoholic Steatohepatitis
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George Boon-Bee Goh, Pik-Eu Jason Chang, Dina Tiniakos, Qin Wang, Lai Wei, Chee-Kiat Tan, Wei-Keat Wan, Huiying Rao, Elisabetta Bugianesi, Kiat Hon Lim, Salvatore Petta, Quentin M. Anstee, Wei Qiang Leow, Jingmin Zhao, Aileen Wee, Xiaoxiao Wang, Manuel Romero-Gómez, Feng Liu, Stephen A. Harrison, Liu, Feng, Goh, George Boon‐Bee, Tiniakos, Dina, Wee, Aileen, Leow, Wei‐Qiang, Zhao, Jing‐Min, Rao, Hui‐Ying, Wang, Xiao‐Xiao, Wang, Qin, Wan, Wei‐Keat, Lim, Kiat‐Hon, Romero‐Gomez, Manuel, Petta, Salvatore, Bugianesi, Elisabetta, Tan, Chee‐Kiat, Harrison, Stephen A., Anstee, Quentin M., Jason Chang, Pik‐Eu, and Wei, Lai
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Liver Cirrhosis ,Male ,0301 basic medicine ,Biopsy ,Chronic liver disease ,Severity of Illness Index ,Gastroenterology ,Hepatitis ,0302 clinical medicine ,Non-alcoholic Fatty Liver Disease ,Fibrosis ,Nonalcoholic fatty liver disease ,qFibrosis ,NASH ,automated ,qFIBS ,quantitative evaluation ,NASH, FIBROSIS ,medicine.diagnostic_test ,Middle Aged ,Reference Standards ,3. Good health ,Liver ,Dimensional Measurement Accuracy ,Liver biopsy ,Female ,030211 gastroenterology & hepatology ,Algorithms ,medicine.medical_specialty ,digestive system ,White People ,03 medical and health sciences ,Asian People ,Internal medicine ,Image Interpretation, Computer-Assisted ,Severity of illness ,medicine ,Humans ,Hepatology ,Receiver operating characteristic ,business.industry ,Reproducibility of Results ,medicine.disease ,digestive system diseases ,Confidence interval ,Fatty Liver ,030104 developmental biology ,Steatosis ,business - Abstract
[Background and Aims] Nonalcoholic steatohepatitis (NASH) is a common cause of chronic liver disease. Clinical trials use the NASH Clinical Research Network (CRN) system for semiquantitative histological assessment of disease severity. Interobserver variability may hamper histological assessment, and diagnostic consensus is not always achieved. We evaluate a second harmonic generation/two‐photon excitation fluorescence (SHG/TPEF) imaging‐based tool to provide an automated quantitative assessment of histological features pertinent to NASH., [Approach and Results] Images were acquired by SHG/TPEF from 219 nonalcoholic fatty liver disease (NAFLD)/NASH liver biopsy samples from seven centers in Asia and Europe. These were used to develop and validate qFIBS, a computational algorithm that quantifies key histological features of NASH. qFIBS was developed based on in silico analysis of selected signature parameters for four cardinal histopathological features, that is, fibrosis (qFibrosis), inflammation (qInflammation), hepatocyte ballooning (qBallooning), and steatosis (qSteatosis), treating each as a continuous rather than categorical variable. Automated qFIBS analysis outputs showed strong correlation with each respective component of the NASH CRN scoring (P < 0.001; qFibrosis [r = 0.776], qInflammation [r = 0.557], qBallooning [r = 0.533], and qSteatosis [r = 0.802]) and high area under the receiver operating characteristic curve values (qFibrosis [0.870‐0.951; 95% confidence interval {CI}, 0.787‐1.000; P < 0.001], qInflammation [0.820‐0.838; 95% CI, 0.726‐0.933; P < 0.001), qBallooning [0.813‐0.844; 95% CI, 0.708‐0.957; P < 0.001], and qSteatosis [0.939‐0.986; 95% CI, 0.867‐1.000; P < 0.001]) and was able to distinguish differing grades/stages of histological disease. Performance of qFIBS was best when assessing degree of steatosis and fibrosis, but performed less well when distinguishing severe inflammation and higher ballooning grades., [Conclusions] qFIBS is an automated tool that accurately quantifies the critical components of NASH histological assessment. It offers a tool that could potentially aid reproducibility and standardization of liver biopsy assessments required for NASH therapeutic clinical trials.
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- 2019
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