By Benjamin Ross 

January 5, 2017 | The old adage still rings true that when one door closes another one opens. In a recent article published in PLOS Medicine (DOI:10.1371/journal.pmed.1002177), authors Francisco Beca, Staff Scientist at Beth Israel Deaconess Medical Center Instructor in Pathology, Harvard Medical School, and Andrew H. Black, co-author of the commentary and academic editor for the article, discussed the outcome of a Phase II trial testing the outcome of human epidermal growth factor receptor 2 (HER2)-positive inflammatory breast cancer (IBC).

The results are intriguing, though not necessarily for the reasons one might expect. The novelty of the trial is not in its outcome, but in how the researchers came to their conclusions. The clinical trial has helped shed new light on the implications of genomic evolution in clinical trials, especially as it pertains to trial design.

The trial, conducted by Charles Swanton from the Francis Crick Institute and his colleagues, was set up into two parts, with the overall objective being to test afatinib in a cohort of HER2-positive IBC patients. The first part of the trial focused on recruiting patients and giving them afatinib for monotherapy, and passing those that progressed into the second part of the trial, where vinorelbine was added to afatinib. Patients’ tumors were sequenced before treatment and after the first part of the trial “to assess the mutational landscape of IBC and evolutionary trajectories during therapy.”

The trial was the first—as far as Beca and Black could tell—to prospectively integrate longitudinal whole exome sequencing (WES) in a trial for drug development specifically for IBC.

“This could have been a more traditional clinical trial testing afatinib as a monotherapy in this population of patients,” said Francisco Beca in an interview with Clinical Informatics News. “But I would say that with minimal effort and investments the investigators of the trial were able to collect genomic data in a prospective and longitudinal way in order to track tumor evolution.”

Unfortunately the trial was cut short due to another trial’s results, an LUX-Breast 1 trial in which an afatinib regimen was less tolerable than a regimen containing trastuzumab in HER2-positive metastatic breast cancer.

The results of the truncated study were published in PLOS Medicine (DOI:10.1371/journal.pmed.1002136). Being one of the reviewers of the article, Black still thought the data was worth considering and wrote the commentary article with Beca.

“Some of the analyses were a little bit underpowered due to the relatively small sample size,” said Beca. “But still we think that some of the findings were important, and the cost and doing this additional biopsy collection and genomic analysis was novel in this group of patients and the results thought-provoking.”

Important observations were made—even from a short-lived trial—“because of the prospectively planned WES analysis,” Beca and Black wrote in their commentary. The planned sequencing demonstrated “the ability of prospectively planned genomic profiling within the setting of a clinical trial to improve knowledge about IBC in individual patients, even when the study’s overall sample size is small and the overall therapeutic benefit of the experimental treatment is not established,” they continued.  

A fair question to ask is, why don’t other trials implement these concepts? “I think that sometimes the only detail that fails is the planning of the trial,” said Beca. “I think that molecular pathologists with solid clinical research experience should be more involved in the planning of the trials. This was the case where they could manage this sort of analysis with tumor samples collection and whatever sort of genomics analysis you want to do.”

Beca is certain that we’ll start to see more trials with these sort of data collection points. “During the last five to ten years [tumor evolution] has become more interesting again for the scientific community, so we’ll see more and more trials with this sort of data collection and this sort of tumor evolutionary analysis that hopefully will lead to improved outcomes for cancer patients.”