PXD016475

PXD016475 is an original dataset announced via ProteomeXchange.

Title	Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for renal cell carcinoma treatment
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.
HostingRepository	PRIDE
AnnounceDate	2021-09-09
AnnouncementXML	Submission_2021-09-08_17:59:32.260.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Sander Piersma
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	phosphorylated residue; acetylated residue; monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2019-11-27 03:43:33	ID requested
⏵ 1	2021-09-08 17:59:34	announced

Rausch M, Weiss A, Zoetemelk M, Piersma SR, Jimenez CR, van Beijnum JR, Nowak-Sliwinska P, Optimized Combination of HDACI and TKI Efficiently Inhibits Metabolic Activity in Renal Cell Carcinoma and Overcomes Sunitinib Resistance. Cancers (Basel), 12(11):(2020) [pubmed]

submitter keyword: Human, renal cell carcinoma, phosphokinase ranking, label-free, single-shot, phosphoproteomics, drug selection, combination therapy

Connie Ramona Jimenez
contact affiliation	Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
contact email	c.jimenez@amsterdamumc.nl
lab head
Sander Piersma
contact affiliation	OncoProteomics Laboratory, dept of Medical Oncology, VUmc Medical Center, Amsterdam, The Netherlands
contact email	s.piersma@vumc.nl
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD016475
     1. Label: PRIDE project
     2. Name: Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for renal cell carcinoma treatment