PROTEOMICS – Clinical Applications最新文献

Purpose: Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis of more than 1500 samples from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial of adults with type 2 diabetes.

Methods: Using LC-MS with data-independent acquisition we evaluated four variables: plasma protein depletion, EDTA or citrated anti-coagulant blood collection tubes, plasma lipid depletion strategies and plasma freeze-thaw cycles. Optimised methods were applied in a pilot study of FIELD participants.

Results: LC-MS of undepleted plasma conducted over a 45 min gradient yielded 172 proteins after excluding immunoglobulin isoforms. Cibachrome-blue-based depletion yielded additional proteins but with cost and time expenses, while immunodepleting albumin and IgG provided few additional identifications. Only minor variations were associated with blood collection tube type, delipidation methods and freeze-thaw cycles. From 65 batches involving over 1500 injections, the median intra-batch quantitative differences in the top 100 proteins of the plasma external standard were less than 2%. Fenofibrate altered seven plasma proteins.

Conclusions and clinical relevance: A robust plasma handling and LC-MS proteomics workflow for abundant plasma proteins has been developed for large-scale biomarker studies that balance proteomic depth with time and resource costs.

Purpose: Apolipoprotein monitoring is useful for diagnosing cardiovascular diseases, as they are risk factors of arteriosclerosis and other neutral fat-related diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is advantageous for simultaneous apolipoprotein quantification, differentiation, and standardization including their isoforms. However, fast and straightforward sample preparation that retains quantification accuracy remains challenging in clinical MS.

Experimental design: We developed a simultaneous assay for serum apolipoprotein A-I (ApoA-I), apolipoprotein B100 family, and apolipoprotein C-III (ApoC-III) using a high-throughput LC-MS/MS platform coupled with a BRAVO system. The assay was simplified by using sodium deoxycholate and trypsin/lys-C without reduction and alkylation steps.

Results: Simple sample preparation reduced turnaround time by 1.5 h and neat goat serum was chosen as an optimal calibration matrix for accurate protein quantification. Assay precision, linearity, correlation, accuracy, limit of detection (LOD), limit of quantitation (LOQ), and carryover were validated according to CLSI guidelines over 41 days using more than 100 human serum samples. Good correlation compared with turbidimetric immunoassay (TIA) was observed by Deming regression for all analytes.

Conclusions and clinical relevance: A high-throughput LC-MS/MS and BRAVO assay for simultaneous apolipoprotein analysis was validated using a simple preparation method with a human serum calibrator in goat serum matrix. The assay is readily expandable to include other target serum proteins and/or their isoforms.

Purpose: Lung cancer (LC) is the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and poor prognosis. Saliva is an important source for discovering biomarkers and contains an abundance of biological information. The purpose of this study was to determine whether galactosylation levels of salivary proteins are associated with LC.

Experimental design: First, we analyzed the alterations of the glycopatterns recognized by Bandeiraea Simplicifolia Lectin I (BS-I) in five groups (healthy volunteers [HV]: 28, benign pulmonary disease [BPD]: 27, lung adenocarcinoma [ADC]: 39, squamous cell carcinoma [SCC]: 28, small-cell lung cancer [SCLC]: 22) of 144 saliva samples using lectin microarrays. Pooled samples from each group were subsequently validated by the lectin blotting technique. Finally, the N-glycan profiles of their salivary glycoproteins isolated by the BS-I-magnetic particle conjugates from pooled samples for each group were analyzed by MALDI-TOF/TOF-MS.

Results: The results showed that the expression level of galactosylated glycans recognized by BS-I was significantly increased in patients with LC compared with BPD and HV. Receiver operating characteristic (ROC) analysis indicated that the levels of salivary glycopattern recognized by BS-I could discriminate lung disease (BPD, ADC, SCC, and SCLC) and HV with an AUC of 0.700 (95% CI: 0.589-0.812), and discriminate LC and BPD with an AUC of 0.860 (95% CI: 0.763-0.956). Also, the proportion of galactosylated N-glycans in ADC (38.4%), SCC (43.1%), and SCLC (39.5%) increased compared to HV (30.1%) and BPD (33.7%), and two galactosylated N-glycan peaks (m/z 1828.683, 2418.853) could be identified only in the LC groups (ADC, SCC, and SCLC).

Conclusions and clinical relevance: These findings could provide crucial information on galactosylated N-linked glycans associated with LC and facilitate the study of LC biomarkers based on precise alterations of galactosylated N-glycans in saliva.

Background: Mycosis Fungoides (MF) is a common cutaneous T-cell lymphoma. It can sometimes be challenging to diagnose MF using current clinico-histopathological criteria. Non-invasive molecular profiling analysis has the potential to aid the diagnosis and understanding of MF.

Method: Lesional and body site matched normal stratum corneum samples were obtained from the same MF patients (n = 28) using adhesive discs, followed by proteomic analyses using data-independent acquisition mass spectrometry (DIA-MS). Differential abundance analyses and bioinformatic analyses were performed to identify differentially abundant proteins and altered biofunctions between the MF and normal stratum corneum samples.

Results: In total, 1303 proteins were identified, of which 290 proteins were significantly changed in the MF cohort compared to the normal stratum corneum. Ingenuity pathway analysis (IPA) predicted the significant inhibition of cell death of cancer cells and significant activation of immune-related activities and viral infection in the MF lesions. MF lesions were also associated with upstream regulators relating to immuno-oncologic dysfunctions. The top-250 variating proteins efficiently separated normal stratum corneum from matched MF samples.

Conclusion: Non-invasive proteomic analysis could transform the diagnosis of MF by reducing the need for invasive biopsy. The identification of altered biological functions may serve as useful biomarkers to predict MF progression.

Purpose: Chronic kidney disease (CKD) is defined by a reduced renal function, that is, glomerular filtration rate, and the extent of kidney damage is assessed by determining serum creatinine levels and proteins in urine, diagnosed as proteinuria/albuminuria. Albuminuria increases with age and can result from glomerular and/or proximal tubule (PT) alterations. Brush border membranes (BBMs) on PT cells are important in maintaining the stability of PT functions.

Experimental design: An LC-MS/MS bottom-up proteomics analysis of BBMs from four groups of rat models was applied to investigate protein abundance alterations associated with CKD progression. Moreover, systems biology analyses were used to identify key proteins that can provide insight into the different regulated molecular pathways and processes associated with CKD.

Results: Our results indicated that 303 proteins showed significantly altered expressions from the severe CKD BBM group when compared to the control. Focusing on renal diseases, several proteins including Ctnnb1, Fah, and Icam1 were annotated to kidney damage and urination disorder. The up-regulation of Ctnnb1 (β-catenin) could contribute to CKD through the regulation of the WNT signaling pathway.

Conclusion and clinical relevance: Overall, the study of protein abundance changes in BBMs from rat models helps to reveal protein corrections with important pathways and regulator effects involved in CKD. Although this study is focused on rat models, the results provided more information for a deeper insight into possible CKD mechanisms in humans.

Purpose: Lung cancer is the most common cause of death from cancer worldwide, largely due to late diagnosis. Thus, there is an urgent need to develop new approaches to improve the detection of early-stage lung cancer, which would greatly improve patient survival.

Experimental design: The quantitative protein expression profiles of microvesicles isolated from the sera from 46 lung cancer patients and 41 high-risk non-cancer subjects were obtained using a mass spectrometry method based on a peptide library matching approach.

Results: We identified 33 differentially expressed proteins that allow discriminating the two groups. We also built a machine learning model based on serum protein expression profiles that can correctly classify the majority of lung cancer cases and that highlighted a decrease in the levels of Arysulfatase A (ARSA) as the most discriminating factor found in tumors.

Conclusions and clinical relevance: Our study identified a preliminary, non-invasive protein signature able to discriminate with high specificity and selectivity early-stage lung cancer patients from high-risk healthy subjects. These results provide the basis for future validation studies for the development of a non-invasive diagnostic tool for lung cancer.

Purpose: Peritoneal carcinomatosis (PC), metastasized from colorectal cancer (CRC), remains a highly lethal disease. Outcomes of PC is significantly influenced by the amount of intra-abdominal tumor burden and therefore diagnostic tests that facilitate earlier diagnosis could improve PC treatment and patient outcomes.

Experimental design: Using mass-spectrometry-based proteomics, we characterized the protein features of circulating exosomes in the context of CRC PC, CRC with liver metastasis, and primary CRC limited to the colon. We profiled exosomes isolated from patient plasma to identify exosome-associated protein cargoes released by these cancer types.

Results: Analysis of the resulting data identified metastasis-specific exosome protein signatures. Bioinformatic analyses confirmed enrichment of proteins annotated to vesicle-associated processes and intracellular compartments, as well as representation of cancer hallmark functions and processes.

Conclusion and clinical relevance: This research yielded distinct protein profiles for the CRC patient groups and suggests the utility of plasma exosome proteomic analysis for a better understanding of PC development and metastasis.