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Colorectal cancers (CRCs) are characterized by diffuse infiltration of tumor cells into the regional lymph nodes and metastasis to distant organs, and its highly invasive nature contributes to disease recurrence and poor outcomes. The molecular mechanisms underlying CRC cell invasion remain incompletely understood. Here, we identified the upregulation of DNA damage repair-related protein RAD23B in CRC cells and tissues and showed that it associates with coronin 1C or coronin 3 (CORO1C) to facilitate invasion. We found that knockdown of RAD23B expression significantly inhibited the proliferation, invasion, and migration abilities of CRC cells both in vitro and in vivo, and suppressed the talin1/2/integrin/FAK/RhoA/Rac1/CORO1C signaling pathways. Interestingly, RAD23B interacted and co-localized with CORO1C, and CORO1C aggregated toward the margin of cancer cells in both CRC cells and tissues when RAD23B overexpressed. Mechanistically, overexpression of RAD23B and/or CORO1C further increased invadopodia formation and matrix degradation in SW480 and HCT8 CRC cells. Conversely, silencing of RAD23B expression suppressed tumorigenesis and liver metastasis in xenotransplant murine models. Furthermore, we found that RAD23B was significantly overexpressed in paired tumor tissues (n = 720) compared to adjacent non-tumor tissues (n = 694) of patients with CRC. Finally, we identified a strong correlation between higher levels of cytoplasmic expression of RAD23B, and poor prognosis and liver metastasis in CRC patients. Taken together, our data highlight a novel RAD23B-CORO1C signaling axis in CRC cell invasion and metastasis that may be of clinical significance.

Amniotic fluid contains large amounts of proteins produced by amnion epithelial cells, fetal tissues, fetal excretions and placental tissues; thus, it is an important potential source of biomarkers for identifying fetal pathologies. In this study, a pooled AF sample from 7 healthy volunteers was used to provide a comprehensive profile of normal human AF proteome using immunoaffinity depletion of 14 high-abundance proteins. Each individual AF sample was used to analyze inter-individual variations with iTRAQ method. As a result, a total of 2881 non-redundant proteins were identified, and 1624 proteins were quantified based on the peak intensity-based semi-quantification (iBAQ) method. Gene Ontology (GO) analysis showed that the AF proteome was enriched in extracellular region and extracellular matrix. Further function annotation showed that the top canonical pathway was axonal guidance signaling. The inter-individual variation analysis of 7 individual AF samples showed that the median inter-individual CV (Coefficient of variation) was 0.22. iBAQ quantification analysis revealed that the inter-individual variations were not correlated with protein abundance. GO analysis indicated that intracellular proteins tended to have higher CVs, and extracellular proteins tended to have lower CVs. These data will contribute to a better understanding of amniotic fluid proteomic analysis and biomarker discovery. SIGNIFICANCE: Amniotic fluid is an important potential source of biomarkers for identifying fetal pathologies. This study provided a large database for the normal human amniotic fluid proteome and analysis of inter-individual variations in amniotic fluid proteomes, which will offer a baseline reference for further AF proteomic analysis and pregnancy-related disease biomarker discovery.

Background The human brain is the most complex organ in the body, and it is important to have a better understanding of how the protein composition in the brain regions contributes to the pathogenesis of associated neurological disorders. Methods In this study, a comparative analysis of the frontal and temporal cortex proteomes was conducted by isobaric tags of relative and absolute quantification (iTRAQ) labeling and two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS). Brain protein was taken from relatively normal tissue that could not be avoided of damage during emergent surgery of the TBI (traumatic brain injury) patients admitted in Beijing Tiantan Hospital from 2014 to 2017. Eight cases were included. Four frontal lobes and 4 temporal lobes proteome were analyzed and the proteins were quantitated. Gene Ontology (GO), Ingenuity Pathway Analysis (IPA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze the biological function of identified proteins, unchanged proteins, and differentially expressed proteins (DEPs). Results A total number of 2127 protein groups were identified in the frontal and temporal lobe proteomes. A total of 1709 proteins could be quantitated in both the frontal and temporal cortex. Among 90 DEPs, 14 proteins were screened highly expressed in the temporal cortex, including MAPT, SNCG, ATP5IF1, GAP43, HSPE1, STMN1, NDUFS6, LDHB, SNCB, NDUFA7, MRPS36, EPDR1, CISD1, and RALA. In addition, compared to proteins expressed in the frontal cortex, 14 proteins including EDC4, NIT2, VWF, ASTN1, TGM2, SSB, CLU, HBA1, STOM, CRP, LRG1, SAA2, S100A4, and VTN were a low expression in the temporal cortex. The biological process enrichment showed that unchanged proteins between the frontal and temporal cortex mainly take part in regulated exocytosis, axon guidance, and vesicle-mediated transport. The KEGG pathway analysis showed that unchanged proteins between the frontal and temporal cortex mainly take part in oxidative phosphorylation, carbon metabolism, Huntington’s disease, and Parkinson’s disease. Conclusions The majority of proteins are unchanged between the frontal and temporal cortex, and unchanged proteins are closely related to its function. Among DEPs, MATP (tau) is upregulated in the temporal cortex, closely related to Alzheimer’s disease (AD), and is one of the targets for the treatment of AD. CLU is downregulated in the temporal cortex which functions as an extracellular chaperone that prevents aggregation of non-native proteins. It was suggested that the temporal lobe may not be the “functional dumb area” of the traditional view, but could be involved in important neural metabolic circuits.

Pheochromocytoma/paraganglioma (PPGL) is an endocrine tumor of the chromaffin cells in the adrenal medulla or the paraganglia. Currently, about 70% of PPGLs can be explained by germline or somatic mutations in several broadly expressed susceptibility genes including RET, VHL, and SDHB, while for the remaining, mainly sporadic cases, the pathogenesis is still unclear. Even for known susceptible genes, how mutations in these mostly ubiquitous genes result in tissue-specific pathogenesis remains unanswered, and why RET-mutated tumors almost always occur in the adrenal while SDHB-mutated tumors mostly occur extra-adrenal remains a mystery. By analyzing 22 sporadic PPGLs using SNP 6.0 genotyping arrays combined with expression profiling of 4 normal and 4 tumor tissues, we identified GIPC2, a gene located at 1p31.1 with preferential expression in adrenal and inducible by adrenal glucocorticoid, as a novel putative tumor suppressor gene for PPGLs. Copy number deletion and GIPC2 promoter hypermethylation but not GIPC2 mutation, accompanied with reduced GIPC2 expression, were observed in 39 of 55 PPGLs in our cohort. Examination of a published expression database consisting of 188 PPGLs found little GIPC2 expression in Cluster 1A (SDHx-associated) and Cluster 2A (NF1/RET-associated) tumors, but less pronounced reduction of GIPC2 expression in Cluster 1B (VHL-associated) and Cluster 2B/2C tumors. GIPC2 induced p27, suppressed MAPK/ERK and HIF-1ɑ pathways as well as cancer cell proliferation. Overexpressing GIPC2 in PC12 cells inhibited tumor growth in nude mice. We found GIPC2 interacted with the nucleoprotein NONO and both proteins regulated p27 transcription through the same GGCC box on p27 promoter. Significantly, low expression of both GIPC2 and p27 was associated with shorter disease-free survival time of PPGLs patients in the TCGA database. We found that PPGL-causing mutations in RET and in SDHB could lead to primary rat adrenal chromaffin cell proliferation, ERK activation, and p27 downregulation, all requiring downregulating GIPC2. Notably, the RET-mutant effect required the presence of dexamethasone while the SDHB-mutant effect required its absence, providing a plausible explanation for the tumor location preference. In contrast, the PPGL-predisposing VHL mutations had no effect on proliferation and GIPC2 expression but caused p53 downregulation and reduced apoptosis in chromaffin cells compared with wild-type VHL. Thus, our study raises the importance of cortical hormone in PPGL development, and GIPC2 as a novel tumor suppressor provides a unified molecular mechanism for the tumorigenesis of both sporadic and hereditary tumors of Clusters 1A and 2A concerning SDHB and RET, but not tumors of Cluster 1B concerning VHL and other clusters.

Aqueous humor (AH) proteins are involved in many physiological and pathological processes of the eye. The proteome analysis of AH is important to understand its physiological and pathophysiological functions. In the present study, AH samples obtained from 21 cataract volunteers were pooled together. After high-pH RPLC offline separation, the pooled sample was analyzed by LC-MS/MS to provide a comprehensive profile of AH proteome. The function analysis was provided by the GO and IPA annotation. In order to determine whether the AH proteome can reflect the pathophysiological changes of the disease, DIA technology was used to analyze the AH samples obtained from three neovascular glaucoma (NVG) patients (six samples) before and after drug treatment. The differential proteins were validated by PRM technology in an independent group (14 samples). In the AH proteome database, 802 proteins were identified, and 318 proteins were identified for the first time. Furthermore, 480 proteins were quantified based on the peak intensity-based semiquantification (iBAQ), which ranged by approximately 7 orders of magnitude. These proteins are primarily involved in immunity- and inflammation-related pathways. The differential AH proteomic analysis in NVG treatment revealed that the AH proteome can reflect the pathophysiological changes of drug treatment. Angiogenesis and thrombus coagulation progression are deeply involved in NVG treatment. The present experiment provided a comprehensive AH proteome analysis and expanded the profile of human AH proteome. The differential AH proteomic analysis of NVG treatment indicated that AH proteome can reflect the pathophysiological changes in drug intervention.

Knowledge about the mouse brown adipose tissue (BAT) proteome can provide a deeper understanding of the function of mammalian BAT. Herein, a comprehensive analysis of interscapular BAT from C57BL/6J female mice was conducted by 2DLC and high-resolution mass spectrometry to construct a comprehensive proteome dataset of mouse BAT proteins. A total of 4949 nonredundant proteins were identified, and 4495 were quantified using the iBAQ method. According to the iBAQ values, the BAT proteome was divided into high-, middle- and low-abundance proteins. The functions of the high-abundance proteins were mainly related to glucose and fatty acid oxidation to produce heat for thermoregulation, while the functions of the middle- and low-abundance proteins were mainly related to protein synthesis and apoptosis, respectively. Additionally, 497 proteins were predicted to have signal peptides using SignalP4 software, and 75 were confirmed in previous studies. This study, for the first time, comprehensively profiled and functionally annotated the BAT proteome. This study will be helpful for future studies focused on biomarker identification and BAT molecular mechanisms.

Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography-mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.

Plasma metabolomics and lipidomics have been commonly used for biomarker discovery. Studies in white and Japanese populations suggested that gender and age can affect circulating plasma metabolite profiles; however, the metabolomics characteristics in Chinese population has not been surveyed. In our study, we applied liquid chromatography-mass spectrometry-based approach to analyze Chinese plasma metabolome and lipidome in a cohort of 534 healthy adults (aging from 15 to 79). Fatty-acid metabolism was found to be gender- and age-dependent in Chinese, similar with metabolomics characteristics in Japanese and white populations. Differently, lipids, such as TGs and DGs, were found to be gender-independent in Chinese population. Moreover, nicotinate and nicotinamide metabolism was found to be specifically age-related in Chinese. The application of plasma metabolome and lipidome for renal cell carcinoma diagnosis (143 RCC patients and 34 benign kidney tumor patients) showed good accuracy, with an area under the curve (AUC) of 0.971 for distinction from healthy control, and 0.839 for distinction from the benign. Bile acid metabolism was found to be related to RCC probably combination with intestinal microflora. Definition of the variation and characteristics of Chinese normal plasma metabolome and lipidome might provide a basis for disease biomarker analysis.

Despite advances in cancer treatments, early diagnosis of cancer is still the most promising way to improve outcomes. Without homeostatic control, urine reflects systemic changes in the body and can potentially be used for early detection of cancer. In this study, a tumor‐bearing rat model was established by subcutaneous injection of Walker 256 cells. Urine samples from tumor‐bearing rats were collected at five time points during cancer development. Dynamic urine proteomes were profiled using liquid chromatography coupled with tandem mass spectrometry (LC‐MS/MS). Several urine proteins that changed at multiple time points were selected as candidate cancer biomarkers and were further validated by multiple reaction monitoring (MRM) analysis. It was found that the urinary protein patterns changed significantly with cancer development in a tumor‐bearing rat model. A total of 10 urinary proteins (HPT, APOA4, CO4, B2MG, A1AG, CATC, VCAM1, CALB1, CSPG4, and VTDB) changed significantly even before a tumor mass was palpable, and these early changes in urine could also be identified with differential abundance at late stages of cancer. Our results indicate that urine proteins could enable early detection of cancer at an early onset of tumor growth and monitoring of cancer progression.

Hippocampus and temporal cortex are important brain regions, which play distinct, but complimentary roles in mediating learning and memory. Herein, we utilized label-free differential proteome strategy to explore function of normal human hippocampus and temporal cortex in learning and memory. As a result, a total of 5529 and 5702 proteins were identified in hippocampus and temporal cortex, respectively, 516 of which were significantly differential expressed, with abundance span 5 orders of magnitudes. Pathways analysis showed that temporal cortex was involved in growth of axons growth and synapse density regulation, through which could regulate long-term potentiation and long-term retention of trace memory. Hippocampus was involved in regulation of cell survival and cell viability, and regulates neurons proliferation by actin dynamics changes, through which involved in both short-term memory and long-term memory. Four selected differential proteins were further validated by Western blot and immunohistochemistry. For the first time, we identified proteins and associated pathways of hippocampus and temporal cortex in human cognition process using proteomic strategy, which would provide references for generating corresponding insights in hippocampus and temporal cortex-related cognitive function. The original data files can be downloaded at http://211.102.209.254/page/PSV023.html;?url = 1489542083729AFHp (password: kYxh). Significance This study explored the potential molecular mechanism of hippocampus and temporal cortex in human cognition function using proteomics strategy, which will offer a baseline reference for further cognitive disorders study and reveal insights into physiology of temporal cortex and hippocampus.

Knowledge about human tissue proteome will provide insights into health organ physiology. To construct a comprehensive data set of human pituitary and thyroid proteins, post-mortem pituitaries and thyroids from 10 normal individuals were used. The pooled samples were prepared using two methods. One part of the sample was processed using 14 high-abundance proteins immunoaffinity column. The other part was directly subjected to digestion. Finally, a total of 7596 proteins in pituitary and 5602 proteins in thyroid with high confidence were identified, with 6623 and 4368 quantified, respectively. A total of 5781 of pituitary and 3178 of thyroid proteins have not been previously reported in the normal pituitary and thyroid proteome. Comparison of pituitary and thyroid proteome indicated that thyroid prefers to be involved in nerve system regeneration and metabolic regulation, while pituitary mainly performs functions of signal transduction and cancer modulation. Our results, for the first time, comprehensively profiled and functionally annotated the largest high-confidence data set of proteome of two important endocrine glands, pituitary and thyroid, which is important for further studies on biomarker identification and molecular mechanisms of pituitary and thyroid disorders. The mapping results can be freely downloaded at http://www.urimarker.com/pituitary/ and http://www.urimarker.com/thyroid/ . The raw data are available via ProteomeXchange with identifier PXD006471.

Objective To investigate a proteomics analysis of liver proteins from rats with spleen-deficiency syndrome (SDS) induced by chronic improper diet consumption and fatigue. Methods This study used a liver proteomic profiling method to identify differentially expressed proteins and altered pathways involved in SDS rats. Specifically, we collected liver samples from a control group and a group with SDS induced by chronic improper diet consumption and fatigue for 4 weeks. The pooled liver proteins in each group were labeled with 8-plex isobaric tags for relative and absolute quantitation reagents. The labeled control and SDS group samples were pooled together and separated by high-pH reverse-phase liquid chromatography. The differentially expressed proteins from the liver proteomes were analyzed to identify potential biomarkers of SDS. Differentially expressed proteins were selected in conjunction with gene ontology and ingenuity pathway analysis. Results We identified 2176 protein clusters with more than two peptides in the SDS group, with 141 proteins quantified as differentially expressed proteins. Of these, 75 proteins were up-regulated, and 66 were down-regulated. Three activated signaling pathways, the thrombin, CXCR4 and synaptic long term depression signaling pathways, and a large multi-protein complex within the network were revealed in the liver proteomic analysis of SDS rats. Conclusions This is the first report of a differential liver proteome under SDS conditions. The results suggest that the liver proteome partially reflects the pathological changes involved in SDS. The findings provide important information for comprehensively understanding the mechanisms of dysfunction or injury in the liver at the molecular level as a result of SDS. Furthermore, they provide a novel understanding of the connotation of SDS in the field of traditional Chinese Medicine.

Background To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC. Methods In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. Results The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N′-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria. Conclusions UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

Renal cell carcinoma (RCC) is the second most lethal urinary cancer. RCC is frequently asymptomatic and it is already metastatic at diagnosis. There is an urgent necessity for RCC specific biomarkers selection for diagnostic and prognostic purposes. In present study, we applied liquid chromatography—mass spectrometry (LC-MS) based metabolomics to analyze urine samples of 100 RCC, 34 benign kidney tumors and 129 healthy controls. Differential metabolites were analyzed to investigate if urine metabolites could differentiate RCC from non-RCC. A panel consisting of 9 metabolites showed the best predictive ability for RCC from the health controls with an area under the curve (AUC) values of 0.905 for the training dataset and 0.885 for the validation dataset. Separation was observed between the RCC and benign samples with an AUC of 0.816. RCC clinical stages (T1 and T2 vs. T3 and T4) could be separated using a panel of urine metabolites with an AUC of 0.813. One metabolite, N-formylkynurenine, was discovered to have potential value for RCC diagnosis from non-RCC subjects with an AUC of 0.808. Pathway enrichment analysis indicated that tryptophan metabolism was an important pathway in RCC. Our data concluded that urine metabolomics could be used for RCC diagnosis and would provide candidates for further targeted metabolomics analysis of RCC.

Myocardial infarction (MI) is a disease characterized by high morbidity and mortality rates. MI biomarkers are frequently used in clinical diagnosis; however, their specificity and sensitivity remain unsatisfactory. Urinary proteome is an easy, efficient and noninvasive source to examine biomarkers associated with various diseases. The present study, to the best of the authors' knowledge, is the first to examine the urinary proteome using the isobaric tags for relative and absolute quantitation (iTRAQ) technology to identify potential diagnostic biomarkers of MI. The urinary proteome was analyzed within 12 h following the first symptoms of early-onset MI and at day 7 following percutaneous coronary intervention via iTRAQ labeling and two-dimensional liquid chromatography-tandem mass spectrometry. Candidate biomarkers were validated by multiple reaction monitoring (MRM) analysis. A total of 233 urinary proteins were differentially expressed. Gene enrichment analysis identified that the urinary proteome in patients with MI was associated with atherosclerosis, abnormal coagulation and abnormal cell metabolism. In total, 12 differentially expressed urinary proteins were validated by MRM analysis, five of which were associated with MI for the first time in the present study. Binary logistic regression analysis suggested that the combination of five urinary proteins (antithrombin-III, complement C3, α-1-acid glycoprotein 1, serotransferrin and cathepsin Z) may be used to diagnose MI with 94% sensitivity and 93% specificity. In addition, the protein expression levels of three proteins were significantly restored to normal levels following surgical treatment. The verified candidate biomarkers may be used for the diagnosis of MI, and for monitoring the disease status and the effects of treatments for MI. The present results may facilitate future clinical applications of the urinary proteome to diagnose MI.

Glaucoma is the leading cause of irreversible blindness worldwide. The proteome characterization of glaucoma is not clearly understood. A total of 175 subjects, including 57 primary acute angle-closure glaucoma (PAACG), 50 primary chronic angle-closure glaucoma (PCACG), 35 neovascular glaucoma (NVG), and 33 cataract patients, were enrolled and comparison proteomic analysis was provided. The samples were randomly divided into discovery group or validation group, whose aqueous humor proteome was analyzed by data-independent acquisition or by parallel reaction monitoring. The common proteome features of three types of glaucoma were immune response, lipid metabolism, and cell death. Three proteins, VTN, SERPIND1, and CD14, showed significant upregulation in glaucoma and could discriminate glaucoma from cataract. Mutual differential proteomic analysis of PAACG, PCACG, and NVG showed different proteome characterization of the three types of glaucoma. NVG was characterized with activated angiogenesis. PAACG was characterized with activation of inflammation response. SERPIND1 was discovered to play vital role in glaucoma occurrences, which is associated with eye transparency decrease and glucose metabolism. This study would provide insights in understanding proteome characterization of glaucoma and benefit the clinical application of AH proteome., Graphical Abstract, Highlights • Aqueous humor proteome of different glaucoma (PACG, NVG) was profiled. • Potential protein biomarkers for glaucoma were proposed. • Potential mechanism of glaucoma was described. • SERPIND1 was discovered to have potential value for glaucoma diagnosis., In Brief Liu et al. characterized the proteome of aqueous humor from three types of glaucoma. Fifty-seven primary acute angle-closure glaucoma (PAACG), 50 primary chronic angle-closure glaucoma (PCACG), 35 neovascular glaucoma (NVG), and 33 cataract patient samples were analyzed using data-independent analysis and parallel reaction monitoring. Lipid metabolism, immune response, and cell death pathways showed different degrees of activation among the three types of glaucoma but were all higher relative to cataract. SERPIND1 was discovered as a vital protein in glaucoma.

Objective To identify candidate urinary protein biomarkers to distinguish medulloblastoma (MB) patients from healthy patients or benign brain disease control patients. Methods The tandem mass tag (TMT)-labeled quantitative proteomics approach was used to identify differential proteins in the urinary proteome of 9 pre- and postsurgery MB patients and 9 healthy control patients, respectively. Ingenuity pathway analysis was used for functional annotation of differential proteins. The biomarker candidates were validated by the parallel reaction monitoring (PRM) method in 112 samples (29 pre- and postsurgery MB patients, 26 healthy control patients, and 28 benign brain disease control patients). Receiver operating characteristic (ROC) curves were developed to evaluate candidate biomarkers. Results A total of 114 differential proteins were found. Bioinformatic analysis revealed that the urinary proteome could reflect changes in MB. Seventeen candidate biomarkers were validated by PRM. The combination of CADH1, FGFR4 and FIBB could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884. Conclusion This report describes the first application of a TMT-PRM workflow to identify and validate MB–specific biomarkers in urine. These findings might contribute to the application of urinary proteomics for detecting and monitoring MB. Biological significance Medulloblastoma (MB) is among the most common pediatric brain malignancies. This tumor has a highly aggressive clinical course with a high tendency for relapses. Magnetic resonance imaging (MRI) is the major means of diagnosis and for radiographic surveillance after surgery. In MRI, sedation is often required in young children, which could expose them to a series of risks, including airway obstruction and even death. Aside from MRI, there is no reliable biomarker for clinical screening or monitoring of the disease. These facts introduce the clinical need of noninvasive biomarkers for early screening or monitoring of MB. This study is focused on the investigation of a marker panel based on urinary proteome, as a tool for the detection of MB in selected patients at risk. Upon evaluation of the marker model in an independent blinded set of 112 samples, the panel (CADH1, FGFR4 and FIBB) could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884.

Background IgA nephropathy (IgAN) is one of the most common forms of idiopathic glomerular diseases and might lead to end-stage kidney disease. Accurate and non-invasive biomarkers for early diagnosis are required for early intervention and consequent therapy for IgAN patients. Because variance in the disease incidence and predisposing genes of IgAN has been detected among different ethnicities, the ethnicity factor should be considered in IgAN biomarker discovery. The differences in the protein profiles and pathological mechanisms of IgAN in patients of Uygur ethnicity need to be clearly illustrated. Methods In this study, we used urinary proteomics to discover candidate biomarkers of IgAN in patients of Uygur ethnicity. The urinary proteins from Uygur normal control and Uygur IgAN patients were extracted and analyzed using 2D-LC-MS/MS and isobaric tags for relative and absolute quantitation (iTRAQ) analysis. Results A total of 277 proteins were found to be differentially represented in Uygur IgAN compared with the respective normal controls. The bioinformatics analysis revealed that the immune response, cell survival, and complement system were activated in Uygur IgAN. Many differentially expressed proteins were found to be related to nephropathy and kidney injuries. Four candidate biomarkers were validated by Western blot, and these results were consistent with the iTRAQ results. ICAM1, TIMP1, SERPINC1 and ADIPOQ were upregulated in Uygur IgAN. Bioinformatic analysis revealed that the increase of ICAM1 and TIMP1 might be caused by IgAN, but the increase of SERPINC1 and ADIPOQ might be caused by proteinuria. SERPINC1 and ICAM1 were identified as the candidate biomarkers with excellent area-under-the-curve (AUC) values (0.84) for distinguishing Uygur IgAN from normal controls. Conclusions Using urinary proteomic analysis, we identified several candidate biomarkers for IgAN in patients of Uygur ethnicity. These results will prove helpful for exploring the pathological mechanism of IgAN in patients of Uygur ethnicity and for developing better treatments for these patients. Electronic supplementary material The online version of this article (10.1186/s12882-018-1139-3) contains supplementary material, which is available to authorized users.

Pregnancy is associated with the onset of many adaptation processes that are likely to change over the course of gestation. Understanding normal metabolites’ variation with pregnancy progression is crucial for gaining insights of the key nutrients for normal fetal growth, and for comparative research of pregnancy-related complications. This work presents liquid chromatography-mass spectrum-based urine metabolomics study of 50 health pregnant women at three time points during pregnancy. The influence of maternal physiological factors, including age, BMI, parity and gravity to urine metabolome was explored. Additionally, urine metabolomics was applied for early prediction of two pregnancy complications, gestational diabetes mellitus and spontaneous abortion. Our results suggested that during normal pregnancy progression, pathways of steroid hormone biosynthesis and tyrosine metabolism were significantly regulated. BMI is a factor that should be considered during cross-section analysis. Application analysis discovered potential biomarkers for GDM in the first trimester with AUC of 0.89, and potential biomarkers for SA in the first trimester with AUC of 0.90. In conclusion, our study indicated that urine metabolome could reflect variations during pregnancy progression, and has potential value for pregnancy complications early prediction. The clinical trial number for this study is NCT03246295.

Biomarkers are measurable changes associated with the disease. Urine can reflect the changes of the body while blood is under control of the homeostatic mechanisms; thus, urine is considered an important source for early and sensitive disease biomarker discovery. A comprehensive profile of the urinary proteome will provide a basic understanding of urinary proteins. In this paper, we present an in-depth analysis of the urinary proteome based on different separation strategies, including direct one dimensional liquid chromatography–tandem mass spectrometry (LC/MS/MS), two dimensional LC/MS/MS, and gel-eluted liquid fraction entrapment electrophoresis/liquid-phase isoelectric focusing followed by two dimensional LC/MS/MS. A total of 6085 proteins were identified in healthy urine, of which 2001 were not reported in previous studies and the concentrations of 2571 proteins were estimated (spanning a magnitude of 106) with an intensity-based absolute quantification algorithm. The urinary proteins were annotated by their tissue distribution. Detailed information can be accessed at the “Human Urine Proteome Database” (www.urimarker.com/urine).

White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 106) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90–99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99–100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.

Endometriosis is a common gynecologic disorder and due to a lack of non-invasive detection methods, it can take up to 12 years before an affected woman obtains a diagnosis and receives appropriate treatment. Therefore, the identification of a specific biomarker that can be detected quickly and non-invasively is urgently needed. In this study, the urine proteome, a potentially rich source of biomarkers, is examined in patients with or without endometriosis in an attempt to identify novel protein biomarkers that can be used to diagnose endometriosis. This study is the first to combine tandem mass tags and parallel reaction monitoring approaches to aid in identifying and validating urine biomarkers for endometriosis. The findings presented herein support previous conclusions that endometriosis is a chronic inflammatory disease. Additionally, Histone 4 was identified as a potential biomarker and/or therapeutic target for endometriosis. At a cutoff of 14.2, the area under the curve for H4 was 0.848, with a sensitivity of 70% and specificity of 80%. Moreover, to our knowledge, this is the first study to observe an elevated histone level in body fluids obtained from endometriosis patients. While this study provides a good foundation, further studies are required to further validate the results presented. Significance Endometriosis is a common gynecologic disorder and due to a lack of non-invasive detection methods, it can take up to 12 years before an affected woman obtains a diagnosis and receives appropriate treatment. Therefore, the identification of a specific biomarker that can be detected quickly and non-invasively is urgently needed. We believe our results have an important impact on detection and treatment of endometriosis. Firstly, this study is the first to combine tandem mass tags and parallel reaction monitoring approaches to aid in identifying and validating urine biomarkers for endometriosis, which has established the methodology required for subsequent studies. Secondly, this is also the first study to observe an elevated histone level in body fluids obtained from endometriosis patients. Compared with other urine biomarkers reported in literature, histone 4 has a potential to serve as a biomarker of endometriosis and a therapeutic target. Thirdly, our study supports previous conclusions that endometriosis is a chronic inflammatory disease. These findings can warrant further investigation of the pathophysiology of endometriosis.

Purpose As an important part of the data-independent acquisition-mass spectrometry (DIA-MS) analysis approach, spectral library generation is closely related to the final protein identification and quantitation. Experimental design In this study, an attempt is made to evaluate the influence of different sample separation methods (reversed-phase liquid chromatography (RPLC) linear gradient elution and spin column step gradient fractionation) and data acquisition modes (data-dependent acquisition (DDA) and DIA) on library generation of the human urine proteome. Results The RPLC separation method provides more proteins for generating the library than the spin column; however, the spin column library leads to identification of more proteins when used for the urine proteome analysis. The DDA mode can provide a larger spectral library than the DIA mode and the DDA-library leads to more protein identifications in the study. Use of a combined urinary protein library provides the most complete protein and peptide information, and the DIA approach can provide accurate protein quantitative information even for low-abundance proteins. Conclusions and clinical relevance When the combined library is used to analyze the normal individual urine proteome (18 males and 18 females), gender-related and age-related proteins are discovered and functionally analyzed. This strategy may benefit urine proteome DIA analysis.

Rationale Fast digestion methods can dramatically accelerate enzyme digestion and increase the throughput of proteomic analysis. However, the peptide characteristics of fast digestion methods and their performance in discovery and targeted proteomic analysis must be systematically evaluated. Methods Three digestion methods, including overnight digestion, microwave-assisted protein enzymatic digestion (MAPED), and high-intensity focused ultrasonic-assisted enzymatic digestion (HIFUSAED), in trypsin or in trypsin/Lys-C were comprehensively compared in both discovery and targeted proteomics analysis using the HeLa cell proteome. In discovery proteomic analysis, the highest numbers of peptides and proteins were identified when the sample was digested via the MAPED method with trypsin/Lys-C. Results The fast digestion methods showed a higher mis-cleavage rate and a lower semi-tryptic rate than the overnight digestion method. In both label-free quantitative analysis and targeted proteomic analysis, both fully cleaved peptides (FCPs) and mis-cleaved peptides (MCPs) from the fast digestion methods and the overnight digestion method showed good reproducibility if they showed good abundance. Conclusions When both the FCPs and MCPs were included in the analysis, the MAPED with trypsin/Lys-C method showed the best results for both discovery proteomic analysis and relative quantitative targeted proteomic analysis. These results will be beneficial for the application of fast digestion methods to proteomics.

Depression is a global mental disorder disease and greatly threatened human health and stress is considered to be one of the important factors that lead to depression. In this study, we used newly developed iTRAQ labeling and high performance liquid chromatography (HPLC) and mass spectrum united analysis technology obtained the 2176 accurate proteins. Successively, we used the GO analysis and IPA software to analyze the 98 differentially expressed proteins of liver in depression rats due to chronic restraint stress, showing a map of proteomics analysis of liver proteins from the aspects of related functions, disease and function analysis, canonical pathway analysis, and associated network. This study provide important information for comprehensively understanding the mechanisms of dysfunction or injury in the liver in depression.

Purpose Human saliva is an important source for disease biomarker discovery. This study is to investigate the influence of gender and acid stimulation on the normal human salivary proteome. Experimental design Unstimulated and acid-stimulated saliva samples from 5 males and 5 females were labeled with 4-plex iTRAQ and analyzed by 2-DLC MS/MS. By bioinformatics analysis the gender and acid stimulation related proteins were defined. According to protein annotation the important proteins were validated by multiple reaction monitor analysis. Results A total of 1770 proteins were identified, and 82 proteins in unstimulated saliva were found to be gender-specific, mainly associated with immune function, metabolism and inflammation. However, no gender-specific proteins were found in acid-stimulated saliva. In addition, 182 and 307 differential proteins were found to be acid stimulation-specific in male samples and female samples, respectively, mainly participated in the process of cellular movement, immune function and inflammatory response. Besides, it was found that acid stimulation caused more significant alteration and played a more important role in the human salivary proteome than gender. Gender-specific (IGHG2 and TIMP1) and acid stimulation (PERL, ENOA, ACTB, B4E022 and CALL3) related proteins were validated by MRM analysis. Conclusions and clinical relevance The results indicate that gender differences exist in the unstimulated salivary proteome, and the influence of acid stimulation on the salivary proteome was more significant than that of gender. The above results may be helpful for salivary proteome research in the future.

Tumor-derived exosomes are important for cell-cell communication. However, the role of TP53 in the control of exosome production in colorectal cancer (CRC) is controversial and unclear. The features of exosomes secreted from HCT116 TP53-wild type (WT), TP53-knockout (KO) and constructed TP53 (R273H)-mutant (MT) cells were assessed. The exosomes from the MT and KO cells exhibited significantly reduced sizes compared with the WT cells. A comprehensive proteomic analysis of exosomal proteins was performed using the isobaric tag for relative and absolute quantitation (iTRAQ)-2D-LC-MS/MS strategy. A total of 3437 protein groups with ≥2 matched peptides were identified. Specifically, hepatocyte growth factor-regulated tyrosine kinase substrate (HGS) was consistently down-regulated in the exosomes from the MT and KO cells. Functional studies demonstrated that low HGS levels were responsible for the decreased exosome size. TP53 regulated HGS expression and thus HGS-dependent exosome formation. Furthermore, the HGS expression was gradually increased concomitant with CRC carcinogenesis and was an independent poor prognostic factor. In conclusion, a novel HGS-dependent TP53 mechanism in exosome formation was identified in CRC. HGS may serve as a novel prognostic biomarker and a candidate target for therapeutic interventions.

Purpose Body fluid is considered a rich source of disease biomarkers. Proteins in many body fluids have potential clinical applications for disease diagnostic and prognostic predictions. Experimental design To determine differences in the protein components and functional features of body fluids, a proteomic comparison of five body fluids (plasma, urine, cerebrospinal fluid, saliva, and amniotic fluid) was conducted by high-resolution mass spectrometry. Results A total of 4717 nonredundant proteins were identified, and the concentrations of 3433 proteins were estimated by an intensity-based algorithm quantitation method. Among them, 564 proteins were shared among the five body fluids, with common functions in the coagulation/prothrombin system and inflammatory response. A total of 36.7% of the proteins were detected in only one body fluid and were closely related to their adjacent tissues by function. The functional analysis of the remaining 2986 proteins showed that similar functions might be shared among different body fluids, which highlighted intimate connection in the body. Conclusions and clinical relevance The quantitative comparative functional analysis indicated that body fluids might reflect the diverse functions of the whole body rather than the characteristics of their adjacent tissues. The above data might indicate the potential application of body fluids for biomarker discovery.