Dataset Information

The phosphoproteomic landscape of two FLT3+ Acute Myeloid Leukemia (AML) patient samples.

ABSTRACT: Acute myeloid leukemia (AML) is a clonal hematopoietic malignancy, characterized by expansion of immature leukemic blasts in the bone marrow. In AML, specific tyrosine kinases have been implicated in leukemogenesis, and are associated with poor treatment outcome. However, targeted therapy using kinase inhibitors (KIs) has had limited success, and may be improved by proper patient selection. We performed phosphotyrosine (pY) based, label-free phosphoproteomics to identify hyperphosphorylated, active kinases in two FLT3+ AML Pt samples.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood

DISEASE(S): Acute Leukemia

SUBMITTER: Sander Piersma

LAB HEAD: Connie Ramona Jimenez

PROVIDER: PXD015639 | Pride | 2020-03-02

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	MaxQuant_zip.zip	Other
	QE1_160411_OPL1013_CvA_pTyrIP_blood_patient_bench_A.raw	Raw
	QE1_160411_OPL1013_CvA_pTyrIP_blood_patient_bench_B.raw	Raw
	QE1_160411_OPL1013_CvA_pTyrIP_blood_patient_bench_C.raw	Raw
	QE1_160411_OPL1013_CvA_pTyrIP_blood_patient_bench_D.raw	Raw

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Publications

Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines.

van Alphen Carolien C Cloos Jacqueline J Beekhof Robin R Cucchi David G J DGJ Piersma Sander R SR Knol Jaco C JC Henneman Alex A AA Pham Thang V TV van Meerloo Johan J Ossenkoppele Gert J GJ Verheul Henk M W HMW Janssen Jeroen J W M JJWM Jimenez Connie R CR

Molecular & cellular proteomics : MCP 20200226 5

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, la ...[more]

PMID: 32102969

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Project description:Renal cell carcinoma (RCC) is one of the ten most common malignancies. Even though recent paradigm changes led to inclusion of immune checkpoint inhibitor combination therapy in treatment of naive metastatic RCC, insight in the biology and management of RCC would still favour the use of a combination of kinase inhibitors to target multiple pathways, presenting the possibility of enhanced efficacy and reduced development of resistance. We have used the streamlined-feedback system control (s-FSC) technique, a phenotypic approach, to identify optimized drug combinations (ODC) in 5 different human RCC lines. This approach requires no a priori mechanistic information on drug mechanism of action, and uses statistical modelling circumventing the need to experimentally screen large numbers of combinations. Different ODC with up to 90% effectivity were obtained for the 5 cell lines, importantly, by combining drug at doses that individually only inhibit 5-25% cell viability. Cell viability was reduced and apoptosis induced, accompanied by a general inhibition of downstream survival and growth promoting effector kinase RPS6. Global phosphoproteomics analysis of the cell lines revealed that in all cases where the ODC showed >50% efficacy, the most active kinases were targets of the selected drugs in the ODC. Interestingly, we observed considerable overlap in the top 20 most active kinases in all 5 cell lines, suggesting a universal ODC might be effective in all cells. Indeed, a combination of erlotinib and dasatinib, targeting EGFR and EPHA2/SRC signaling respectively, combined with AZD4547 or axitinib (targeting VEGFR and FGFR signaling), displayed excellent activity. The effect of the 786-O cell-line specific ODC was analysed in more detail using phosphoproteomics coupled to kinase activity analysis using the INKA pipeline.approaches. As expected, the activity of the main targets of erlotinib and dasatinib was reduced, but the activity of several untargeted kinases, including AXL, PTK2 and MET, remained high or increased, having potential implications for the development of resistance. Addition of crizotinib, targeting MET and PTK2, to the 3-drug ODC but not exchange with axitinib, further enhanced drug combination efficacy. In conclusion, we show that the phenotypic s-FSC method is highly effective in selecting optimized combinations of drugs, and that phosphoproteomics analysis can help further refine the selection of drugs included in the screen or final drug mixture.