Prediction of response to sunitinib in patients with advanced renal cell carcinoma (RCC) using mass spectrometry-based (phospho) proteomics.
Authors: van der Wijngaart Hanneke , Beekhof Robin , Knol Jaco C. , Henneman Alex A. , de Goeij - de Haas Richard , Piersma Sander R. , Pham Thang V. , Jimenez Connie R. , Verheul Henk M.W. , Labots Mariette 
Published: June 2021

e16556

Background: Sunitinib, a multi-targeted antiangiogenic tyrosine kinase inhibitor has improved the outcome of patients with advanced RCC considerably. Unfortunately, ± 30% of patients are intrinsically resistant, which underscores the urgent need to develop a clinically applicable method to select sunitinib treatment for patients. Since RCC is not single oncogene driven, but rather by multiple aberrantly activated kinase signaling pathways, we hypothesized that a functional read-out by large scale (phospho)proteomics can identify predictive biomarkers for sunitinib. Methods: Frozen tumor tissue of 26 patients (pts) with RCC, treated with sunitinib upon recurrence or progression, was obtained. Pts were classified as primary resistant (progression-free survival (PFS) < 3 months, n = 8) or sensitive (PFS ≥ 3 months, n = 18). Mass spectrometry-based tyrosine (pTyr) phosphoproteomics was performed by pTyr-immunoprecipitation followed by LC-MS/MS. Discriminatory phosphosites (p-sites) were identified (p < 0.05, fold-change (FC) > 2). Expression proteomics was performed by LC-MS/MS and differentially expressed proteins identified (p < 0.05, FC > 2, ≥ 50% data presence in group with highest abundance). Tumor biology was further analyzed by INferred Kinase Activity analysis, posttranslational modifications signature enrichment analysis (PTM-SEA, Krug et al 2019) and gene ontology mining. Results: pTyr-phosphoproteomics was successfully performed in 23 of 26 samples. Seventy-eight differential p-sites were identified, of which 22 (4 unique; BCAR3, NOP58, EIF4A2, GDI1) were upregulated in resistant and 56 in sensitive pts (35 unique). Supervised cluster analysis of these p-sites resulted in near-complete separation of the groups. EIF4A1 and its homolog EIF4A2 were differentially expressed in resistant pts both at the (phospho-)proteome and, in an independent cohort, at transcriptome level. Significantly higher inferred kinase activity of MAPK3 (p = 0.026) and EGFR (p = 0.045) was found in sensitive pts. PTM-SEA showed 3 p-site-centric signatures that were significantly enriched (p < 0.05) in resistant pts, including FGF1 and prolactin pathways. Fifteen signatures were significantly enriched (p < 0.05) in sensitive pts, including insulin, VEGF and FGF2 treatment and KIT receptor pathway. Expression proteomics revealed significantly higher expression (p < 0.05) of proteins related to vesicle mediated transport in resistant pts, while this was not the case in sensitive pts. Conclusions: This MS-based (phospho)proteomics analysis of RCC tissues revealed discriminatory phosphosite and protein signatures and differential kinase and pathway activities that are associated with sensitive and resistant tumors. These findings warrant validation in an independent cohort and the clinical utility for treatment selection remains to be demonstrated.