1. Nalley, Catlin

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A team of researchers have developed a bioinformatics-based approach for monitoring key changes in cancer cells. This new method, which identifies cancer-specific changes in metabolic pathways, can help distinguish patients more likely to respond to cancer therapies.

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What prompted these efforts? "We had been studying the significance of the high rate of flux through the polyamine pathway in the prostate and prostate cancer, and we wanted to know if other disease sites had similar metabolic dysregulation," explained Dominic Smiraglia, PhD, Associate Professor of Oncology in the Department of Cancer Genetics and Genomics at Roswell Park Comprehensive Cancer Center.


"We also began questioning why this pathway was dysregulated in prostate cancer. From there, we began applying these questions to all metabolic pathways in all types of cancer so that we might identify metabolic pathways that were highly dysregulated in cancers, but not normal tissues," he continued. "By identifying these pathways, we could identify more tumor-specific therapeutic targets in different disease sites."


Study Details

The researchers, led by Smiraglia, examined the similarities and differences in cell metabolism among 10,704 tumors representing 26 major cancer types, including breast, prostate, colon, lung, liver, and skin cancer (Nat Commun 2018; doi:10.1038/s41467-018-07232-8).


Utilizing transcriptomic data from The Cancer Genome Atlas, cancerous tumors were differentiated from healthy tissue based on the expression patterns of genes within 114 metabolic pathways regulating various aspects of cell metabolism.


"We were able to look at the expression of genes from a particular pathway across all patients with a particular type of cancer and ask if some patients highly dysregulate this pathway, while others do not, and if this correlates with other clinical data such as molecular subtype of cancer or clinical outcomes," noted Smiraglia. "When we mapped transcripts onto these pathways, we were also able to successfully identify patterns of metabolic flux and, therefore, metabolites of interest that should be found to have increased or decreased expression.


"We could then enrich these patterns of transcriptional dysregulation for master metabolic transcriptional regulators, which could be responsible for the dysregulation of these pathways in multiple diseases sites, or in some disease sites as opposed to others," he continued. "Further, we were able to use these signatures of dysregulation to determine drugs they should and should not be responsive to, based on the DeSigN software, to determine potential inhibitors/stimulators of dysregulated pathways of interest, and showed with a significant amount of accuracy that we could specifically target not only a disease site, but a specific molecular subtype of a disease site with metabolic therapies."


This study highlighted the differences in metabolic reprogramming that not only occur in tumor as opposed to normal tissue, but also changes that exist between different tissues, according to Smiraglia. "It also highlights the enhanced susceptibility of different disease sites to different metabolism-targeted therapies and our ability to more specifically target these pathways in different disease sites," he told Oncology Times.


Based upon the transcriptomic data available across 26 different disease sites with matched normal tissue, the researchers demonstrated that they can:


* identify highly dysregulated pathways in the tumor as compared to the normal tissue;


* map the transcriptional reprogramming to better understand and predict patterns of metabolic flux;


* attribute these transcriptional changes to master metabolic transcriptional regulators; and


* predict and target these pathways with a high amount of specificity.



In addition, the research also identified metabolic pathways uniquely dysregulated among different subtypes of breast cancer. The findings suggest that metabolic-based therapies can be tailored to different subtypes of the disease.


Implications & Next Steps

This research supports the potential utilization of metabolic therapies in clinical practice.


"Traditionally, metabolism-targeted therapies have been avoided due to a high level of toxicity, given that cancer and normal tissues heavily rely on many of the same pathways," Smiraglia noted. "By identifying pathways that are more highly dysregulated in the tumor, as compared to the normal tissue, as well as those that are more specific to a particular disease site, you have the potential to more effectively use these metabolism-targeted therapies in the clinic with reduced toxicity.


"This bioinformatics pipeline also demonstrates that we can correctly map potential changes in metabolic flux, and thereby informs future metabolomics studies, as well as future basic research," he added.


What's next for Smiraglia and his team? Given the continued move towards personalized medicine, his lab is investigating the effects of targeting some of the uniquely dysregulated pathways in prostate cancer.


"Further, we are trying to better understand the role that these master metabolic transcriptional regulators play in the sensitivity to targeted therapies, and how this could be used to inform who should and should not be receiving these drugs in the clinic," he noted. "Our hope is to not only eventually have a clinical trial targeting a metabolic pathway, but to have the ability to stratify patients into those most or least likely to respond."


Catlin Nalley is a contributing writer.