Another missed Nobel

The newswires carried the story of Dr. Victor McKusick's passing today. McKusick was the first to catalog human mutations (as Mendelian Inheritance in Man, now better known as OMIM in its Online version), and can be truly seen as one of the founders of genomics. I won't claim to know his full biography, but compiling lists of human mutations way back when probably seemed like a bit of an odd task to a lot of his contemporaries.

This follows the sudden passing of Judah Folkman earlier this year in stealing from us a great light in biology, both of whom which the Nobel Committee failed to recognize.

Of course, there are only three Medicine awardees a year (sometimes the biologists sneak in on the Chemistry prize, but clearly McKusick & Folkman would have been in consideration for the Medicine prize). Nobel picking is a strange and unfathomable world. I'm not complaining about anyone unworthy getting it (though the Nobels have some serious closeted skeletons from the early days -- prefrontal lobotomies for all!), but it's too bad so many miss out who would deserve it.

History better learned late than never

I've always been interested in history, and the history of science is no exception. I thought I knew a bit about the history of DNA sequencing, so it was a bit of a rude surprise to read the obituaries on Wed for Dr. Ray Wu and discover that he had published one of the first DNA sequencing methods, a method that is credited with being the forerunner of Sanger sequencing. I was totally unaware of this history.
Sadly, the Wikipedia article on DNA sequencing doesn't cover this at all.

A bit of Medline hunting, aided by Dr. Wu's page at Cornell, found a few articles in PubMed, most sans abstracts and few with full text (Somebody PLEASE arrange legally to get classic J Mol Biol as free full text!). Luckily there are a few papers -- this NAR paper and an earlier PNAS one. If I'm reading it correctly, then it involved 2D analysis of digestion maps, which I had heard of so perhaps my historical knowledge isn't totally deficient.

The one question that occurs is why didn't Dr. Wu stay in the DNA sequencing business. I wonder if he left any thoughts -- was it just not interesting enough or did Sanger & Gilbert just jump ahead so he felt like it wasn't the right place to be. Whatever his reasons it can't really be criticized -- Wu had quite a publication record and appeared to be active essentially to the end of his life. It would just be interesting to understand why he took the direction he did.

Portrait of a scientist

Judah Folkman's passing this week was a sad event. I got to hear the great man speak -- at Millennium's spectacular internal seminar series 'Innovators in Medicine' -- and he was great -- inspiring, friendly, insightful. He will be missed.

Folkman was well known for having enduring brutal ridicule around his angiogenesis hypothesis. In his talk, he mentioned that he kept a room at his lab wallpapered with the years of rejection notices for grant applications and journal submission, using it to remind his students and staff that such difficulties could be overcome. One of the obits even published the crack that angiogenic factors exist 'only in the mind of the principal investigator'.

It was good to see the Globe reprint, although buried inside a section (the lead on the obituary did make the bottom of the front page) a wonderful portrait of Folkman. I don't know how long the article will remain free, but a smaller image shows up with the search. Folkman is shown framed by a lab bench with a face mixing weariness and thought. He did have quite a face! Not a movie star face, but one rich in features and details.

It isn't easy to think of good scientific portraits. Most departmental shots are straight formal shots, if not near mugshots. A few sterotyped poses predominate: for example, googling on Folkman yields some standards: hand on chin thoughtful, looking up from a microscope, teaching in front of a blackboard, listening to a colleague.

One classic is the shot of Watson & Crick with their model, though the photographer had Crick point with a slide rule, a tool utterly alien to the work. Any favorites out there? What are the best photos which illustrate the character and nature of a scientist?

Two more farewells

Today's paper's obituaries brought the news of Stanley Miller's passing. Miller's experiment with Harold Urey is notable for many reasons. First, it sparked the whole field of abiogenesis, and second it is recognizable to many persons outside of biology or chemistry. Indeed, there used to be a video at the National Air & Space Museum of Julia Child running the experiment, cooking primordial soup (I think the video can be found in some libraries). Miller's experiment did not prove abiogenesis, nor did it prove a particular model, but it did demonstrate that interestingly complex organic compounds could be generated from simple processes that might have existed on a pre-life Earth. Indeed, it is the fact that Miller's work stimultated debate & testing about what the prebiotic Earth was or was not like, the hallmark of good science on the outer fringe.

The obituary also noted that Miller's thesis advisor, Nobel Laureate Harold Urey, insisted that he be sole author on the paper. I've always known this as the Miller-Urey experiment, but that was awfully gracious of a senior scientist, and a model not always followed. At my department at Harvard there was a story of a graduate student whose defense was snubbed by his advisor due to a dispute about failing to include the advisor on a submitted paper.

I've been meaning to note one other passing of a great pioneer. In The Right Stuff, there is a scene of the potential Mercury astronauts enduring an exhalation test, and at the end only Scott Carpenter & John Glenn are still blowing bubbles. That is now the case in real life with the passing of Wally Schirra. Schirra was notorious as a jokester, but it is also notable that when it came time to name his capsule, he picked Sigma 7, for the letter's relevance to math, science & engineering. His sigma was indeed spectacular, splashing down within sight of his recovery craft. As a kid I never understood why Schirra retired just before he would have had a lock on a slot to go to the moon. As an adult, I can begin to fathom how exhausting all the training was.

Farewell Kilgore Trout

The passing this week of Kurt Vonnegut was strongly felt here, as he is one of my favorite authors. I first was keyed into Vonnegut by a high school English teacher (by the name of French!) and started reading a few. When I got to college, I started plowing through the whole shelf of Vonnegut novels & catching his few last ones as they came out. If you've never savored the ever-relevant bitter humor of Mother Night or the absurdity of Cat's Cradle, you're missing out. Breakfast of Champions & Sirens of Titan are great fun too, and even the lesser works have lots of good bits in them. Vonnegut isn't for prudes, though has texts are really pretty tame compared to a lot of other literature before and after (e.g., my current soul-enriching time sink, The Good Soldier Svejk -- now there is some inspired vulgarisms!)

Please don't take this the wrong way, but I enjoy reading good obituaries. Not that I'm happy to see someone pass, but good obituaries teach you something you didn't know -- perhaps because you never knew the person existed (but should have), but other times because you didn't know something interesting about a familiar figure. I never knew that Vonnegut had studied to be a biochemist. I think Asimov was also originally a biochemist as well -- but surely to group them in this way is to engage a granfalloon. Hi Ho!

454? How Roche!

Today's GenomeWeb bears the news that Roche Diagnostics is buying out 454 Life Sciences. Since Roche was previously the sole distributor of 454's sequencers and Curagen had announced their desire to sell the subsidiary, this is hardly a shocking development. But it is the third next generation sequencing company to be bought by an established player -- ABI slurped up Agencourt Personal Genomics and Illumina recently bought Solexa. So far, Affymetrix and Agilent have stayed out -- as has Nimblegen. There are plenty of other startup next generation sequencing shops out there, and certainly other candidates for acquirers. Roche, of course, got the clear current front runner, though it may be that the next wave of sequencer launches will close the gap quickly.

Whether these acquisitions are good for next generation sequencer development is an open question. On the one hand, these larger organizations bring deep pockets and substantial marketing expertise. But, there are plenty of pitfalls. For both ABI and Illumina, the new machines compete with their old machines -- smart companies see this as inevitable, but many companies completely botch the job due to internal conflicts (as amply documented by Clayton Christiansen in his books). It isn't encouraging that the Agencourt Personal Genomics technology is impossible to find on the ABI website.

It will also be interesting to see how long the 454 moniker lasts -- one hates to see pioneers go, but on the other hand I find naming a subsidiary after the accounting code tres gauche.

An interesting note in the GW item is that Roche was previously prohibited from marketing regulated diagnostics built on the 454 platform. Roche has previously tried to launch some molecular diagnostics -- the D word is after all in their name -- so this is a clear fit. On the other hand, a run on the 454 is reputed to be serious money, so they'll need to either find a very high value application (in a field notorious for antiquated, miserly reimbursement rules) or figure out a way to run lots of tests simultaneously. Given the rather long read lengths of the 454, one approach to the latter would be to use sequence tags near the beginning of the read to identify the original samples.

Another GW item describes some roundtable discussion at a recent meeting on next generation sequencing. The price for a genome in 2010 is still a big question, but a lot of bets are apparently in the $10K-$25K range. Some of the leaders in the field are taking a realistic view of the utility of such sequencers at such a price tag -- if you can scan the most informative SNPs for $1K, then why sequence? I'm guessing that other than a few pioneers (J.Craig is apparently resequencing his genome), there won't be a lot at those prices. On the other hand, cancer genomics is a natural fit, as each genome is different (indeed, each sample probably has many distinguishable genomes) and understanding all the fine molecular details will be valuable. SNP chips can estimate copy numbers, but not tell you how those pieces are stitched together nor find all the interesting mutations.

Even with the price at $1K, sequencing will certainly not be 'too cheap to meter'. Notions of sequencing a big chunk of the human population have appeal, but do we really want to blow another few billion dollars on human sequencing? On the other hand, as I've suggested before, other mammalian genomes may provide a lot of interesting biology for the buck (or bark). What are the most interesting unbagged genomes out there -- that sounds like the topic for another day's post...

Personalized Medicine: The long slog

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.

Eight Ligands A Leaping

There are few things you can appreciate better than something you have striven hard at yet failed. For a bit of time I was a minor expert in G-protein coupled receptors (GPCRs) -- well, really just the curator of a private database.

GPCRs are molecular wonders. The human genome contains around a thousand of so, but a large fraction of these are olfactory receptors -- our detectors of scents. These are organized into at least three major sequence families -- there were always a few more trying to break in, and I've lost track of the current opinion on these unusual families.

GPCRs have two key characteristics. First, they signal by coupling to heterotrimeric GTP-binding proteins, or G-proteins. Second, they have seven membrane spanning domains. Indeed, the main reason to claim some new looks-like-nothing-else protein as a GPCR was the prediction of this seven transmembrane, or 7TM, character. That 7TM character also makes them crystallographic sinkholes -- I think it is still true that only one crystal structure has been reported (bovine rhodopsin).

GPCRs have an amazing variety of ligands, ranging from small proteins to peptides to sugars to lipids to nucleotides to what have you. As mentioned above, our sense of smell is largely driven by GPCRs -- the discovery of this large subfamily led to a Nobel prize. All sorts of molecules have smells, suggesting the versatility of these proteins. Some fundamental tastes are also detected by GPCRs. Our very entry into this world is governed by a GPCR (oxytocin receptor). Perhaps the most amazing GPCRs are those that detect light and enable our vision. While a photon isn't truly the ligand for these receptors (a photoisomerization product of a covalently bound small molecule is), it is fun to think of it that way. If someday a physiological role is found for a noble gas, I wouldn't want to bet against a GPCR being the receptor for it.

GPCRs are also key drug targets. Many neurotransmitters are detected by GPCRs, along with many important hormones. Because they are such important drug targets, special care was made by every genomics company in sifting through their data to ensure that no GPCR slipped through unnoticed. Many that were found resembled olfactory receptors and probably are -- though sometimes they are clearly expressed in rather peculiar places outside the nose.

Once found, life is not easy. In order to configure a high-throughput screen for a small molecule (a few GPCRs are antibody targets, namely the chemokine receptors), you really need to know what the input is and which G-protein the output is sent out on. This also doesn't hurt in deducing the physiological role for the GPCR. The G-protein is the easy side. The specificity is mostly in the alpha subunit, which there are around 20 of but which also fall into a few subfamilies. Most GPCRs talk to only one of these subfamilies, and better yet for drug discovery there are mutants which seem to be rather promiscuous. So that's taken care of.

But finding a ligand: good luck! Again, since GPCRs seem to bind anything you can assume a novel one might bind just about anything. Treeing them with their kinfolk can suggest possible ligand classes, as neighborhoods on the tree will often have similar ligands, but that's no help if your novel GPCR doesn't look much like the rest. So every lab would throw a small kitchen sink of candidate ligands at their 'orphan' GPCRs and look for a signal -- and based on our experience & what's in the literature, that wasn't very often. New ligands would appear, often in small cascades -- once a new class of ligand was identified (such as short chain fatty acids), then a slew of papers would follow after a bunch of these had been explored on orphan receptors. But the last time I checked my database of receptors of interest without ligands, the list was still long.

One interesting possibility is that some of these receptors don't have specific ligands, because they may not function on their own Heterodimerization of GPCRs has been reported, and other families of receptors (kinases, nuclear hormone receptors) show how proteins lacking in some key receptor functions can still be very important via heterodimerizing with close relatives.

So it is with a bit of envy I view the recent press release from Compugen, an Israeli company that built an informatics approach to identifying novel transcripts and splice variants. They report finding, and demonstrating the function of, eight novel peptide ligands for GPCRs, some for orphan GPCRs and others as additional ligands for previously characterized ones. These are a challenging problem -- one which I and several more clever people at MLNM beat their head on -- and clearly Compugen has done well. Part of their identification relied on finding characteristic amino acid motifs recognized by the proteases which process these peptides -- many peptide GPCR ligands are clipped from larger precursors. Often, multiple ligands are encoded by the same precursor. Finding novel precursors is not trivial -- not only are they very short open reading frames, and therefore are difficult to distinguish from random open reading frames appearing in DNA, but many are also on fast evolutionary clocks -- which means that finding these peptides by cross-searching the human and mouse (for example) genomes isn't always much help.

So hats off to Compugen. I would be shocked if we are done finding GPCR ligands, but to find eight at once is quite an achievement.