Disease-Specific IgG Fc Glycosylation Ratios as Personalized Biomarkers to Differentiate Non-Small Cell Lung Cancer from Benign Lung Diseases

Protein glycosylation in lung cancer from a mass spectrometry perspective

Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer. Differences in glycosylation patterns have been previously observed between healthy and cancerous samples as well as between different lung cancer subtypes, which suggests untapped diagnostic potential. In addition, understanding the changes mediated by glycosylation may shed light on possible novel therapeutic targets and personalized treatment strategies for lung cancer patients. Mass spectrometry based glycomics and glycoproteomics have emerged as powerful tools for in-depth characterization of changes in protein glycosylation, providing valuable insights into the molecular basis of lung cancer. This paper reviews the literature on the analysis of protein glycosylation in lung cancer using mass spectrometry, which is dominated by manuscripts published over the past 5 years. Studies analyzing N-glycosylation, O-glycosylation, and glycosaminoglycan patterns in tissue, serum, plasma, and rare biological samples of lung cancer patients are highlighted. The current knowledge on the potential utility of glycan and glycoprotein biomarkers is also discussed.

Disease-Specific Haptoglobin N-Glycosylation in Inflammatory Disorders between Cancers and Benign Diseases of 3 Types of Female Internal Genital Organs

BACKGROUND

N-glycosylation of the haptoglobin is closely related to pathological states. This study aims to evaluate the association of glycosylation of disease-specific Hp (DSHp) β chain with different pathological states of the cervix, uterus, and ovary to explore differences in their inflammatory responses and to screen potential biomarkers to distinguish cancer from benign diseases.

METHODS

DSHp-β chains of 1956 patients with cancers and benign diseases located in the cervix, uterus, and ovary organs were separated from serum immunoinflammatory-related protein complexes (IIRPCs). The N-glycopeptides from DSHp-β chains were detected using mass spectrometry, followed by an analysis of machine learning algorithms.

RESULTS

55 N-glycopeptides at N207/N211, 19 at N241, and 21 at N184 glycosylation sites of DSHp for each sample were identified. Fucosylation and sialylation of DSHp in cervix, uterus, and ovary cancer were significantly increased compared to their corresponding benign diseases (p < 0.001). The cervix diagnostic model, a combination of G2N3F, G4NFS, G7N2F2S5, GS-N&GS-N, G2N2&G4N3FS, G7N2F2S5, G2S2&G-N, and GN2F&G2F at N207/N211 sites, G3NFS2 and G3NFS at N241site, G9N2S, G6N3F6, G4N3F5S, G4N3F4S2, and G6N3F4S at N184 site), has shown a good diagnostic capability to distinguish cancer from benign diseases, with the area under curve (AUC) of 0.912. The uterus diagnostic model including G4NFS, G2S2&G2S2, G3N2S2, GG5N2F5, G2&G3NFS, and G5N2F3S3 at N207/N211 sites, and G2NF3S2 at N184 site, with an AUC of 0.731. The ovary diagnostic model including G2N3F, GF2S-N &G2F3S2, G2S&G2, and G2S&G3NS at N207/N211 sites; G2S and G3NFS at N241 site, G6N3F4S at N184 site, with an AUC of 0.747.

CONCLUSIONS

These findings provide insights into differences in organ-specific inflammatory responses of DSHp for different pathological states among the organs of the cervix, uterus, and ovary.

Intra-Individual Variation in Disease-Specific IgG Fc Glycoform Ratios to Monitor the Disease Progression of Lung Cancer

Aberrant protein glycosylation is an active pathological alteration related to the progression of cancers. The speed of progression varies among individuals, increasing the difficulties of prognosis assessment. Hence, evaluating variation in glycosylation using patients themselves as their own controls is a potential way to reduce the impact of individual differences on progression monitoring. Here, following a longitudinal follow-up study involving 125 lung cancer (LC) patients with progressive disease, we isolated disease-specific IgG from serum using polyacrylamide gel electrophoresis, obtained IgG glycoform ratios using mass spectrometry, and then set a fold-change cutoff of 1.5 to utilize the intra-individual variation in IgG glycosylation to monitor PD. We found that the serial monitoring of 15 types of glycoform ratios provided an effective way for monitoring LC progression. Over 1.5-fold changes in glycoform ratios relative to the first observed value were detected in 117 of 125 LC patients (93.6%). Our established method predicted LC progression 55.8 (IQR 31.1-90.1) weeks earlier than imaging examination did. In summary, intra-individual variation in IgG glycoform ratios is useful to monitor LC progression, expanding our knowledge about the relationship between IgG glycosylation and cancer prognosis. The raw data files are available via the ProteomeXchange Consortium with the identifier PXD037541.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Protein Glycopatterns in Bronchoalveolar Lavage Fluid as Novel Potential Biomarkers for Diagnosis of Lung Cancer

Lung cancer is one of the most prevalent and life-threatening neoplasias worldwide due to the deficiency of ideal diagnostic biomarkers. Although aberrant glycosylation has been observed in human serum and tissue, little is known about the alterations in bronchoalveolar lavage fluid (BALF) that are extremely associated with lung cancer. In this study, our aim was to systematically investigate and assess the alterations of protein glycopatterns in BALF and possibility as biomarkers for diagnosis of lung cancer. Here, lectin microarrays and blotting analysis were utilized to detect the differential expression of BALF glycoproteins from patients with 80 adenocarcinomas (ADC), 77 squamous carcinomas (SCC), 51 small cell lung cancer (SCLC), and 73 benign pulmonary diseases (BPD). These 281 specimens were then randomly divided into a training cohort and validation cohort for constructing and verifying the diagnostic models based on the glycopattern abundances. Moreover, an independent test was performed with 120 newly collected BALF samples enrolled in the double-blind cohort to further assess the clinical application potential of the diagnostic models. According to the results, there were 15 (e.g., PHA-E, EEL, and BPL) and 14 lectins (e.g., PTL-II, LCA, and SJA) that individually showed significant variations in different types and stages of lung cancer compared to BPD. Notably, the diagnostic models achieved better discriminate power in the validation cohort and exhibited high accuracies of 0.917, 0.864, 0.712, 0.671, and 0.781 in the double-blind cohort for the diagnosis of lung cancer, early stage lung cancer, ADC, SCC, and SCLC, respectively. Taken together, the present study revealed that the abnormally altered protein glycopatterns in BALF are expected to be novel potential biomarkers for the identification and early diagnosis of lung cancer, which will contribute to explain the mechanism of the development of lung cancer from the perspective of glycobiology.

Alterations in serum protein glycopatterns related to small cell lung cancer, adenocarcinoma and squamous carcinoma of the lung

Background: The main reason why lung cancer has maintained a high rate of morbidity and mortality is that its early diagnosis is difficult. No current lung cancer screening is recommended by any major medical organization due to the lack of sensitive and specific screening technologies. Thus, this study aimed to systematically investigate the correlation between the alterations in serum glycosylation and three main types of lung cancers (SCLC, ADC and SqCC). Materials and methods: We investigated the protein glycopatterns in sera from 333 subjects (65 healthy volunteers, 38 benign lung disease patients, 49 small cell lung cancer patients, and 181 NSCLC patients) using a lectin microarray. A serum microarray was produced to evaluate and verify the terminal carbohydrate moieties of the glycoproteins in individual serum samples from 30 cases simultaneously. Results: There were 16 lectins (e.g., RCA120, BS-I, and UEA-I), 24 lectins (e.g., HHL, PTL-I, and MAL-II), and 18 lectins (e.g., GSL-I, LEL, and ACA) that exhibited significant differences in serum protein glycopatterns in the patients with SCLC, ADC and SqCC compared with the controls (HV and BPD). There were 6 lectins (e.g., EEL, NPA, and LEL) that exhibited significantly increased NFIs in ADC and SqCC compared with SCLC. Also, there were 5 lectins (e.g., Jacalin, BS-I, and UEA-I) that exhibited significantly decreased NFIs in ADC compared with SCLC and SqCC. Conclusions: This study can facilitate the discovery of potential biomarkers for the differential diagnosis of lung cancer based on the precise alteration in serum protein glycopatterns.

The main reason why lung cancer has maintained a high rate of morbidity and mortality is that its early diagnosis is difficult.