For the second time in just over a week, the Boston Globe Sunday was discussing protein kinases in the context of cancer. A group from the Broad has just published a sequencing study (Sanger!) identifying mutations in the protein kinase DDR2 in about 4% of squamous cell carcinomas of the lung. This is a common form of smoking-induced non-small cell lung cancer (NSCLC) and one for which many therapies useful in lung cancer are contraindicated. The prior study by another group at the Broad was published a bit over a week ago in Nature detailing an extensive look at myelomas by sequencing, and found mutations in the kinase BRAF in 4% of myelomas.
The myeloma study is quite a watershed and in some ways raises the bar for cancer genomics publications. Whereas most papers have published a single cancer genome and a few have published single digit genomes, this one looked at 38 myelomas. Now, not to overstate things, as only in 23 patients were matched normal and myeloma whole genomes sequenced; for the other 15 patients just the exomes were sequenced (one additional exome pair was run in a patient with whole genome sequencing, to enable comparison). Clearly this is a serious scaling up of effort, enabled by dropping costs. By sequencing multiple genomes, the possibility exists both to discover rare variants as well as get some rough mutation frequency information.
The myeloms study is curious in one aspect: the results were first discussed about a year ago at AACR, the big pre-clinical meeting going on right now, and were described as submitted at a conference I attended at MIT last June. Indeed, the paper states "Received 11 June 2010; accepted 17 January 2011". While there is a bit of functional investigation of one gene (siRNA vs. HOXA9) and some Western blots of coagulation factors, this is primarily a genomics paper. Is Nature becoming reluctant to publish such papers? What really held this up for so long?
In any case, the primary finding in both of these papers is low but measurable frequency mutation of protein kinases in human cancers. This should come as no surprise, as a previous paper from the same groups in lung adenocarcinoma (the other major class of NSCLC), multiple kinases were found to be mutated beyond the relatively high frequency EGFR, again including BRAF but also a host of other kinases. The new DDR2 paper also found mutations in multiple kinases, though any follow-up was focused on DDR2. Another 5%-or-so slice of adenocarcinoma carries a fusion protein of the kinase ALK, which can be treated with inhibitors developed against ALK. It also may be an opportunity to target ALK by a different strategy, one which my company has explored (yes, I have a financial interest there!).. The challenge is to determine which, if any, of these mutations are driving tumors and which are just passengers.
In the case of the DDR2 paper, the authors built a pretty nice story. One big bonus to protein kinases is that there has been extensive efforts in the last 30 or so years to study them, with many inhibitors available. A raging argument in the field is whether clinically useful inhibitors need to be exquisitely specific or can be as subtle as a wrecking ball, and the truth is that clinically approved kinase inhibitors run the gamut. Imatinib (Gleevec) is quite specific, though it still hits multiple kinases and that has proven useful as it has enabled targeting multiple cancers. For example, some gastrointestinal stromal tumors are driven by c-KIT mutations and others by PDGFR mutations, but luckily imatinib hits both. Other inhibitors such as sorafenib and suntinib are less discriminating, but still tolerable.
In the case of DDR2, the approved inhibitor dasatinib turns out to be effective, and the new paper shows this first in cell lines. Cell lines carrying DDR2 mutations are more sensitive to dasatinib than those which do not, but the trend continues both in mouse xenograft models and finally in a single human patient carrying a DDR2 mutation in her tumor. Alas, the patient apparently had to discontinue therapy due to side effects.
Now that genomics has demonstrated the ability to find these low frequency mutations, the question is quite open as to how to move them into clinical practice. One model would be to simply sequence extensively and treat each patient by the best guess for their mutations; this approach has been published and is apparently being used in the case of author Christopher Hitchens. While whole genome or exome sequencing might be too costly or slow for routine use, targeted mutation panels are another possible approach (though honestly, exome sequencing is getting down in the $2.5K range these days). Such targeted panels can attempt to focus on the most frequent and actionable mutations, though DDR2 in squamous cell carcinoma appears to not have any one mutation particularly favored.
The alternative is to try to run clinical trials to carefully appraise the clinical utility of these approaches. When I mentioned the BRAF in myeloma story a while back to a co-worker (who happens to have developed multiple drugs, including an effective one in myeloma) and expressed the opinion that it is a slam-dunk to use a BRAF inhibitor (which is near approval in melanoma) in such cases, he took a more cautious view. How do you know these are really the important mutations? How will you know how long the treatment lasts? Perhaps the BRAF mutations in myeloma help the tumor but are not critical. How will you know the correct dose schedule? Combination therapy? Whether drug is getting to a very different tumor? To truly answer these questions rigorously, trials are needed.
But the difficulty in running such trials cannot be underestimated. For example, a company thinking of running a clinical trial looking at BRAF in squamous cell carcinoma faces quite a task. Now, the market is not small: according to Wikipedia (an easy lookup late at night, though perhaps with large error bars) there are about 500K new cases yearly, and a quarter of those are squamous. Presumably at least a quarter of those cases are in the U.S., so around 70K new cases per year. Four percent of 70K (error bars growing with each estimate) is 2.8K patients, which is possibly attractive but getting small..
However, to get the trial going you are going to need to screen to find that 4% of patients. Squamous is a standard diagnosis, so you can start there, but will still need to recruit, consent and screen to get that small fraction. In the mean time, you are competing with every other trial out there to recruit, consent and screen patients. Sure, once they miss another trial they might come to yours -- or might not. To top it off, a lot of patients either are never offered or will never consent to a trial; the farther you are from a large academic cancer center, the less likely you will have a trial available to you.
Now, if oncogenic mutation screening becomes a standard part of cancer care, as it has at MGH and probably some other leading institutions, then if these mutations are in the panels it may be that many patients will know their mutation status before you recruit them into your trial. But until this becomes widespread, and only if your gene of interest is sufficiently covered, will this method work.
Yet another approach is to design trials which test multiple therapies. One prominent example in lung cancer is the BATTLE trial, which is trying 4 different therapies with an adaptive design which uses molecular testing as part of the therapy-assignment scheme. Designs such as BATTLE are quite complicated (well beyond my expertise to critique) and get only more so with more drug regimens; if lung cancer is driven by a dozen or so kinases suggesting a slightly smaller number of therapies, can a trial to test these therapies be designed, patients accrued and useful results out? In such studies, will they be judged by whether the study overall improves survival, or can each treatment be viewed as a separate study?
For the sake of patients, these issues need to be tackled. They'll be hard in lung cancer, and far worse in a disease like myeloma. If we ballpark myeloma at 15K new cases per year in the U.S., 4% of that is getting to be a small group (600 patients). Any sizable trial is going to need to recruit a huge fraction of these patients. Now, with patient advocacy groups and publicity it may be possible to find that small population, but it will certainly be challenging. Indeed, the Multiple Myeloma Research Foundation (which sponsored the sequencing) is already talking about how to support such efforts.
So, in closing, these sequencing studies are suggesting very real therapeutic options for patients. However, driving these findings to routine clinical use, even when drugs are available off-the-shelf for the kinases of interest, will continue to challenge all of the scientists working on translational oncology research.
Let's be honest here, have the scientific honesty to say that this is a daunting task that has no commercial value what so ever. At best public programs for screening, public trial funding have a long shot. The complexity of the mutation, the potential sample heterogeneity and the absence of a time line are all additional factors still not computed (and frankly impossible to elaborate). Not a single company will want to look at this.
Now here is a premise for you, I was just in Las Vegas and I am pretty sure I started mutating in my lungs from second hand smoke, it was so vile:
1-Ban smoking in all public places
2-Educate Americans against fast food and for low meat diets
3-Reduce salt, sugar and fat content in all foods, ban trans fat usage and coloring agents.
4-Introduce 3 more hours of forced exercise in primary, secondary schools and work places.
I don't know about you but if people stop smoking, stop eating crap and beer in fat land tailgating parties and start exercising, me thinks we will have done better than a million new cancer genome sequences. This genomic lobby has got to start presenting an honest, scalable, measurable result to all the money we are throwing at it.
I know for a fact that I can have a better life with a 100$ a year pair of running show. Can you measure your genomic success ?
What worries me here is that society hopes for cure as a cheap lazy solution and genomics is almost giving that hope 'hey guess what Mr Hutchens, you can keep kicking back that JD on the rocks every night and humor yourself about being drunk to death every week end while you entertain a morbid abdomen fat layer, doesn't matter, we found that one in a million mutation and we are working on a therapy,keep smoking away, cost: 200,000$...'
This is not sustainable and you know it. Be honest. I am. I have seen this data, I work in the field, and to me this is just another increase in expectations that scientist will not be able to live up to. When the US become so critically in debt and panels start looking at gov spending, scientists better have a golden explanation on this escalation (or what I call the third genomic bubble). Collins will finally walk away, and we start putting some sense in easy, simple genomic therapies and genomic solutions. This study is a mess IMO, the sole premise of using the words pre-clinical or therapeutic here make me pretty sad. Millions of lives can be saved now with basic, very basic human hygiene, here we go on about ridiculous claims and outrageous studies...Wake up scientists and MBAs ! Do the math, look at the business case ! No wonder it took a year to publish, there is little in here but a jacked up data dump.
Your point on smoking cessation is well taken, and many cancers could be avoided by better lifestyle choices.
On the other hand, ALK fusions are found primarily in never smokers, and do not account for anywhere near the majority of such cases. And, even if smoking were utterly eliminated tomorrow there is still the overhang of all the current smokers.
Lung cancer is the "easy" one; in myeloma we know virtually nothing about the causes. What prescription would you offer there?
Interesting article Keith!
Some comments...First, from what I understand, the Myeloma Nature paper was accepted last year, however, the journal has a long backlog of articles that it needs to publish, and so this was the reason for the paper to come out so late. However, I agree that this paper was rather bland, descriptive, with not much functional data, nor any identification of highly recurrent mutations that would point to an obvious targeted therapy for treating the disease.
With regards to the rare BRAF mutations, I'm of the opinion that it would be a slam dunk. Though it is known that some genes have context-dependent effects in cancer and thus may act as either tumor suppressors or oncogenes (eg. PAX5 in ALL versus in mature B lymphomas), the nature of the mutation should indicate whether it is oncogenic or not. Since the BRAF mutations in myeloma are identical to those in melanoma, we can assume that they are oncogenic, activating mutations and are driving the tumor. Of course this is all speculation until someone gives PLX4032 to the patient.
With regards to conducting trials on small populations, I completely agree that the logistics of it all are extremely challenging. There was an interesting articles in Forbes suggesting that the FDA should consider designating common cancers with rare mutations as a 'pseudo-orphan disease' to make drug development more amenable for those patients. For example, a single arm Phase II to show tumor reduction in a pre-defined percentage of patients harboring a particular mutation may make for a reasonable trial design---in the case of PLX4032, this trial would show nearly 100% tumor reduction, which might be hard data to ignore for conditional approval (with post-market survival data followup).
Additionally, I think we should also be careful to be so reductionist in thinking that only a particular mutation will be the sole biomarker for a targeted therapy's efficacy. Other mutations that may occur upstream from for example, BRAF, may also be susceptible to BRAF inhibition simply because it is executing the downstream signaling.
In the ideal world, we will know all the recurrent mutations, have you bioinformaticians sort out what networks these mutations fall into, and inhibit the majority of these mutations through the most common downstream node...and then, I'm out of a job---onto the next disease!
hello all bioinformaticians and other late night kinase enthusiasts...see the newly launched database: www.kinopediaweb.com
It will map all the kinases and their substrates of your dreams... now don't get too excited and run there at once!! Anyway, check it out, i has nice free info.
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