Dataset Information

Shotgun proteomics of thyroid carcinoma exosomes: insight into the role of exosomal proteins in carcinogenesis and thyroid homeostasis

ABSTRACT: The transport of molecules via exosomes is one of the factors involved in cancer development, and transferred molecules can serve as specific tumor biomarkers. The aim of the study was the LC MS/MS proteomic analysis of exosomes released by FTC and 8305C thyroid cancer cell lines, and reference Nthy-ori 3-1 normal thyroid follicular cells. A total of 1769 unique proteins were identified in the exosome samples. For exosomes derived from Nthy ori 3 1 cell the highest number of 1504 proteins was identified, while exosomes from thyroid carcinomas FTC and 8305C cell lines had 730 and 1304 identified proteins, respectively. For the identified proteins, gene ontology analysis was performed in terms of their cellular location, molecular function and involvement in biological processes. For proteins that only appeared in tumor derived FTC- and 8305C-derived exosomes, enriched categories were related to cancer progression and included cell adhesion and positive regulation of cell migration. Also, proteins related to protein N linked glycosylation, drug resistance, and cell response to NK and T cell cytotoxicity were among those unique proteins. Finally label free quantification (LFQ) was performed for identified differentially expressed proteins between all possible group parings. For exosomes from thyroid cancer cells, the most differentiating proteins included collagen alpha 2(I) chain, tenascin, matrix metalloproteinase 1, Interstitial collagenase and C type lectin domain family 11 member A. The obtained results broadened the knowledge about the role of exosomal proteins in thyroid cancer and indicated potential biomarkers for further evaluation in clinical conditions.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Malgorzata Przybylo

PROVIDER: MSV000093152 | MassIVE | Thu Oct 19 06:28:00 BST 2023

SECONDARY ACCESSION(S): PXD046240

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Shotgun proteomics of thyroid carcinoma exosomes - Insight into the role of exosomal proteins in carcinogenesis and thyroid homeostasis.

Surman Magdalena M Wilczak Magdalena M Jankowska Urszula U Skupień-Rabian Bożena B Przybyło Małgorzata M

Biochimica et biophysica acta. General subjects 20240716 9

<h4>Background</h4>Transport of molecules via exosomes is one of the factors involved in thyroid cancer development, and transported molecules may serve as cancer biomarkers. The aim of the study was to characterize protein content of thyroid-derived exosomes and their functional effect exerted on recipient cells.<h4>Methods</h4>LC-MS/MS proteomics of exosomes released by FTC and 8305C thyroid carcinoma cell lines, and Nthy-ori 3-1 normal thyroid follicular cells was performed, followed by bioin ...[more]

PMID: 39025337

Similar Datasets

Project description:<p><strong>BACKGROUND:</strong> Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.</p><p><strong>METHODS:</strong> Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.</p><p><strong>RESULTS: </strong>Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.</p><p><strong>CONCLUSIONS:</strong> IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.</p>

Project description:Background. Radioiodide 131I is commonly used to treat thyroid cancer and hyperthyroidism, and 131I releases during nuclear accidents have resulted in increased incidence of thyroid cancer in children. To develop a better understanding of underlying cellular mechanisms behind 131I exposure and identify potential biomarkers, the aim of this work was to study the long-term dose-related effects of 131I exposure in thyroid tissue and plasma in young rats. Materials and methods. Male Sprague Dawley rats (5-week-old) were i.v. injected with 0.5, 5.0, 50 or 500 kBq 131I (Dthyroid ca 1–1000 mGy), and killed after nine months at which time the thyroid and blood samples were collected. Gene expression microarray analysis (thyroid samples) and LC-MS/MS analysis (thyroid and plasma samples) were performed to assess differential gene and protein expression patterns in treated and corresponding untreated control samples. Bioinformatics analyses were performed using the DAVID functional annotation tool and Ingenuity Pathway Analysis (IPA). Results. Nine 131I exposure-related biomarkers (Afp and RT1-Bb,ARF3, DLD, IKBKB, NONO, RAB6A, RPN2, and SLC25A5) were identified in thyroid tissue. Four dose-related biomarker candidates (APRT, LDHA) and (TGM3 and DSG4) were identified in thyroid and plasma, respectively. Candidate biomarkers for thyroid function were the upstream regulator PPARG and the proteins ACADL and SORBS2 (all activities), TPO and TG (low activities)). 131I exposure was shown to have a profound effect on metabolism, the immune system, apoptosis and cell death. Furthermore, several signalling pathways essential for normal cellular function (actin cytoskeleton signalling, HGF signalling, NRF2-mediated oxidative stress, integrin signalling, calcium signalling) were also significantly regulated. Conclusion. Exposure-related and dose-related effects on gene and protein expression were observed, thereby identifying several candidate genes that could be used as potential biomarkers for exposure, absorbed dose and thyroid function.

Project description:Thiele2013 - Thyroid gland glandular cells The model of thyroid gland glandular cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000 ). This model is described in the article: A community-driven global reconstruction of human metabolism. Thiele I, et al . Nature Biotechnology Abstract: Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/. This model is hosted on BioModels Database and identified by: MODEL1310110015 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.