A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Mass Spectrometry Identification of Biomarkers in Extracellular Vesicles From Plasmodium vivax Liver Hypnozoite Infections

Latent liver stages termed hypnozoites cause relapsing Plasmodium vivax malaria infection and represent a major obstacle in the goal of malaria elimination. Hypnozoites are clinically undetectable, and presently, there are no biomarkers of this persistent parasite reservoir in the human liver. Here, we have identified parasite and human proteins associated with extracellular vesicles (EVs) secreted from in vivo infections exclusively containing hypnozoites. We used P. vivax-infected human liver-chimeric (huHEP) FRG KO mice treated with the schizonticidal experimental drug MMV048 as hypnozoite infection model. Immunofluorescence-based quantification of P. vivax liver forms showed that MMV048 removed schizonts from chimeric mice livers. Proteomic analysis of EVs derived from FRG huHEP mice showed that human EV cargo from infected FRG huHEP mice contain inflammation markers associated with active schizont replication and identified 66 P. vivax proteins. To identify hypnozoite-specific proteins associated with EVs, we mined the proteome data from MMV048-treated mice and performed an analysis involving intragroup and intergroup comparisons across all experimental conditions followed by a peptide compatibility analysis with predicted spectra to warrant robust identification. Only one protein fulfilled this stringent top-down selection, a putative filamin domain-containing protein. This study sets the stage to unveil biological features of human liver infections and identify biomarkers of hypnozoite infection associated with EVs.     

Multiple Reaction Monitoring-Mass Spectrometry Enables Robust Quantitation of Plasma Proteins Regardless of Whole Blood Processing Delays That May Occur in the Clinic

Plasma is an important biofluid for clinical research and diagnostics. In the clinic, unpredictable delays—from minutes to hours—between blood collection and plasma generation are often unavoidable. These delays can potentially lead to protein degradation and modification and might considerably affect intact protein measurement methods such as sandwich enzyme-linked immunosorbent assays that bind proteins on two epitopes to increase specificity, thus requiring largely intact protein structures. Here, we investigated, using multiple reaction monitoring mass spectrometry (MRM-MS), how delays in plasma processing affect peptide-centric “bottom-up” proteomics. We used validated assays for proteotypic peptide surrogates of 270 human proteins to analyze plasma generated after whole blood had been kept at room temperature from 0 to 40 h to mimic delays that occur in the clinic. Moreover, we evaluated the impact of different plasma-thawing conditions on MRM-based plasma protein quantitation. We demonstrate that >90% of protein concentration measurements were unaffected by the thawing procedure and by up to 40-h delayed plasma generation, reflected by relative standard deviations (RSDs) of <30%. Of the 159 MRM assays that yielded quantitative results in 60% of the measured time points, 139 enabled a stable protein quantitation (RSD <20%), 14 showed a slight variation (RSD 20–30%), and 6 appeared unstable/irreproducible (RSD > 30%). These results demonstrate the high robustness and thus the potential for MRM-based plasma-protein quantitation to be used in a clinical setting. In contrast to enzyme-linked immunosorbent assay, peptide-based MRM assays do not require intact three-dimensional protein structures for an accurate and precise quantitation of protein concentrations in the original sample.     

Tracking the Stability of Clinically Relevant Blood Plasma Proteins with Delta-S-Cys-Albumin—A Dilute-and-Shoot LC/MS-Based Marker of Specimen Exposure to Thawed Conditions

Biomolecular integrity can be compromised when blood plasma/serum (P/S) specimens are improperly handled. Compromised analytes can subsequently produce erroneous results—without any indication of having done so. We recently introduced an LC/MS-based marker of P/S exposure to thawed conditions called ΔS-Cys-Albumin which, aided by an established rate law, quantitatively tracks exposure of P/S to temperatures greater than their freezing point of ?30 °C. The purposes of this study were to (1) evaluate ΔS-Cys-Albumin baseline values in gastrointestinal cancer patients and cancer-free control donors, (2) empirically assess the kinetic profiles of ΔS-Cys-Albumin at 23 °C, 4 °C, and ?20 °C, and (3) empirically link ΔS-Cys-Albumin to the stability of clinically relevant proteins. ΔS-Cys-Albumin was measured at ≥ 9 different time points per exposure temperature in serum and K₂EDTA plasma samples from 24 separate donors in aliquots kept separately at 23 °C, 4 °C, and ?20 °C. Twenty-one clinically relevant plasma proteins were measured at four time points per temperature via a multiplexed immunoassay on the Luminex platform. Protein stability was assessed by mixed effects models. Coordinated shifts in stability between ΔS-Cys-Albumin and the unstable proteins were documented by repeated measures and Pearson correlations. Plasma ΔS-Cys-Albumin dropped from approximately 20% to under 5% within 96 h at 23 °C, 28 days at 4 °C, and 65 days at ?20 °C. On average, 22% of the 21 proteins significantly changed in apparent concentration at each exposure temperature (p < 0.0008 with >10% shift). A linear inverse relationship was found between the percentage of proteins destabilized and ΔS-Cys-Albumin (r = ?0.61; p < 0.0001)—regardless of the specific time/temperature of exposure. ΔS-Cys-Albumin tracks cumulative thawed-state exposure. These results now enable ΔS-Cys-Albumin to approximate the percentage of clinically relevant proteins that have been compromised by incidental plasma exposure to thawed-state conditions.     

Etiology-, Sex-, and Tumor Size-Based Differences in Adrenocorticotropin-Dependent Cushing Syndrome

ObjectiveTo examine demographic, clinical, and biochemical differences in patients with adrenocorticotropin (ACTH)-dependent Cushing syndrome (CS) based on etiology, sex, and tumor size.MethodsThis was a single-center study of 211 patients with ACTH-dependent CS followed for 35 years. Patients were stratified into 3 groups based on etiology: Cushing disease (CD)/transsphenoidal surgery, Cushing disease/total bilateral adrenalectomy (CD/TBA), and ectopic ACTH secretion (EAS). Patients were also stratified based on sex and tumor size (nonvisualized, microadenoma, and macroadenoma).ResultsCD was the commonest cause of ACTH-dependent CS (190; 90%). Most patients presented in the third decade (median age, 29 years). Clinical features, cortisol, and ACTH were significantly greater in the EAS group. The CD/TBA group had more nonvisualized tumors (22% vs 8%; P = .000) and smaller tumor size (4 vs 6 mm; P = .001) compared with the CD/transsphenoidal surgery group. There was female predominance in CD (2.06:1) and male predominance in EAS (2:1). Men had shorter duration of symptoms (2 years; P = .014), were younger (23 years; P = .001), had lower body mass index (25.1 kg/m²; P = .000), and had more severe disease (low bone mineral density, hypokalemia). Macroadenomas were frequent (46; 24.2%), and ACTH correlated with tumor size in CD (r = 0.226; P = .005).ConclusionOur cohort presented at an earlier age than the Western population with a distinct, but slightly lower, female predilection. Patients with CD undergoing TBA had frequent negative imaging. Men had a clinical profile suggesting aggressive disease. Microadenoma and macroadenoma were difficult to distinguish on a clinicobiochemical basis.     

An Optimized Proteomics Approach Reveals Novel Alternative Proteins in Mouse Liver Development

Alternative ORFs (AltORFs) are unannotated sequences in genome that encode novel peptides or proteins named alternative proteins (AltProts). Although ribosome profiling and bioinformatics predict a large number of AltProts, mass spectrometry as the only direct way of identification is hampered by the short lengths and relative low abundance of AltProts. There is an urgent need for improvement of mass spectrometry methodologies for AltProt identification. Here, we report an approach based on size-exclusion chromatography for simultaneous enrichment and fractionation of AltProts from complex proteome. This method greatly simplifies the variance of AltProts discovery by enriching small proteins smaller than 40 kDa. In a systematic comparison between 10 methods, the approach we reported enabled the discovery of more AltProts with overall higher intensities, with less cost of time and effort compared to other workflows. We applied this approach to identify 89 novel AltProts from mouse liver, 39 of which were differentially expressed between embryonic and adult mice. During embryonic development, the upregulated AltProts were mainly involved in biological pathways on RNA splicing and processing, whereas the AltProts involved in metabolisms were more active in adult livers. Our study not only provides an effective approach for identifying AltProts but also novel AltProts that are potentially important in developmental biology.     

Impact of Pancreatic Neuroendocrine Tumor on Mortality in Patients With von Hippel-Lindau Disease

ObjectiveThe main causes for morbidity and mortality in von Hippel-Lindau (VHL) disease are central nervous system hemangioblastoma and clear cell renal cell carcinoma, but the effect of VHL-related pancreatic neuroendocrine tumors (PNET) on patient outcome is unclear. We assessed the impact of PNET diagnosis in patients with VHL on all-cause mortality (ACM) risk.MethodsWe used the Surveillance, Epidemiology, and End Results database. Of 16 344 patients, 170 had VHL based on clinical diagnostic criteria, and 510 patients had PNET (91 VHL-related and 419 sporadic).ResultsSurvival analysis demonstrated a lower ACM among patients with VHL-related PNET compared to patients with sporadic PNET (log-rank test, P = .011). Among patients with VHL, ACM risk was higher with vs without PNET (P = .029). The subgroup analysis revealed a higher ACM risk with metastatic PNET (sporadic P = .0031 and VHL-related P = .08) and a similar trend for PNET diameter ≥3 cm (P = .06 and P = 0.1 in sporadic and VHL-related PNET, respectively). In a multivariable analysis of patients with VHL, diagnosis with PNET by itself was associated with a trend of lower risk for ACM, while presence of metastatic PNET was independently associated with increased ACM risk.ConclusionDiagnosis with PNET is not associated with a higher ACM risk in VHL by itself. The independent association of advanced PNET stage with higher mortality risk emphasizes the importance of active surveillance for detecting high-risk PNET at an early stage to allow timely intervention.     

New Views of Old Proteins: Clarifying the Enigmatic Proteome

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.     

Resistin,Elastase, and Lactoferrin as Potential Plasma Biomarkers of Pediatric Inflammatory Bowel Disease Based on Comprehensive Proteomic Screens

Inflammatory bowel disease (IBD) is an immune-mediated chronic inflammation of the intestine, which can present in the form of ulcerative colitis (UC) or as Crohn’s disease (CD). Biomarkers are needed for reliable diagnosis and disease monitoring in IBD, especially in pediatric patients. Plasma samples from a pediatric IBD cohort were interrogated using an aptamer-based screen of 1322 proteins. The elevated biomarkers identified using the aptamer screen were further validated by ELISA using an independent cohort of 76 pediatric plasma samples, drawn from 30 CD, 30 UC, and 16 healthy controls. Of the 1322 proteins screened in plasma from IBD patients, 129 proteins were significantly elevated when compared with healthy controls. Of these 15 proteins had a fold change greater than 2 and 28 proteins had a fold change >1.5. Neutrophil and extracellular vesicle signatures were detected among the elevated plasma biomarkers. When seven of these proteins were validated by ELISA, resistin was the only protein that was significantly higher in both UC and CD (p < 0.01), with receiver operating characteristic area under the curve value of 0.82 and 0.77, respectively, and the only protein that exhibited high sensitivity and specificity for both CD and UC. The next most discriminatory plasma proteins were elastase and lactoferrin, particularly for UC, with receiver operating characteristic area under the curve values of 0.74 and 0.69, respectively. We have identified circulating resistin, elastase, and lactoferrin as potential plasma biomarkers of IBD in pediatric patients using two independent diagnostic platforms and two independent patient cohorts.     

Differences in Clinical Manifestations and Tumor Features Between Metastatic Pheochromocytoma/Paraganglioma Patients With and Without Germline SDHB Mutation

ObjectiveTo compare metastatic pheochromocytoma/paraganglioma (MPP) patients with germline SDHB mutations (SDHB MPP) and without SDHB mutations (non-SDHB MPP) in terms of baseline clinical manifestations, tumor characteristics, and outcomes.MethodsClinical data were retrospectively reviewed in 101 MPP patients, including 34 SDHB MPP patients and 61 non-SDHB MPP patients.ResultsSDHB MPP patients presented at a younger age at onset, diagnosis, or metastasis (25 ± 16 vs 36 ± 14, 28 ± 17 vs 38 ± 15, and 31 ± 17 vs 44 ± 14 years old, respectively, P < .01 for all) than non-SDHB patients. Compared with their non-SDHB counterparts, SDHB patients were more likely to have paragangliomas (83% vs 47%, P < .05), synchronous metastases (44% vs 23%, P < .05), bone metastases (80% vs 48%, P < .01), and a shorter progression-free survival (3 years vs 5 years, P < .01). The Ki-67 index was higher in SDHB tumors (P < .05). The 5- and 10-year survival rates were 79% and 74%, respectively, in all patients. Seventeen patients died from MPP, and the time from metastasis to death in patients who had received systemic therapy was significantly longer than in those who had not (3.1 ± 1.5 vs 1.4 ± 0.7 years, P < .01).ConclusionCompared with MPP patients without SDHB mutations, MPP patients with SDHB mutations were younger at onset, diagnosis, or metastasis; had a higher incidence of synchronous metastases, higher ratio of paraganglioma, and higher Ki-67 index; had a shorter postoperative progression-free survival; and were more likely to develop bone metastasis or sole liver metastasis. Our results suggest that patients with SDHB mutations should be identified early and monitored regularly to achieve optimal clinical outcomes.     

Does Multifocal Papillary Thyroid Microcarcinoma With a Total Tumor Diameter >1 cm Indicate Poor Biological Behavior? The Evidence is Insufficient

ObjectiveMultifocal cancer is common in papillary thyroid microcarcinoma (PTMC). Our aim was to investigate the correlation between multifocal PTMC, total tumor diameter (TTD), and clinicopathologic features.MethodsIn total, 206 patients were included and grouped as stage cT1a or cT1b. The primary tumor diameter and TTD (the sum of the maximal diameter of each focus) were calculated. These patients were further subgrouped as TTD ≤1 cm or 1 cm < TTD ≤ 2 cm. The relationships of clinicopathological features between these groups were analyzed.ResultsMultifocal cancer was more likely to occur with stage cT1a than stage cT1b (P = .028). Stage cT1b papillary thyroid carcinoma was more prone to central lymph node metastasis (CLNM) and capsular invasion than stage cT1a. There was no difference in clinicopathological factors, such as sex, age, CLNM, number of CLNMs, capsular invasion, BRAF mutation, or recurrence between the multifocal PTMC and TTD >1 cm and primary tumor diameter + TTD ≤1 cm groups. Comparing stage cT1a and cT1b tumors with a 1 cm < TTD ≤ 2 cm using a multivariate analysis, stage cT1b tumors were more prone to capsular invasion than stage cT1a tumors, with an odds ratio of 19.013 (95% confidence interval, 2.295-157.478), but there was no significant correlation with CLNM.ConclusionStage cT1b tumors are more prone to capsular invasion and CLNM than than stage cT1a tumors. For multifocal PTMC, calculating the TTD to evaluate adverse biological behavior is insufficient and limited, and further research is needed.     

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors’ samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.     

Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma

Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry–based proteomics methods. We conducted label-free liquid chromatography–tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20). Based on progression-free survival (PFS), the samples were divided into two groups: good (PFS ≥18 months) and poor prognosis groups (PFS <18 months). Proteomic profiles were compared between the two groups. Referring to proteomics data that we previously obtained using frozen cancer tissues from chemotherapy-naïve patients with HGSOC, overlapping protein biomarkers were selected as candidate biomarkers. Biomarkers were validated using an independent set of HGSOC plasma samples (n = 202) via enzyme-linked immunosorbent assay (ELISA). To construct models predicting the 18-month PFS rate, we performed stepwise selection based on the area under the receiver operating characteristic curve (AUC) with 5-fold cross-validation. Analysis of differentially expressed proteins in plasma samples revealed that 35 and 61 proteins were upregulated in the good and poor prognosis groups, respectively. Through hierarchical clustering and bioinformatic analyses, GSN, VCAN, SND1, SIGLEC14, CD163, and PRMT1 were selected as candidate biomarkers and were subjected to ELISA. In multivariate analysis, plasma GSN was identified as an independent poor prognostic biomarker for PFS (adjusted hazard ratio, 1.556; 95% confidence interval, 1.073–2.256; p = 0.020). By combining clinical factors and ELISA results, we constructed several models to predict the 18-month PFS rate. A model consisting of four predictors (FIGO stage, residual tumor after surgery, and plasma levels of GSN and VCAN) showed the best predictive performance (mean validated AUC, 0.779). The newly developed model was converted to a nomogram for clinical use. Our study results provided insights into protein biomarkers, which might offer clues for developing therapeutic targets.     

Relative Quantification of Proteins in Formalin-Fixed Paraffin-Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays

The identification of clinically relevant biomarkers represents an important challenge in oncology. This problem can be addressed with biomarker discovery and verification studies performed directly in tumor samples using formalin-fixed paraffin-embedded (FFPE) tissues. However, reliably measuring proteins in FFPE samples remains challenging. Here, we demonstrate the use of liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM/MS) as an effective technique for such applications. An LC-MRM/MS method was developed to simultaneously quantify hundreds of peptides extracted from FFPE samples and was applied to the targeted measurement of 200 proteins in 48 triple-negative, 19 HER2-overexpressing, and 20 luminal A breast tumors. Quantitative information was obtained for 185 proteins, including known markers of breast cancer such as HER2, hormone receptors, Ki-67, or inflammation-related proteins. LC-MRM/MS results for these proteins matched immunohistochemistry or chromogenic in situ hybridization data. In addition, comparison of our results with data from the literature showed that several proteins representing potential biomarkers were identified as differentially expressed in triple-negative breast cancer samples. These results indicate that LC-MRM/MS assays can reliably measure large sets of proteins using the analysis of surrogate peptides extracted from FFPE samples. This approach allows to simultaneously quantify the expression of target proteins from various pathways in tumor samples. LC-MRM/MS is thus a powerful tool for the relative quantification of proteins in FFPE tissues and for biomarker discovery.