The BOOSTER trial was originally designed to be able to harvest archives from patients with early lung cancer so that complete profiling could be done before and after surgery in order to discover biomarkers of the disease and to see if there were diagnostic as well as prognostic biomarkers that could be used for the monitoring of the disease. My role in helping to design that really depended upon my ability to know how to do archiving and I’ve been doing archiving for the last thirty years, since the National Cancer Institute, and have established a nice archive that reflects clinical stage 1 lung cancer and that’s what I presented at the meeting.
In what ways are you collaborating with Dr Amir Onn?
Amir became the principle investigator for BOOSTER and he will be running the trial and we will be a participating site in the United States so that we’ll be able to collect specimens for the trial. Those specimens will be collected under a given standard operating procedure that we’ve been using for the last ten years at NYU which ensures that all of our specimens will be collected and archived and processed uniformly.
What’s the scale of this going to be?
It was 4,000 and the question is whether that’s too ambitious and whether it’s going to be 400. It’s really going to depend upon how many sites will commit, how many sites will actually do their accrual and do what they promise they’re going to do. And then also it’s going to depend upon the quality of the archiving. So the archive is one part but having the clinical demographics to be able to go along with the archive is just as important.
What are you looking out for in these samples?
The present technologies include cell free DNA, proteomics, looking for certain protein profiles that can say that a lung cancer is present and then you can look post-operatively to see whether that profile is gone or changes back to a more normal profile. Then you can also look at the cellular content of blood, including the peripheral mononuclear cells, whether they’re isolated by a Ficoll gradient or whether it’s buffy coat. So there’s a wealth of opportunities, not only genomically and proteomically but also epigenetically, to look at different platforms to look at this archive.
What are the benefits and drawbacks of looking at RNA?
RNA is of great interest to myself as well as microRNAs but RNA from the blood, if you use certain tubes called PAXgene tubes, it will be preserved and it will be well preserved but it’s not as good, in my opinion, as blood that’s cryopreserved or snap frozen at the time and not have to have it in a preservative.
How can anyone watching get involved in the BOOSTER trial?
It’s very important that the institutions that are part of the WIN Consortium commit to that. They will need to really have a good working relationship between their pathologists, their surgeons, as well as to have a system already in process so that the specimens will truly be of value. Because the quality control of the specimens will be of utmost importance for something like this.
You emphasised the difference between progressors and non-progressors in disease, tell us about that.
You can take the curve, the survival curve, of the worst of the stage 1 lung cancers and you can look at time to progression, one of the sub-cohorts. Not every one of those patients progresses, therefore not every one of those patients dies of lung cancer but yet they have a picture under the microscope that looks like a very bad tumour. So obviously there must be differences between that subgroup of patients who are going to do well and patients who are not.
Well, you don’t want to give a potentially toxic therapy to patients who you know are going to do well, despite the fact they have this other characteristic. So I think it’s very important that we be able to, as mentioned at this conference, sub-categorise different groups molecularly, either by RNA or other ways, to be able to determine which ones need further therapy and which ones do not.
