Personalized medicine is a wonderful concept: instead of lumping huge groups of patients with similar symptoms together to be treated with a standard regimen, therapy would be tailored to each patient based on the specifics of their disease. This fine-grained diagnosis would be dtermined using the fruits of the human genome project.
In some sense this is simply an attempt to accerate the long-term trend in medicine of subdividing diseases. From four humors we have moved to a myriad of diseases. In a more specific sense, consider leukemia. In the 1940's, when my paternal grandmother succumbed to this disease, there were (as far as I can tell) less than a half dozen recognized leukemia subtypes; these days there are certainly over one hundred. This is not idle splitting; each disease has its own diagnostic hallmarks, treatment strategies, and outcome expectations. Great (but not universal) success has been achieved with childhood leukemias, whereas some other leukemias are still very grim sentences.
To realize the dream of personalized medicine is going to require a lot of hard work, both in the lab and in the clinic. I'm going to go into some detail on one such endeavor, one which I am very familiar with because I was peripherally involved with it. Now, in the interest of full disclosure, it must be stated that I still retain a small financial interest in my former employer, Millennium Pharmaceuticals, and that several of the authors are good friends. However, it should also be pointed out that while Millennium once trumpeted every baby step towards personalized medicine, the electronic publication of this story engendered no press release. If the company thinks it can't perk up its share price with the story, there is faint reason to think I can.
Multiple myeloma is a malignancy of the antibody secreting cells, the plasma B cells. Two famous victims are the columnist Ann Landers and actor Peter Boyle; a well-known long-term survivor is former vice presidential candidate Geraldine Ferraro. Cancers are often loosely broken into two categories: "liquid" tumors such as leukemias and solid tumors. Myelomas occupy the mushy middle: while they are derangements of the immune system like leukemias, myelomas can form distinct tumors (plasmacytomas) in the body. A hallmark of the disease is bone destruction around the tumors; patients' X-rays can have a 'swiss-cheese' appearance.
Myelomas are a devastating disease, but also occupy an important place in biotech history. Because myelomas sprout from a single deranged antibody-secreting cell, the blood (and ultimately urine) of patients becomes full of a single antibody, the M-protein (also known historically as a Bence-Jones protein). A flash of inspiration led Koehler & Milstein to realize that if they could have that antibody be one of their choosing, then a limitless source of a specific antibody could be at hand. The monoclonal antibody technology which they invented led to a host of useful reagents and tools, including home pregnancy kits. The last decade has finally seen monoclonal antibodies become important therapeutic options, particularly in cancer, and a number are being tried on myeloma: a complete circle.
The drug of interest here is not an antibody but rather a small molecule: bortezomib, tradename Velcade and known in the older literature as MLN341, LDP341 or PS341. Bortezomib works like no other drug on the market: it blocks the action of a large complex called the proteasome. A key normal function of the proteasome is to serve as the cells main protein disposal system, chewing old or broken proteins back into amino acids. Destruction of proteins by the proteasome can also be a regulated process and appears to be a component of many genetic processes.
Bortezomib has been tried as a therapeutic agent, either alone or in concert with other drugs, against a wide array of tumors. It has disappointed often, still tantalizes in some areas, and has received FDA approval for two malignancies: multiple myeloma and another B-cell malignancy called mantle cell lymphoma.
Early in the clinical trial process Millennium decided to build a personalized medicine component into the main Velcade trials in multiple myleoma. The justification for this was a mix of different ideas: including a desire to show results in personalized medicine, a potential to use the personalized medicine element to support FDA approval should trial results be equivocal, an opportunity to understand why myelomas are sensitive to proteasome inhibition.
The design was both simple and audacious: in each trial patients would be asked to supply a bone marrow biopsy for analysis by RNA profiling, which can examine the levels of each gene's mRNA. It sounds simple; in practice this would use a cutting edge technology (RNA profiling) notorious for sensitivity to sample processing. It would also be the first use of such technology in a prospective clinical trial; prior publications had either used archived samples or new samples from available patient populations. Protocols would have to be devised, staff trained at each clinical center in a multi-center trial.
The results can now be seen in Blood as Mulligan et al. You will need paid access to the journal to read the details, which most large academic libraries should have. Also, the sponsors of Blood (American Society of Hematologists) have some mechanism for patient access -- and eventually (I think it is 6 months) they make everything free. The data supplement and methods supplement are free.
Table 1 gives you some hint why few companies will be eager to invest in this kind of study again, as it details how many samples actually made it to the analysis. One can envision the path from trial to data ready to analyze as a pipeline of many steps, each of which is leaky. Patients must consent, the myleoma fraction purified, RNA captured, arrays analyzed and finally useful survival data obtained. Patient consent refusals (or later paperwork deficiencies), poor samples, patients lost to follow-up, etc. eat into the starting material. Even good clinical luck can be problematic: one of the key bortezomib trials was halted early because the drug was clearly working better than the control drug. This was great news for patients, who needed (and still need) more treatment options, and great news for the company, which could more quickly obtain approval to sell the drug. But it both deprived the personalized medicine study of anticipated patients and muddied the waters on many others. For example, samples had been obtained from control arm patients, but now many of these patients were crossing over to bortezomib and were no longer useful controls.
How leaky was the pipeline? Four clinical studies had RNA profiling components (another complication; each study was on a different trial population, with different disease characteristics). Looking at evaluable survival (meaning the patient stayed in the study long enough to figure out if the drug helped them live longer or not): 13%, 22%, 23% and 22% of patients from the 4 trials (024, 025, 039 & 040 respectively) had data for evaluation.
On the other end, many studies were accumulating information that myleoma has many genetic subtypes: perhaps at least seven or so major ones, and many of these can be further subdivided. For example, one major translocation driving myleoma involves a gene called MMSET. In a subset of these patients, a second gene (FGFR3) is also activated by the translocation. Many other classical clinical measures are used by clinicians, such as albumin and CRP levels. A very interesting question would be whether bortezomib had greater or lesser activity in any of the subtypes (or sub-subtypes); but with the ferocious sample attrition, the sample numbers just aren't great enough to be able to draw conclusions. This also illustrates the power & problem of RNA microarrays: you can look at tens of thousands of genes, allowing you to find patterns with few preconceived biases. But, you are looking at tens of thousands of genes, so the multiple testing problem is very acute.
The other thing most frustrating about this study, as in a large number of RNA profiling studies, is that there is no Eureka! moment coming from the data. Gene sets were successfully identified which can predict response or survival, but what do they mean? The hope that RNA profiling would provide the Cliff's Notes to a tumor is a hope rarely realized; instead the tumor reveals a nearly inscrutable scrawl. The study succeeded scientifically, but commercially it was not a contributor.
This will probably be more the norm than the exception in the quest for personalized medicine. Huge investments will need to be made in large clinical studies, many of which won't bear fruit, at least immediately. Combined with other myleoma studies, the Mulligan et al study will enhance our knowledge of myleoma. The execution of the study provides a roadmap for other such studies. New technologies are available which weren't when these studies began. In particular, for cancer one might opt for DNA profiling to map the underlying genetic makeup of the tumor (greatly hashed), rather than RNA. While RNA is where the action really is, DNA is much more stable and therefore may lead to results more consistent between clinical sites. And once in a while, a study might just have results that have oncologists running through the streets, making the whole exercise worthwhile.