دورية أكاديمية
Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library
| العنوان: | Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library |
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| المؤلفون: | 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 |
| المصدر: | Molecular Oncology, Vol 17, Iss 8, Pp 1567-1580 (2023) |
| بيانات النشر: | Wiley, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| مصطلحات موضوعية: | chemotherapy resistance, data‐independent acquisition, machine learning, MS spectral library, ovarian cancer, targeted proteomics, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| الوصف: | 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 (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high‐quality ovary‐specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan‐human spectral library (DPHL), this spectral library provides 10% more ovary‐specific and 3% more ovary‐enriched proteins. This library was then applied to analyze data‐independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six‐protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log‐rank test, P = 0.002). The classifier was validated with 57 patients from an independent clinical center (P = 0.014). Thus, we have developed an ovary‐specific spectral library for targeted proteome analysis, and propose a six‐protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT‐IDS treatment. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1878-0261 1574-7891 55247989 |
| Relation: | https://doaj.org/toc/1574-7891; https://doaj.org/toc/1878-0261 |
| DOI: | 10.1002/1878-0261.13410 |
| URL الوصول: | https://doaj.org/article/8619fcefd55247989b5c3a84bdf9c3e1 |
| رقم الأكسشن: | edsdoj.8619fcefd55247989b5c3a84bdf9c3e1 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 18780261 15747891 55247989 |
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| DOI: | 10.1002/1878-0261.13410 |