Dataset Information

Quantitative Proteomics Identifies Sytenin-1 as a Universal Biomarker of Exosomes

ABSTRACT: Exosomes are extracellular vesicles derived from the endosomal compartment. They contain a multitude of bioactive constituents and mediate intercellular communication in health and disease. The frequently used biomarkers of exosomes are heterogeneous and do not exhibit universal utility across different cell types. To uncover ubiquitous and abundant proteins that can serve as universal biomarkers of exosomes, we employed an unbiased and quantitative proteomic approach based on Super SILAC coupled to high-resolution mass spectrometry (MS). In total 1,243 proteins were consistently quantified in the proteome of exosomes, irrespective of the cellular source or isolation method. Among them, a cohort of 22 proteins were universally enriched, and 15 proteins consistently depleted in the proteome of exosomes when compared to cells. Among the enriched proteins, we found several membrane proteins and GTPases, whereas the cohort of depleted proteins was predominantly composed by nuclear proteins. Our study revealed that Syntenin-1 is the most abundant ubiquitous protein in exosomes from distinct cell sources, thus representing an ideal candidate for universal biomarker of exosomes.

INSTRUMENT(S): Orbitrap Fusion Lumos, Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: Kelly Hodge

LAB HEAD: Sara Zanivan

PROVIDER: PXD020260 | Pride | 2021-06-10

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20180626_KEH_HF_SA_FEK_EXT_040618_BJ-r01_010.raw	Raw
	20180626_KEH_HF_SA_FEK_EXT_040618_BJ-r02_011.raw	Raw
	20180626_KEH_HF_SA_FEK_EXT_040618_BJ-r03_012.raw	Raw
	20180626_KEH_HF_SA_FEK_EXT_040618_MCF10A-r01_007.raw	Raw
	20180626_KEH_HF_SA_FEK_EXT_040618_MCF10A-r02_008.raw	Raw

Items per page:

1 - 5 of 63

Similar Datasets

Project description:Background: A fundamental hallmark of cancer cells is their ability to sustain proliferative signaling and cell survival, reflected in a cellular chemotherapy response that is poorly understood. We questioned whether chemotherapy modulated phospho-signaling at 4 and 24 h in vivo could provide information about long-term survival in acute myeloid leukemia (AML), and if the signaling response to therapy was more informative than analysis at time of diagnosis. Methods: Peripheral blood was collected from 32 younger AML patients (age 16-74 years), before, 4- and 24 hours after start of induction chemotherapy. Samples were analyzed by 36-dimensional mass cytometry for assessment of alterations in immunophenotypes and intracellular signaling using unsupervised and supervised machine learning approaches. Results were validated by RNA sequencing and mass spectrometry proteomics (Super SILAC). Targeted sequencing was used to characterize patient samples for recurrent AML mutations. Drug sensitivity and resistance testing ex vivo was compared to activation of relevant signal transduction pathways and mutational profile. Findings: 5-year patient survival was accurately predicted in the leukemic cell population at 24 hours after therapy onset by phospho-proteins p-ERK1/2 (T202/Y204) and p-p38 (T180/Y182). RNA sequencing showed induction of MAPK target gene expression and the AP-1 transcription complex in patients with high p-ERK1/2. Super-SILAC proteomics confirmed an increase in the abundance of p38 prime target MAPKAPK2(MK2) 24 hours after start of induction therapy. Ex vivo drug sensitivity testing demonstrated high sensitivity to MEK inhibitors in the patient cells with high p-ERK1/2 measured at diagnosis or 24 hours after start of chemotherapy. Interpretation: Early single cell signaling response to chemotherapy provided precise prognostic information independent of stratification by genetics. We propose that early functional measurement of chemotherapy-potentiated MAPK pathway signaling could identify non-responders to intensive chemotherapy allowing precise treatment adjustment.

Dataset Information

Quantitative Proteomics Identifies Sytenin-1 as a Universal Biomarker of Exosomes

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets