Distinguishing Benign and Malignant Thyroid Nodules and Identifying Lymph Node Metastasis in Papillary Thyroid Cancer by Plasma N-Glycomics

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Elevated level of multibranched complex glycan reveals an allergic tolerance status

BACKGROUND

Allergen immunotherapy (AIT) is the only disease-modifying therapy that can achieve immune tolerance in patients through long-term allergen stimulation. Glycans play crucial roles in allergic disease, but no information on changes in glycosylation related to an allergic tolerance status has been reported.

METHODS

Fifty-seven patients with house dust mite (HDM) allergies were enrolled. Twenty-eight patients were not treated with AIT, 19 patients had just entered the AIT maintenance treatment phase, and 10 patients had been in the AIT maintenance phase for more than 1 year. Serum protein N-glycans were analyzed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), which included linkage-specific sialylation information.

RESULTS

Eighty-four N-glycans were identified in all three groups. Compared with the patients treated without AIT, the patients treated with AIT for a shorter time showed downregulated expression of high-mannose glycans and upregulated expression of α2,6 sialic acid. The patients treated with AIT in the maintenance phase for over 1 year, which was considered the start of immunological tolerance, showed downregulated expression of biantennary N-glycans and upregulated expression of multibranched and complex N-glycans. Nine N-glycans were changed between allergic and allergic-tolerant patients.

CONCLUSIONS

The glycan form changed from mannose to a more complex type as treatment time increased, and multibranched complex glycans have the potential to be used as a monitoring indicator of immune tolerance. This serum N-glycome analysis provided important information for a deeper understanding of AIT treatment at the molecular level.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Capitalizing glycomic changes for improved biomarker-based cancer diagnostics

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

Serum protein N-glycome patterns reveal alterations associated with endometrial cancer and its phenotypes of differentiation

Background

Aberrant N-glycosylation and its involvement in pathogenesis have been reported in endometrial cancer (EC). Nevertheless, the serum N-glycomic signature of EC remains unknown. Here, we investigated serum N-glycome patterns of EC to identify candidate biomarkers.

Methods

This study enrolled 34 untreated EC patients and 34 matched healthy controls (HC) from Peking Union Medical College Hospital. State-of-the-art MS-based methods were employed for N-glycans profiling. Multivariate and univariate statistical analyses were used to identify discriminative N-glycans driving classification. Receiver operating characteristic analyses were performed to evaluate classification accuracy.

Results

EC patients displayed distinct differences in serum N-glycome and had abnormal high-mannose and hybrid-type N-glycans, fucosylation, galactosylation, and linkage-specific sialylation compared with HC. The glycan panel built with the four most discriminative and biologically important derived N-glycan traits could accurately identify EC (random forest model, the area under the curve [AUC]=0.993 [95%CI 0.955-1]). The performance was validated by two other models. Total hybrid-type N-glycans significantly associated with the differentiation types of EC could effectively stratify EC into well- or poorly-differentiated subgroups (AUC>0.8).

Conclusion

This study provides the initial evidence supporting the utility of serum N-glycomic signature as potential markers for the diagnosis and phenotyping of EC.

Case Report: A papillary thyroid microcarcinoma patient with skip lymph node metastasis and multiple distant metastasis

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Papillary thyroid microcarcinoma (PTMC) is defined as PTC with a diameter less than 1 centimeter. Most lymph nodes of PTC patients have metastasized to the central neck, and a few lymph nodes have metastasized to the lateral neck. Skip lymph node metastasis, that is, lateral cervical lymph node metastasis without central lymph node metastasis, is even less common. Additionally, distant metastasis of PTMC is also rare, mainly occurring in the lung and bone. Here, we reported a case of PTMC patient with skip lymph node metastasis and multiple distant metastasis. The patient presented with a huge shoulder mass and the primary tumor was found to originate from the thyroid. However, the patient only suffered with PTMC via postoperative pathological results, and interestingly, the patient only had skip lymph node metastasis. Thus, we should focus on PTMC patients with lateral cervical lymph nodes metastasis, especially those with skip metastasis. In addition, this case provides a new perspective for us to understand of skip lymph metastasis and distant metastasis of PTMC.

An analytical study on the identification of N-linked glycosylation sites using machine learning model

N-linked is the most common type of glycosylation which plays a significant role in identifying various diseases such as type I diabetes and cancer and helps in drug development. Most of the proteins cannot perform their biological and psychological functionalities without undergoing such modification. Therefore, it is essential to identify such sites by computational techniques because of experimental limitations. This study aims to analyze and synthesize the progress to discover N-linked places using machine learning methods. It also explores the performance of currently available tools to predict such sites. Almost seventy research articles published in recognized journals of the N-linked glycosylation field have shortlisted after the rigorous filtering process. The findings of the studies have been reported based on multiple aspects: publication channel, feature set construction method, training algorithm, and performance evaluation. Moreover, a literature survey has developed a taxonomy of N-linked sequence identification. Our study focuses on the performance evaluation criteria, and the importance of N-linked glycosylation motivates us to discover resources that use computational methods instead of the experimental method due to its limitations.

Nomograms Based on Serum N-glycome for Diagnosis of Papillary Thyroid Microcarcinoma and Prediction of Lymph Node Metastasis

Non-invasive biomarkers for the diagnosis and prognosis of papillary thyroid microcarcinoma (PTMC) are still urgently needed. We aimed to characterize the N-glycome of PTMC, and establish nomograms for the diagnosis of PTMC and the prediction of lymph node metastasis (LNM). N-glycome of PTMC (LNM vs. non-LNM, capsular invasion (CI) vs. non-CI (NCI)) and matched healthy controls (HC) were quantitatively analyzed based on mass spectrometry. N-glycan traits associated with PTMC/LNM were used to create binomial logistic regression models and were visualized as nomograms. We found serum N-glycome differed between PTMC and HC in high-mannose, complexity, fucosylation, and bisection, of which, four N-glycan traits (TM, CA1, CA4, and A2Fa) were significantly associated with PTMC. The nomogram based on four traits achieved good performance for the identification of PTMC. Two N-glycan traits (CA4 and A2F0S0G) showed strong associations with LNM. The nomogram based on two traits showed relatively good performance in predicting LNM. We also found differences between CI and NCI in several N-glycan traits, which were not the same as that associated with LNM. This study reported serum N-glycosylation signatures of PTMC for the first time. Nomograms constructed from aberrant glycans could be useful tools for PTMC diagnosis and stratification.

Relationship between serum NDRG3 and papillary thyroid carcinoma

BACKGROUND

In recent years, papillary thyroid carcinoma is considered to be one of the fastest increaseing cancer. NDRG family member 3 (NDRG3) has been proposed as a molecular marker of tumor, and is expected to be used in clinic.

METHODS

Enzyme-linked immunosorbent assay was used to detect the serum NDRG3 expression in 81 papillary thyroid carcinoma cases, 75 benign thyroid nodules cases and 77 healthy control cases, respectively. Electrochemiluminescence method was applied to measure the levels of triiodothyronine, tetraiodothyronine, thyrotropin, thyroglobulin antibody and thyroid peroxidase antibody. Immunohistochemical staining was used to detect the expression of NDRG3 in papillary thyroid carcinoma, benign thyroid nodules and normal tissues adjacent to cancer.

RESULTS

The expression of serum triiodothyronine, tetraiodothyronine, thyrotropin, thyroglobulin antibody and thyroid peroxidase antibody and NDRG3 were significantly different among benign thyroid nodules, papillary thyroid carcinoma cases and healthy control groups (P <0.001). Only the expression of serum NDRG3 was significantly different between benign thyroid nodules and papillary thyroid carcinoma groups (P <0.001). Immunohistochemistry showed that NDRG3 was expressed in all three groups, the lowest in papillary thyroid carcinoma, the second in benign thyroid nodules, and the highest in normal tissues adjacent to cancer. Logistic regression analysis showed that serum NDRG3 was an independent protective factor for papillary thyroid carcinoma (OR =0.964, 95%CI =0.953 to 0.974, P <0.001). The ROC curve of non-papillary thyroid carcinoma diagnosed by serum NDRG3 showed the optimal cut-off value of 481.38 pg/ml, sensitivity of 72.4%, specificity of 90.1%, and the maximum area under the curve (AUC =0.902, 95%CI =0.863 to 0.940, P <0.001). The ROC curve of benign thyroid nodules diagnosed by serum NDRG3 showed the optimal critical value of 459.28 pg/ml, sensitivity of 81.3%, and specificity of 74.1% (AUC =0.863, 95%CI =0.808 to 0.919, P <0.001). The expression level of serum NDRG3 was significantly correlated with extrathyroid extensionand (P =0.007) and lymphatic metastasis of papillary thyroid carcinoma (P =0.019).

CONCLUSIONS

The decrease of NDRG3 expression can not only differential diagnosis benign thyroid nodules and papillary thyroid carcinoma, but also serve as a molecular marker for the diagnosis of papillary thyroid carcinoma.

Serum Linkage-Specific Sialylation Changes Are Potential Biomarkers for Monitoring and Predicting the Recurrence of Papillary Thyroid Cancer Following Thyroidectomy

BACKGROUND

Although papillary thyroid cancer (PTC) could remain indolent, the recurrence rates after thyroidectomy are approximately 20%. There are currently no accurate serum biomarkers that can monitor and predict recurrence of PTC after thyroidectomy. This study aimed to explore novel serum biomarkers that are relevant to the monitoring and prediction of recurrence in PTC using N-glycomics.

METHODS

A high-throughput quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was used to obtain serum protein N-glycomes of well-differentiated PTC, postoperative surveillance (PS), postoperative recurrence (PR), and matched healthy controls (HC) including linkage-specific sialylation information.

RESULTS

Serum N-glycan traits were found to differ among PTC, PS, PR, and HC. The differentially expressed N-glycan traits consisting of sixteen directly detected glycan traits and seven derived glycan traits indicated the response to surgical resection therapy and the potential for monitoring the PTC. Two glycan traits representing the levels of linkage-specific sialylation (H4N3F1L1 and H4N6F1E1) which were down-regulated in PS and up-regulated in PR showed high potential as biomarkers for predicting the recurrence after thyroidectomy.

CONCLUSIONS

To the best of our knowledge, this study provides comprehensive evaluations of the serum N-glycomic changes in patients with PS or PR for the first time. Several candidate serum N-glycan biomarkers including the linkage-specific sialylation have been determined, some of which have potential in the prediction of recurrence in PTC, and others of which can help to explore and monitor the response to initial surgical resection therapy. The findings enhanced the comprehension of PTC.