Genetic Analysis Spots Cancer Therapies With Potential to Treat PH

Marisa Wexler, MS avatar

by Marisa Wexler, MS |

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PH cancer treatments | Pulmonary Hypertension News | image of researchers in lab

By analyzing how medications affect the genetic activity of cells, researchers developed a computational pipeline that may be useful in repurposing cancer treatments for use in other diseases.

Leveraging this pipeline, the team identified two compounds, I-BET762 and BRD2889, that might be refined — more quickly and at lower cost than new compounds — to treat pulmonary hypertension (PH).

Results were described in the study, “Computational repurposing of therapeutic small molecules from cancer to pulmonary hypertension,” published in Science Advances.

“Repurposing drugs can cut down the time and cost of developing treatments for rare diseases, which historically don’t receive much investment into research and drug development,” Stephen Chan, MD, PhD, a professor of medicine at the University of Pittsburgh and the study’s senior author, said in a press release.

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“Pulmonary hypertension is an example of a rare disease where there is an unmet need for new treatments, given its devastating consequences,” Chan added. “We developed this pipeline to rapidly predict which drugs are effective for PH and get these treatments to patients faster.”

The pipeline focuses on how different medicines impact gene expression — the extent to which different genes are turned “on or off” within a cell. Based on prior studies, the researchers identified certain patterns of gene expression that are characteristic of the blood vessel remodeling taking place in people with PH.

Leveraging expression data from 800 cancer cell lines that had been exposed to hundreds of cancer medicines, the researchers looked for medications that affected these particular genes.

“When we overlay these [cancer] networks with PH-specific gene networks, we can predict which drugs may be effective in treating PH,” said Seungchan Kim, PhD, a chief scientist and executive professor in the department of engineering and computer science Prairie View A&M University and a study co-author.

Results identified I-BET762 and BRD2889 as likely candidates for a PH treatment.

A battery of tests in cell and rodent disease models demonstrated that both compounds were able to engage with their PH-related genetic targets as expected. Treatment with the compounds was also seen to alleviate some of the remodeling characteristics of PH in these models.

BRD2889 is an analog of piperlongumine, a compound with anti-cancer properties that is derived from long pepper plants. Neither BRD2889 nor piperlongumine have ever been tested for PH in clinical trials, though other preclinical studies have indicated that piperlongumine may be beneficial in PH.

I-BET762 belongs to a class of medications known as BET inhibitors. Another BET inhibitor, called apabetalone, is currently being developed by Resverlogix as a treatment for pulmonary arterial hypertension (PAH). Results of a small clinical trial of apabetalone were positive, supporting this treatment’s potential to be well-tolerated and to lessen pressure in the lung’s blood vessels.

This newly developed pipeline, the researchers said, may also be useful in identifying potential treatments for other conditions. “With this algorithm in hand, we may be able to repurpose existing cancer drugs for the treatment of other rare and emerging diseases,” Chan said.

Overall, “this work establishes the validity for a platform of computational repositioning of cancer drugs in other rare and emerging diseases that has not yet been possible,” the team concluded.

Of note, the researchers have applied for a provisional patent for BRD2889, and plan to test the compound in future clinical trials.

They also intend to further refine their pipeline, aiming to “establish a wide-ranging … platform to redefine cancer drugs for use in noncancerous conditions,” the researchers wrote.

“Given the increasing appreciation of links of lung cancer specifically to PH, [this algorithm’s] predictions could also be further honed by concentrating only on lung cancer cell responses to various tested compounds,” they added.