B. Arman Aksoy

An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort.

Abstract 4271: The cBioPortal for Cancer Genomics as a clinical decision support tool

As sequencing of tumor samples is entering clinical practice, there is an urgent need for new tools that facilitate the interpretation of sequence data so that they can effectively inform treatment decisions. To this end, we are evolving the cBioPortal for Cancer Genomics into a clinical decision support tool. The cBioPortal is a web-based visualization and analysis engine that makes complex cancer genomics data accessible to a wide range of cancer researchers and clinicians. To transition the cBioPortal towards use in clinical practice, we have recently developed the following new functions: 1. Filtering of oncogenic mutations: By using information about the known or likely oncogenic effects of specific mutations, the portal can now filter out passenger events and highlight known and potentially druggable drivers. 2. Clinical timelines: Compact and interactive visualization of a patient9s clinical and treatment history 3. Image support: Interactive visualization of histology images 4. Support for multiple tumor samples from a single patient: The portal can display genomic differences and similarities of different samples (e.g. multiple sites of the same tumor, recurrence, metastasis, post-treatment) in the context of a patient9s treatment history. 5. Tumor clonality: Assessment of a tumor9s purity and clonality / heterogeneity 6. Targeted treatment suggestions: The portal matches drugs to drug targets that are altered in the patient9s tumor. 7. Clinical trial matching: Based on a patient9s clinical history and the genomic alterations found in the tumor, the cBioPortal will identify relevant clinical trials. By making complex genomic data easily interpretable and linking it to information about drugs and clinical trials, the system has the potential to facilitate the proper use of genomic data in clinical decision making. We are constantly improving the software and will initially focus most strongly on the matching of patients to clinical trials. We are sharing the software with other hospitals, where it can be used by oncologists and tumor boards. Citation Format: JianJiong Gao, B. Arman Aksoy, Benjamin Gross, Gideon Dresdner, Yichao Sun, S. Onur Sumer, Chris Sander, Nikolaus Schultz. The cBioPortal for Cancer Genomics as a clinical decision support tool. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4271. doi:10.1158/1538-7445.AM2014-4271