Abstract 5687: Integrative -omics analysis to identify drug targets for ccRCC immunotherapy
Authors: Reustle Anna , Marco Moreno Di , Büttner Florian , Winter Stefan , Kandabarau Siarhei , Kowalewski Daniel , Backert Linus , Rausch Steffen , Hennenlotter Joerg , Scharpf Marcus , Fend Falko , Stenzl Arnulf , Bedke Jens , Stevanovic Stefan , Schwab Matthias , Schaeffeler Elke 
Published: August 2018

Abstract
Background
Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer and frequently diagnosed at advanced disease stages. Cure of advanced and metastatic ccRCC is achieved only in rare cases with currently available therapies, consisting of tyrosine kinase and mTOR inhibitors, due to intrinsic or acquired resistance mechanisms. We developed a workflow to identify potential drug targets involved in ccRCC pathogenesis for immunotherapeutic approaches and combinatorial treatment strategies.
Methods
We analyzed frequent ccRCC-specific peptides by HLA ligandomics of 55 ccRCC tumors, paired non-tumor tissues and 158 other benign tissues from various organs. To extract cellular pathways with enrichment in ccRCC compared to the S3 region of kidney proximal tubules, which represents the region of ccRCC origin, we performed transcriptome and gene set enrichment analyses in 51 of the 55 tumor tissues of our study cohort and in a microdissected sample of the S3 region (S3-transcriptome data taken from Cheval et al., PloS One 2012). ccRCC-specific pathway genes were intersected with the tumor-exclusive peptide source genes from the HLA ligandome analysis to retrieve a list of candidate target genes. By integrating gene expression data of an independent ccRCC cohort from the Cancer Genome Atlas (TCGA KIRC, n=452), the candidates were validated on the level of individual gene expression and pathway enrichment. Integration of DNA methylation (TCGA KIRC, n=273) and somatic mutation data (TCGA KIRC, n=392) was used to refine the candidate list.
Results
Of the frequent ccRCC-specific HLA class I and II peptide source genes, 203 were involved in ccRCC-enriched pathways in both cohorts. 136 of the genes passed the selection criteria of minimal expression in tumors (&gt; 7.2 log2 FPKM-UQ) and induction compared to paired non-tumor tissues. 89 of the candidate targets were affected by somatic point mutations in one up to eight patients, potentially giving rise to patient-specific neo-epitopes. 110 of the candidate genes displayed altered DNA methylation patterns in tumors compared to non-tumor tissues, offering the possibility of epigenetic targeting.
Conclusion
The presented workflow, integrating HLA ligandomics, transcriptomics and genomics, yields a list of genes with frequent ccRCC-specific HLA-presented peptides that could be targeted in immunotherapeutic approaches, such as ccRCC-directed peptide vaccines. Moreover, the selected genes are involved in ccRCC-enriched cellular pathways and might therefore be important factors of ccRCC pathogenesis, potentially restraining rapid resistance development when they are used as drug targets. The list represents a pre-selection of potential drug targets for novel immunotherapeutic and combinatorial therapy approaches, which need to be further evaluated.
Citation Format: Anna Reustle, Moreno Di Marco, Florian Büttner, Stefan Winter, Siarhei Kandabarau, Daniel Kowalewski, Linus Backert, Steffen Rausch, Joerg Hennenlotter, Marcus Scharpf, Falko Fend, Arnulf Stenzl, Jens Bedke, Stefan Stevanovic, Matthias Schwab, Elke Schaeffeler. Integrative -omics analysis to identify drug targets for ccRCC immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5687.