Name: Gil Mor
Position: Associate professor, department of obstetrics and gynecology, Yale University, 2003 to present; director, Translation Research in Gynecologic Oncology: Discovery To Cure: Ovarian Cancer detection and treatment Program, department of obstetrics and gynecology Yale University/ Yale Cancer Center.
Background: Assistant professor, department of obstetrics and gynecology, Yale University, 1998 to 2002; postdoc fellow, Laboratory of Immunobiology, Center for Biologics Evaluation and Research, FDA, National Institutes of Health, 1994 to 1996.
In 2005, Gil Mor and colleagues announced that they had developed a protein-based ovarian cancer test that they said had a sensitivity and specificity of 95 percent. The test, based on a panel of four proteins, was to be marketed as a laboratory-based diagnostic test by the Laboratory Corporation of America. However, Mor said he decided against commercializing the test until he could improve its specificity.
Building on that test, he and his colleagues developed a six-protein test with a sensitivity of 95 percent and a specificity of 99 percent. The test is currently in phase II clinical testing. In a statement issued last week, LabCorp said it hopes to launch the test by the end of the year and market it as a routine test akin to mammography or a Pap smear.
The test and the work developing it is described in an article published in the Feb. 15 edition of Clinical Cancer Research.
Below is an edited version of a recent conversation ProteoMonitor had with Mor about the development of the test.
There are so many ovarian cancer diagnostics under development. Why should people care about this one?
That is correct, there are a lot of reports and always with the new markers and so on. The publication that we have … is [a] validation and an improvement of the test that we reported in 2005. If you see, there are many papers [in which the authors] publish once and they never come back with a validation.
I think we really are the first ones who really have a second publication following a validation of the first discovery. This is not a discovery, this is a validation.
In terms of the improvement, what I mean is we have a new platform that is a multiplex technology. And using this new platform, we were able to validate and replicate the same results we found previously.
In addition, when we included two markers [for] a total of six, we were able to improve from 95 percent to 99 percent [specificity]. [Another difference] with other reports is that in this report, we did a discovery phase and then a blind clinical trial to test the test, and in that blind study, we obtained that sensitivity and specificity.
Those percents are not the results when you’re just comparing the two groups for the discovery phase. When you have two groups, it always looks very promising. Those numbers are from the clinical trial, from the blind group.
I’m always asked ‘Why does this [test] have such a high sensitivity and specificity?’ It’s … because the components of this panel [are] not only proteins that are produced by the tumor.
It has always been the dogma that if you want to have a marker for cancer, you have to find the protein that is produced by the tumor. That is true when you have a tumor that is in late stages of disease, or when you have a big mass in stage III or IV. It produces so much tumor proteins that you easily detect [them] in the blood.
But at that stage, who cares? Ultrasound will do exactly the same [thing], and even better.
In early stages of a tumor, it’s like a little baby. It’s just a little group of cells and what it produces is very low, and in many cases [is] undetectable in the blood. However, and this is the important thing, the stroma surrounding the tumor, and I call this the body, recognizes the presence of those malignant cells. And that response can be detected in the blood.
Is that a new approach? That sounds like an obvious hypothesis.
Absolutely, it’s a new approach. That’s the uniqueness of our study.
Some things that look reasonable and common sense — we scientists who study the human body lead with dogma, and we create dogmas. And one of the dogmas that has been with us for many years is [that] a marker has to be something produced by the tumor. And people didn’t want to look outside of the tumor.
And I can tell you that I still find a lot of people who don’t accept that, although it makes sense.
But I see many publications [that are taking this same approach]. There is a group in Pittsburgh who is using [this approach] for colon cancer, also looking at cytokines, growth factors, everything that in many cases, you will not see in the tumor.
Describe the new multiplex platform that you mention.
The original test [in 2005] was done using ELISAs. In ELISAs you have for each protein an independent assay. When you do multiple proteins, it’s time consuming and it’s very expensive.
In the multiplex technology, it’s the same principle as the ELISA, the sandwich, but you do everything in one single reaction and in suspension. In an ELISA, the antibodies are attached to the surface of the plate, so you can put only one antibody. Here, the antibodies are attached to beads that are floating.
Each bead has its specific coat, so with a computer, you can identify whether that bead is recognizing prolactin, or leptin, and so on. So, in the multiplex, you can test several proteins in one single reaction. The amount of material required is minimal, so for example, from serum, you need only 15 microliters, and the whole test can be done in one day.
So is the advantage of this technology that you use fewer samples, or that it’s quicker, or both?
It’s both. First of all, it’s quicker, it’s simple, and, of course, it’s more economical. And we don’t sacrifice anything, in terms of specificity and sensitivity.
It sounds like this technology is particularly suited for a clinical setting.
Absolutely, it was originally developed for screening DNA mutations, later it was applied to proteins.
Who developed it?
The multiplex technology, the machine was developed by Luminex.
For this panel, you added two new proteins, macrophage inhibitory factor and CA-125. How did you decide to include these two?
Those two proteins were part of the discovery group. We tried more than those two, and the interesting thing is sometimes we think more is better. It’s not.
So when you start with 10 proteins or 12 proteins, the sensitivity and specificity goes down.
Because it creates more noise?
Exactly. So we tested several proteins in different combinations until we found the right ones, which also gave us the right sensitivity in combination. And those six are the ones [we included in this study].
It’s looking for the right proteins that will combine to give us the specificity and sensitivity.
Can you describe the decision to move beyond the four-protein test? Why was that panel not good enough?
The thinking was that maybe adding more proteins would increase the sensitivity. We went through a lot of proteins, a panel of 10, and that didn’t help. And the reason is there is a lot of variation between patients. What we tried to do was create a specific profile for ovarian cancer.
In the test, in order to have a positive result, it’s not required to have all the proteins [expressed at abnormal levels]. The model that we developed may have three proteins normal, but depending on the levels of normality of the other three proteins, it will give us a positive result.
That is the reason having more proteins allows you more types of combinations in order to have a positive or negative result.
Have you decided that six proteins is the ideal number, or are you going to further develop this with more proteins?
I don’t think we will go for more. I don’t think we can improve on this.
Did the four-protein test ever make it to market?
No, we’re replacing the four-protein test with this one. It never made it to the market. We decided to stop it. We wanted to improve it to the 99 percent [specificity level] that is necessary for screening, so we decided to hold it until the results of this.
You’re doing phase II clinical trials now.
Correct, the study will be finished, hopefully by the end of March.
If your results hold up, what will it mean to women? Who are the patients who will be diagnosed with the test who can’t be diagnosed currently?
There are two groups of patients whom we are screening. One is what we call the high-risk patient. And [in] the high-risk patient, the age where you will see cancer is around the 40s. So that is the first population that you study [while they’re still young].
What is high-risk? It means they have genetic mutations, or they have a [family] history of ovarian cancer.
Now, if you [look at] a curve in the incidence of ovarian cancer, we see that there is an increase in women when they reach the age of 65, so clearly there is a correlation between aging and ovarian cancer.
If we are detecting a peak of cancer in stages III and IV at 65, you would like to start screening 10 years earlier, so we say around 55 for another population who may be at risk for ovarian cancer.
Is this test being developed as a substitute for CA-125?
Absolutely, completely, yes. This will replace CA-125.
Your paper says that this year about 15,000 patients will die from ovarian cancer.
Fifteen thousand in the United States will die of ovarian cancer. That is correct.
Have you done any estimates on how many of these 15,000 would have be saved if your test works the way you think it should?
Those patients are dying because the disease is in later stages. When you [diagnose] it in late stages, there is nothing to do. There’s no way to cure this cancer. If you discover those patients in early stages, you can cure it. So it depends on how many patients will be screened, and how many will have the appropriate treatment.
So, no, I don’t have any idea how many can be saved. But the majority, if they are [diagnosed] earlier, they can be saved.