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A high-resolution mass spectrometry based proteomic dataset of human regulatory T cells.

ABSTRACT: Regulatory T cells (Tregs) play a core role in maintaining immune tolerance, homeostasis, and host health. High-resolution analysis of the Treg proteome is required to identify enriched biological processes and pathways distinct to this important immune cell lineage. We present a comprehensive proteomic dataset of Tregs paired with conventional CD4⁺ (Conv CD4⁺) T cells in healthy individuals. Tregs and Conv CD4⁺ T cells were sorted to high purity using dual magnetic bead-based and flow cytometry-based methodologies. Proteins were trypsin-digested and analysed using label-free data-dependent acquisition mass spectrometry (DDA-MS) followed by label free quantitation (LFQ) proteomics analysis using MaxQuant software. Approximately 4,000 T cell proteins were identified with a 1% false discovery rate, of which approximately 2,800 proteins were consistently identified and quantified in all the samples. Finally, flow cytometry with a monoclonal antibody was used to validate the elevated abundance of the protein phosphatase CD148 in Tregs. This proteomic dataset serves as a reference point for future mechanistic and clinical T cell immunology and identifies receptors, processes, and pathways distinct to Tregs. Collectively, these data will lead to a better understanding of Treg immunophysiology and potentially reveal novel leads for therapeutics seeking Treg regulation.

SUBMITTER: Weerakoon H

PROVIDER: S-EPMC8671522 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Retinoblastoma is an ocular neoplastic cancer caused primarily due to the mutation/deletion of RB1 gene. Due to the rarity of the disease very limited information is available on molecular changes in primary retinoblastoma. High throughput analysis of retinoblastoma transcriptome is available however the proteomic landscape of retinoblastoma remains unexplored. In the present study we used high resolution mass spectrometry-based quantitative proteomics to identify proteins associated with pathogenesis of retinoblastoma. METHODS:We used five pooled normal retina and five pooled retinoblastoma tissues to prepare tissue lysates. Equivalent amount of proteins from each group was trypsin digested and labeled with iTRAQ tags. The samples were analyzed on Orbitrap Velos mass spectrometer. We further validated few of the differentially expressed proteins by immunohistochemistry on primary tumors. RESULTS:We identified and quantified a total of 3587 proteins in retinoblastoma when compared with normal adult retina. In total, we identified 899 proteins that were differentially expressed in retinoblastoma with a fold change of ?2 of which 402 proteins were upregulated and 497 were down regulated. Insulin growth factor 2 mRNA binding protein 1 (IGF2BP1), chromogranin A, fetuin A (ASHG), Rac GTPase-activating protein 1 and midkine that were found to be overexpressed in retinoblastoma were further confirmed by immunohistochemistry by staining 15 independent retinoblastoma tissue sections. We further verified the effect of IGF2BP1 on cell proliferation and migration capability of a retinoblastoma cell line using knockdown studies. CONCLUSIONS:In the present study mass spectrometry-based quantitative proteomic approach was applied to identify proteins differentially expressed in retinoblastoma tumor. This study identified the mitochondrial dysfunction and lipid metabolism pathways as the major pathways to be deregulated in retinoblastoma. Further knockdown studies of IGF2BP1 in retinoblastoma cell lines revealed it as a prospective therapeutic target for retinoblastoma.

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A high-resolution mass spectrometry based proteomic dataset of human regulatory T cells.

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