News Releases

Study of rare cancer yields therapeutic clues to combat drug resistance

August 31, 2018, New York—Stephen Elledge and his team did not set out to find therapies that could render tumors less resistant to therapy or make existing drugs more potent against a rare form of cancer. But these are precisely the clinical insights that their most recent study has yielded.

Elledge, an investigator with the Ludwig Center at Harvard and Gregor Mendel professor of Genetics and of Medicine at Brigham and Women’s Hospital and Harvard Medical School, set out with graduate student Sida Liao to explore cancer drivers that help NUT midline carcinoma—a rare, aggressive cancer that can arise in multiple organs—resist therapy. Their results, published in Genes & Development, may apply to several forms of cancer fueled by the same mutated driver gene, and their approach may be applicable to many other types of cancer.

NUT midline carcinoma affects fewer than 100 people in the United States each year, with an average patient survival of 9.5 months. The cancer is driven by one chromosomal abnormality: the NUTM1 gene breaks off and, in about three-quarters of cases, fuses with the gene for the BET protein. The cancer may be treated with bromodomain and extraterminal domain inhibitors (BETi), which interfere with BET proteins and are currently being evaluated in clinical trials. But cancer cells can develop resistance against the drug through a variety of mechanisms.

Elledge and colleagues uncovered six general classes of genes that appeared to help drive resistance to BET inhibitors. In particular, they found evidence that genes targeted by another class of drugs—known as CDK4/6 inhibitors—seemed to be involved in resistance. In preclinical experiments carried out in the lab and in animal models, combining pre-clinical versions of BET inhibitors and CDK4/6 inhibitors completely stopped tumors from growing.

The study sets the stage for a clinical trial evaluating this combination for patients with NUT midline carcinoma. More broadly, the approach of using a list of cancer drivers predicted by the algorithm TUSON Explorer, which relies on data from fully sequenced cancer genomes, could bring to light the drivers of resistance for other cancer types.

“We always hope that our findings will turn into something that can help people. We hope that this is the case here,” Elledge said.

The press release from which this summary is derived can be found here.


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