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Researchers Combine Metabolism and Transcriptional Profiling to Predict Poor Breast Cancer Outcome

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By Molika Ashford

Researchers at Thomas Jefferson University reported this week that a method combining measurement of cell metabolism with genome-wide transcriptional profiling could predict recurrence, metastasis, and poor clinical outcomes in breast cancer

In the April 15 online issue of Cell Cycle, researchers led by Ubaldo Martinez-Outschoorn of TJU described the link between cancer cell metabolism — specifically the presence of lactate and ketones — and aggressive tumor cell behavior. Treatment with these metabolites, they reported, causes cancer cells to express gene profiles associated with “stemness,” and these gene signatures could, in turn, predict poor clinical outcome in breast cancer patients.

A researcher involved with the study said that the so-called “metabolo-genomics” approach could be used to discover cancer biomarkers, find new uses for antioxidants in cancer treatment, and lead to the development of new personalized oncologics.

“Moving from the assumption that dangerous cancer cells use lactate and ketones as a fuel, we found out that if you give cancer cells this fuel, the gene signature looks like [the gene signature for] stem cells” Michael Lisanti, a researcher at Jefferson’s Kimmel Cancer Center, told PGx Reporter. “Then, we showed that [the signature] predicts outcome.”

Lisanti said the group is working to validate its findings with the aim of developing a diagnostic test, as well as new drugs targeted at the mechanisms of this type of cancer cell metabolism.

In the meantime, the authors reported in the paper that currently available antioxidants, like the type II diabetes drug metfomin, could be used to treat cancers that exhibit this metabolite-induced gene signature. Metformin is a mild mitochondrial poison, which targets oxidative mitochondrial metabolism, the process by which cancer cells consume these high-energy metabolites.

According to the study authors, “high lactate production has long been known to be a predictor of poor clinical outcome for a variety of different types of malignancies." The new work provides more insight into the mechanism behind this link and is a step toward a diagnostic and therapeutic strategy.

Lisanti said his previous research showed that loss of the tumor suppressor protein caveolin-1 induces mitochondrial oxidative stress in the stromal micro-environment, specifically fibroblasts. Under this oxidative stress, fibroblasts undergo authophagy, turning themselves into a high-energy fuel for cancer cells.

Working from this previous lead, the study aimed to generate a gene-expression signature associated with cancer cells on a “diet” of this fuel that could then be tested as a prognostic for high-risk breast cancer.

“We took cancer cells, MCF7 cells, and gave them the high-energy nutrients in addition to what they normally get – glucose, amino acids. The idea was that if we give them the nutrients, then we can make a gene signature and it should then be able to predict outcome,” said Lisanti.

The researchers cultured the MCF7 cells with either L-lactate or ketones (3-hydroxy-butyrate) and subjected them to transcriptional analysis using Affymetrix exon arrays.

The group compared gene expression in the lactate/ketone-exposed cells to a control group. They measured approximately 4,131 genes that were upregulated in the case of lactate and around 4,141 upregulated in the presence of ketones.

Gene set enrichment analysis revealed which cellular processes were linked to these changes in regulation. Both the lactate and the ketone-induced profiles were “tightly associated” with “stemness”, a reduction in DNA damage, and with breast cancer, the authors report in their study.

“If you give lactate they look like neural stem cells with P value of 10 to the minus 23. If you give ketones, they look like hematopoietic stem cells,” Lisanti said. Gene signatures that overlapped between both metabolites looked most like embryonic stem cells, he added.

To test the prognostic potential of these signatures, the team then applied the lactate and ketone-induced gene signatures to data from human breast cancer patients, evaluating the expression profiles against clinical microarray data in the public repositories Gene Expression Omnibus and ArrayExpress.

Using information from a total of 1,292 (967 ER-positive and 325 ER-negative) breast cancer samples in these databases, researchers analyzed how survival data correlated with patient expression signatures.

They found that the metabolite-induced gene expression signatures were significantly correlated with reductions in survival in ER-positive breast cancer patients. Further analysis showed that the signatures were specifically associated with tumor recurrence, metastasis, and dramatically reduced survival in the most common form of breast cancer, the luminal A subtype. Overall patient survival was associated with p-values between 0.0001 and 0.00001, the study reported.

The results demonstrate that it is possible to produce a predictive gene signature for poor clinical outcome based on the metabolic status of a tumor. “It's exciting, because we didn’t put new oncogenes in, we didn’t introduce mutations, or alter their genetic profile,” Lisanti said. “All we did was give them a high energy diet and it changed their transcriptional profile.”

“Based on the analysis, it appears that lactate and/or ketone utilization by cancer cells may be a general phenomenon that can be exploited to identify aggressive predictive gene signatures for a wide variety of different types of human cancers,” the authors wrote in the paper.

According to Lisanti, similar prognostic signatures for other types of cancer could be generated by the same method, opening a new avenue for biomarker discovery and “the rapid development of personalized cancer medicine."

Metformin is now being investigated as a cancer treatment in clinical trials, Lisanti said. Other currently available drugs that target oxidative mitochondrial metabolism could also be effective, he added. Further research into the influence of these gene signatures on patient outcome may influence the development of new targeted drugs.

Lisanti said he is open to working with pharma toward this end. “If we were to work with the right people we could design a whole new line of potential therapeutics to target high-risk patients.”

The study was funded by grants from the National Cancer Institute, the Susan G. Komen Breast Cancer Foundation, the Breast Cancer Alliance, Landenberger Foundation, American Cancer Society, and the Pennsylvania Department of Health.


Have topics you'd like to see covered in Pharmacogenomics Reporter? Contact the editor at mashford [at] genomeweb [.] com.

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