Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library

Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library

High‐grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5‐year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced‐stage HGSOC unsuitable for primary debulking surgery (...

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Bibliographic Details
Main Authors: Liujia Qian, Jianqing Zhu, Zhangzhi Xue, Tingting Gong, Nan Xiang, Liang Yue, Xue Cai, Wangang Gong, Junjian Wang, Rui Sun, Wenhao Jiang, Weigang Ge, He Wang, Zhiguo Zheng, Qijun Wu, Yi Zhu, Tiannan Guo
Format: Article
Language:English
Published: Wiley 2023-08-01
Series:Molecular Oncology
Subjects:
chemotherapy resistance
data‐independent acquisition
machine learning
MS spectral library
ovarian cancer
targeted proteomics
Online Access:https://doi.org/10.1002/1878-0261.13410

Internet

https://doi.org/10.1002/1878-0261.13410

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