High‐Throughput Analyses of Glycans, Glycosites, and Intact Glycopeptides Using C4‐and C18/MAX‐Tips and Liquid Handling System

Chen, Shao-Yung; Clark, David; Zhang, Hui

doi:10.1002/cpz1.186

Cited by 7 publications

(7 citation statements)

References 46 publications

(58 reference statements)

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“…After the intact glycopeptide enrichment, we added 2 μl PNGaseF to remove all N‐linked glycans from glycopeptides. The detailed sample preparation procedure of intact glycopeptide enrichment was referenced as our previous publication [28].…”

Section: Methodsmentioning

confidence: 99%

“…Each pre-DRE urine sample (500 μl) was desalted, protease digested and followed by intact glycopeptide enrichment automatically on Versette (Thermo Fisher Scientific) following our published experimental workflow [23,27,28]. The desalting and digestion processes were done on C4-tips via conditioning, sample loading, washing, and "on-tip" protein digestion steps.…”

Section: Automated Digestion Of Human Urine Specimens By Proteasesmentioning

confidence: 99%

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Differentially expressed glycoproteins in pre‐ and post‐digital rectal examination urine samples for detecting aggressive prostate cancer

et al. 2023

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Urinary glycoproteins associated with aggressive prostate cancer (AG‐PCa) were previously reported using post‐digital rectal examination (DRE) urine specimens. To explore the potential of using pre‐DRE urine specimens for detecting AG‐PCa, we compared glycoproteins between pre‐ and post‐DRE urine specimens, verified the previously identified post‐DRE AG‐PCa‐associated urinary glycoproteins in pre‐DRE urine specimens, and explored potential new glycoproteins for AG‐PCa detection in pre‐DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre‐DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non‐AG‐PCa (Gleason score = 6), and 65 patients with AG‐PCa (Gleason score 7 or above). Compared to glycopeptides from the post‐DRE urine data, humoral immunity‐related proteins were enriched in pre‐DRE urine samples, whereas cell mediated immune response proteins were enriched in post‐DRE urine samples. Analyses of AG‐PCa‐associated glycoproteins from pre‐DRE urine revealed that the three urinary glycoproteins, prostate‐specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post‐DRE urine samples, were also observed as AG‐PCa associated glycoproteins in pre‐DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG‐PCa in pre‐DRE urine specimens. In summary, glycoprotein profiles differ between pre‐ and post‐DRE urine specimens. The identified AG‐PCa‐associated glycoproteins may be further evaluated in large cohort of pre‐DRE urine specimens for detecting clinically significant PCa.

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Section: Methodsmentioning

confidence: 99%

Section: Automated Digestion Of Human Urine Specimens By Proteasesmentioning

confidence: 99%

Differentially expressed glycoproteins in pre‐ and post‐digital rectal examination urine samples for detecting aggressive prostate cancer

et al. 2023

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“…The global proteomic sample processing procedure is derived from Clark et al, , which is termed C4-Tip. Briefly, C4-Tips were conditioned with 50% acetonitrile (ACN) in 0.1% trifluoroacetic acid (TFA) followed by 0.1% TFA for 10 cycles each.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…Intact glycopeptides were isolated from the peptide mixture according to our previously published automated method. , Samples were dried and reconstituted in 0.1% TFA while C18/MAX-Tip conditioning was performed using (1) ACN, (2) 100 mM triethyl ammonium acetate, (3) 95% ACN + 1% TFA, and (4) 0.1% TFA (sequentially, 10 cycles each) as described in the previous publication . Reconstituted samples were bound onto C18/MAX-Tip (20 cycles) and washed with 0.1% TFA for 10 cycles.…”

Section: Materials and Methodsmentioning

confidence: 99%

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins

Chen

Lih

et al. 2022

ACS Omega

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Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests. However, the specific molecular signatures from different urogenital cancers are needed to relate changes in urine to various cancer detections. Herein, we utilized a previously published C4-Tip and C18/MAX-Tip workflow for enrichment of glycopeptides from urine samples and evaluated urinary glycopeptides for its cancer specificity. We analyzed 66 urine samples from bladder cancer ( n = 27), prostate cancer ( n = 4), clear cell renal cell carcinoma (ccRCC, n = 3), and benign plastic hyperplasia (BPH, n = 32) and then compared them with a previous publication that reported glycopeptides associated with aggressive prostate cancer (Gleason score ≥ 8). We further demonstrated the cancer specificity of the glycopeptides associated with aggressive prostate cancer. In this study, a total of 33 glycopeptides were identified to be specifically differentially expressed in prostate cancer compared to other urogenital cancer types as well as BPH urines. By cross-comparison with our previous urinary glycoproteomic dataset for aggressive prostate cancer, we reported a total of four glycopeptides from glycoproteins DSC2, MGAM, PIK3IP1, and CD55, commonly identified to be prostate cancer-specific. Together, these results deepen our understanding of the urinary glycoproteins associated with urogenital cancer types and expand our knowledge of the cancer specificity of urinary glycoproteins among urogenital cancer progression.

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“…Protein glycosylation is an important and abundant post-translational modification ( 21 ). It is a process in which saccharides are transferred to the polypeptide chain skeleton, mediated by glycosyltransferase, glycosidase, and other enzymes ( 22 ).…”

Section: Introductionmentioning

confidence: 99%

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy

et al. 2022

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Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson’s correlation analysis, Cox regression, and Kaplan–Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography–tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

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High‐Throughput Analyses of Glycans, Glycosites, and Intact Glycopeptides Using C4‐and C18/MAX‐Tips and Liquid Handling System

Cited by 7 publications

References 46 publications

Differentially expressed glycoproteins in pre‐ and post‐digital rectal examination urine samples for detecting aggressive prostate cancer

Differentially expressed glycoproteins in pre‐ and post‐digital rectal examination urine samples for detecting aggressive prostate cancer

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy

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