Ontology highlight
ABSTRACT:
PROVIDER: PRJEB38062 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR4079050.fastq.gz | Fastqsanger.gz | |||
| ERR4079060.fastq.gz | Fastqsanger.gz | |||
| ERR4079070.fastq.gz | Fastqsanger.gz | |||
| ERR4079080.fastq.gz | Fastqsanger.gz | |||
| ERR4079090.fastq.gz | Fastqsanger.gz |
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Project description:Decreased salivary flow rates and/or changes in protein composition reported after autologous hematopoietic stem cell transplantation (ASCT) reduces the protective function of saliva. This might be associated with the development of oral mucositis (OM), an inflammation of the oral mucosa as a result of chemotherapy before ASCT which affects patients, quality of life and risk factor for systemic infections. In this study, a TMT-labelled proteomics experiment, a label-free quantification (LFQ) proteomics experiment and a DIA-MS proteomics experiment were used to identify differences in the salivary proteome between patients with ulcerative OM (uOM; WHO score 2) and those without (nOM).
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Project description:Decreased salivary flow rates and/or changes in protein composition reported after autologous hematopoietic stem cell transplantation (ASCT) reduces the protective function of saliva. This might be associated with the development of oral mucositis (OM), an inflammation of the oral mucosa as a result of chemotherapy before ASCT which affects patients? quality of life and risk factor for systemic infections. In this study, a TMT-labelled proteomics experiment, a label-free quantification (LFQ) proteomics experiment and a DIA-MS proteomics experiment were used to identify differences in the salivary proteome between patients with ulcerative OM (uOM; WHO score ? 2) and those without (nOM). For the TMT-labelled experiment, saliva samples of 5 uOM and 5 nOM were pooled at different time points: baseline, 1, 2, and 3 weeks after ASCT and 3 months after ASCT. A different salivary proteome was suggested by a distinct clustering of the OM pools at baseline, week 2 and week 3 after ASCT.
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Project description:Decreased salivary flow rates and/or changes in protein composition reported after autologous hematopoietic stem cell transplantation (ASCT) reduces the protective function of saliva. This might be associated with the development of oral mucositis (OM), an inflammation of the oral mucosa as a result of chemotherapy before ASCT which affects patients? quality of life and risk factor for systemic infections. In this study, a TMT-labelled proteomics experiment, a label-free quantification (LFQ) proteomics experiment and a DIA-MS proteomics experiment were used to identify differences in the salivary proteome between patients with ulcerative OM (uOM; WHO score ? 2) and those without (nOM). For the TMT-labelled experiment, saliva samples of 5 uOM and 5 nOM were pooled at different time points: baseline, 1, 2, and 3 weeks after ASCT and 3 months after ASCT. A different salivary proteome was suggested by a distinct clustering of the OM pools at baseline, week 2 and week 3 after ASCT.
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Project description:<p>Despite improvement in clinical management, allogeneic hematopoietic stem cell transplantation (HSCT) is still hampered by high morbidity and mortality rates, mainly due to Graft versus host disease (GvHD). Recently, it has been demonstrated that the allogeneic immune response might be influenced by external factors such as tissues microenvironment or host microbiota.</p><p>Here we used high throughput metabolomics (UPLC-MS/MS) in two cohorts of genotypically HLA-identical related recipient and donor pairs. A first monocentric cohort from Saint Louis hospital (Paris, France) was used as an exploratory cohort (n=43) and a second multicentric national cohort from Cryostem biobank was used as a confimatory cohort (n=56).</p><p>Metabolomic profile markedly differed between recipients and donors. At the onset of acute GvHD, in addition to host-derived metabolites, we identified significant variation in microbiota-derived metabolites, especially in Aryl hydrocarbon Receptor (AhR) ligands, bile acids and plasmalogens. Altogether, our findings support that the allogeneic immune response during acute GvHD might be influenced by bile acids and by the decreased production of AhR ligands by microbiota that could limit indoleamine 2,3-dioxygenase (IDO) induction and influence allogeneic T-cell reactivity.</p><p><br></p><p><a href='https://www.ebi.ac.uk/metabolights/editor/study/MTBLS204/descriptors' rel='noopener noreferrer' target='_blank'>MTBLS204</a> contains study information relating to cohort 1.</p><p><a href='https://www.ebi.ac.uk/metabolights/editor/study/MTBLS205/descriptors' rel='noopener noreferrer' target='_blank'>MTBLS205</a> contains study information relating to cohort 2.</p>
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Project description:<p>Despite improvement in clinical management, allogeneic hematopoietic stem cell transplantation (HSCT) is still hampered by high morbidity and mortality rates, mainly due to Graft versus host disease (GvHD). Recently, it has been demonstrated that the allogeneic immune response might be influenced by external factors such as tissues microenvironment or host microbiota.</p><p>Here we used high throughput metabolomics (UPLC-MS/MS) in two cohorts of genotypically HLA-identical related recipient and donor pairs. A first monocentric cohort from Saint Louis hospital (Paris, France) was used as an exploratory cohort (n=43) and a second multicentric national cohort from Cryostem biobank was used as a confimatory cohort (n=56).</p><p>Metabolomic profile markedly differed between recipients and donors. At the onset of acute GvHD, in addition to host-derived metabolites, we identified significant variation in microbiota-derived metabolites, especially in Aryl hydrocarbon Receptor (AhR) ligands, bile acids and plasmalogens. Altogether, our findings support that the allogeneic immune response during acute GvHD might be influenced by bile acids and by the decreased production of AhR ligands by microbiota that could limit indoleamine 2,3-dioxygenase (IDO) induction and influence allogeneic T-cell reactivity.</p><p><br></p><p><a href='https://www.ebi.ac.uk/metabolights/editor/study/MTBLS204/descriptors' rel='noopener noreferrer' target='_blank'>MTBLS204</a> contains study information relating to cohort 1.</p><p><a href='https://www.ebi.ac.uk/metabolights/editor/study/MTBLS205/descriptors' rel='noopener noreferrer' target='_blank'>MTBLS205</a> contains study information relating to cohort 2.</p>
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