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用于鉴定和定量宫颈阴道液中子宫内膜癌蛋白质生物标志物的综合文库生成

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

作者信息

Njoku Kelechi, Chiasserini Davide, Geary Bethany, Pierce Andrew, Jones Eleanor R, Whetton Anthony D, Crosbie Emma J

机构信息

Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, 5th Floor Research, St Mary's Hospital, Oxford Road, Manchester M13 9WL, UK.

Department of Obstetrics and Gynaecology, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK.

出版信息

Cancers (Basel). 2021 Jul 28;13(15):3804. doi: 10.3390/cancers13153804.

Abstract

Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

摘要

子宫内膜癌是高收入国家最常见的妇科恶性肿瘤,其发病率正在上升。借助高灵敏度和特异性的生物标志物进行早期检测,有可能改善治疗结果,因为在最有可能治愈时即可提供治疗。全理论质谱图序列窗口采集(SWATH-MS)是一种用于分析生物样品的准确且可重复的平台,由于其可重复性、灵敏度以及数据重新分析的潜力,为生物标志物发现提供了一项技术进步。SWATH-MS需要一个光谱库来从多路复用质谱数据中识别和定量肽段。在此,我们展示了一个定制的光谱库,其中包含154,206个跃迁,可识别绝经后患有子宫内膜癌或有子宫内膜癌风险的女性宫颈阴道液中的19,394个肽段和2425种蛋白质。我们已将这些数据与基于对两种子宫内膜癌细胞系的质谱分析生成的6000多种蛋白质的文库相结合。这一独特资源有助于研究用于在宫颈阴道液中检测子宫内膜癌的蛋白质生物标志物。数据可通过ProteomeXchange获取,唯一标识符为PXD025925。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae68/8345211/ccd0f16c0425/cancers-13-03804-g001.jpg

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