Urinary glycoproteins associated with aggressive prostate cancer

Abstract

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer. Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort. Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort. Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

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

“…Normalization was performed on glycopeptides to the total protein amount in the individual urine sample. 16 Across 66 urine samples, 872 glycopeptides originating from 485 glycoproteins were identified and quantified with an FDR < 0.01 for both proteins and peptides ( Table S2 ).…”

“…After the de- N -glycopeptides were identified and quantified, normalization was performed on the glycopeptide intensity to the total protein amount of the individual urine samples. 16 …”

Mass Spectrometry-Based Glycoproteomics and Prostate Cancer

“…For example, Vermassen et al showed that average total PSA urinary concentration (tPSA) before and after DRE was, respectively, 75.5 µg/L and 13,030 µg/L [ 48 ]. Dong et al analysed EPS-urines from 74 and 68 patients with AG PCa and NAG PCa, respectively; they aimed to detect differentially expressed glycoproteins among the two groups by data independent analysis (DIA) [ 49 ]. Briefly, the digestion of 500 µL of EPS-urine was performed by automated tryptic digestion on C4-tips (Lys-C 1 h and trypsin 6 h) [ 50 ]; after digestion, N-glycopeptides were isolated by automated C18/MAX-tip method followed by de-glycosylation with PNGase F and peptide purification by C18 StageTip [ 51 ].…”

An Ultrafast N-Glycoproteome Analysis Method Using Thermoresponsive Magnetic Fluid-Immobilized Enzymes

“…From the general biological process, such as cell adhesion and signal transduction, to specific functions of proteins like folding and stability, the complexity imparted to a proteome by N- glycosylation is immense (Schjoldager et al, 2020 ). Moreover, the N- glycans biosynthesis process is very sensitive to the physiological and pathological states in cells (Mereiter et al, 2019 ; Dong et al, 2020 ), and glycoproteins are a main type of current therapeutic targets and disease biomarkers (Pan et al, 2020 ; Zhao et al, 2020 ). Fueled by the increasing discovery of disease-related N- glycans alterations, the interest in large-scale N -glycosylation profiling in clinical samples is proliferating.…”