Dataset Information

Targeted morphoproteomic profiling of Ewing's sarcoma treated with insulin-like growth factor 1 receptor (IGF1R) inhibitors: response/resistance signatures.

ABSTRACT: Insulin-like growth factor 1 receptor (IGF1R) targeted therapies have resulted in responses in a small number of patients with advanced metastatic Ewing's sarcoma. We performed morphoproteomic profiling to better understand response/resistance mechanisms of Ewing's sarcoma to IGF1R inhibitor-based therapy.This pilot study assessed two patients with advanced Ewing's sarcoma treated with IGF1R antibody alone followed by combined IGF1R inhibitor plus mammalian target of rapamycin (mTOR) inhibitor treatment once resistance to single-agent IGF1R inhibitor developed. Immunohistochemical probes were applied to detect p-mTOR (Ser2448), p-Akt (Ser473), p-ERK1/2 (Thr202/Tyr204), nestin, and p-STAT3 (Tyr 705) in the original and recurrent tumor. The initial remarkable radiographic responses to IGF1R-antibody therapy was followed by resistance and then response to combined IGF1R plus mTOR inhibitor therapy in both patients, and then resistance to the combination regimen in one patient. In patient 1, upregulation of p-Akt and p-mTOR in the tumor that relapsed after initial response to IGF1R antibody might explain the resistance that developed, and the subsequent response to combined IGF1R plus mTOR inhibitor therapy. In patient 2, upregulation of mTOR was seen in the primary tumor, perhaps explaining the initial response to the IGF1R and mTOR inhibitor combination, while the resistant tumor that emerged showed activation of the ERK pathway as well.Morphoproteomic analysis revealed that the mTOR pathway was activated in these two patients with advanced Ewing's sarcoma who showed response to combined IGF1R and mTOR inhibition, and the ERK pathway in the patient in whom resistance to this combination emerged. Our pilot results suggests that morphoproteomic assessment of signaling pathway activation in Ewing's sarcoma merits further investigation as a guide to understanding response and resistance signatures.

SUBMITTER: Subbiah V

PROVIDER: S-EPMC3071831 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Targeted morphoproteomic profiling of Ewing's sarcoma treated with insulin-like growth factor 1 receptor (IGF1R) inhibitors: response/resistance signatures.

Subbiah Vivek V Naing Aung A Brown Robert E RE Chen Helen H Doyle Laurence L LoRusso Patricia P Benjamin Robert R Anderson Pete P Kurzrock Razelle R

PloS one 20110406 4

<h4>Background</h4>Insulin-like growth factor 1 receptor (IGF1R) targeted therapies have resulted in responses in a small number of patients with advanced metastatic Ewing's sarcoma. We performed morphoproteomic profiling to better understand response/resistance mechanisms of Ewing's sarcoma to IGF1R inhibitor-based therapy.<h4>Methodology/principal findings</h4>This pilot study assessed two patients with advanced Ewing's sarcoma treated with IGF1R antibody alone followed by combined IGF1R inhib ...[more]

PMID: 21494688

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Project description:Background:The aim of this study was to identify the driver genes associated with chemotherapy resistance of Ewing's sarcoma and potential targets for Ewing's sarcoma treatment. Methods:Two mRNA microarray datasets, GSE12102 and GSE17679, were downloaded from the Gene Expression Omnibus database, which contain 94 human Ewing's sarcoma samples, including 65 from those who experienced a relapse and 29 from those with no evidence of disease. The differen tially expressed genes (DEGs) were identified using LIMMA package R. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for DEGs using Database for Annotation, Visualization and Integrated Analysis. The protein-protein interaction network was constructed using Cytoscape software, and module analysis was performed using Molecular Complex Detection. Results:A total of 206 upregulated DEGs and 141 downregulated DEGs were identified. Upregulated DEGs were primarily enriched in DNA replication, nucleoplasm and protein kinase binding for biological processes, cellular component and molecular functions, respectively. Downregulated DEGs were predominantly involved in receptor clustering, membrane raft, and ligand-dependent nuclear receptor binding. The protein-protein interaction network of DEGs consisted of 150 nodes and 304 interactions. Thirteen hub genes were identified, and biological analysis revealed that these genes were primarily enriched in cell division, cell cycle, and mitosis. Furthermore, based on closeness centrality, betweenness centrality, and degree centrality, the three most significant genes were identified as GAPDH, AURKA, and EHMT2. Furthermore, the significant network module was composed of nine genes. These genes were primarily enriched in mitotic nuclear division, mitotic chromosome condensation, and nucleoplasm. Conclusion:These hub genes, especially GAPDH, AURKA, and EHMT2, may be closely associated with the progression of Ewing's sarcoma chemotherapy resistance, and further experiments are needed for confirmation.

Project description:BackgroundCuproptosis is copper-induced cell death. Copper metabolism related genes (CMRGs) were demonstrated that used to assess the prognosis out of tumors. In the study, CMRGs were tested for their effect on TME cell infiltration in Ewing's sarcoma (ES).MethodsThe GEO and ICGC databases provided the mRNA expression profiles and clinical features for downloading. In the GSE17674 dataset, 22prognostic-related copper metabolism related genes (PR-CMRGs) was identified by using univariate regression analysis. Subsequently, in order to compare the survival rates of groups with high and low expression of these PR-CMRGs,Kaplan-Meier analysis was implemented. Additionally, correlations among them were examined. The study employed functional enrichment analysis to investigate probable underlying pathways, while GSVA was applied to evaluate enriched pathways in the ES (Expression Set). Through an unsupervised clustering algorithm, samples were classified into two clusters, revealing significant differences in survival rates and levels of immune infiltration.ResultsUsing Lasso and step regression methods, five genes (TFRC, SORD, SLC11A2, FKBP4, and AANAT) were selected as risk signatures. According to the Kaplan-Meier survival analysis, the high-risk group had considerably lower survival rates than the low-risk group(p=6.013e-09). The area under the curve (AUC) values for the receiver operating characteristic (ROC) curve were 0.876, 0.883, and 0.979 for 1, 3, and 5 years, respectively. The risk model was further validated in additional datasets, namely GSE63155, GSE63156, and the ICGC datasets. To aid in outcome prediction, a nomogram was developed that incorporated risk levels and clinical features. This nomogram's performance was effectively validated through calibration curves.Additionally, the study evaluated the variations in immune infiltration across different risk groups, as well as high-expression and low-expression groups. Importantly, several drugs were identified that displayed sensitivity, offering potential therapeutic options for ES.ConclusionThe findings above strongly indicate that CMRGs play crucial roles in predicting prognosis and immune status in ES.

Dataset Information

Targeted morphoproteomic profiling of Ewing's sarcoma treated with insulin-like growth factor 1 receptor (IGF1R) inhibitors: response/resistance signatures.

Publications

Targeted morphoproteomic profiling of Ewing's sarcoma treated with insulin-like growth factor 1 receptor (IGF1R) inhibitors: response/resistance signatures.

Similar Datasets

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