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Your search keyword '"Wu, Ji-Tao"' showing total 15 results
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15 results on '"Wu, Ji-Tao"'

1. Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study

Author

Gui, Cheng-Peng, Chen, Yu-Hang, Zhao, Hong-Wei, Cao, Jia-Zheng, Liu, Tian-Jie, Xiong, Sheng-Wei, Yu, Yan-Fei, Liao, Bing, Cao, Yun, Li, Jia-Ying, Huang, Kang-Bo, Han, Hui, Zhang, Zhi-Ling, Chen, Wen-Fang, Jiang, Ze-Ying, Gao, Ye, Han, Guan-Peng, Tang, Qi, Ouyang, Kui, Qu, Gui-Mei, Wu, Ji-Tao, Guo, Jian-Ping, Li, Cai-Xia, Li, Pei-Xing, Liu, Zhi-Ping, Hsieh, Jer-Tsong, Cai, Mu-Yan, Li, Xue-Song, Wei, Jin-Huan, and Luo, Jun-Hang

Published
2023
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4. Predictive value of single-nucleotide polymorphism signature for recurrence in localised renal cell carcinoma: a retrospective analysis and multicentre validation study

Author

Wei, Jin-Huan, Feng, Zi-Hao, Cao, Yun, Zhao, Hong-Wei, Chen, Zhen-Hua, Liao, Bing, Wang, Qing, Han, Hui, Zhang, Jin, Xu, Yun-Ze, Li, Bo, Wu, Ji-Tao, Qu, Gui-Mei, Wang, Guo-Ping, Liu, Cong, Xue, Wei, Liu, Qiang, Lu, Jun, Li, Cai-Xia, Li, Pei-Xing, Zhang, Zhi-Ling, Yao, Hao-Hua, Pan, Yi-Hui, Chen, Wen-Fang, Xie, Dan, Shi, Lei, Gao, Zhen-Li, Huang, Yi-Ran, Zhou, Fang-Jian, Wang, Shao-Gang, Liu, Zhi-Ping, Chen, Wei, and Luo, Jun-Hang

Published
2019
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14. The complete mitochondrial genome sequence of the prostate adenocarcinoma rat R3327.

Author

Zhang, Peng, Wang, Jian-ming, Shi, Lei, Liu, Qing-zuo, Lin, Chun-hua, Wu, Ji-tao, Men, Chang-ping, Zhao, Jun-jie, Gao, Zhen-li, and Shi, Ben-kang

Subjects
MITOCHONDRIAL DNA, ADENOCARCINOMA, PROSTATE cancer, LABORATORY rats, NUCLEOTIDE sequencing, GENETICS
Abstract

The prostate adenocarcinoma of the Copenhagen rat (R3327) is recognized as a suitable model for human prostate carcinoma. In this study, we sequenced its complete mitogenome and total length of the genome was 16,310 bp (GenBank Accession Number KM820831). It contains 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes. This mitochondrial genome sequence will provide new genetic resource into prostate adenocarcinoma disease. [ABSTRACT FROM PUBLISHER]

Published
2016
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15. A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Author

Huang KB, Gui CP, Xu YZ, Li XS, Zhao HW, Cao JZ, Chen YH, Pan YH, Liao B, Cao Y, Zhang XK, Han H, Zhou FJ, Liu RY, Chen WF, Jiang ZY, Feng ZH, Jiang FN, Yu YF, Xiong SW, Han GP, Tang Q, Ouyang K, Qu GM, Wu JT, Cao M, Dong BJ, Huang YR, Zhang J, Li CX, Li PX, Chen W, Zhong WD, Guo JP, Liu ZP, Hsieh JT, Xie D, Cai MY, Xue W, Wei JH, and Luo JH

Subjects
Humans, Male, Female, Middle Aged, Aged, Prognosis, Genomics methods, Adult, Neoplasm Staging, Deep Learning, Disease-Free Survival, Carcinoma, Renal Cell genetics, Carcinoma, Renal Cell pathology, Kidney Neoplasms genetics, Kidney Neoplasms pathology, Kidney Neoplasms surgery, Neoplasm Recurrence, Local genetics
Abstract

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy., (© 2024. The Author(s).)

Published
2024
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