Incidence and risk factors of stress urinary incontinence after laparoscopic hysterectomy.

OBJECTIVE: To observe the long-term effects of total hysterectomy on urinary function, evaluate the effects of preoperative nutritional status, urinary occult infection, and surgical factors on the induction of postoperative stress urinary incontinence (SUI), and explore the incidence and risk factors of SUI. STUDY DESIGN: From January 2017 to December 2017, 164 patients with benign non-prolapsing diseases who underwent a laparoscopic total hysterectomy in the First People's Hospital of Taicang were selected as the analysis objects. The International Incontinence Standard Questionnaire for Female Lower Urinary Tract Symptoms (ICIQ-FLUTS) and Pelvic Floor Impact Questionnaire-short version 20 (PFDI-20) were used for telephone follow-up to subjectively assess the urinary function of patients, collect their medical records, and statistically analyze the number of postoperative SUI cases. Logistic multivariate analysis was used to analyze the influencing factors of postoperative female SUI, presented as adjusted odds ratios with 95% confidence intervals. RESULTS: Only 97 out of 164 patients completed the ICIQ-FLUTS and PFDI-20 questionnaires. Among these participants, 28 patients (28.86%) were diagnosed with SUI (study group), while 69 patients (71.13%) were classified as women without SUI (control group). The age, menopause, parity ≥ 2 times, Body mass index (BMI) ≥ 28 kg/m2, neonatal weight ≥ 4000 g, history of chronic cough, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, preoperative uterine volume ≥ 90 cm3, intraoperative blood loss, and operation time of the study group were compared with those of the control group. The differences were statistically significant (P < 0.05). Further Logistic multivariate analysis showed that menopause, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, uterine volume ≥ 90 cm3, history of chronic cough, BMI ≥ 28 kg/m2 were risk factors for postoperative SUI in patients undergoing hysterectomy (P < 0.05). CONCLUSIONS: Hysterectomy for benign non-prolapse diseases has a long-term potential impact on the urinary system of patients, and the risk of postoperative SUI increases. The main risk factors of SUI are parity, menopausal status, obesity, preoperative nutritional status, and occult infection of the urinary system.

The CDK4/6 Inhibitor Palbociclib Induces Cell Senescence of High-grade Serous Ovarian Cancer Through Acetylation of p53.

Cell senescence is an anti-cancer strategy following DNA repair and apoptosis, which is associated with the initiation, progression, and treatment of ovarian cancer. The CDK4/6 inhibitor alters cell cycle and induces cell senescence dependent on retinoblastoma (RB) family proteins. Objective Herein, we aimed to explore the effects of Palbociclib (a CDK4/6 inhibitor) on cellular senescence of high-grade serous ovarian cancer (HGSOC). Cell viability and cell cycle were evaluated by cell counting kit-8 and flow cytometry. Cell senescence was analyzed using the SA-ß-gal staining assay. The senescence-associated secretory phenotype was assessed using quantitative PCR (qPCR). Senescence-related markers were tested using western blot. The role of Palbociclib in vivo was clarified using xenograft tumor. Acetylation of p53 was evaluated by qPCR and western blot. The results showed that Palbociclib inhibited cell viability, blocked cell cycle at G0/G1 phase, and induced cell senescence. A rescue study indicated that knockdown of p53 reversed the effects on cell cycle and senescence induced by Palbociclib. Moreover, we found that Palbociclib promotes P300-mediated p53 acetylation, thus increasing p53 stability and transcription activity. Moreover, Palbociclib suppressed tumor growth in vivo with increased p53 and acetylated p53 levels. In conclusion, Palbociclib induced cell senescence of HGSOC through P300-mediated p53 acetylation, suggesting that Palbociclib may have the effect of treating HGSOC.

Nuclear and cytoplasmic specific RNA binding proteome enrichment and its changes upon ferroptosis induction.

The key role of RNA-binding proteins (RBPs) in posttranscriptional regulation of gene expression is intimately tied to their subcellular localization. Here, we show a subcellular-specific RNA labeling method for efficient enrichment and deep profiling of nuclear and cytoplasmic RBPs. A total of 1221 nuclear RBPs and 1333 cytoplasmic RBPs were enriched and identified using nuclear/cytoplasm targeting enrichment probes, representing an increase of 54.4% and 85.7% compared with previous reports. The probes were further applied in the omics-level investigation of subcellular-specific RBP-RNA interactions upon ferroptosis induction. Interestingly, large-scale RBPs display enhanced interaction with RNAs in nucleus but reduced association with RNAs in cytoplasm during ferroptosis process. Furthermore, we discovered dozens of nucleoplasmic translocation candidate RBPs upon ferroptosis induction and validated representative ones by immunofluorescence imaging. The enrichment of Tricarboxylic acid cycle in the translocation candidate RBPs may provide insights for investigating their possible roles in ferroptosis induced metabolism dysregulation.

Integrative proteomics and n-glycoproteomics reveal the synergistic anti-tumor effects of aspirin- and gemcitabine-based chemotherapy on pancreatic cancer cells.

OBJECTIVE AND DESIGN: Pancreatic cancer is a highly malignant tumor that is well known for its poor prognosis. Based on glycosylation, we performed integrated quantitative N-glycoproteomics to investigate the synergistic anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells and explore the potential molecular mechanisms of chemotherapy in pancreatic cancer. METHODS AND RESULTS: Two pancreatic cancer cell lines (PANC-1 and BxPC-3) were treated with gemcitabine, aspirin, and a combination (gemcitabine + aspirin). We found that the addition of aspirin enhanced the inhibitory effect of gemcitabine on the activity of PANC-1 and BxPC-3 cells. Quantitative N-glycoproteome, proteome, phosphorylation, and transcriptome data were obtained from integrated multi-omics analysis to evaluate the anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells. Mfuzz analysis of intact N-glycopeptide profiles revealed two consistent trends associated with the addition of aspirin, which showed a strong relationship between N-glycosylation and the synergistic effect of aspirin. Further analysis demonstrated that the dynamic regulation of sialylation and high-mannose glycoforms on ECM-related proteins (LAMP1, LAMP2, ITGA3, etc.) was a significant factor for the ability of aspirin to promote the anti-tumor activity of gemcitabine and the drug resistance of pancreatic cancer cells. CONCLUSIONS: In-depth analysis of N-glycosylation-related processes and pathways in pancreatic cancer cells can provide new insight for future studies regarding pancreatic cancer therapeutic targets and drug resistance mechanisms.

Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients.

BACKGROUND: Microvascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction. METHODS: We conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57). RESULTS: Urinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell-cell adhesion, and cell-cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts. CONCLUSIONS: The four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.

Discovery of highly potent and selective KRASG12C degraders by VHL-recruiting PROTACs for the treatment of tumors with KRASG12C-Mutation.

Although several covalent KRASG12C inhibitors have made great progress in the treatment of KRASG12C-mutant cancer, their clinical applications are limited by adaptive resistance, motivating novel therapeutic strategies. Through drug design and structure optimization, a series of highly potent and selective KRASG12C Proteolysis Targeting Chimeras (PROTACs) were developed by incorporating AMG510 and VHL ligand VH032. Among them, degrader YN14 significantly inhibited KRASG12C-dependent cancer cells growth with nanomolar IC50 and DC50 values, and ＞ 95 % maximum degradation (Dmax). Molecular dynamics (MD) simulation showed that YN14 induced a stable KRASG12C: YN14: VHL ternary complex with low binding free energy (ΔG). Notably, YN14 led to tumor regression with tumor growth inhibition (TGI%) rates more than 100 % in the MIA PaCa-2 xenograft model with well-tolerated dose-schedules. We also found that KRASG12C degradation exhibited advantages in overcoming adaptive KRASG12C feedback resistance over KRASG12C inhibition. Furthermore, combination of RTKs, SHP2, or CDK9 inhibitors with YN14 exhibited synergetic efficacy in KRASG12C-mutant cancer cells. Overall, these results demonstrated that YN14 holds exciting prospects for the treatment of tumors with KRASG12C-mutation and boosted efficacy could be achieved for greater clinical applications via drug combination.

Absolute Quantification of Dynamic Cellular Uptake of Small Extracellular Vesicles via Lanthanide Element Labeling and ICP-MS.

Small extracellular vesicles (sEVs) are increasingly reported to play important roles in numerous physiological and pathological processes. Cellular uptake of sEVs is of great significance for functional regulation in recipient cells. Although various sEV quantification, labeling, and tracking methods have been reported, it is still highly challenging to quantify the absolute amount of cellular uptake of sEVs and correlate this information with phenotypic variations in the recipient cell. Therefore, we developed a novel strategy using lanthanide element labeling and inductively coupled plasma-mass spectrometry (ICP-MS) for the absolute and sensitive quantification of sEVs. This strategy utilizes the chelation interaction between Eu3+ and the phosphate groups on the sEV membrane for specific labeling. sEVs internalized by cells can then be quantified by ICP-MS using a previously established linear relationship between the europium content and the particle numbers. High Eu labeling efficiency and stability were demonstrated by various evaluations, and no structural or functional alterations in the sEVs were discovered after Eu labeling. Application of this method revealed that 4020 ± 171 sEV particles/cell were internalized by HeLa cells at 37 °C and 61% uptake inhibition at 4 °C. Further investigation led to the quantitative differential analysis of sEV cellular uptake under the treatment of several chemical endocytosis inhibitors. A 23% strong inhibition indicated that HeLa cells uptake sEVs mainly through the macropinocytosis pathway. This facile labeling and absolute quantification strategy of sEVs with ppb-level high sensitivity is expected to become a potential tool for studying the functions of sEVs in intracellular communication and cargo transportation.

Differential analysis of core-fucosylated glycoproteomics enabled by single-step truncation of N-glycans.

Alpha-1,6 fucosylation of N-glycans (core fucosylation, CF) represents a unique form of N-glycans and is widely involved in disease progression. In order to accurately identify CF glycoproteins, several approaches have been developed based on sequential cleavage with different glycosidases to truncate the N-glycans. Since multi-step sample treatments may introduce quantitation bias and affect the practicality of these approaches in large-scale applications. Here, we systematically evaluated the performance of the single-step treatment of intact glycopeptides by endoglycosidase F3 for CF glycoproteome. The single-step truncation (SST) strategy demonstrated higher quantitative stability and higher efficiency compared with previous approaches. The strategy was further practiced on both cell lines and serum samples. The dysregulation of CF glycopeptides between preoperative and postoperative serum from patients with pancreatic ductal adenocarcinoma was revealed, and the CF modifications of BCHE_N369, CDH5_N112 and SERPIND1_N49 were found to be potential prognostic markers. This study thus provides an efficient solution for large-scale quantitative analysis of the CF glycoproteome.

FASFLNet: feature adaptive selection and fusion lightweight network for RGB-D indoor scene parsing.

RGB-D indoor scene parsing is a challenging task in computer vision. Conventional scene-parsing approaches based on manual feature extraction have proved inadequate in this area because indoor scenes are both unordered and complex. This study proposes a feature adaptive selection, and fusion lightweight network (FASFLNet) for RGB-D indoor scene parsing that is both efficient and accurate. The proposed FASFLNet utilizes a lightweight classification network (MobileNetV2), constituting the backbone of the feature extraction. This lightweight backbone model guarantees that FASFLNet is not only highly efficient but also provides good performance in terms of feature extraction. The additional information provided by depth images (specifically, spatial information such as the shape and scale of objects) is used in FASFLNet as supplemental information for feature-level adaptive fusion between the RGB and depth streams. Furthermore, during decoding, the features of different layers are fused from top-bottom and integrated at different layers for final pixel-level classification, resulting in an effect similar to that of pyramid supervision. Experimental results obtained on the NYU V2 and SUN RGB-D datasets indicate that the proposed FASFLNet outperforms existing state-of-the-art models and is both highly efficient and accurate.

Proteomic overview of hepatocellular carcinoma cell lines and generation of the spectral library.

Cell lines are extensively used tools, therefore a comprehensive proteomic overview of hepatocellular carcinoma (HCC) cell lines and an extensive spectral library for data independent acquisition (DIA) quantification are necessary. Here, we present the proteome of nine commonly used HCC cell lines covering 9,208 protein groups, and the HCC spectral library containing 253,921 precursors, 168,811 peptides and 10,098 protein groups. The proteomic overview reveals the heterogeneity between different cell lines, and the similarity in proliferation and metastasis characteristics and drug targets-expression with tumour tissues. The HCC spectral library generating consumed 108 hours' runtime for data dependent acquisition (DDA) of 48 runs, 24 hours' runtime for database searching by MaxQuant version 2.0.3.0, and 1 hour' runtime for processing by SpectronautTM version 15.2. The HCC spectral library supports quantification of 7,637 protein groups of triples 2-hour DIA analysis of HepG2 and discovering biological alteration. This study provides valuable resources for HCC cell lines and efficient DIA quantification on LC-Orbitrap platform, further help to explore the molecular mechanism and candidate therapeutic targets.

A Cytological Atlas of the Human Liver Proteome from PROTEOMESKY-LIVERHu 2.0, a Publicly Available Database.

The liver plays a unique role as a metabolic center of the body, and also performs other important functions such as detoxification and immune response. Here, we establish a cell type-resolved healthy human liver proteome including hepatocytes (HCs), hepatic stellate cells (HSCs), Kupffer cells (KCs), and liver sinusoidal endothelial cells (LSECs) by high-resolution mass spectrometry. Overall, we quantify total 8354 proteins for four cell types and over 6000 proteins for each cell type. Analysis of this data set and regulatory pathway reveals the cellular labor division in the human liver follows the pattern that parenchymal cells make the main components of pathways, but nonparenchymal cells trigger these pathways. Human liver cells show some novel molecular features: HCs maintain KCs and LSECs homeostasis by producing cholesterol and ketone bodies; HSCs participate in xenobiotics metabolism as an agent deliverer; KCs and LSECs mediate immune response through MHC class II-TLRs and MHC class I-TGFß cascade, respectively; and KCs play a central role in diurnal rhythms regulation through sensing diurnal IGF and temperature flux. Together, this work expands our understandings of liver physiology and provides a useful resource for future analyses of normal and diseased livers.

Strategy for Microscale Extraction and Proteome Profiling of Peripheral Blood Mononuclear Cells.

Peripheral blood mononuclear cells (PBMCs) play vital roles in physiological and pathological processes and represent a rich source for disease monitoring. Typical molecular profiling on PBMCs involves the sorting of cell subsets and thus requires a large volume of peripheral blood (PB), which impedes the clinical practicability of omics tools in PBMC measurements. It would be clinically invaluable to develop a convenient approach for preparing PBMCs from small volumes of PB and for deep proteome profiling of PBMCs. To this end, here, we designed an apparatus (PBMC-mCap) for microscale enrichment and proteome analysis of PBMCs, which pushed the needed PB volume from the normal 2 mL or higher to 100 µL or lower, comparable to the volume of a drop of finger blood. A PBMC-specific mass spectra library containing 8869 proteins and 121,956 peptides was further built, which, in combination with the optimized data-independent acquisition strategy, helped to identify 6000 and 6500 proteins from PBMCs with 100 µL and 1 mL of PB as initial materials, respectively. Further application of the strategy for PBMC proteomes revealed a steady difference between gender (male vs female) and upon stimulus (COVID-19 vaccination). For the latter, we observed differentially expressed genes and pathways involving the activation of immune cells, including the NF-κB pathway, inflammation response, and antiviral response. Our strategy for the proteome analysis of microscale PBMCs may provide a convenient clinical toolkit for disease diagnosis and healthy state monitoring.

Pancreatic cancer cells spectral library by DIA-MS and the phenotype analysis of gemcitabine sensitivity.

Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteome strategies are increasingly used for detecting and validating protein biomarkers and therapeutic targets. Here, based on an in-depth proteome analysis of seven pancreatic cancer cell lines, we built a pancreas-specific mass spectrum library containing 10633 protein groups and 184551 peptides. The proteome difference among the seven pancreatic cancer cells was significant, especially for the divergent expression of proteins related to epithelial-mesenchymal transition (EMT). The spectra library was applied to explore the proteome difference of PANC-1 and BxPC-3 cells upon gemcitabine (GEM) treatment, and potential GEM targets were identified. The cytotoxicity test and GEM target analysis found that HPAC, CFPAC-1, and BxPC-3 were sensitive to GEM treatment, whereas PANC-1 and AsPC-1 were resistant. Finally, we found EMT was significant for CFPAC-1, AsPC-1, and PANC-1 cells, whereas BxPC-3 and HPAC cells showed more typical epithelial features. This library provides a valuable resource for in-depth proteomic analysis on pancreatic cancer cell lines, meeting the urgent demands for cell line-dependent protein differences and targeted drug analysis.

Global characterization of modifications to the charge isomers of IgG antibody.

Posttranslational modifications of antibody products affect their stability, charge distribution, and drug activity and are thus a critical quality attribute. The comprehensive mapping of antibody modifications and different charge isomers (CIs) is of utmost importance, but is challenging. We intended to quantitatively characterize the posttranslational modification status of CIs of antibody drugs and explore the impact of posttranslational modifications on charge heterogeneity. The CIs of antibodies were fractionated by strong cation exchange chromatography and verified by capillary isoelectric focusing-whole column imaging detection, followed by stepwise structural characterization at three levels. First, the differences between CIs were explored at the intact protein level using a top-down mass spectrometry approach; this showed differences in glycoforms and deamidation status. Second, at the peptide level, common modifications of oxidation, deamidation, and glycosylation were identified. Peptide mapping showed nonuniform deamidation and glycoform distribution among CIs. In total, 10 N-glycoforms were detected by peptide mapping. Finally, an in-depth analysis of glycan variants of CIs was performed through the detection of enriched glycopeptides. Qualitative and quantitative analyses demonstrated the dynamics of 24 N-glycoforms. The results revealed that sialic acid modification is a critical factor accounting for charge heterogeneity, which is otherwise missed in peptide mapping and intact molecular weight analyses. This study demonstrated the importance of the comprehensive analyses of antibody CIs and provides a reference method for the quality control of biopharmaceutical analysis.

YTHDF2 Inhibits the Migration and Invasion of Lung Adenocarcinoma by Negatively Regulating the FAM83D-TGFß1-SMAD2/3 Pathway.

OBJECTIVE: YTH domain family 2 (YTHDF2) is an important N6-methyladenosine (m6A) reader, but its role in lung adenocarcinoma remains elusive. This study assessed its function in lung adenocarcinoma. METHODS: YTHDF2 expression in lung adenocarcinoma was explored using public databases, such as The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumour Analysis Consortium (CPTAC). The effect of YTHDF2 on a lung adenocarcinoma cell line was explored by performing cytological and molecular experiments. Molecules downstream of YTHDF2 were identified using proteomics, and the related pathways were verified through cytological and molecular biology experiments. RESULTS: YTHDF2 expression was upregulated in lung adenocarcinoma, and patients with high YTHDF2 expression experienced prolonged overall survival. In two lung cancer cell lines, YTHDF2 knockdown inhibited proliferation but promoted migration, invasion, and the epithelial-mesenchymal transition. The proteomic analysis identified 142 molecules downstream of YTHDF2, and 11 were closely related to survival. Further experiments revealed that YTHDF2 inhibited expression of the family with sequence similarity 83D (FAM83D)-TGFß1-SMAD2/3 pathway components. This study is the first to show that YTHDF2 regulated the downstream TGFß1-SMAD2/3 pathway through FAM83D in lung adenocarcinoma. CONCLUSION: YTHDF2 inhibits the migration and invasion of lung adenocarcinoma cells by regulating the FAM83D-TGFß1-pSMAD2/3 pathway, which may play an important role in lung cancer metastasis.

Integrated Strategy for Unbiased Profiling of the Histidine Phosphoproteome.

Histidine phosphorylation (pHis), which plays a key role in signal transduction in bacteria and lower eukaryotes, has been shown to be involved in tumorigenesis. Due to its chemical instability, substoichiometric properties, and lack of specific enrichment reagents, there is a lack of approaches for specific and unbiased enrichment of pHis-proteins/peptides. In this study, an integrated strategy was established and evaluated as an unbiased tool for exploring the histidine phosphoproteome. First, taking advantage of the lower charge states of pHis-peptides versus the non-modified naked peptides at weak acid solution (∼pH 2.7), strong cation exchange (SCX) chromatography was used to differentiate modified and non-modified naked peptides. Furthermore, selective enrichment of the pHis-peptide was performed by applying Cu-IDA beads enrichment. Finally, stable isotope dimethyl labeling was introduced to guarantee high-confidence assignment of pHis-peptides. Using this integrated strategy, 563 different pHis-peptides (H = 1) in 385 proteins were identified from HeLa lysates. Motif analysis revealed that pHis prefers hydrophobic amino acids and has the consensus motif-HxxK, which covered the reports from different approaches. Thus, our method may provide an unbiased and effective tool to reveal histidine phosphoproteome and to study the biological process and function of histidine phosphorylation.

An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells.

Single-cell-based genomics and transcriptomics analysis have revealed substantial cellular heterogeneity among seemingly identical cells. Knowledge of the cellular heterogeneity at multiomics levels is vital for a better understanding of tumor metastasis and drug resistance, stem cell differentiation, and embryonic development. However, unlike genomics and transcriptomics studies, single-cell characterization of metabolites, proteins, and post-translational modifications at the omics level remains challenging due to the lack of amplification methods and the wide diversity of these biomolecules. Therefore, new tools that are capable of investigating these unamplifiable "omes" from the same single cells are in high demand. In this work, a microwell chip was prepared and the internal surface was modified for hydrophilic interaction liquid chromatography-based tandem extraction of metabolites and proteins and subsequent protein digestion. Next, direct electrospray ionization mass spectrometry was adopted for single-cell metabolome identification, and a data-independent acquisition-mass spectrometry approach was established for simultaneous proteome profiling and phosphoproteome analysis without phosphopeptide enrichment. This integrated strategy resulted in 132 putatively annotated compounds, more than 1200 proteins, and the first large-scale phosphorylation data set from single-cell analysis. Application of this strategy in chemical perturbation studies provides a multiomics view of cellular changes, demonstrating its capability for more comprehensive investigation of cellular heterogeneity.

[Large-scale enrichment and identification of human urinary N-glycoproteins/N-glycopeptides].

N-Glycosylation of proteins, an important post-translational modification in eukaryotic cells, plays an essential role in the regulation of cell adhesion, migration, signal transduction, and apoptosis. Abnormal changes in protein glycosylation are closely related to the occurrence of many critical diseases, including diabetes, tumors, and neurological, kidney, and inflammatory diseases. A non-invasive type of liquid biopsy, urine sampling has the advantage of reducing the complexity of proteomic analysis. This facilitates the design of large-scale and continuous or multi-time point sampling strategies. However, the dynamic range of urinary protein abundance is relatively large, owing to individual differences and physiological conditions. Currently, there is a lack of specialized research on individual differences, physiological fluctuations, and physiological abundance ranges of urinary N-glycoproteins in large healthy populations. Therefore, it is difficult to accurately distinguish individual differences and normal physiological fluctuations from changes caused by disease; this poses a great challenge in disease marker research. Liquid chromatography-mass spectrometry (LC-MS) is an analytical technique widely used for the large-scale profiling of proteomes in biological systems, and the enrichment of N-glycopeptides is a prerequisite for their detection by MS.In this study, we established an approach based on hydrophilic interaction chromatography (HILIC) by optimizing the activation, cleaning, and elution processes of the enrichment method, for instance through the optimization of particle size and solvent composition, and investigated the identification number, selectivity, and stability of N-glycoprotein/N-glycopeptide enrichment under different experimental conditions. We found that N-glycoproteins and N-glycopeptides were highly enriched in a trifluoroacetic acid system with 5-µm filling particles in the HILIC column. On this basis, we analyzed the levels of N-glycoproteins/N-glycopeptides in urine samples. The consistency of N-glycoprotein/N-glycopeptide levels in urine samples taken from the same healthy person for five consecutive days was investigated by correlation analysis. This analysis revealed that the urinary N-glycoproteome of the same healthy person was relatively stable over a short period of time. Next, urinary samples from 20 healthy male volunteers and 20 healthy female volunteers were enriched for N-glycoproteins/N-glycopeptides, which were profiled by MS through qualitative and quantitative analyses. Screening and functional analysis of differential proteins were then carried out. A total of 1016 N-glycoproteins and 2192 N-glycopeptides were identified in the mid-morning urine samples of the 40 healthy volunteers. A label-free quantitation strategy was used to investigate the fluctuation range of the physiologically abundant urinary N-glycopeptides. The abundance of urinary N-glycopeptides spanned across approximately five orders of magnitude. Subsequently, gender differences in the N-glycosylation levels of urinary proteins were also explored in healthy people. Functional analysis of the N-glycoproteins that exhibited gender differences in abundance was performed. Based on multivariate statistical analysis, 206 differentially expressed proteins (p<0.05, fold change (FC)> 4) were identified. In females, we found 175 significantly down-regulated N-glycoproteins and 31 significantly up-regulated N-glycoproteins with respect to males. The expression levels of N-glycopeptides between the two groups suggested a clear gender difference. To investigate the biological processes and functions of these proteins, gene ontology (GO) analysis was performed on the N-glycoproteins/N-glycopeptides differentially expressed between males and females. Metabolic pathway analysis was also carried out based on the kyoto encyclopedia of genes and genomes (KEGG). Differentially expressed N-glycoproteins were mostly associated with platelet degranulation, extracellular region, and ossification. The top three relevant pathways were glycan biosynthesis and metabolism, metabolism of cofactors and vitamins, and lipid metabolism. Overall, sex may be an important factor for urinary N-glycoproteome differences among normal individuals and should be considered in clinical applications. This study provides relevant information regarding the function and mechanisms of the urinary glycoproteome and the screening of clinical biomarkers.