The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends DOI Creative Commons
Philipp E. Geyer, Daniel Hornburg, Maria Pernemalm

и другие.

Journal of Proteome Research, Год журнала: 2024, Номер unknown

Опубликована: Окт. 31, 2024

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest using these novel methods for studying the circulating proteome, as blood offers accessible window into health. However, every methodological innovation and analytical progress calls reassessing existing approaches routines ensure that new data will add value greater biomedical research community avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present 2024 survey current community, including latest build PeptideAtlas now comprises 4608 proteins detected 113 sets. We then discuss updates established methods, emerging technologies, investigations proteoforms, protein networks, extracellualr vesicles, antibodies microsamples. Finally, provide a prospective view tools studies proteins.

Язык: Английский

Metastatic phenotype and immunosuppressive tumour microenvironment in pancreatic ductal adenocarcinoma: Key role of the urokinase plasminogen activator (PLAU) DOI Creative Commons
S. M. Zahid Hosen, Md. Nazim Uddin, Zhihong Xu

и другие.

Frontiers in Immunology, Год журнала: 2022, Номер 13

Опубликована: Дек. 14, 2022

Background Previous studies have revealed the role of dysregulated urokinase plasminogen activator (encoded by PLAU ) expression and activity in several pathways associated with cancer progression. However, systematic investigation into association factors that modulate PDAC (pancreatic ductal adenocarcinoma) progression is lacking, such as those affecting stromal stellate cell, PSC)-cancer cell interactions, tumour immunity, subtypes clinical outcomes from potential inhibition. Methods This study used an integrated bioinformatics approach to identify prognostic markers correlated using different transcriptomics, proteomics, data sets. We then determined signatures oncogenic pathways, metastatic phenotypes, stroma, immunosuppressive microenvironment (TME) outcome. Finally, vivo orthotopic model pancreatic cancer, we confirmed predicted effect inhibiting on growth metastasis. Results Our analyses upregulation not only numerous other but also activation various signalling aggressive phenotypes relevant metastasis, proliferation, epithelial-mesenchymal transition (EMT), stemness, hypoxia, extracellular matrix (ECM) degradation, signatures, immune suppression (TME). Moreover, was directly connected known mediate PSC-cancer interactions. Furthermore, basal/squamous phenotype significantly reduced overall survival, indicating this subset patients may benefit therapeutic interventions inhibit activity. a clinically showed even short-term inhibition sufficient halt and, importantly, eliminate visible Conclusion Elevated correlates increased score, PDAC. closely basal subtype type PDAC; are at high risk mortality disease targeting .

Язык: Английский

Процитировано

30

Fast proteomics with dia‐PASEF and analytical flow‐rate chromatography DOI Creative Commons
Łukasz Szyrwiel,

Christoph Gille,

Michael Mülleder

и другие.

PROTEOMICS, Год журнала: 2023, Номер 24(1-2)

Опубликована: Июнь 7, 2023

Abstract Increased throughput in proteomic experiments can improve accessibility of platforms, reduce costs, and facilitate new approaches systems biology biomedical research. Here we propose combination analytical flow rate chromatography with ion mobility separation peptide ions, data‐independent acquisition, data analysis the DIA‐NN software suite, to achieve high‐quality from limited sample amounts, at a up 400 samples per day. For instance, when benchmarking our workflow using 500‐μL/min 3‐min chromatographic gradients, report quantification 5211 proteins 2 μg mammalian cell‐line standard high quantitative accuracy precision. We further used this platform analyze blood plasma cohort COVID‐19 inpatients, gradient alternating column regeneration on dual pump system. The method delivered comprehensive view proteome, allowing classification patients according disease severity revealing biomarker candidates.

Язык: Английский

Процитировано

23

Comprehensive proteomics and meta-analysis of COVID-19 host response DOI Creative Commons
Haris Babačić, Wanda Christ, J.E. Araújo

и другие.

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Сен. 22, 2023

Abstract COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered be mediated blood. Therefore, better understand host response SARS-CoV-2 infection, we performed systematic analyses circulating, soluble proteins blood through global proteomics mass-spectrometry (MS) proteomics. Here, show that a large part proteome altered COVID-19, among them elevated levels interferon-induced and proteasomal proteins. Some have alternating cells after infection vitro different organs patients deregulated blood, suggesting shared infection-related changes.The availability public proteomic resources on alterations leaves uncertainty about change given protein during COVID-19. Hence, review meta-analysis MS studies proteomes, including up 1706 individuals (1039 patients), provide concluding estimates for alteration 1517 Finally, based developed CoViMAPP, an open-access resource effect sizes diagnostic potential publicly available research, clinical, academic community.

Язык: Английский

Процитировано

21

Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation DOI Creative Commons
Anders Mälarstig, Felix Graßmann, Leo Dahl

и другие.

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Ноя. 24, 2023

Abstract Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source biomarker discovery but so far, few proteins have been identified with risk. Here, we measure 2929 unique in plasma from 598 women selected the Karolinska Mammography Project explore association between protein levels, clinical characteristics, gene variants, identify a causal role cancer. We present 812 cis-acting quantitative trait loci 737 which are used as instruments Mendelian randomisation analyses Of those, five (CD160, DNPH1, LAYN, LRRC37A2 TLR1) that show potential risk confirmatory results independent cohorts. Our study suggests these should be further explored biomarkers drug targets

Язык: Английский

Процитировано

21

Longitudinal Fluctuations in Protein Concentrations and Higher-Order Structures in the Plasma Proteome of Kidney Failure Patients Subjected to a Kidney Transplant DOI Creative Commons
Sofia Kalaidopoulou Nteak,

Franziska Völlmy,

Marie V. Lukassen

и другие.

Journal of Proteome Research, Год журнала: 2024, Номер 23(6), С. 2124 - 2136

Опубликована: Май 3, 2024

Using proteomics and complexome profiling, we evaluated in a year-long study longitudinal variations the plasma proteome of kidney failure patients, prior to after transplantation. The post-transplant period was complicated by bacterial infections, resulting dramatic changes proteome, attributed an acute phase response (APR). As positive proteins (APPs), being elevated upon inflammation, observed well-described C-reactive protein Serum Amyloid A (SAA), but also Fibrinogen, Haptoglobin, Leucine-rich alpha-2-glycoprotein, Lipopolysaccharide-binding protein, Alpha-1-antitrypsin, Alpha-1-antichymotrypsin, S100, CD14. negative APPs, downregulated identified well-documented Serotransferrin Transthyretin, added Kallistatin, Heparin cofactor 2, interalpha-trypsin inhibitor heavy chain H1 H2 (ITIH1, ITIH2). For patient with most severe APR, performed profiling SEC-LC-MS on all samples. We that several displaying alike concentration patterns coelute form macromolecular complexes. By expose how SAA1 SAA2 become incorporated into high-density lipid particles, replacing largely Apolipoprotein (APO)A1 APOA4. Overall, our data highlight combination in-depth can shed further light correlated abundance inflammatory events.

Язык: Английский

Процитировано

8

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project DOI
Gilbert S. Omenn, Lydie Lane, Christopher M. Overall

и другие.

Journal of Proteome Research, Год журнала: 2021, Номер 20(12), С. 5227 - 5240

Опубликована: Окт. 20, 2021

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) 19 778 predicted proteins coded in human genome, a gain 483 since 2020 from reports throughout world reanalyzed by HPP. Conversely, number neXtProt PE2, PE3, and PE4 missing reduced 478 to 1421. This represents remarkable progress on proteome parts list. utilization proteomics broad array biological clinical studies likewise continues expand with many important findings effective integration other omics platforms. We present highlights Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, Cancers B/D-HPP teams Knowledgebase, Mass Spectrometry, Antibody Profiling, Pathology resource pillars, as well ethical considerations biomarkers.

Язык: Английский

Процитировано

37

A proteomic meta-analysis refinement of plasma extracellular vesicles DOI Creative Commons

Milene C. Vallejo,

Soumyadeep Sarkar, Emily C. Elliott

и другие.

Scientific Data, Год журнала: 2023, Номер 10(1)

Опубликована: Ноя. 28, 2023

Abstract Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data refine the EV composition by separating proteins contaminants into different clusters. We obtained two clusters with total 1717 that were depleted known enriched markers independently validated 71% true-positive. These had 133 differentiation (CD) antigens from signaling. compared our deposited PeptideAtlas, making refined protein list resource for mechanistic studies. As use case example this resource, type 1 diabetes proplatelet basic EVs showed it regulates apoptosis β cells macrophages, key players disease development. Our approach provides refinement scientific community.

Язык: Английский

Процитировано

14

Identification of Novel Biomarkers for Alzheimer’s Disease and Related Dementias Using Unbiased Plasma Proteomics DOI Creative Commons
Benjamin Lacar, Shadi Ferdosi, Amir Hossein Alavi

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 8, 2024

Abstract Alzheimer’s disease (AD) and related dementias (ADRD) is a complex with multiple pathophysiological drivers that determine clinical symptomology progression. These diseases develop insidiously over time, through many pathways mechanisms continue to have huge societal impact for affected individuals their families. While emerging blood-based biomarkers, such as plasma p-tau181 p-tau217, accurately detect Alzheimer neuropthology are associated faster cognitive decline, the full extension of proteomic changes in ADRD remains unknown. Earlier detection better classification different subtypes may provide opportunities earlier, more targeted interventions, perhaps higher likelihood successful therapeutic development. In this study, we aim leverage unbiased mass spectrometry proteomics identify novel, biomarkers decline. 1,786 samples from 1,005 patients were collected 12 years partcipants Massachusetts Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, dementia rating (CDR) scores taken concurrently. The Proteograph TM Product Suite (Seer, Inc.) liquid-chromatography mass-spectrometry (LC-MS) analysis used process cohort generate data. Data-independent acquisition (DIA) results yielded 36,259 peptides 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD healthy controls. Machine learning diagnosis identified potential candidate including MBP, BGLAP, APoD. Cox regression created association progression suggest CLNS1A, CRISPLD2, GOLPH3 targets further investigation biomarkers. workflow provided deep, coverage proteome at speed enabled study almost 1,800 samples, which largest, conducted date.

Язык: Английский

Процитировано

6

Proteomics of prostate cancer serum and plasma using low and high throughput approaches DOI Creative Commons
Ghaith M. Hamza, Rekha Raghunathan,

Stephanie Kay Ashenden

и другие.

Clinical Proteomics, Год журнала: 2024, Номер 21(1)

Опубликована: Март 12, 2024

Abstract Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations biomarker disease studies. In this work, we used cutting-edge technologies to construct label-based label-free workflows, capable of quantifying approximately 2,000 proteins biofluids. With 70µL blood a single depletion strategy, conducted an analysis homogenous cohort ( n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) healthy donors. The results revealed dozens differentially expressed both plasma serum. We identified the upregulation Prostate Specific Antigen (PSA), well-known for cancer, serum cohort. Further bioinformatics highlighted noteworthy which appear be secreted into bloodstream, making them good candidates further exploration.

Язык: Английский

Процитировано

6

Secretome analysis using Affinity Proteomics and Immunoassays: a focus on Tumor Biology DOI Creative Commons
Vanessa M. Beutgen, V. A. Shinkevich,

Johanna Pörschke

и другие.

Molecular & Cellular Proteomics, Год журнала: 2024, Номер 23(9), С. 100830 - 100830

Опубликована: Авг. 14, 2024

The study of the cellular secretome using proteomic techniques continues to capture attention research community across a broad range topics in biomedical research. Due their untargeted nature, independence from model system used, historically superior depth analysis, as well comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based assays have massively gained analytical depth, which together with high sensitivity, dynamic coverage throughput capabilities render them exquisitely suited analysis. In this review, we revisit challenges implied by secretomics and provide an overview platforms currently available for analyses, tumor example basic translational

Язык: Английский

Процитировано

6