- Proto-oncogene Pokemon in thyroid cancer: a potential promoter of tumorigenesis in papillary thyroid carcinoma
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Kyungseek Chang, Sung-Im Do, Kyungeun Kim, Seoung Wan Chae, In-gu Do, Hyun Joo Lee, Dong Hoon Kim, Jin Hee Sohn
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J Pathol Transl Med. 2021;55(5):317-323. Published online August 9, 2021
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DOI: https://doi.org/10.4132/jptm.2021.06.28
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 Abstract
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- Background
Pokemon is an oncogenic transcription regulator that plays a critical role in cellular differentiation. Although it has been found to be overexpressed in several types of cancer involving different organs, its role in thyroid gland has yet to be reported. The objective of this study was to evaluate the expression of Pokemon in papillary thyroid carcinoma (PTC) based on clinicopathological parameters.
Methods
Tissue microarray samples derived from patients with PTC or benign thyroid disease were used to evaluate Pokemon expression based on immunohistochemical analysis. Correlations of its expression with various clinicopathological parameters were then analyzed.
Results
Pokemon expression was observed in 22.0% of thyroid follicular cells from the normal group, 44.0% from the group with benign thyroid diseases, and 92.1% from the group with PTC (p < .001). The intensity of Pokemon expression was markedly higher in the PTC group. Pokemon expression level and PTC tumor size showed an inverse correlation. T1a tumors showed strong expression levels of Pokemon. However, larger tumors showed weak expression (p = .006).
Conclusions
Pokemon expression is associated with tumorigenesis of PTC, with expression showing an inverse correlation with PTC tumor size. This might be related to the negative regulation of aerobic glycolysis by Pokemon.
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Citations
Citations to this article as recorded by  - Systems biology approach delineates critical pathways associated with papillary thyroid cancer: a multi-omics data analysis
Febby Payva, Santhy K. S., Remya James, Amrisa Pavithra E, Venketesh Sivaramakrishnan
Thyroid Research.2025;[Epub] CrossRef - ZBTB7A as a therapeutic target for cancer
Ying Zhou, Xisha Chen, Xuyu Zu
Biochemical and Biophysical Research Communications.2024; 736: 150888. CrossRef - Knockdown of FBI-1 Inhibits the Warburg Effect and Enhances the Sensitivity of Hepatocellular Carcinoma Cells to Molecular Targeted Agents via miR-3692/HIF-1α
Juan Liu, Chao Yang, Xiao-Mei Huang, Pan-Pan Lv, Ya-Kun Yang, Jin-Na Zhao, Si-Yuan Zhao, Wan-Jun Sun
Frontiers in Oncology.2021;[Epub] CrossRef
- Prognostic Role of Metastatic Lymph Node Ratio in Papillary Thyroid Carcinoma
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Jung-Soo Pyo, Jin Hee Sohn, Kyungseek Chang
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J Pathol Transl Med. 2018;52(5):331-338. Published online August 30, 2018
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DOI: https://doi.org/10.4132/jptm.2018.08.07
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7,533
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128
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15
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13
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Abstract
PDF
- Background
The aim of this study is to elucidate the clinicopathological significances, including the prognostic role, of metastatic lymph node ratio (mLNR) and tumor deposit diameter in papillary thyroid carcinoma (PTC) through a retrospective review and meta-analysis.
Methods
We categorized the cases into high (≥ 0.44) and low mLNR (< 0.44) and investigated the correlations with clinicopathological parameters in 64 PTCs with neck level VI lymph node (LN) metastasis. In addition, meta-analysis of seven eligible studies was used to investigate the correlation between mLNR and survival.
Results
Among 64 PTCs with neck level VI LN metastasis, high mLNR was found in 34 PTCs (53.1%). High mLNR was significantly correlated with macrometastasis (tumor deposit diameter ≥ 0.2 cm), extracapsular spread, and number of metastatic LNs. Based on linear regression test, mLNR was significantly increased by the largest LN size but not the largest metastatic LN (mLN) size. High mLNR was not correlated with nuclear factor κB or cyclin D1 immunohistochemical expression, Ki-67 labeling index, or other pathological parameters of primary tumor. Based on meta-analysis, high mLNR significantly correlated with worse disease-free survival at the 5-year and 10-year follow-up (hazard ratio [HR], 4.866; 95% confidence interval [CI], 3.527 to 6.714 and HR, 5.769; 95% CI, 2.951 to 11.275, respectively).
Conclusions
Our data showed that high mLNR significantly correlated with worse survival, macrometastasis, and extracapsular spread of mLNs. Further cumulative studies for more detailed criteria of mLNR are needed before application in daily practice.
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Citations
Citations to this article as recorded by - The application of a clinical-multimodal ultrasound radiomics model for predicting cervical lymph node metastasis of thyroid papillary carcinoma
Chang Liu, Shangjie Yang, Tian Xue, Qian Zhang, Yanjing Zhang, Yufang Zhao, Guolin Yin, Xiaohui Yan, Ping Liang, Liping Liu
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Lei Gao, Xiuli Wen, Guanghui Yue, Hui Wang, Ziqing Lu, Beibei Wu, Zhihong Liu, Yuming Wu, Dongmei Lin, Shijian Yi, Wei Jiang, Yi Hao
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Ana Rita Ferreira, Diogo Ramalho, Daniela Martins, Andreia Amado, Susana Graça, Carlos Soares, Bela Pereira, Maria João Oliveira, Manuel Oliveira, Antónia Póvoa
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Zhe Xu Cao, Jiang Sheng Huang, Ming Ming Wang
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Helene Lindfors, Marie Karlsen, Ellinor Karlton, Jan Zedenius, Catharina Larsson, Catharina Ihre Lundgren, C. Christofer Juhlin, Ivan Shabo
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Renan Aguera Pinheiro, Ana Kober Leite, Beatriz Godoi Cavalheiro, Evandro Sobroza de Mello, Luiz Paulo Kowalski, Leandro Luongo Matos
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WenYi Wang, JiaJing Liu, XiaoFan Xu, LiQun Huo, XuLin Wang, Jun Gu
Technology in Cancer Research & Treatment.2023;[Epub] CrossRef - Lymph Node Ratio Predicts Recurrence in Patients with Papillary Thyroid Carcinoma with Low Lymph Node Yield
Il Ku Kang, Joonseon Park, Ja Seong Bae, Jeong Soo Kim, Kwangsoon Kim
Cancers.2023; 15(11): 2947. CrossRef - Superiority of metastatic lymph node ratio over number of node metastases and TNM/AJCC N classification in predicting cancer‐specific survival in medullary thyroid cancer
Andreas Machens, Kerstin Lorenz, Frank Weber, Henning Dralle
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Yanfang Wang, Fang Nie, Guojuan Wang, Ting Liu, Tiantian Dong, Yamin Sun
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Ji Eun Choi, Ja Seong Bae, Dong-Jun Lim, So Lyung Jung, Chan Kwon Jung
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Zeming Liu, Sichao Chen, Yihui Huang, Di Hu, Min Wang, Wei Wei, Chao Zhang, Wen Zeng, Liang Guo
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