Genomic and transcriptomic landscape of advanced renal cell cancer to individualize treatment strategy

de Joode, K.; van de Geer, W. S.; van Leenders, G. J. L. H.; Hamberg, P.; Westgeest, H. M.; Beeker, A.; Oosting, S. F.; van Rooijen, J. M.; Beerepoot, L. V.; Labots, M.; Mathijssen, R. H. J.; Lolkema, M. P.; Cuppen, E.; Sleijfer, S.; van de Werken, H. J. G.; van der Veldt, A. A. M.

doi:10.1101/2022.04.22.488773

bioRxiv · 10.1101/2022.04.22.488773

Genomic and transcriptomic landscape of advanced renal cell cancer to individualize treatment strategy

de Joode, K.·van de Geer, W. S.·van Leenders, G. J. L. H.·Hamberg, P.·Westgeest, H. M.·Beeker, A.·Oosting, S. F.·van Rooijen, J. M.·Beerepoot, L. V.·Labots, M.·Mathijssen, R. H. J.·Lolkema, M. P.·Cuppen, E.·Sleijfer, S.·van de Werken, H. J. G.·van der Veldt, A. A. M.

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Abstract

BackgroundDifferences in the clinical course and treatment responses in individual patients with advanced renal cell carcinoma (RCC) can largely be explained by the different genomics of this disease. To improve the personalized treatment strategy and survival outcomes for patients with advanced RCC, the genomic make-up in patients with advanced RCC was investigated to identify putative actionable mutations and signatures. MethodsIn this prospective multicenter study (NCT01855477), whole-genome sequencing (WGS) data of locally advanced and metastatic tissue biopsies and matched whole-blood samples were collected from 91 patients with histopathologically confirmed RCC. WGS data were analyzed for small somatic variants, copy-number alterations and structural variants. For a subgroup of patients, RNA sequencing (RNA-Seq) data could be analyzed. RNA-Seq data were clustered on immunogenic and angiogenic gene expression patterns according to a previously developed angio-immunogenic gene signature. ResultsFor papillary and clear cell RCC, putative actionable drug targets were detected by WGS in 100% of the patients. RNA-Seq data of clear cell and papillary RCC were clustered using a previously developed angio-immunogenic gene signature. Analyses of driver mutations and RNA-Seq data revealed clear differences among different RCC subtypes, showing the added value of WGS and RNA-Seq over clinicopathological data. ConclusionsBy improving both histological subtyping and the selection of treatment according to actionable targets and immune signatures, WGS and RNA-Seq may improve therapeutic decision making for most patients with advanced RCC, including patients with non-clear cell RCC for whom no standard treatment is available to data. Prospective clinical trials are needed to evaluate the impact of genomic and transcriptomic diagnostics on survival outcome for advanced RCC patients.

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de Joode, K., van de Geer, W. S., van Leenders, G. J. L. H., Hamberg, P., Westgeest, H. M., Beeker, A., Oosting, S. F., van Rooijen, J. M., Beerepoot, L. V., Labots, M., Mathijssen, R. H. J., Lolkema, M. P., Cuppen, E., Sleijfer, S., van de Werken, H. J. G., van der Veldt, A. A. M.. 2022-04-22. Genomic and transcriptomic landscape of advanced renal cell cancer to individualize treatment strategy. https://doi.org/10.1101/2022.04.22.488773

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