Abstract 684: Integrative proteomics and transcriptomics to define the cell surface landscape of neuroblastoma
Authors: Weiner Amber K. , Sidoli Simone , Glisovic-Aplenc Tina , Maris John M. , Garcia Benjamin A. , Diskin Sharon J. 
Published: July 2017

BACKGROUND. Neuroblastoma (NB) is an embryonal tumor of the sympathetic nervous system that accounts for 12% of childhood cancer deaths. Despite intense multimodal therapy, survival probability for high-risk NB patients remains below 50% and relapsed NB is essentially incurable. To date, the cell surface landscape of NB at diagnosis and relapse is currently unknown. An unbiased survey of these proteins and their isoforms will greatly facilitate the identification of candidate immunotherapeutic targets for preclinical validation. 

METHODS. To identify proteins on the cell surface of NB, we performed plasma membrane protein extraction utilizing an optimized sucrose density gradient methodology followed by nano-liquid chromatography coupled to mass spectrometry (nLC-MS/MS) in NB cell lines. Proteomic data is integrated with RNA-sequencing data to assess the correlation between these data types, determine differential expression between NB (n=2242) and normal tissues (n=7859), and investigate NB-specific isoforms. In parallel, we have developed a software tool to aid in proteomic data analysis and interpretation. 

RESULTS. To date, we have applied our proteomic approach to nine NB cell lines stratified by MYCN amplification. This methodology has yielded on average 66% (range: 60-68%) membrane protein enrichment with high reproducibility between biological replicates (80%; range: 78-84% ). This has allowed us to confirm known cell surface proteins that are currently being developed as immunotherapeutic targets (ALK, GPC2 and NCAM1). We are currently integrating the mass spectrometry based proteomics data, where we identified 4826 membrane proteins, with RNA-sequencing data to evaluate proteins expressed uniquely in neuroblastoma and those that correlate with MYCN amplification. We are further determining how RNA and protein levels correlate on the cell surface and will utilize these data to detect NB-specific isoforms. In parallel, we have also created GiaPronto, an efficient tool for data analysis and visualization. After normalization, our program outputs several plots and figure legends that assess data quality, regulated or abundant proteins, and Gene Ontology. 

CONCLUSION. We have developed robust methodology for cell surface protein isolation and quantification along with a software package to facilitate downstream analyses. Parallel proteomic and transcriptomic studies in patient derived xenografts (PDX) and patient tumors are ongoing to define the cell surface landscape in both diagnostic and relapsed NB.

Citation Format: Amber K. Weiner, Simone Sidoli, Tina Glisovic-Aplenc, John M. Maris, Benjamin A. Garcia, Sharon J. Diskin. Integrative proteomics and transcriptomics to define the cell surface landscape of neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 684. doi:10.1158/1538-7445.AM2017-684