Cheng-Kun Tsai

Dr. Cheng-Kun Tsai


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 March 2020 in Journal of Clinical Medicine
Verified
Journal Article
Open access
PDF file
CTCheng-Kun Tsai
Cheng-Kun Tsai
CLChien Yu Lin
Chien Yu Lin
CKChung-Jan Kang
Chung-Jan Kang
CLChun-Ta Liao
Chun-Ta Liao
WWWan-Ling Wang
Wan-Ling Wang
Gigin LinGigin Lin
Gigin Lin
Extranodal extension (ENE) is an independent adverse prognostic factor in oral squamous cell carcinoma (OSCC), and is difficult to identify preoperatively. We aimed to discover biomarkers for high risk patients with ENE. Tandem tissue, plasma, and urine samples of 110 patients with OSCC were investigated through 600-MHz nuclear magnetic resonance (NMR) metabolomics analysis. We found that the levels of creatine, creatine phosphate, glycine, and tyramine in plasma significantly decreased in stage IV ENE positive OSCC compared with stage IV ENE negative OSCC. To understand the underlying mechanism behind the alteration of plasma metabolites, our tissue analysis revealed that the carnitine level significantly increased in tumors but significantly decreased in the adjacent normal tissue in advanced stage OSCC, in addition to decreased levels of alanine and pyruvate in tumor tissues. The global metabolomics analysis on tumor tissues also showed that stage IV tumors with an ENE positive status demonstrated higher levels of aspartate, butyrate, carnitine, glutamate, glutathione, glycine, glycolate, guanosine, and sucrose but lower levels of alanine, choline, glucose, isoleucine, lactate, leucine, myo-inositol, O-acetylcholine, oxypurinol, phenylalanine, pyruvate, succinate, tyrosine, valine, and xanthine than tumors with an ENE negative status. We concluded that metabolomics alterations in tumor tissues correspond to an increase in the tumor stage and are detectable in plasma samples. Metabolomic alterations of OSCC can serve as potential diagnostic markers and predictors of ENE in patients with stage IV OSCC.

9 May 2019 in Cancers
Verified
Journal Article
Open access
PDF file
YLYing-Chieh Lai
Ying-Chieh Lai
TYTa-Sen Yeh
Ta-Sen Yeh
RWRen-Chin Wu
Ren-Chin Wu
CTCheng-Kun Tsai
Cheng-Kun Tsai
LYLan-Yan Yang
Lan-Yan Yang
MKMichael D. Kuo
Michael D. Kuo
Chromosomal instability (CIN) of gastric cancer is correlated with distinct outcomes. This study aimed to investigate the role of computed tomography (CT) imaging traits in predicting the CIN status of gastric cancer. We screened 443 patients in the Cancer Genome Atlas gastric cancer cohort to filter 40 patients with complete CT imaging and genomic data as the training cohort. CT imaging traits were subjected to logistic regression to select independent predictors for the CIN status. For the validation cohort, we prospectively enrolled 18 gastric cancer patients for CT and tumor genomic analysis. The imaging predictors were tested in the validation cohort using receiver operating characteristic curve (ROC) analysis. Thirty patients (75%) in the training cohort and 9 patients (50%) in the validation cohort had CIN subtype gastric cancers. Smaller tumor diameter (p = 0.017) and acute tumor transition angle (p = 0.045) independently predict CIN status in the training cohort. In the validation cohort, acute tumor transition angle demonstrated the highest accuracy, sensitivity, and specificity of 88.9%, 88.9%, and 88.9%, respectively, and areas under ROC curve of 0.89. In conclusion, this pilot study showed acute tumor transition angle on CT images may predict the CIN status of gastric cancer.

28 April 2021 in Molecules
Verified
Journal Article
Open access
PDF file
Yi-Hsiu ChungYi-Hsiu Chung
Yi-Hsiu Chung
CTCheng-Kun Tsai
Cheng-Kun Tsai
CYChing-Fang Yu
Ching-Fang Yu
WWWan-Ling Wang
Wan-Ling Wang
CYChung-lin Yang
Chung-lin Yang
Gigin LinGigin Lin
Gigin Lin
Purpose: By taking advantage of 18F-FDG PET imaging and tissue nuclear magnetic resonance (NMR) metabolomics, we examined the dynamic metabolic alterations induced by liver irradiation in a mouse model for hepatocellular carcinoma (HCC). Methods: After orthotopic implantation with the mouse liver cancer BNL cells in the right hepatic lobe, animals were divided into two experimental groups. The first received irradiation (RT) at 15 Gy, while the second (no-RT) did not. Intergroup comparisons over time were performed, in terms of 18F-FDG PET findings, NMR metabolomics results, and the expression of genes involved in inflammation and glucose metabolism. Results: As of day one post-irradiation, mice in the RT group showed an increased 18F-FDG uptake in the right liver parenchyma compared with the no-RT group. However, the difference reached statistical significance only on the third post-irradiation day. NMR metabolomics revealed that glucose concentrations peaked on day one post-irradiation both, in the right and left lobes—the latter reflecting a bystander effect. Increased pyruvate and glutamate levels were also evident in the right liver on the third post-irradiation day. The expression levels of the glucose-6-phosphatase (G6PC) and fructose-1, 6-bisphosphatase 1 (FBP1) genes were down-regulated on the first and third post-irradiation days, respectively. Therefore, liver irradiation was associated with a metabolic shift from an impaired gluconeogenesis to an enhanced glycolysis from the first to the third post-irradiation day. Conclusion: Radiation-induced metabolic alterations in the liver parenchyma occur as early as the first post-irradiation day and show dynamic changes over time.

9 January 2023 in Metabolites
Verified
Journal Article
Open access
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Yi-Hsiu ChungYi-Hsiu Chung
Yi-Hsiu Chung
Tsai-Hsien HungTsai-Hsien Hung
Tsai-Hsien Hung
CYChing-Fang Yu
Ching-Fang Yu
CTCheng-Kun Tsai
Cheng-Kun Tsai
CWChi-Chang Weng
Chi-Chang Weng
Gigin LinGigin Lin
Gigin Lin
We aim to establish a noninvasive diagnostic platform to capture early phenotypic transformation for metastasis using 18F-FDG PET and 1H-NMR-based serum metabolomics. Mice with implantation of NCI-H460 cells grew only primary lung tumors in the localized group and had both primary and metastatic lung tumors in the metastatic group. The serum metabolites were analyzed using 1H-NMR at the time of PET/CT scan. The glycolysis status and cell proliferation were validated by Western blotting and staining. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of SUVmean and serum metabolites in metastasis. In the metastatic mice, the SUVmean of metastatic tumors was significantly higher than that of primary lung tumors in PET images, which was supported by elevated glycolytic protein expression of HK2 and PKM2. The serum pyruvate level in the metastatic group was significantly lower than that in the localized group, corresponding to increased pyruvate-catalyzed enzyme and proliferation rates in metastatic tumors. In diagnosing localized or metastatic tumors, the areas under the ROC curves of SUVmean and pyruvate were 0.92 and 0.91, respectively, with p < 0.05. In conclusion, the combination of 18F-FDG PET and 1H-NMR-based serum metabolomics demonstrated the feasibility of a glycolytic platform for diagnosing metastatic lung cancers.

10 November 2017 in Molecules
Verified
Journal Article
Open access
PDF file
Yi-Hsiu ChungYi-Hsiu Chung
Yi-Hsiu Chung
CTCheng-Kun Tsai
Cheng-Kun Tsai
CWChiun-Chieh Wang
Chiun-Chieh Wang
HCHsi-Mu Chen
Hsi-Mu Chen
KLKuan-Ying Lu
Kuan-Ying Lu
Gigin LinGigin Lin
Gigin Lin
We aim to characterize the metabolic changes associated with early response to radiation therapy in a prostate cancer mouse model by 2-deoxy-2-[18F]fluoro-d-glucose ([18F]FDG) and [11C]acetate ([11C]ACT) positron emission tomography, with nuclear magnetic resonance (NMR) metabolomics corroboration. [18F]FDG and [11C]ACT PET were performed before and following irradiation (RT, 15Gy) for transgenic adenocarcinoma of mouse prostate xenografts. The underlying metabolomics alterations of tumor tissues were analyzed by using ex vivo NMR. The [18F]FDG total lesion glucose (TLG) of the tumor significant increased in the RT group at Days 1 and 3 post-irradiation, compared with the non-RT group (p < 0.05). The [11C]ACT maximum standard uptake value (SUVmax) in RT (0.83 ± 0.02) and non-RT groups (0.85 ± 0.07) were not significantly different (p > 0.05). The ex vivo NMR analysis showed a 1.70-fold increase in glucose and a 1.2-fold increase in acetate in the RT group at Day 3 post-irradiation (p < 0.05). Concordantly, the expressions of cytoplasmic acetyl-CoA synthetase in the irradiated tumors was overexpressed at Day 3 post-irradiation (p < 0.05). Therefore, TLG of [18F]FDG in vivo PET images can map early treatment response following irradiation and be a promising prognostic indicator in a longitudinal preclinical study. The underlying metabolic alterations was not reflected by the [11C]ACT PET.