Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor. Notwithstanding tremendous efforts having been put in multi-omics research to profile the dysregulated molecular mechanisms and cellular pathways, there is still a lack of understanding about the glycoproteomic of GBM. Glycosylation as one of the most important post-translational modifications is crucial in regulating cell proliferation and relevant oncogenic pathways. In the study, we systematically profiled N-glycoproteomics of para-cancerous and cancerous tissues from GBM patients to reveal the site-specific N-glycosylation pattern defined by intact glycopeptides. We identified and quantified 1863 distinct intact glycopeptides (IGPs) with 161 N-linked glycan compositions and 326 glycosites. There were 396 IGPs from 43 glycoproteins differed between adjacent tissues and GBM. Then, proteomic and glycoproteomic data were combined, and the normalized glycosylation alteration was calculated to determine whether the difference was attributed to the global protein levels or glycosylation. The altered glycosylation triggered by site-specific N-glycans and glycoprotein abundance, as well as glycosite heterogeneity, were demonstrated. Ultimately, an examination of the overall glycosylation levels revealed a positive contribution of sialylated or/and fucosylated glycans. Overall, the dataset highlighted molecular complexity and distinct profiling at translational and post-translational levels, providing valuable information for novel therapeutic approaches and specific detection strategies.

Abstract Integrating functional proteomics and next-generation sequencing (NGS) offers a comprehensive approach to unraveling the molecular intricacies of breast cancer. This study investigates the functional interplay between genomic alterations and protein expression in Taiwanese breast cancer patients. By analyzing 61 breast cancer samples using tandem mass tag (TMT) labeling and mass spectrometry, coupled with whole-exome sequencing (WES) or targeted sequencing, we identified key genetic mutations and their impact on protein expression. Notably, pathogenic variants in BRCA1, BRCA2, PTEN, and PIK3CA were found to be clinically relevant, potentially guiding targeted therapy decisions. Additionally, we discovered trans correlations between specific gene alterations (FANCA, HRAS, PIK3CA, MAP2K1, JAK2) and the expression of 22 proteins, suggesting potential molecular mechanisms underlying breast cancer development and progression. These findings highlight the power of integrating proteomics and NGS to identify potential therapeutic targets and enhance personalized medicine strategies for Taiwanese breast cancer patients.

The standard “7 + 3” induction results in 30% of de novo acute myeloid leukemia (AML) patients not achieving complete remission (CR). We aimed to utilize the Olink® platform to compare the bone marrow plasma proteomic profiles of newly diagnosed de novo AML patients who did and did not achieve CR following “7 + 3” induction treatment. This prospective study included 43 untreated AML patients, stratified into CR (n = 29) and non-CR (n = 14) groups based on their response to “7 + 3” induction therapy. We employed the Olink® Explore-384 Inflammation platform for proteomic analysis to investigate differences in bone marrow plasma protein levels between the CR and non-CR groups. Proteomic analysis demonstrated that the CR group exhibited significantly higher bone marrow plasma levels of ARTN and CCL23 than did the non-CR group. Immunohistochemical staining confirmed a higher proportion of tissue samples with intense staining for ARTN (25.40% vs. 7.05%, p = 0.013) and CCL23 (24.14% vs. 14.29%, p = 0.039) in the CR group. These findings were corroborated by bulk-RNA-seq, which indicated significantly elevated mRNA expression levels of ARTN (1.93 vs. -0.09; p = 0.003) and CCL23 (1.50 vs. 0.12; p = 0.021) in the CR group. The Human Protein Atlas provided external support for our findings. The results suggest that ARTN and CCL23 may serve as biomarkers for predicting responsiveness to the “7 + 3” induction in untreated AML. Using an enzyme-linked immunosorbent assay to identify the roles of ARTN and CCL23 in predicting AML chemosensitivity may enhance clinical applicability in the future.

Pancreatic cancer is a highly aggressive tumor with a poor prognosis due to a low early detection rate and a lack of biomarkers. Most of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC). Alterations in the N-glycosylation of plasma immunoglobulin G (IgG) have been shown to be closely associated with the onset and development of several cancers and could be used as biomarkers for diagnosis. The study aimed to explore intact N-glycosylation profile of IgG in patients with PDAC and find relation between intact N-glycosylation profile of IgG and clinical information such as diagnosis and prognosis. In this study, we employed a well-evaluated approach (termed GlycoQuant) to assess the site-specific N-glycosylation profile of human plasma IgG in both healthy individuals and patients with pancreatic ductal adenocarcinoma (PDAC). The datasets generated and analyzed during the current study are available in the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) via the iProX partner repository, with the dataset identifier PXD051436. The analysis of rapidly purified IgG samples from 100 patients with different stages of PDAC, in addition to 30 healthy controls, revealed that the combination of carbohydrate antigen 19 − 9 (CA19-9), IgG1-GP05 (IgG1-TKPREEQYNSTYR-HexNAc [4]Hex [5]Fuc [1]NeuAc [1]), and IgG4-GP04 (IgG4-EEQFNSTYR- HexNAc [4]Hex [5]Fuc [1]NeuAc [1]) can be used to distinguish between PDAC patients and healthy individuals (AUC = 0.988). In addition, cross validation of the diagnosis model showed satisfactory result. The study demonstrated that the integrated quantitative method can be utilized for large-scale clinical N-glycosylation research to identify novel N-glycosylated biomarkers. This could facilitate the development of clinical glycoproteomics.

The therapeutic potential of mesenchymal stem cells (MSCs) may be partly attributed to their secretion growth factors, cytokines and chemokines. In various preclinical studies, the use of MSC-conditioned media (CM) has demonstrated promising potential for promoting vascular repair. To gain a comprehensive understanding of the variations in conditioned media derived from different sources of mesenchymal stem cells (MSCs) including umbilical cord, adipose and bone marrow, we investigated their reparative effects on human umbilical vein endothelial cells (HUVECs) subjected to damage induced by high glucose. Initially, the secreted proteins from the three types of MSCs were assessed using the bicinchoninic acid (BCA) method. Subsequently, we examined the influence of different type of MSC secreted proteins on the proliferation of HUVECs under high glucose conditions. Following this, transwell migration experiments were conducted to evaluate the impact of MSC source on the migration of HUVECs damaged by high glucose. We further compared the effects of adding secreted proteins from the three types of MSCs on the tube formation ability of HUVECs subjected to high glucose damage. Finally, tandem mass tag (TMT) labeling quantitative proteomics was performed to analyze differently expressed proteins in the secreted proteins of three type MSC by using LC–MS/MS. In this study, we observed a significantly higher secretion of proteins from umbilical cord mesenchymal stem cells (UMSCs) compared to adipose-derived stem cells (ADSCs). Subsequently, we found that the of proliferation HUVECs was significantly improved with supplementing the three MSCs secreted proteins under high glucose medium. Notably, the reparative effects of bone marrow mesenchymal stem cells (BMSCs) and UMSCs were superior to those of ADSCs. Afterwards, UMSCs exhibited the strongest ability to repair cell migration when HUVECs damaged by high glucose. Moreover, all three MSCs’ secreted proteins exhibited the ability to enhance tube formation. Importantly, the UMSCs’ secretome showed the most pronounced improvement in tube formation, as evidenced by the evaluation of parameters such as the number of nodes, the number of branches, and total length. These findings suggest that the UMSCs’ secretome plays a crucial role in biological processes such as vasculature development, cell adhesion, and tissue remodeling. Additionally, the BMSCs’ secretome was found to promote vascular development. The results collectively indicate the diverse therapeutic potential of MSC secretomes in influencing various aspects of cellular function and tissue repair. In conclusion, this study offers a valuable reference for the selection of more suitable sources of mesenchymal stem cells (MSCs) in the treatment of diabetic cardiovascular disease.

Radiation-induced lung injury (RILI) is a common adverse effect of radiation therapy that negatively affects treatment progression and the quality of life of patients. Identifying biomarkers for RILI can provide reference for the prevention and treatment of RILI in clinical practice. In this study, to explore key proteins related to RILI, we constructed a rat model of RILI and analyzed RILI tissues and normal lung tissues using tandem mass spectrometry labeling and quantitative proteomics technology. We used Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Gene Ontology (GO) enrichment and protein–protein interaction (PPI) networks for bioinformatics analysis of Differentially expressed proteins (DEPs). The results identified 185 differentially expressed proteins in lung tissue from the RILI group compared with the controls, including 110 up-regulated proteins and 75 down-regulated proteins. GO analysis showed that the differentially expressed proteins were involved oxidation-reduction process, cellular biosynthetic processes and extracellular matrix. KEGG results demonstrated that the differentially expressed proteins were mainly involved in the PI3K-Akt, ECM receptor interactions, arachidonic acid metabolism, glutathione metabolism and other pathways. These results on the functions and signaling pathways of the differentially expressed proteins provide a theoretical basis for further study of the mechanism of RILI.

Tuberculosis (TB) diagnostic monitoring is paramount to clinical decision-making and the host biomarkers appears to play a significant role. The currently available diagnostic technology for TB detection is inadequate. In the present study, we aimed to identify biomarkers for diagnosis of pulmonary tuberculosis (PTB) using urinary metabolomic and proteomic analysis. Methods: In the study, urine from 40 PTB, 40 lung cancer (LCA), 40 community-acquired pneumonia (CAP) patients and 40 healthy controls (HC) was collected. Biomarker panels were selected based on random forest (RF) analysis. Results: A total of 3,868 proteins and 1,272 annotated metabolic features were detected using pairwise comparisons. Using AUC ≥ 0.80 as a cutoff value, we picked up five protein biomarkers for PTB diagnosis. The five-protein panel yielded an AUC for PTB/HC, PTB/CAP and PTB/LCA of 0.9840, 0.9680 and 0.9310, respectively. Additionally, five metabolism biomarkers were selected for differential diagnosis purpose. By employment of the five-metabolism panel, we could differentiate PTB/HC at an AUC of 0.9940, PTB/CAP of 0.8920, and PTB/LCA of 0.8570. Conclusion: Our data demonstrate that metabolomic and proteomic analysis can identify a novel urine biomarker panel to diagnose PTB with high sensitivity and specificity. The receiver operating characteristic curve analysis showed that it is possible to perform non-invasive clinical diagnoses of PTB through these urine biomarkers.

Abstract Background The effect of varying brain ventricular volume on the cerebrospinal fluid (CSF) proteome has been discussed as possible confounding factors in comparative protein level analyses. However, the relationship between CSF volume and protein levels remains largely unexplored. Moreover, the few existing studies provide conflicting findings, indicating the need for further research. Methods Here, we explored the association between levels of 88 pre-selected CSF proteins and ventricular volume derived from magnetic resonance imaging (MRI) measurements in 157 cognitively healthy 70-year-olds from the H70 Gothenburg Birth Cohort Studies, including individuals with and without pathological levels of Alzheimer’s disease (AD) CSF markers (n = 123 and 34, respectively). Both left and right lateral, the inferior horn as well as the third and the fourth ventricular volumes were measured. Different antibody-based methods were employed for the protein measurements, with most being analyzed using a multiplex bead-based microarray technology. Furthermore, the associations between the protein levels and cortical thickness, fractional anisotropy, and mean diffusivity were assessed. Results CSF levels of many brain-derived proteins correlated with ventricular volumes in A-T- individuals, with lower levels in individuals with larger ventricles. The strongest negative correlations with total ventricular volume were observed for neurocan (NCAN) and neurosecretory protein VGF (rho = -0.34 for both). Significant negative correlations were observed also for amyloid beta (Ab) 38, Ab40, total tau (t-tau), and phosphorylated tau (p-tau), with correlation ranging between − 0.34 and − 0.28, while no association was observed between ventricular volumes and Ab42 or neurofilament light chain (NfL). Proteins with negative correlations to ventricular volumes further demonstrated negative correlations to mean diffusivity and positive correlation to fractional anisotropy. However, only weak or no correlations were observed between the CSF protein levels and cortical thickness. A + T + individuals demonstrated higher CSF protein levels compared to A-T- individuals with the most significant differences observed for neurogranin (NRGN) and synuclein beta (SNCB). Conclusions Our findings suggest that the levels of many brain-derived proteins in CSF may be subjected to dilution effects depending on the size of the brain ventricles in healthy individuals without AD pathology. This phenomenon could potentially contribute to the inter-individual variations observed in CSF proteomic studies.

Alternative N-glycosylation of serum proteins has been observed in colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC) and gastric cancer (GC), while comparative study among those three cancers has not been reported before. We aimed to identify serum N-glycans signatures and introduce a discriminative model across the gastrointestinal cancers. The study population was initially screened according to the exclusion criteria process. Serum N-glycans profiling was characterized by a high-throughput assay based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Diagnostic model was built by random forest, and unsupervised machine learning was performed to illustrate the differentiation between the three major gastrointestinal (GI) cancers. We have found that three major gastrointestinal cancers strongly associated with significantly decreased mannosylation and mono-galactosylation, as well as increased sialylation of serum glycoproteins. A highly accurate discriminative power (> 0.90) for those gastrointestinal cancers was obtained with serum N-glycome based predictive model. Additionally, serum N-glycome profile exhibited distinct distributions across GI cancers, and several altered N-glycans were hyper-regulated in each specific disease. Serum N-glycome profile was differentially expressed in three major gastrointestinal cancers, providing a new clinical tool for cancer diagnosis and throwing a light upon the disease-specific molecular signatures.

Mucosal healing is the therapeutic target for ulcerative colitis (UC). While amino acids (AAs) and the gut microbiota are known to be involved in the pathogenesis of UC, their specific roles in mucosal healing have not been fully defined. To longitudinally assess the changes in AA concentrations and the gut microbiota composition in the context of mucosal healing in UC patients, with the aim of identifying new biomarkers with predictive value for mucosal healing in UC patients and providing a new theoretical basis for dietary therapy. A total of 15 UC patients with infliximab-induced mucosal healing were enrolled. Serum and fecal AA concentrations before and after mucosal healing were determined via targeted metabolomics. A receiver operating characteristic (ROC) curve was plotted to evaluate the value of different AAs in predicting mucosal healing in UC patients. The changes in the composition of the fecal gut microbiota were analyzed via metagenomics, and bioinformatics was used to analyze the functional genes and metabolic pathways associated with different bacterial species. Spearman correlation analyses of fecal AAs with significantly different concentrations and the differentially abundant bacterial species before and after mucosal healing were performed. 1. The fecal concentrations of alanine, aspartic acid, glutamic acid, glutamine, glycine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine and valine were significantly decreased after mucosal healing. The serum concentrations of alanine, cysteine and valine significantly increased, whereas that of aspartic acid significantly decreased. Glutamic acid, leucine, lysine, methionine and threonine could accurately predict mucosal healing in UC patients, and the area under the curve (AUC) was > 0.9. After combining the 5 amino acids, the AUC reached 0.96. 2. There were significant differences in the gut microbiota composition before and after mucosal healing in UC, characterized by an increase in the abundance of beneficial microbiota (Faecalibacterium prausnitzii and Bacteroides fragilis) and a decrease in the abundance of harmful microbiota (Enterococcus faecalis). LEfSe analysis identified 57 species that could predict mucosal healing, and the AUC was 0.7846. 3. Amino acid metabolic pathways were enriched in samples after mucosal healing, was associated with the abundance of multiple species, such as Faecalibacterium prausnitzi, Bacteroides fragilis, Bacteroides vulgatus and Alistipes putredinis. 4. The fecal concentrations of several AAs were negatively correlated with the abundance of a variety of beneficial strains, such as Bacteroides fragilis, uncultured Clostridium sp., Firmicutes bacterium CAG:103, Adlercreutzia equolifaciens, Coprococcus comes and positively correlated with the abundance of several harmful strains, such as Citrobacter freundii, Enterococcus faecalis, Klebsiella aerogenes, Salmonella enterica. Altered concentrations of amino acids and their associations with the gut microbiota are implicated in the mucosal healing of UC patients and can serve as noninvasive diagnostic biomarkers.

The gut-brain axis has garnered increasing attention, with observational studies suggesting its involvement in the disease activity and progression of inflammatory bowel disease (IBD), but the precise mechanisms remain unclear. In this study, we aimed to investigate “novel proteins” underlying IBD in the brain using a comprehensive multi-omics analysis approach. We performed integrated analyses of proteomics and transcriptomics in the human prefrontal cortex (PFC) tissue, coupled with genome-wide association studies (GWAS) of IBD, crohn’s disease (CD), and ulcerative colitis (UC). This included performing protein-wide association studies (PWAS), transcriptome-wide association studies (TWAS), Mendelian randomization (MR), and colocalization analysis to identify brain proteins associated with IBD and its subtypes. PWAS analyses identified and confirmation 9, 9, and 6 brain proteins strongly associated with IBD, CD, and UC, respectively. Subsequent MR analyses revealed that increased abundance of GPSM1, AUH, TYK2, SULT1A1, and FDPS, along with corresponding gene expression, led to decreased risk of IBD. For CD, increased abundance of FDPS, SULT1A1, and PDLIM4, along with corresponding gene expression, also decreased CD risk. Regarding UC, only increased abundance of AUH, along with corresponding gene expression, was significantly associated with decreased UC risk. Further TWAS and colocalization analyses at the transcriptome level supported strong associations of SULT1A1 and FDPS proteins with reduced risk of IBD and CD. The two “novel proteins,” SULT1A1 and FDPS, are strongly associated with IBD and CD, elucidating their causal relationship in reducing the risk of IBD and CD. This provides new clues for identifying the pathogenesis and potential therapeutic targets for IBD and CD.

The diagnosis and treatment of colorectal cancer (CRC), especially metastatic colorectal cancer (mCRC), is a major priority and research challenge. We screened for expression differences in the plasma exosomal proteomes of patients with mCRC, those with CRC, and healthy controls (HCs) to discover potential biomarkers for mCRC. Plasma samples from five patients with mCRC, five patients with CRC, and five HCs were collected and processed to isolate exosomes by ultracentrifugation. Exosomal protein concentrations were determined using the BCA kit, and liquid chromatography-mass spectrometry was utilized to identify and analyze the proteins. From the exosomes isolated from plasma samples, a total of 994 quantifiable proteins were detected, including 287 differentially expressed proteins identified by quantitative proteomics analyses. Totals of 965, 963 and 968 proteins were identified in mCRC patients, CRC patients, and HCs, respectively. The study identified 83 proteins with differential expression in the plasma exosomes of mCRC patients. The top 10 upregulated proteins in the mCRC group and CRC groups were ITGA4, GNAI1, SFTPA2, UGGT1, GRN, LBP, SMIM1, BMP1, HMGN5, and MFAP4, while the top 10 downregulated proteins were PSMB8, LCK, RAB35, PSMB4, CD81, CD63, GLIPR2, RAP1B, RAB30, and CES1. Western Blot validation data confirmed that ITGA4 and GNAI1 were unequivocally enriched in plasma-derived exosomes from mCRC patients. These differential proteins offer potential new candidate molecules for further research on the pathogenesis of mCRC and the identification of therapeutic targets. This study sheds light on the potential significance of plasma exosome proteomics studies in our understanding and treatment of mCRC.

Mycosis fungoides (MF) is the most common type of cutaneous T cell lymphoma. As the early clinical manifestations of MF are non-specific (e.g., erythema or plaques), it is often misdiagnosed as inflammatory skin conditions (e.g., atopic dermatitis, psoriasis, and pityriasis rosea), resulting in delayed treatment. As there are no effective biological markers for the early detection and management of MF, the aim of the present study was to perform a proteomic analysis of urine samples (as a non-invasive protein source) to identify reliable MF biomarkers. Thirteen patients with early-stage MF were administered a subcutaneous injection of interferon α-2a in combination with phototherapy for 6 months. The urine proteome of patients with early-stage MF before and after treatment was compared against that of healthy controls by liquid chromatography-tandem mass spectrometry. The differentially expressed proteins were subjected to Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Clusters of Orthologous Groups analyses. For validation, the levels of the selected proteins were evaluated by enzyme-linked immunosorbent assay (ELISA). We identified 41 differentially expressed proteins (11 overexpressed and 30 underexpressed) between untreated MF patients and healthy control subjects. The proteins were mainly enriched in focal adhesion, endocytosis, and the PI3K-Akt, phospholipase D, MAPK, and calcium signaling pathways. The ELISA results confirmed that the urine levels of Serpin B5, epidermal growth factor (EGF), and Ras homologous gene family member A (RhoA) of untreated MF patients were significantly lower than those of healthy controls. After 6 months of treatment, however, there was no significant difference in the urine levels of Serpin B5, EGF, and RhoA between MF patients and healthy control subjects. The area under the receiver operating characteristic curve values for Serpin B5, EGF, and RhoA were 0.817, 0.900, and 0.933, respectively. This study showed that urine proteomics represents a valuable tool for the study of MF, as well as identified potential new biomarkers (Serpin B5, EGF, and RhoA), which could be used in its diagnosis and management.

Abstract Background Estrogen receptor-positive (ER+) breast cancer accounts for two-thirds of all breast cancers, and its early and late recurrences still threaten patients’ long-term survival and quality of life. Finding candidate tumor antigens and potential therapeutic targets is critical to addressing these unmet needs. Method The isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to identify the differentially expressed proteins (DEPs) between ER + breast cancer and corresponding adjacent normal tissue. Candidate DEPs were screened by bioinformatic analyses, and their expression was confirmed by immunohistochemical (IHC) staining and western blot. A series of in vitro experiments, including wound healing assay, colony formation, and cell cycle assay, were performed to reveal the functions of selected DEPs. Additionally, their clinical significances were further analyzed. Result A total of 369 DEPs (fold change ≥ 2.0 or ≤ 0.66, P < 0.05) were discovered. Compared with normal tissue, 358 proteins were up-regulated and 11 proteins were down-regulated in ER + breast cancer. GO and KEGG enrichment analysis showed that DEPs were closely associated with RNA regulation and metabolic pathways. STRING analysis found ESF1 and MIPEP were the hub genes in breast cancer, whose increased expressions were verified by the IHC staining and western blot. Knocking down ESF1 and MIPEP inhibited colony formation and increased cell apoptosis. Besides, knocking down ESF1 inhibited wound healing but not MIPEP. In addition, ESF1 and MIPEP expression were negatively associated with patient prognosis. Conclusion The upregulation of ESF1 and MIPEP promoted ER + breast cancer proliferation, which might provide novel targets for the development of new therapies.

Abstract Purpose The primary objective of this investigation is to systematically screen and identify differentially expressed proteins (DEPs) within the plasma of individuals afflicted with sepsis. This endeavor employs both Data-Independent Acquisition (DIA) and enzyme-linked immunosorbent assay (ELISA) methodologies. The overarching goal is to furnish accessible and precise serum biomarkers conducive to the diagnostic discernment of sepsis. Method The study encompasses 53 sepsis patients admitted to the Affiliated Hospital of Southwest Medical University between January 2019 and December 2020, alongside a control cohort consisting of 16 individuals devoid of sepsis pathology. Subsequently, a subset comprising 10 randomly selected subjects from the control group and 22 from the sepsis group undergoes quantitative proteomic analysis via DIA. The acquired data undergoes Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses, facilitating the construction of a Protein-Protein Interaction (PPI) network to discern potential markers. Validation of core proteins is then accomplished through ELISA. Comparative analysis between the normal and sepsis groups ensues, characterized by Receiver Operating Characteristic (ROC) curve construction to evaluate diagnostic efficacy. Result A total of 187 DEPs were identified through bioinformatic methodologies. Examination reveals their predominant involvement in biological processes such as wound healing, coagulation, and blood coagulation. Functional pathway analysis further elucidates their engagement in the complement pathway and malaria. Resistin emerges as a candidate plasma biomarker, subsequently validated through ELISA. Notably, the protein exhibits significantly elevated levels in the serum of sepsis patients compared to the normal control group. ROC curve analysis underscores the robust diagnostic capacity of these biomarkers for sepsis. Conclusion Data-Independent Acquisition (DIA) and Enzyme-Linked Immunosorbent Assay (ELISA) show increased Resistin levels in sepsis patients, suggesting diagnostic potential, warranting further research.

Abstract Background Tumorigenesis and progression of prostate cancer (PCa) are indispensably dependent on androgen receptor (AR). Antiandrogen treatment is the principal preference for patients with advanced PCa. However, the molecular characteristics of PCa with antiandrogen intervention have not yet been fully uncovered. Methods We first performed proteome analysis with 32 PCa tumor samples and 10 adjacent tissues using data-independent acquisition (DIA)- parallel accumulation serial fragmentation (PASEF) proteomics. Then label-free quantification (LFQ) mass spectrometry was employed to analyze protein profiles in LNCaP and PC3 cells. Results M-type creatine kinase CKM and cartilage oligomeric matrix protein COMP were demonstrated to have the potential to be diagnostic biomarkers for PCa at both mRNA and protein levels. Several E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) were significantly altered in PCa and PCa cells under enzalutamide treatment, and these proteins might reprogram proteostasis at protein levels in PCa. Finally, we discovered 127 significantly varied proteins in PCa samples with antiandrogen therapy and further uncovered 4 proteins in LNCaP cells upon enzalutamide treatment. Conclusions Our research reveals new potential diagnostic biomarkers for prostate cancer and might help resensitize resistance to antiandrogen therapy.

Abstract 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.

Abstract Background Currently, no effective measures are available to predict the curative efficacy of small-cell lung cancer (SCLC) chemotherapy. We expect to develop a method for effectively predicting the SCLC chemotherapy efficacy and prognosis in clinical practice in order to offer more pertinent therapeutic protocols for individual patients. Methods We adopted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinPro Tools system to detect serum samples from 154 SCLC patients with different curative efficacy of standard chemotherapy and analyze the different peptides/proteins of SCLC patients to discover predictive tumor markers related to chemotherapy efficacy. Ten peptide/protein peaks were significantly different in the two groups. Results A genetic algorithm model consisting of four peptides/proteins was developed from the training group to separate patients with different chemotherapy efficacies. Among them, three peptides/proteins (m/z 3323.35, 6649.03 and 6451.08) showed high expression in the disease progression group, whereas the peptide/protein at m/z 4283.18 was highly expressed in the disease response group. The classifier exhibited an accuracy of 91.4% (53/58) in the validation group. The survival analysis showed that the median progression-free survival (PFS) of 30 SCLC patients in disease response group was 9.0 months; in 28 cases in disease progression group, the median PFS was 3.0 months, a statistically significant difference (χ2 = 46.98, P < 0.001). The median overall survival (OS) of the two groups was 13.0 months and 7.0 months, a statistically significant difference (χ2 = 40.64, P < 0.001). Conclusions These peptides/proteins may be used as potential biological markers for prediction of the curative efficacy and prognosis for SCLC patients treated with standard regimen chemotherapy.

Abstract Background To comprehend the complexities of pathophysiological mechanisms and molecular events that contribute to proliferative diabetic retinopathy (PDR) and evaluate the diagnostic value of aqueous humor (AH) in monitoring the onset of PDR. Methods A cohort containing 16 PDR and 10 cataract patients and another validation cohort containing 8 PDR and 4 cataract patients were studied. AH was collected and subjected to proteomics analyses. Bioinformatics analysis and a machine learning-based pipeline called inference of biomolecular combinations with minimal bias were used to explore the functional relevance, hub proteins, and biomarkers. Results Deep profiling of AH proteomes revealed several insights. First, the combination of SIAE, SEMA7A, GNS, and IGKV3D-15 and the combination of ATP6AP1, SPARCL1, and SERPINA7 could serve as surrogate protein biomarkers for monitoring PDR progression. Second, ALB, FN1, ACTB, SERPINA1, C3, and VTN acted as hub proteins in the profiling of AH proteomes. SERPINA1 was the protein with the highest correlation coefficient not only for BCVA but also for the duration of diabetes. Third, “Complement and coagulation cascades” was an important pathway for PDR development. Conclusions AH proteomics provides stable and accurate biomarkers for early warning and diagnosis of PDR. This study provides a deep understanding of the molecular mechanisms of PDR and a rich resource for optimizing PDR management.

Abstract Background Cardio-metabolic disorders (CMDs) are common in aging people and are pivotal risk factors for cardiovascular diseases (CVDs). Inflammation is involved in the pathogenesis of CVDs and aging, but the underlying inflammatory molecular phenotypes in CMDs and aging are still unknown. Method We utilized multiple proteomics to detect 368 inflammatory proteins in the plasma of 30 subjects, including healthy young individuals, healthy elderly individuals, and elderly individuals with CMDs, by Proximity Extension Assay technology (PEA, O-link). Protein-protein interaction (PPI) network and functional modules were constructed to explore hub proteins in differentially expressed proteins (DEPs). The correlation between proteins and clinical traits of CMDs was analyzed and diagnostic value for CMDs of proteins was evaluated by ROC curve analysis. Result Our results revealed that there were 161 DEPs (adjusted p < 0.05) in normal aging and EGF was the most differentially expressed hub protein in normal aging. Twenty-eight DEPs were found in elderly individuals with CMDs and MMP1 was the most differentially expressed hub protein in CMDs. After the intersection of DEPs in aging and CMDs, there were 10 overlapping proteins: SHMT1, MVK, EGLN1, SLC39A5, NCF2, CXCL6, IRAK4, REG4, PTPN6, and PRDX5. These proteins were significantly correlated with the level of HDL-C, TG, or FPG in plasma. They were verified to have good diagnostic value for CMDs in aging with an AUC > 0.7. Among these, EGLN1, NCF2, REG4, and SLC39A2 were prominently increased both in normal aging and aging with CMDs. Conclusion Our results could reveal molecular markers for normal aging and CMDs, which need to be further expanded the sample size and to be further investigated to predict their significance for CVDs.

Abstract Background Adamantinomatous craniopharyngiomas (ACPs) are rare benign epithelial tumours with high recurrence and poor prognosis. Biological differences between recurrent and primary ACPs that may be associated with disease recurrence and treatment have yet to be evaluated at the proteomic level. In this study, we aimed to determine the proteomic profiles of paired recurrent and primary ACP, gain biological insight into ACP recurrence, and identify potential targets for ACP treatment. Method Patients with ACP (n = 15) or Rathke’s cleft cyst (RCC; n = 7) who underwent surgery at Sanbo Brain Hospital, Capital Medical University, Beijing, China and received pathological confirmation of ACP or RCC were enrolled in this study. We conducted a proteomic analysis to investigate the characteristics of primary ACP, paired recurrent ACP, and RCC. Western blotting was used to validate our proteomic results and assess the expression of key tumour-associated proteins in recurrent and primary ACPs. Flow cytometry was performed to evaluate the exhaustion of tumour-infiltrating lymphocytes (TILs) in primary and recurrent ACP tissue samples. Immunohistochemical staining for CD3 and PD-L1 was conducted to determine differences in T-cell infiltration and the expression of immunosuppressive molecules between paired primary and recurrent ACP samples. Results The bioinformatics analysis showed that proteins differentially expressed between recurrent and primary ACPs were significantly associated with extracellular matrix organisation and interleukin signalling. Cathepsin K, which was upregulated in recurrent ACP compared with that in primary ACP, may play a role in ACP recurrence. High infiltration of T cells and exhaustion of TILs were revealed by the flow cytometry analysis of ACP. Conclusions This study provides a preliminary description of the proteomic differences between primary ACP, recurrent ACP, and RCC. Our findings serve as a resource for craniopharyngioma researchers and may ultimately expand existing knowledge of recurrent ACP and benefit clinical practice.

Abstract Background Colorectal Cancer (CRC) is a prevalent form of cancer, and the effectiveness of the main postoperative chemotherapy treatment, FOLFOX, varies among patients. In this study, we aimed to identify potential biomarkers for predicting the prognosis of CRC patients treated with FOLFOX through plasma proteomic characterization. Methods Using a fully integrated sample preparation technology SISPROT-based proteomics workflow, we achieved deep proteome coverage and trained a machine learning model from a discovery cohort of 90 CRC patients to differentiate FOLFOX-sensitive and FOLFOX-resistant patients. The model was then validated by targeted proteomics on an independent test cohort of 26 patients. Results We achieved deep proteome coverage of 831 protein groups in total and 536 protein groups in average for non-depleted plasma from CRC patients by using a Orbitrap Exploris 240 with moderate sensitivity. Our results revealed distinct molecular changes in FOLFOX-sensitive and FOLFOX-resistant patients. We confidently identified known prognostic biomarkers for colorectal cancer, such as S100A4, LGALS1, and FABP5. The classifier based on the biomarker panel demonstrated a promised AUC value of 0.908 with 93% accuracy. Additionally, we established a protein panel to predict FOLFOX effectiveness, and several proteins within the panel were validated using targeted proteomic methods. Conclusions Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC.

Abstract Background Cardiac rupture (CR) is a rare but catastrophic mechanical complication of acute myocardial infarction (AMI) that seriously threatens human health. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of CR has yet to be elucidated. Methods In the present study, a quantitative approach with tandem mass tag (TMT) labeling and liquid chromatography–tandem mass spectrometry was used to characterize the differential protein expression profiles of patients with CR. Plasma samples were collected from patients with CR (n = 37), patients with AMI (n = 47), and healthy controls (n = 47). Candidate proteins were selected for validation by multiple reaction monitoring (MRM) and enzyme-linked immunosorbent assay (ELISA). Results In total, 1208 proteins were quantified and 958 differentially expressed proteins (DEPs) were identified. The difference in the expression levels of the DEPs was more noticeable between the CR and Con groups than between the AMI and Con groups. Bioinformatics analysis showed most of the DEPs to be involved in numerous crucial biological processes and signaling pathways, such as RNA transport, ribosome, proteasome, and protein processing in the endoplasmic reticulum, as well as necroptosis and leukocyte transendothelial migration, which might play essential roles in the complex pathological processes associated with CR. MRM analysis confirmed the accuracy of the proteomic analysis results. Four proteins i.e., C-reactive protein (CRP), heat shock protein beta-1 (HSPB1), vinculin (VINC) and growth/differentiation factor 15 (GDF15), were further validated via ELISA. By receiver operating characteristic (ROC) analysis, combinations of these four proteins distinguished CR patients from AMI patients with a high area under the curve (AUC) value (0.895, 95% CI, 0.802–0.988, p < 0.001). Conclusions Our study highlights the value of comprehensive proteomic characterization for identifying plasma proteome changes in patients with CR. This pilot study could serve as a valid foundation and initiation point for elucidation of the mechanisms of CR, which might aid in identifying effective diagnostic biomarkers in the future.