Novel Insight into the Etiology of Haff Disease by Mapping the N-Glycome with Orthogonal Mass Spectrometry

Liu, Si; Liu, Yuanyuan; Lin, Jiajing; Liu, Bi‐Feng; He, Zhenyu; Wu, Xiaomin; Liu, Xin

doi:10.1016/j.eng.2022.09.012

Cited by 3 publications

(4 citation statements)

References 47 publications

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“…N-glycome profile was characterized by a MALDI-MS based high-throughput analytical assay. 55 Profiling of Serum N-glycans were performed with the same manner as reported in our recent study, 56 , 57 including N-glycan release, chemical derivatization, MALDI-MS analysis and MS data processing.…”

Section: Methodsmentioning

confidence: 99%

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Zhang,

Liu,

Wang

et al. 2024

iScience

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Section: Methodsmentioning

confidence: 99%

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Zhang,

Liu,

Wang

et al. 2024

iScience

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“…Blood samples from all patients were obtained at the time of admission, before any treatment. N‐glycans in serum samples were released, derivatized, and purified as described in a previous publication, which has been demonstrated with favorable reproducibility [18, 19]. Briefly, 10 µL of serum was diluted in 84 µL of ultra‐pure water and then mixed with 3.6 µL of 10 × PNGase F buffer and 2.4 µL of denaturing buffer.…”

Section: Methodsmentioning

confidence: 99%

“…N-glycans in serum samples were released, derivatized, and purified as described in a previous publication, which has been demonstrated with favorable reproducibility [18,19] PyAOP at room temperature for 30 min. Then, the derived N-glycans were added with 500 μL of butanol-EtOH-water (4:1:1) and purified with a MCC SPE column, using 50% EtOH as elution buffer.…”

Section: Serum N-glycan Profilingmentioning

confidence: 99%

“…However, these imaging examinations are flawed by poor specificity, high cost, and radiation hazards. Likewise, the sensitivity and specificity of traditional tumor biomarkers like carcinoembryonic antigen (CEA), cytokeratin 19 fragments antigen (CYFRA21-1), and squamous cell carcinoma antigen (SCCA) are unsatisfactory for early screening [7]. Therefore, it is urgent to identify useful biomarkers for the early detection of NSCLC so as to optimize disease management and improve cancer survival.…”

mentioning

confidence: 99%

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Comprehensive serum N‐glycan profiling identifies a biomarker panel for early diagnosis of non‐small‐cell lung cancer

Wang

Liu

et al. 2023

Proteomics

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Aberrant serum N‐glycan profiles have been observed in multiple cancers including non‐small‐cell lung cancer (NSCLC), yet the potential of N‐glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N‐glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI‐TOF‐MS. The levels of serum N‐glycans and N‐glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N‐glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N‐glycan structures were identified in human serum. Compared with healthy controls, 29 serum N‐glycans were increased or decreased in NSCLC patients. N‐glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N‐glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early‐stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N‐glycan profiles in NSCLC and provides supports potential application of N‐glycan biomarker panel in clinical NSCLC detection.

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Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

Liu,

Tu,

Zhang

et al. 2024

J Ovarian Res

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Background Ovarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer. Methods Herein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed. Results It was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets. Conclusions These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

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Novel Insight into the Etiology of Haff Disease by Mapping the N-Glycome with Orthogonal Mass Spectrometry

Cited by 3 publications

References 47 publications

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Comprehensive serum N‐glycan profiling identifies a biomarker panel for early diagnosis of non‐small‐cell lung cancer

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

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