Trial reportJournal of translational medicine2024
Development and validation of a model and nomogram for breast cancer diagnosis based on quantitative analysis of serum disease-specific haptoglobin N-glycosylation.
Trial report in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Identification of Glycoprotein Biomarkers in Breast Cancer by MALDI.Life (Basel, Switzerland) · 2026Review
- Article
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundA better diagnostic marker is in need to distinguish breast cancer from suspicious breast lesions. The abnormal glycosylation of haptoglobin has been documented to assist cancer diagnosis. This study aims to evaluate disease-specific haptoglobin (DSHp)-β N-glycosylation as a potential biomarker for breast cancer diagnosis.
methodsDSHp-β chains of 497 patients with suspicious breast lesions who underwent breast surgery were separated from serum immunoinflammatory-related protein complexes. DSHp-β N-glycosylation was quantified by mass spectrometric analysis. After missing data imputation and propensity score matching, patients were randomly assigned to the training set (n = 269) and validation set (n = 113). Logistic regression analysis was employed in model and nomogram construction. The diagnostic performance was analyzed with receiver operating characteristic and calibration curves.
results95 N-glycopeptides at glycosylation sites N207/N211, N241, and N184 were identified in 235 patients with benign breast diseases and 262 patients with breast cancer. DSHp-β N-tetrafucosyl and hexafucosyl were significantly increased in breast cancer compared with benign diseases (p < 0.001 and p = 0.001, respectively). The new diagnostic model and nomogram included GN2F2, G6N3F6, GN2FS at N184, G-N&G2S2, G2&G3NFS, G2N3F, GN3 at N207/N211, CEA, CA153, and could reliably distinguish breast cancer from benign diseases. For the training set, validation set, and training and validation sets, the area under the curves (AUCs) were 0.80 (95% CI: 0.75-0.86, specificity: 87%, sensitivity: 62%), 0.77 (95% CI:0.69-0.86, specificity: 75%, sensitivity: 69%), and 0.80 (95% CI:0.76-0.84, specificity: 77%, sensitivity: 68%), respectively. CEA, CA153, and their combination yielded AUCs of 0.62 (95% CI: 0.56-0.67, specificity: 29%, sensitivity: 90%), 0.65 (95% CI: 0.60-0.71, specificity: 74%, sensitivity: 51%), and 0.67 (95% CI: 0.62-0.73, specificity: 60%, sensitivity: 68%), respectively.
conclusionsThe combination of DSHp-β N-glycopeptides, CEA, and CA153 might be a better serologic marker to differentiate between breast cancer and benign breast diseases. The dysregulated N-glycosylation of serum DSHp-β could provide insights into breast tumorigenesis.
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