Investigators at Memorial Sloan Kettering Cancer (MSK) Center reported they have developed a metabologram and a smart phone app that may help change how kidney cancer is diagnosed and managed.1

The researchers are sharing a new online tool that allows researchers to easily search and view metabolic data obtained from kidney cancer tumors. Changes in cell metabolism are increasingly recognized as an important way tumors develop and progress. Yet, these changes are hard to measure and interpret.

“A metabologram is a visualization tool to help scientists, physicians, and patients understand their cancer in a more integrated way, which will likely prevent us falling into the ‘blind men and an elephant’ type of near-sighted trap,” said James Hsieh, MD, who is a research scientist at MSK in New York, NY.

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Dr Hsieh and his colleagues created an online tool that can help users make sense of metabolic data in order to devise and test new hypotheses. In a study published in the journal Cancer Cell, the researchers used this approach to profile metabolic changes in kidney cancer tumor samples.1

The team obtained samples of tumor tissue and normal tissue from 138 patients with clear cell kidney cancer treated at a single institution. The researchers then used mass spectrometry and liquid and gas chromatography to analyze the levels of more than 800 different metabolites in these samples. By comparing the levels of metabolites in tumors with those in normal tissues, they were able to chart the rise and fall of these chemicals.

The metabologram allows users to review the metabolite data for any number of different metabolic pathways, one pathway at a time. Users can compare metabolites between tumor samples and normal samples, or between lower-stage tumors and higher-stage tumors. They can also see how the metabolic data line up against the gene expression data obtained from The Cancer Genome Atlas.

Taking a bird’s-eye view of the metabolic data, the team found 4 distinct groupings or clusters of tumor samples that they could be distinguished based on levels of metabolites. The clusters differed in their level of tumor aggressiveness and highlighted patients who were high-risk.

“It is still a research tool at this moment but with an enormous potential to be adapted for clinical use. This current kidney cancer database serves as a resource in understanding how kidney cancer metabolic aberration is and how this could contribute to disease progression and possibly prognostication and future therapeutics,” Dr Hsieh told Cancer Therapy Advisor.

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“Cancer metabolism is hard-wired and cannot be simply looked at by a single metabolite or single pathway. Different cancers are likely to have shared and private metabolic programs that are amenable for diagnostic and/or therapeutic prediction. A metabologram-like integrated analysis is essential and sets the benchmark for future integration of metabolomics with transcriptomics, genomics, proteomics, and possibly epigenomics.”

He said the new tool is being made freely available online and it is hoped that it will help researchers generate novel hypotheses about metabolism and kidney cancer, and even encourage other teams to create metabolograms for other cancer types. Dr Hsieh said this is may change how kidney cancer is managed in the future.