While mammograms are the standard tool for breast cancer screening, there remains challenges for mammography to effectively distinguish benign lesions from breast cancers, leading to many unnecessary biopsy procedures. A blood-based biomarker could provide a minimally invasive supplemental assay to increase the specificity of breast cancer screening. Serum N-glycosylation alterations have associations with many cancers and several of the clinical characteristics of breast cancer. The current study utilized a high-throughput mass spectrometry workflow to identify serum N-glycans with differences in intensities between patients that had a benign lesion from patients with breast cancer. The overall N-glycan profiles of the two patient groups had no differences, but there were several individual N-glycans with significant differences in intensities between patients with benign lesions and ductal carcinoma in situ (DCIS). Many N-glycans had strong associations with age and/or body mass index, but there were several of these associations that differed between the patients with benign lesions and breast cancer. Accordingly, the samples were stratified by the patient's age and body mass index, and N-glycans with significant differences between these subsets were identified. For women aged 50-74 with a body mass index of 18.5-24.9, a model including the intensities of two N-glycans, 1850.666Â m/z and 2163.743Â m/z, age, and BMI were able to clearly distinguish the breast cancer patients from the patients with benign lesions with an AUROC of 0.899 and an optimal cutoff with 82% sensitivity and 84% specificity. This study indicates that serum N-glycan profiling is a promising approach for providing clarity for breast cancer screening, especially within the subset of healthy weight women in the age group recommended for mammograms.
Integrating age, BMI, and serum N-glycans detected by MALDI mass spectrometry to classify suspicious mammogram findings as benign lesions or breast cancer.
阅读:4
作者:Blaschke Calvin R K, Hill Elizabeth G, Mehta Anand S, Angel Peggi M, Laronga Christine, Drake Richard R
| 期刊: | Scientific Reports | 影响因子: | 3.900 |
| 时间: | 2022 | 起止号: | 2022 Dec 2; 12(1):20801 |
| doi: | 10.1038/s41598-022-25401-0 | ||
特别声明
1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。
2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。
3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。
4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。
