[2020] 외부기관 발표 (PLoS One. 2020 Apr 9;15(4):e0231004.)
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2020-09-17 10:41
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1995
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231…
Abstract
Blood and serum N-glycans can be used as markers for cancer diagnosis, as alterations in protein glycosylation are associated with cancer pathogenesis and progression. We aimed to develop a platform for breast cancer (BrC) diagnosis based on serum N-glycan profiles using MALDI-TOF mass spectroscopy. Serum N-glycans from BrC patients and healthy volunteers were evaluated using NosQuest's software "NosIDsys." BrC-associated "NosID" N-glycan biomarkers were selected based on abundance and NosIDsys analysis, and their diagnostic potential was determined using NosIDsys and receiver operating characteristic curves. Results showed an efficient pattern recognition of invasive ductal carcinoma patients, with very high diagnostic performance [area under the curve (AUC): 0.93 and 95% confidence interval (CI): 0.917-0.947]. We achieved effective stage-specific differentiation of BrC patients from healthy controls with 82.3% specificity, 84.1% sensitivity, and 82.8% accuracy for stage 1 BrC and recognized hormone receptor-2 and lymph node invasion subtypes based on N-glycan profiles. Our novel technique supplements conventional diagnostic strategies for BrC detection and can be developed as an independent platform for BrC screening.
Breast cancer diagnosis by analysis of serum N-glycans using MALDI-TOF mass spectroscopy.
SB Lee et al. PLoS One (2020)Abstract
Blood and serum N-glycans can be used as markers for cancer diagnosis, as alterations in protein glycosylation are associated with cancer pathogenesis and progression. We aimed to develop a platform for breast cancer (BrC) diagnosis based on serum N-glycan profiles using MALDI-TOF mass spectroscopy. Serum N-glycans from BrC patients and healthy volunteers were evaluated using NosQuest's software "NosIDsys." BrC-associated "NosID" N-glycan biomarkers were selected based on abundance and NosIDsys analysis, and their diagnostic potential was determined using NosIDsys and receiver operating characteristic curves. Results showed an efficient pattern recognition of invasive ductal carcinoma patients, with very high diagnostic performance [area under the curve (AUC): 0.93 and 95% confidence interval (CI): 0.917-0.947]. We achieved effective stage-specific differentiation of BrC patients from healthy controls with 82.3% specificity, 84.1% sensitivity, and 82.8% accuracy for stage 1 BrC and recognized hormone receptor-2 and lymph node invasion subtypes based on N-glycan profiles. Our novel technique supplements conventional diagnostic strategies for BrC detection and can be developed as an independent platform for BrC screening.