Enhanced phosphorylation of c-Jun by cisplatin treatment as a potential predictive biomarker for cisplatin response in combination with patient-derived tumor organoids.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA772734 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Despite recent advancement in sequencing technologies and large-scale drug screenings with hundreds of cell lines, the predictive accuracy of mutation-based biomarkers is still insufficient to guide cancer therapy. Therefore, novel types of diagnostic methods with alternative biomarkers are highly appreciated. To develop the novel methods, we hypothesized that sensitivity-specific changes in phosphorylations of signaling molecules could be useful as predictive biomarkers. Here, we aimed to develop predictive methods for cisplatin with a combination of such type of biomarker(s) and patient-derived tumor organoids (PDOs). We found that cisplatin sensitive cell lines or PDOs showed enhanced phosphorylation of c-Jun (p-c-Jun) within 24 h in response to cisplatin treatment. We also compared responses to cisplatin in 6 PDOs with therapeutic effect of neoadjuvant chemotherapy (docetaxel/cisplatin/5-fluorouracil) in 6 matched patients. Mechanistically, the c-Jun induction was partly related to TNF signaling induced by cisplatin. Thus, our data implicates the feasibility of enhanced p-c-Jun by cisplatin treatment as a predictive biomarker for the efficacy.
2023-06-01 | GSE186142 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE35711: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [CF_S1S3_5Auto_20CF_10HC] GSE35712: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [H1N1_S5_5Pre_5D0] GSE35716: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [Pneu_S3S24_10Pneu_4HC] GSE35725: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114] Refer to individual Series
2012-09-01 | E-GEOD-35713 | biostudies-arrayexpress
Project description:We profiled the secretomes of 6 NSCLC cell lines with varying IC50-values for cisplatin, using label-free GeLC-MS/MS-based proteomics. Out of a total dataset of 2618 proteins, 304 proteins showed significant differences in expression levels between cisplatin sensitive and insensitive cell lines. Functional data mining revealed that the secretion of typically extracellular factors was associated with a higher sensitivity towards cisplatin, while cisplatin insensitivity correlated with increased secretion of theoretically intra-cellular proteins. Stringent statistical analysis and quantitative filtering yielded 58 biomarker candidates, 34 of which could be detected in clinical biofluids of lung cancer patients such as sputum using label-free LC-MS/MS-based proteomics. To assess performance of these biofluid biomarker candidates, we correlated protein expression with patient survival using a publically available clinical gene expression data set (GSE14814). We thus identified 3 top candidates with potential predictive value in determining cisplatin response (UGGT1, COL6A1 and MAP4) for future development as non-invasive biomarkers to guide treatment decisions.
2019-02-15 | PXD011315 | Pride
Project description:We profiled the secretomes of six NSCLC cell lines with varying IC50-values for cisplatin, using label-free GeLC-MS/MS-based proteomics. Out of a total dataset of 2618 proteins, 304 proteins showed significant differences in expression levels between cisplatin sensitive and insensitive cell lines. Functional data mining revealed that the secretion of typically extracellular factors was associated with a higher sensitivity towards cisplatin, while cisplatin insensitivity correlated with increased secretion of theoretically intra-cellular proteins, in line with enhanced levels of non-conventional secretion in cisplatin insensitive cell lines. Stringent statistical analysis and quantitative filtering yielded 41 top biomarker candidates, many of which could also be detected in NSCLC patient sputum using label-free GeLC-MS/MS-based proteomics. A published gene expression dataset was used to determine which of our top secretome cisplatin response prediction candidates might have predictive value in terms of overall survival in patients that received platinum-based treatment. This analysis yielded two cisplatin sensitivity (UGGT1 and MATN2) and one cisplatin resistance (MAP4) candidates that may serve as potential biomarkers for cisplatin response prediction in NSCLC patients in the future.
2022-02-28 | PXD005830 | Pride
Project description:CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients
2021-06-01 | GSE154540 | GEO
Project description:CircRNA as Predictive Biomarker of Penumbra in Acute Ischemic Stroke
| PRJNA772671 | ENA
Project description:CXCL13 is a predictive biomarker in idiopathic multicentric Castleman disease
| PRJNA898421 | ENA
Project description:Reversible protein phosphorylation is one of the most important posttranslational modifications (PTMs) due to its vital role in cellular functions and signaling pathways. Protein phosphorylation is also known to be involved in the regulation of apoptosis. Previously, we have performed a SILAC-based analysis of phosphotyrosinylation of cisplatin-induced apoptotic Jurkat T cells. To further expand this study, we used the same experimental setup and analyzed the global phosphorylation profile. The different steps of the phosphopeptide enrichment protocol using TiO2 beads were tested and the best approach was applied in combination with LC-MS with different normalized collision energy (NCE) values for HCD fragmentation. In total, more than 2,000 phosphoproteins of more than 4,000 phosphopeptides were identified in the four biological replicates of both states. HCD with NCE 25 accounted for 64% and NCE 35 for 36 % of identified phosphopeptides. 425 phosphopeptides were found to be significantly regulated in cisplatin-treated against control samples. KEGG pathway analysis revealed splicosomal proteins and the MAPK signaling pathway to be upregulated and cell cycle proteins to be downregulated. The transcription factors Atf2 and Jun, which are both involved in the MAPK signaling pathway, were further investigated. For Jun, more than 90 spectral counts were found only in apoptotic cells and covered the well-known stress induced phosphorylation sites at S-63/S-73, as well as S-243 which reduces the ability to bind DNA and is required for GSK3 mediated ubiquitinylation at S-239. For Atf2, more than 60 spectral counts were found in apoptotic cells vs. 8 in control cells. Most significantly upregulated sites for Atf2 have been identified at S-90 and S-112, which are less well studied phosphorylation sites of Atf2 as several other sites. Western blot analyses using non-phosphorylated and phosphorylated antibodies were performed to validate the phosphorylation events of Jun and Atf2. Our findings contribute to the current knowledge of the phosphorylation profiles of apoptotic cells.
2017-05-11 | PXD004415 | Pride
Project description:Cisplatin-based chemotherapy is the standard care regimen in bladder cancer (BC). However, resistance to the therapy whose molecular mechanisms of the resistance are not fully elucidated rapidly develops in BC patients. Here we introduced multidimensional proteomic analysis providing different levels of protein information, which included global proteome and phosphorpoteome perturbed by EGF using the cisplatin resistant BC model. Integrated analysis of protein expression and phosphorylation provided comprehensive profiles of altered proteins in cisplatin resistant cells that are dependent and independent on EGF, as well as suggesting significance of protein phosphorylation in resistance mechanisms in BC. From the reconstruction of cisplatin resistance associated network model and subsequent kinase enrichment analysis, we have identified three key kinases, CDK2, CHEK1, and ERBB2 as central regulators mediating cisplatin resistance. Experimental validation showed phosphorylation events in these central kinases and their putative substrates, suggesting evidence that activation of three kinases are important to acquired resistance to cisplatin in BC. Expanded analysis with this proteomic discovery to transcriptome profiles from BC cohorts nominated the 7 gene panel associated with poor survival after cisplatin-based chemotherapy. These findings provide insightful strategies to classify high-risk BC patients upon current chemotherapies and to identify therapeutic targets for recurrence disease.
2020-05-26 | PXD005308 | Pride
Project description:Idiopathic multicentric Castleman disease (iMCD) is a rare and poorly-understood cytokine storm-driven inflammatory disorder. Interleukin-6 (IL-6) is a known disease driver in some patients, but anti-IL-6 therapy with siltuximab is not effective in all patients, and biomarkers indicating success at an early time point following treatment initiation are lacking. Here we show, by comparison of levels of 1,178 proteins in sera of healthy participants (N=42), patients with iMCD (N=88), and with related diseases (N=60), a comprehensive landscape of candidate disease mediators and predictors of siltuximab response. C-X-C Motif Chemokine Ligand-13 (CXCL13) is identified and validated as the protein most prominently up-regulated in iMCD. Early and significant decrease in CXCL13 levels clearly distinguishes siltuximab responders from non-responders; a 17% reduction by day 8 following siltuximab therapy initiation is predictive of response at later time points. Our study thus suggests that CXCL13 is a predictive biomarker of response to siltuximab in iMCD.
2022-11-04 | GSE217351 | GEO