Can we treat the kinase du jour?

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.

The Emperor of All Maladies

I finished yesterday Siddhartha Mukherjee's The Emperor of All Maladies. With the exception of one shocking lapse, it's a very good history of cancer therapy and I strongly recommend it for anyone interested in cancer.

Mukherjee is an oncologist and interleaves his historical view of cancer with the experiences of selected patients he tended. This humanizes the subject and brings useful context. On the historical side, he reaches all the way back to the first written description of cancer, from Pharonic Egypt (which was also the first expression of futility at treating cancer). A major thread running through the early part of the book is the career of Sidney Farber, who pioneered chemotherapy, and Mary Lasker, who reshaped the role of the U.S. government in cancer research despite having never held elective office.

The book is written for a lay audience and I think he does a good job. There are some key lessons which need to be heard widely. Mukherjee describes many of the twists and turns, the clever leaps of logic and the leaps that failed. For example, Farber's key insight was that leukemia was characterized by improperly functioning bone marrow, a trait shared with several nutritional deficiencies which had just been solved. So he tried treating childhood leukemias (deemed utterly untreatable by oncologists of the time) with B-vitamins, to disastrous results. But, then the second leap occurred -- Farber tried B-vitamin antagonists, and soon found success.

Mukherjee also captures many of the missed opportunities and the non-scientific barriers to progress. Farber was shunned by many colleagues because he was not an oncologist, but a pathologist. The initial misstep led to utter non-cooperation from the oncologists, leaving Farber's doctors to sharpen their own needles and dump their patient's bedpans. His supply of anti-folates came from an immigrant doctor who had left for chemistry and industry after his foreign credentials proved useless. Much more recently, there is the story of how Weinberg's group discovered Her-2 but didn't contemplate pursuing therapy against it. Far worse is how the lawyers at the institute Farber founded nearly iced Gleevec, and even after that issue was dealt with (when Gleevec's proponent Brian Druker moved to another institution) the management of Novartis nearly killed it. Similarly, Genentech all but dropped Herceptin; again it was an outside oncologist who drove the project to success.

The book also gives a good overview of how many things needed to be invented along the way and issues which arise. Simple epidemiology noted the high incidence of scrotal cancer in boy chimney sweeps; the intersection of a rare cancer and rare occupation made the relationship unquestionable. But later, researchers were faced with the challenge of proving a common cancer (lung) was linked to a common environmental factor (smoking) and this required new methods such as the case-control study. In the chemotherapeutic arena, the book covers many iterations of trial design and testing strategy and also brushes a bit on the changing ethical landscape.

If you've read my previous book reviews, a typical exercise for me is to ask what else could have gone in. Now, this is admittedly sometimes unfair to the author and one prior reviewee has politely chided me that some of what I missed ended up on the editor's floor. Plus, books that want to be read and not doorstops need to respect certain length limits. But, when I am writing I find it a useful exercise; only when we consider the whole range of possibilities can we be confident that the correct balance has been reached.

Perhaps the most surprising area barely touched on is angiogenesis and anti-angiogenic therapy. Some of this may have to do with timing; most of the book concerns events before about 2004, though with an impressive quick coverage of some of the learnings from cancer genomes. So many of the travails of Avastin would be after that rough divide. Still, this is a hot topic and perhaps that is why I miss it from the book. This book deserves to be widely read and probably will be (it is certainly the de facto Book-of-the-Month at work) and will therefore form the foundation for many public conversations about cancer

Another topic essentially absent from the book are various types of immunotherapy. Again, this is an area having some resurgence (with the approval of the prostate cancer vaccine Provenge), but it isn't clear how important it will be long term. I think there was a passing mention of Coley's toxins, but saw none of the late 70's excitement around interferons (which, alas, became only a niche player in oncology) or the 80's focus on interleukins.

Finally, though there is some coverage of the world of molecular analysis of cancers (such as cancer genomics), the field of microarray classification of cancer and guiding therapy isn't explored. This is a pretty complex topic with a lot of shifting (and, as noted in the recent George Poste Nature opinion piece, far more smoke than light) so it's a bit understandable it was left out.

Overall though, I can't think of anything that is clearly missing. But now my quibble and serious complaint. Certainly the book not only filled in a lot of areas I just hadn't been exposed to, but even had me running for articles very close to where I see my core training.

The quibble is a bit of a pet peeve. The book, like many (and myself), roughly divides cancer chemotherapeutics into two bins (with room for a small "unclassified" bin as well). Cytotoxics are broad-spectrum cell killers and constitute the bulk of cancer therapy agents.

Targeted therapies are the sticking point. For me, it is important to reserve this category for agents that have two critical properties: we know what the drug acts on in cells and we know something about the relevance of that mechanism to a tumor. Mukherjee gives a number of interesting stories about targeted therapies. For example, anti-estrogen therapy for breast cancer can trace back to a doctor hearing from Scottish shepherds that removing a ewe's ovaries would cause their udders to shrink. Another fascinating story relayed in the book shows how these categories can be tricky. By undescribed means (probably random screening), it had been found that cis-retinoic acid could be used to treat the aggressive leukemia APL, though with highly variable results. An inspired leap of logic led to the decision to test all-trans retinoic acid (ATRA) in APL, with stunningly successful results. Only later was it discovered that most APL cases are driven by a fusion protein derived from a retinoic acid receptor. So ATRA started as "other" and only later fits my definition of targeted therapy.

So what's my beef? It's when Mukherjee describes Velcade, thalidomide and Revlimid in multiple myeloma as targeted therapies. He's hardly alone; this is a common description. But in my taxonomy, Velcade is a cytotoxic. We know where it acts in the cell but not why that is important in cancer and not how to select which patients to use it in. Thalidomide and Revlimid probably should go into the "other" bucket; we're not sure of the mechanism but they aren't generically cytotoxic. Even one of the drugs I currently work on (an HSP90 inhibitor) I would generally call a cytotoxic; it's not a perjorative in my book. On the other hand, in one subset of lung cancer there is a strong hypothesis as to how such HSP90 inhibition works at a molecular level. So as with many biological classifications, they're a bit smudgy -- but I still think they are useful and worth being precise about.

Finally, the big complaint. One of the longer stories in the book concerns the apogee of intensive chemotherapy, in which breast cancer patients were given doses high enough to utterly destroy their bone marrow, followed by bone marrow transplants. This was an important and controversial approach to therapy, with patients begging to get into trials and fighting legal battles to have their insurance companies pay for these unproven treatments. Indeed, Masschusetts was one state which enacted legislation to mandate coverage of this particular treatment. However, when the clinical trial results rolled in, all but one large study showed no benefit. The outlier study showed a huge benefit. However, on closer inspection the outlier turned out to a fraud of truly monstrous proportions. In discussing that denouement, Mukerjee points out that a male patient "obviously" couldn't have been a legitimate member of the trials. Breast cancer in men is rare, but rare is not impossible and it is particularly critical for oncologists to not have that blind spot. Indeed, this is particularly important in families with a history of breast cancer; the risk of male breast cancer is much higher in BRCA1/2 familes.

That one blemish aside, though, I can strongly recommend this book. As I've noted before, if many read it then there will be a much stronger general basis for discussing cancer and the public policy around it.

Chromothripsis: Cratering of Chromosomes

A stark frame from Apollo 16 shows a lunar surface remodeled by violent collisions. Even in a single static snapshot hints at the order of events. The large crater near the center of the image was later remodeled by a not small crater breaking the original rim. Careful study of other photographs, especially of the even more chaotic far side of the moon, can piece together the temporal order of events, from such overlaps in craters and their ejecta.

The moon has more than a few parallels to the genomic chaos present in cancer. Most cancers are characterized by a degree of aneuploidy, though a few only have small numbers of genomic alterations, much like the smoother regions pictured. Some cancer cells have chromosome complements like the far side of the moon, battered to the brink of non-recognition. And like the two large craters, we often picture the chromosome alterations as being sequential, with long gaps in between. Such step-wise changes are seen as mirrored in stepwise changes in biology; each new change has the potential to bring new advantages to a proto-tumor cell. A corollary of this is that these changes are ongoing; today's tumor has more changes than several months ago, and a sample several months in the future will look yet different. Indeed, one criticism sometimes launched at cancer genomics efforts is that they are taking a single snapshot of a fast-moving phenomenon.

If you look closer at the lunar photo, another interesting feature will emerge. What might first appear to be a slash pointing at the large crater is actually a chain of craters. These are believed to have arisen from a single object fragmenting before impact, much as the comet Shoemaker-Levy did a number of years ago prior to crashing into Jupiter. Such crater chains are seen many times on our own moon, as well as on Mars and moons of Jupiter. A new paper in Cell brings our attention to the same phenomenon in a subset of cancers, in which genomes are multiply mangled in a single event. And, like Apollo 16, the key evidence for understanding very dynamic events are static genomic snapshots.

For the impatient such as this author, Figure 1 C&D is perhaps the quickest way to dispel doubt that such occurs. These use Circos diagrams to depict the chromomal rearrangements present in a chronic lymphocytic leukemia (CLL) sample at initial presentation and relapse: the rearrangement diagrams look like carbon copies, despite 42 distinct alterations in the diagnosis samples. These were identified by high-throughput paired-end sequencing. Many of these breakpoints are locally clustered on the original chromosome; the long arm of chromosome 4 suffered nine breaks, each re-connected to a different chromosome. Clustered breaks are sometimes remarkably tightly packed: seven rearrangments are from a single 30 kilobase region and another 6 from a 25 kilobase region. However, fragments from such near origins are flung around, often ending up distant from each other in the tumor chromosome.

Digging deeper, a curious pattern emerges from looking at the pattern of loss of heterozygosity versus copy number. Clearly the single copy regions cannot be heterozygous, but what is striking is that all of regions of copy number two are heterozygous. This clearly indicates that none of the copy number two regions are the result of a reduction to single copy followed by an expansion back to two copies; heterozygosity lost cannot reappear. Change points for copy number fall essentially evenly into the four possible intrachromosomal buckets: deletions, head-to-head inverted, tail-to-tail inverted, and tandem duplications.

Now, this could be a single odd case. The researchers combed through the masses of publically available cancer cell line copy number and LOH data (which they largely generated) to find more. Out of 746 cancer cell lines, 18 (2.4%) showed the pattern of frequent changes in copy number in local regions of chromosomes. So the phenomenon appear to not be unique to their original sample, though present in a small minority of cell lines. They selected four cell lines for paired end sequencing to further explore this.

The sequencing reveals the same pattern, though sometimes even more intensely. One line has 239 rearrangements of chromosome 15; another 77 alterations of the short arm of chromosome 9. A third has only 55 rearrangements in chromosome 5. And while these changes are not the only rearrangements in these genomes, the other changes tend to stand aloof from the chromosomes which have been extensively fractured.

Such a chromosome catastrophe (for which the authors coin the term "chromothripsis", "thripsis" is apparently Greek for shattering into pieces) could have a number of beneficial effects for a tumor, as the authors explore. One route is through the amplification of beneficial oncogenes, perhaps through the formation of small auxillary chromosomes. In a small cell lung cancer line, such a chromosome carries only 1.1Mb of original cellular content , but contains the potent oncogene MYC -- and multiple copies even.

Conversely, such a radical remodeling of a chromosome could potentially destroy multiple tumor suppressors in a single event. Possible examples of such simultaneous multiple disruptions were found in one chordoma and several other samples.

The extensive reordering of chromosomes during chromothripsis can also lead to the formation of fusion genes. But, as noted in the paper, it would seem unlikely that these are frequently tumor drivers (though never confuse unlikely with impossible!). In chronically chromosomally unstable cells, there are presumably many different possible rearrangements generated, increasing the odds of finding one with useful advantages. But with chromothripsis, the cell would have to get lucky on one mighty roll of the dice.

What could perform such a genetic wrecking act? One possibility raised in the paper, which was also the first to jump into my mind, would be high-energy ionizing radiation (probably most commonly X-rays from terrestrial sources, but also perhaps cosmic rays). Imagine a condensed chromosome and then picture an energetic particle hitting that chromosome. Some paths through the chromosome would result in one or a few breaks -- but some paths might enfilade the DNA, riddling it with breaks. Alternatively, broken telomeres can lead to the inappropriate fusing of chromosome ends, followed by rebreakage when the chromosomes are pulled to opposite poles during cell division (which in turn now have sticky ends). While this wouldn't technically be simultaneous destruction, a few successive rounds of such "breakage-fusion-bridge cycles" during cell division can generate quite a mess. It is striking and consistent with this that several examples found in the paper involve rearrangements near the end of one chromosomal arm. It will be fascinating to see if anyone tries to replicate these phenomena in controlled settings and try to create chromothripsis in the lab, and thereby determine which mechanism is more consistent with the data -- or perhaps to what fraction each mechanism occurs and any distinguishing genomic artifacts for each mechanism.

This paper has certainly altered my perspective of the chromosomal chaos seen in cancer. My previous gradualist mental model now has an asterisk. Where I previously pictured cells in a constant process of continuing rearrangement and amplification, now I can see that in some cases the genome is actually relatively static. There is a minority school of thought which has argued that aneuploidy is the critical feature of cancer and that any chemotherapeutic regimine is doomed by the dynamics of aneuploidy. Here are clearly some counterexamples; tumors which are not constitutively unstable and which do not progress after treatment due to further rearrangement. It also is a useful paper to recall the next time someone dismisses cancer genomics with the argument that cancers are dynamic, but a genome analysis looks only at one point in time. Sometimes, if you look carefully enough, a single snapshot can tell a very dynamic story.


P.J. Stephens, C.D. Greenstein, B. Fu, F. Yang, G.R. Bignell, L.J. Mudis, E.D. Pleasance, K.W. Lau, D. Beare, L.A. Stebbings, S. McLaren, M-L Lin, D.J. McBride, I. Varela, S. Nik-Zainal, C. Leroy, M. Jia, A. Menzies, A.P. Butler, J.W. Teague, M.A. Quail, J. Burton, H. Swerdlow, N.P. Carter, L.A. Morsberger, C. Iacobuzio-Donahue, G.A. Follows, A.R. Green, A.M. Flanagan, M.R. Stratton, P.A. Futreal, & P.J. Campbell (2011). Massive Genomic Rearrangement Acquired in a Single Catastrophic Event during Cancer Development Cell, 144 (1), 27-40 : 10.1016/j.cell.2010.11.055

[2011-02-03 Fixed URL for paper; Research Blogging apparently has been failing to build it correctly]

Oncogenesis Via Altered Enzyme Specificity, Part I

(Correction: a friend close to the story pointed out EZH2 is a lysine, not arginine methyltransferase. Stupid mistake! -- though I got it right once in the original version -- small consolation)

There's a bit of an involved story I've been meaning to put together & now another paper with a similar theme showed up. After some thought, I realized that the second story should go first.

Oncogenes are genes which when added to a cell can transform it to a cancerous state. A number of different classes of proteins can be oncogenic, but quite a few are either transcription factors or enzymes. I'm going to focus here on enzumes.

Oncogenic enzymes somehow have an enzymatic activity which promotes cell growth. A lot of oncogenic enzymes are protein kinases, and these can be activated by a number of mechanisms. For example, some are activating simply by being overexpressed, which in cancer occurs most commonly by amplification of the underlying chromosomal DNA. Another recurrent mechanism is the removal of inhibitory domains. Other changes alter the equilibrium between active and inactive states. Certain kinases are activated by dimerization, so some oncogenic mutations enhance dimerization. For example, in some fusion kinases, in which a chromosomal rearrangement has fused a kinase with another protein, a key role of the partner protein is to supply a dimerization motif.

The RAS family of GTPases are an interesting variant on this theme. RAS proteins (KRAS, HRAS and NRAS being the most important oncogenes) transmit growth-promoting signals when they have a bound GTP. They also have a slow GTPase activity which hydrolyzes the GTP to GDP, and when RAS proteins have GDP bound they no longer transmit the signal. Exchange of the GDP to GTP reactivates the growth signal. Oncogenic KRAS mutations slow or eliminate the GTPase activity; without this activity the gene never turns off. Hence, only a small number of possible mutations in KRAS will successfully turn it into an oncogene, since mutations must inactivate the GTPase without altering the other functions of the protein.

The two stories, one brand new related here and one which hit a fascinating milestone recently which will be in a future installment, are cases of additional ways enzymes can be altered to promote tumors. In each case, rather than activating or inactivating an enzyme the mutations succeed in tuning the activity of an enzyme in a way favorable to cancer.

About a year ago the Vancouver cancer genomics group published the identification of recurrent mutations in lymphomas of the gene EZH2, a histone methyltransferase. Strikingly, the mutations are strongly concentrated on a single change, modifying Tyr641, though to a number of other amino acids. So what is so important about Tyr641? A new paper provides the mechanistic explanation.

Histone methyltransferases such as EZH2 add a methyl group to lysine residues (other methyltransferases can methylate arginine, which I mistaken pegged EZH2 in the original version of this). Any given lysine can actually have 4 different methylation states: none, single, double, or tri. This means in turn that an lysine methyltransferase has three types of substrates: those with 0, 1 or 2 existing methyl groups. What the new work shows is that Tyr641 is important in selecting the substrates, and these mutations focus the activity on converting dimethyl lysine to trimethyl lysine.

Several lines of evidence point to this conclusion. Two other lysine methyltransferases have been shown to prefer trimethylation when mutated in an analogous way. Molecular modeling suggests that this tyrosine serves to inhibit effective operation on dimethyl substrates. In vivo the mutation acts dominantly to increase trimethylated lysine levels on histones and in vitro the appropriate complex has an increased preference for dimethylated peptides.

This is the first such reported disease-causing mutation of this sort, though as noted above similar mutations have been created by scanning mutagenesis. Will we see other ones? There are many other homologous methyltransferases, but a quick sampling of COSMIC doesn't reveal a homolog with any recurrent pattern of mutation. It's worth keeping a lookout for one, but if not then a new mystery will remain to be explored: why is EZH2 special in this regard?

Going a bit farther afield, could there be oncogenic mutations in kinases which alter the substrate specificity? Given that some kinases require prior ("priming") phosphorylation of substrates, could a mutation in the kinase reduce this requirement? Alternatively, do some kinases phosphorylate both cancer-promoting and cancer-retarding substrates? If so, could mutations exist which shift the balance towards cancer promotion? Seems like a long shot, but who would have guessed in advance of mutations like the EZH2 ones?



Yap DB, Chu J, Berg T, Schapira M, Cheng SW, Moradian A, Morin RD, Mungall AJ, Meissner B, Boyle M, Marquez VE, Marra MA, Gascoyne RD, Humphries RK, Arrowsmith CH, Morin GB, & Aparicio SA (2010). Somatic mutations at EZH2 Y641 act dominantly through a mechanism of selectively altered PRC2 catalytic activity, to increase H3K27 trimethylation. Blood PMID: 21190999

Scenes from the Cancer Personalized Medicine Wilderness

I'm going to attempt to synthesize a number of thoughts which I've long pondered along with a bunch of news items I came across today. With luck, the result will be coherent and I'll not make a fool of myself.

There was a very interesting article last week in the New York Times on a serious ethical dilemma in melanoma and how different specialists in the field are voicing opinions on both sides of the divide. Even better, today I came across an excellent blog post reviewing that article which also added a lot of expert background. I'll summarize the two very quickly.

Metastatic melanoma is an awful diagnosis; the disease is very aggressive. Furthermore, the standard-of-care chemotherapy drug is a very ugly cytotoxic, with nasty side effects and very poor efficacy (more on that later). Sequencing studies have revealed that well over half of metastatic melanomas have a mutant form of the kinase B-RAF (gene: BRAF), most commonly the mutation V600E (which, alas, due to some sequencing error was for a while known as V599E). That's the substitution of an acidic residue (glutamate) for a hydrophobic one (valine), and it is right in the kinase active site.

Now, a biotech called Plexxikon, in conjunction with Roche, has developed an inhibitor of B-RAF called PLX4032. In Phase I trial results reported this summer in the New England Journal of Medicine, very promising tumor regressions were seen. Now remember, this was a single-arm Phase I trial for safety, meaning we don't have an objective comparison to make.

And there begins the rub. To some doctors (and many patients), the combination of great preclinical results, the theoretical and experimental underpinnings for targeting B-RAF in melanoma and the observed regression means we have a winner on our hands and it is now unethical to have a randomized trial comparing the new compound against the standard-of-care.

At the other pole are doctors who worry that we have been fooled before.
My standard example to trot out for such cases is a famous CAST cardiovascular trial to which a placebo arm was grudgingly added -- a sound theory had been advanced that
suppressing arrythmias in certain patients would prevent death. CAST was stopped early when it was clear the placebo arm fared far better; the toxicities of the drugs overwhelmed any benefits. Even closer to our current story is the drug sorafenib, which was originally developed as a B-RAF antagonist. Now, there are many in the field who argued that it really wasn't, but Bayer and Onyx got it to market (probably based on its inhibition of numerous other kinases) and the "raf" syllable in the generic name points to their belief in the B-RAF theory. Unfortunately, in randomized clinical trials it failed to work in V600E melanomas.

One idea that was apparently floated by at least one oncologist working in the trials, but rejected by the corporate sponsors, was to try to win approval based on nearly miraculous recoveries seen in some patients on death's door. What the NYT article failed to discuss is whether the FDA would buy that argument; there are many reasons to think they wouldn't -- they really do not like single arm trials, because all too often spurious results occur do to random chance (or rarely, to manipulation of the trial).

An important idea discussed in all this is the concept that once we have established a therapy as efficacious, it is generally unethical to withhold that therapy from patients. But, we are often not on such solid ground even in this area. Clinical trials represent a horrible case of multiple testing; more than a few drugs that squeaked through their trial would not if you ran the trial again; they just got lucky. Don't believe me? Think back to Iressa, which received accelerated approval for lung cancer and then had it withdrawn (only to later be reintroduced). We now know a key piece of that particular puzzle: Iressa works in patients whose tumors have mutant forms of the EGFR. The first trial, by chance, was enriched for such patients and the second trial (also by chance) was not as enriched. Given that the EGFR hypothesis wasn't known, neither trial could have been manipulated.

But another recent item, covered in a different post on the same blog, reminds us that even well-established clinical approaches may not hold true over time. Screening mammography is a hot potato issue in cancer: can you save lives by screening healthy women for breast cancer. Various studies have tried to ask this question not just for women overall, but by age groups since the incidence of breast cancer and the quality of mammograms changes with patient age. The newest fuel on this fire is a very clever Norwegian study, which I won't attempt to summarize, that suggests that much (but perhaps not all) of the benefit of screening mammography has been eroded by improvements in cancer care. In other words, the advantage of early detection has been blunted by better treatments. Now, I'm not qualified to really review that study, but certainly this is a concept we should keep in mind: the utility of medical strategies may change over time, and not always for the better.

In my mail tonight was a thick magazine-sized volume from Scientific American, which I confess I am not a subscriber of (it's a fine magazine; I just already subscribe to too many fine magazines). This special edition, titled "Pathways: The changing science, business & experience of health", focuses on healthcare with a mix of articles. Some appear to be written by professional writers, while others are thinly-veiled advertisements for various companies.

In scanning the table of contents, I was caught by "Pioneering Personalized Cancer Care", though unfortunately this turns out to be one of the puffier pieces. Written by two principles in the company, it mostly describes N-of-one, a company which has as its customers cancer patients. N-of-one tries to distill the available knowledge on a person's tumor and help them navigate to the most appropriate tests. It's a business model I've sometimes wondered about for myself, since playing an oncologic Sherlock Holmes could be both fascinating and rewarding. On the other hand, the regulatory environment is fraught with uncertainty and most likely this sort of organization will have to rely on wealthy customers willing to pay their own way.

Now, the article did set my teeth on edge early on with the statement "Recently, projects such as the Cancer Genome Atlas have documented thousands of mutations in cancer cells that can lead to unregulated cell growth and prevent apoptosis (cell death), the hallmarks of malignancy". Any regular reader of this space knows that I am a gung-ho proponent of sequencing tumors, but with that comes an obligation to be honest. And the honest truth is that sequencing has yielded thousands of candidates, but only a handful of those have actually been shown to have transforming ability -- there's just no high-throughput way to do that en masse.

But, what N-of-one and others are doing is where I strongly believe the future of oncology lies. But, it will be a complicated place. Getting back to B-RAF, I've heard noise that it has been found in a number of additional tumor types, albeit at low frequency. So, supposes it occurs at 1 in 1000 frequency in some awful tumor type. With routine whole-genome sequencing of tumors, we could detect that. Such sequencing is starting to be used to good effect, as reported recently in Nature. That leads to a conundrum for everyone. For a patient or clinician, do you go with PLX4032, given that we know it targets BRAF -- but knowing that we don't know whether BRAF is really driving your tumor (especially if the mutation is not V600E)? For those wanting to design clinical trials, could you really find enough patients to stock a trial -- or are you willing to have a trial with "any cancer, as long as it has a BRAF mutation"?

This is the challenge that personalized medicine presents us. With genome sequencing (and eventually also routine whole methylome profiling), we can find what makes cancers different -- but how will we ever actually sort through all those differences? Should we move away from randomized trials to going where the science seems to lead us, even knowing that more than a few times there have been dead ends?

I can find only one easy answer to all this: don't trust anyone who offers an easy answer to all this.

ARID1A A Fertile Ground for Mutations in Ovarian Clear Cell Carcinoma

Although ovarian clear cell carcinoma does not respond
well to conventional platinum–taxane chemotherapy
for ovarian carcinoma, this remains
the adjuvant treatment of choice, because effective
alternatives have not been identified.

This sentence is a depressing reminder of the status of medical treatment of far too many tumor types. Present in roughly 12% of U.S. ovarian cancer cases, ovarian clear cell carcinoma (OCCC) is a dreadful diagnosis.

Two papers this week made a significant step forward in understanding the molecular basis -- and heterogeneity -- of this horror. Seemingly the finale of an old-fashioned race to publish, groups centered at the British Columbia Cancer Center (in New England Journal of Medicine) and Johns Hopkins University (in Science) published papers with the same headline finding: inactivating mutations in the chromatin regulating gene ARID1A (whose gene product is known as BAF250) are a key step in many -- but not all -- OCCC. I'll use the shorthand Vancouver and Baltimore to refer to the respective groups.

Both papers got here by the largest applications of second generation sequencing to cancer so far published. The Vancouver work relied on transcriptome sequencing (RNA-Seq) of a discovery cohort of 18 patients; the Baltimore group used hybridization targeted exome sequencing on just 8 patients. Both used Illumina paired-end sequencing for the discovery phase; Vancouver also used the same platform for validation on a larger cohort.

Whole genome sequencing is likely the future for cancer genomics. A non-cancer paper just published 20 genomes in one shot, underscoring how this is becoming routine with easy samples & a work which is apparently in press (I have no inside knowledge; it has been discussed at several public meetings) will have perhaps a dozen human genomes in it. But, there are still cost advantages to focusing on expressed genetic regions (and perhaps a bit more) and perhaps further information to be gleaned from actually looking a gene expression. These two papers give an opportunity, albeit a bit constrained, to compare the two approaches.

One interesting note comes straight out of the Vancouver data. After finding ARID1A mutations in 6/18 discovery samples, they re-screened those samples plus 211 additional samples. In total this set included 1 OCCC cell line, 119 OCCC, 33 endometrioid carcinomas and 76 high-grade serous carcinomas. The validation screen was by long-range PCR (mean product size 2067 bp) products sheared and sequenced on the Illumina. One exon proved troublesome and required further PCR and sequencing by Sanger. In any case, the key bit here is in the discovery cohort this approach found ARID1A mutations which had been missed by the original RNA-Seq. As the authors state, a likely culprit is nonsense mediated decay (NMD). It would be interesting to go into their dataset to see if these samples had a markedly lower expression of ARID1A, though I don't have easy access to it (it has been deposited, but with protections that should be the subject of a future post).

One interesting contrast between the two studies is the haul of genes. The Vancouver group found ARID1A as a recurrently mutated gene; the Hopkins group not only bagged ARID1A but also KRAS, PIK3CA and PPP2R1A. KRAS and PIK3CA are well-known oncogenes in multiple tumor types and had previously been implicated in OCCC, but PP2R1A is a novel find. The Vancouver group did specifically search for KRAS and PIK3CA mutants in their cohorts by PCR assays and found one patient sample and one cell line with KRAS mutations. Again, it would be interesting to review the RNA-Seq data to generate hypotheses as to why these were not found in the Vancouver set. On the other hand, the RNA-Seq data did identify one case of a rearranged ARID1A. While it is possible to use hybridization capture to identify gene fusions, this cannot be practically done in a hypothesis-free manner. In other words, without advance interest in ARID1A that approach would not work. In addition, CTTNB1 (beta catenin) mutations had been found previously in OCCC and were specifically checked (and found) by the Vancouver group, but none were reported by the Baltimore group. One final small discrepancy: both groups looked at cell line TOV21G for their mutations of interest and both found the same activating KRAS and PIK3CA alleles. However, Vancouver found one ARID1A allele but Baltimore found that one and a second one (actually, the two mutations I am calling the same [1645insC and 1650dupC] aren't described precisely the same, though I'm guessing it is a difference in an ambiguous alignment).

One other surprise is that TP53 (p53) and PTEN mutants had apparently been reported either for OCCC or endometriosis-associated tumors, yet neither group reported any.

An analysis that is not explicitly found in either paper but I feel is valuable is to look at the co-occurrence of these mutations. If we look only at patient samples, then the big take-home is that neither group saw co-occurrence of KRAS and ARID1A (the TOV21G cell line is at odds with this conclusion). Mutually-exclusive mutations have been seen in many tumors. For example, KRAS mutations are generally mutually-exclusive with other mutations in the RTK-RAS-RAF-MAPK pathway. In contrast, ARID1A mutations are found in conjunction with mutations in CTTNB1, PIK3CA and PPP2R1A -- one patient sample in the Baltimore data was even triple mutant for ARID1A, PIK3CA and PPP2R1A. About 30-40% of sample are mutated for none of these genes as far as this data can tell; the hunt for further causes will continue. Will they be epigenetic? Mutations in regulatory elements?

Another interesting comparison is simply the number of mutations per sample. The Hopkins exome data typically has very small numbers of mutations (after filtering out germ line variants); as few as 13 in a sample and as many as 125 -- and the high number was from a tumor which had previously been treated with DNA-damaging agents (all of the other tumors in the Hopkins study were treatment naive). In contrast, the Vancouver data often found more than 1000 non-synonymous variants per tumor. Unfortunately, no clinical history information is available for the Vancouver cohort, so we don't know if this is from DNA-damaging therapeutics or differences in the sequencing or variant filtering. In an ideal world, we could filter each data set with the other group's filtering scheme to see how much of an effect that would have.

The Vancouver group went beyond sequencing to examine samples by immunohistochemistry (IHC) for expression of the ARID1A gene product, BAF250. There is a strong, but imperfect, negative correlation between mutations and BAF250 expression. Some mutated but BAF250-expressing samples may be explained by the target of the antibody; the truncated forms may still express the correct epitope. Alternatively, ovarian cells may be very sensitive to the dosage of this gene product (in some samples both wt and mutant alleles were clearly found in the RNA-Seq data). Also of interest will be samples lacking expression but unmutated; these may be the places to identify further mechanisms for tumors to eliminate BAF250 expression.

The Vancouver study illustrates one additional bonus from RNA-Seq data: a list (in the supplemental data) of genes differentially expressed between ARID1A mutant and ARID1A wild-type cells.

Another interesting bit from the Vancouver paper is looking at two cases in which the tumor was adjacent to endometrial tissue. In one of these, the same truncating mutation was found in the adjacent lesion and tumor -- but not in a distant endrometriosis. Hence, the mutation was not driving the endometriosis but occurred afterwards.

I'm sure I'm short-shrifting further details from the paper; there's a lot of data packed in these two reports. But, what will it all mean for ovarian cancer patients? Alas, none of the genes save PIK3CA are obvious druggable targets. PIK3CA encodes the alpha isoform of PI3 kinase, a target many companies are working on. But that wasn't novel to these papers. PP2R1A is a regulatory subunit of a protein phosphatase and the mutations are concentrated on a single amino acid, suggesting these are activating mutations (as seen in ARID1A, inactivating mutations can sprawl all over a gene). Phosphatases have not been a productive source of drugs in the past, but perhaps that can be changed in the future. Chromatin regulation is a hot topic, but ARID1A is deficient here, not active. Given that tumors can apparently live with two mutated copies, the idea of further inactivating complexes with ARID1A mutations is probably not a profitable one. But, perhaps there is a ying-yang relationship with another chromatin regulator which can be leveraged. In other words, perhaps inhibiting an opposing complex could restore balance to the cell's chromatin regulation and inhibit the tumor. That's the sort of work which can build off of the foundation these two cancer genomics papers have provided.




Kimberly C. Wiegand, Sohrab P. Shah, Osama M. Al-Agha, Yongjun Zhao, Kane Tse, Thomas Zeng, Janine Senz, Melissa K. McConechy, Michael S. Anglesio, Steve E. Kalloger, Winnie Yang, Alireza Heravi-Moussavi, Ryan Giuliany,Christine Chow, John Fee, Abdalnas (2010). ARID1A Mutations in Endometriosis-Associated Ovarian Carcinomas New England Journal of Medicine : 10.1056/NEJMoa1008433

Jones S, Wang TL, Shih IM, Mao TL, Nakayama K, Roden R, Glas R, Slamon D, Diaz LA Jr, Vogelstein B, Kinzler KW, Velculescu VE, & Papadopoulos N (2010). Frequent Mutations of Chromatin Remodeling Gene ARID1A in Ovarian Clear Cell Carcinoma. Science (New York, N.Y.) PMID: 20826764

A huge scan through cancer genomes

Genentech and Affymetrix just published a huge paper in Nature using a novel technology to scan 4Mb in 441 tumor genomes for mutations, the largest number of tumor samples screened for many genes. Dan Koboldt over at MassGenomics has given a nice overview of the paper, but there are some bits I'd like to fill in as well. I'll blame some of my sloth in getting this out to the fact I was reading back through a chain of papers to really understand the core technique, but that's a weak excuse.

It's probably clear by now that I am a strong proponent (verging on cheerleader) for advanced sequencing technologies and their aggressive application, especially in cancer. The technology used here is intriguing, but it is in some ways a bit of a throwback. Now, on thinking that (and then saying it aloud) forces me to think about why I say that and perhaps this is a wave of the future, but I am skeptical -- but that doesn't detract from what they did here.

The technology, termed "mismatch repair detection", relies on some clever co-opting of the normal DNA repair mechanisms in E.coli. So clever is the co-opting, that the repair mechanisms are used to sometimes break a perfectly good gene!

The assay starts by designing PCR primers to generate roughly 200 bp amplicons. A reference library is generated from a normal genome and cloned into a special plasmid. This plasmid contains a functional copy of the Cre recombinase gene as well as the usual complement of gear in a cloning plasmid. This plasmid is grown in a host which does not Dam methylate its DNA, a modification in E.coli which marks old DNA to distinguish it from newly synthesized DNA.

The same primers are used to amplify target regions from the cancer genomes. These are cloned into a nearly identical vector, but with two significant differences. First, it has been propagated in a Dam+ E.coli strain; the plasmid will be fully methylated. Second, it also contains a Cre gene, but with a 5 nucleotide deletion which renders it inactive.

If you hybridize the test plasmids to the reference plasmids and then transform E.coli, one of two results occur. If there are no point mismatches, then pretty much nothing happens and Cre is expressed from the reference strand. The E.coli host contains an engineered cassette for resistance to one antibiotic (Tet) but sensitivity to another antibiotic (Str). With active Cre, this cassette is destroyed and the antibiotic resistance phenotype switched to Tet sensitivity and Str resistance.

However, the magic occurs if there is a single base mismatch. In this case, the methylated (test) strand is assumed to be the trustworthy one, and so the repair process eliminates the reference strand -- along with the functional allele of Cre. Without Cre activity, the cells remain resistant to Tet and sensitive to Str.

So, by splitting the transformation pool (all the amplicons from one sample transformed en masse) and selecting one half with Str and the other with Tet, plasmids are selected that either carry or lack a variant allele. Compare these two populations to a two-color resequencing array and you can identify the precise changes in the samples.

A significant limitation of the system is that it is really sensitive only for single base mismatches; any sort of indels or rearrangements are not detectable. The authors wave indels away ash "typically are a small proportion of somatic mutation", but of course they are a very critical type of mutation in cancer as they frequently are a means to knock out tumor suppressors. For large scale deletions or amplifications they use a medium density (244K) array, amusingly from Agilent. Mutation scanning was performed in both tumor tissue and matched normal, enabling the bioinformatic filtering of germline variants (though dbSNP was apparently used as an additional filter).

No cost estimates are given for the approach. Given the use of arrays, the floor can't be much below $500/sample or $1000/patient. The MRD system can probably be automated reasonably well but with a large investment in robots. Now, a comparable second generation approach (scanning about 4Mb) using any of the selection technologies would probably run $1000-$2000 per sample (2X that per patient), or perhaps 2-4X as much. So, if you were planning such an experiment you'd need to trade off your budget versus being blind to any sort of indels. The copy number arrays add expense but enable seeing big deletions and amplifications, though with sequencing the incremental cost of that information in a large study might be a few hundred dollars.

I think the main challenge to this approach is it is off the beaten path. Sequencing based methods are receiving so much investment that they will continue to push the price gap (whatever it is) closer. Perhaps the array step will be replaced with a sequencing assay, but the system both relies on and is hindered by the repair system's blindness to small indels. Sensitivity for the assay is benchmarked at 1%, which is quite good. Alas, no discussion was made of amplicon failure rates or regions of the genome which could not be accessed. Between high/low GC content and E.coli-unfriendly human sequences, there must have been some of this.

There is another expense which is not trivial. In order to scan the 4Mb of DNA, nearly 31K PCR amplicons were amplified out of each sample. This is a pretty herculean effort in itself. Alas, the Materials & Methods section is annoyingly (though not atypically) silent on the PCR approach. With correct automation, setting up that many PCRs is tedious but not undoable (though did they really make nearly 1K 384 well plates per sample??). But, conventional PCR quite often requires about 10ng of DNA per amplification, with a naive implication of nearly half a milligram of input DNA -- impossible without whole genome amplification, which is at best a necessary evil as it can introduce biases and errors. Second generation sequencing libraries can be built from perhaps 100ng-1ug of DNA, a significant advantage on this cost axis (though sometimes still a huge amount from a clinical tumor sample).

Now, perhaps one of the microfluidic PCR systems could be used, but if the hybridization of tester and reference DNAs requires low complexity pools, a technique such as RainDance isn't in the cards. My friend who sells the 48 sample by 48 amplicon PCR arrays would be in heaven if they adopted that technology to run these studies.

One plus of the study is a rigorous sample selection process. In addition to requiring 50% tumor content, every sample was reclassified by a board-certified pathologist and immunohistochemistry was used to ensure correct differentiation of the three different lung tumor types in the study (non-small cell adenocarcinoma, non-small cell squamous, and small cell carcinoma). Other staining was used to subclassify breast tumors by common criteria (HER2, estrogen receptor and progesterone receptor) and the prostate tumors were typed by an RT-PCR assay for a common (70+% of these samples!) driver fusion protein (TMPRSS2-ERG).

Also, it should be noted that they experimentally demonstrated a generic oncogenic phenotype (anchorage independent growth) upon transformation with mutants discovered in the study. That they could scan for so much and test so few is not an indictment of the paper, but a sobering reminder of how fast mutation finding is advancing and how slowly our ability to experimentally test those findings.


Kan Z, Jaiswal BS, Stinson J, Janakiraman V, Bhatt D, Stern HM, Yue P, Haverty PM, Bourgon R, Zheng J, Moorhead M, Chaudhuri S, Tomsho LP, Peters BA, Pujara K, Cordes S, Davis DP, Carlton VE, Yuan W, Li L, Wang W, Eigenbrot C, Kaminker JS, Eberhard DA, Waring P, Schuster SC, Modrusan Z, Zhang Z, Stokoe D, de Sauvage FJ, Faham M, & Seshagiri S (2010). Diverse somatic mutation patterns and pathway alterations in human cancers. Nature PMID: 20668451

Application of Second Generation Sequencing to Cancer Genomics

A review by me titled "Application of Second Generation Sequencing to Cancer Genomics" is now available on the Advance Access section of Briefings in Bioinformatics. You'll need a subscription to read it.

I got a little obsessive about making the paper comprehensive. While the paper does focus on using second generation sequencing for mutation, rearrangement and copy number aberration detection (explicitly ruling out of scope RNA-Seq and epigenomics), it does attempt to touch on every paper in the field up to March 1st. To my chagrin I discovered just after submitting the final revision that I had omitted one paper. I was able to slide it into the final proof, but not without making a small error. There's one other paper I might have mentioned that actually used whole genome amplification upstream of second generation sequencing on a human sample, though it's not a very good paper, the sequencing coverage is horrid and wasn't about cancer. In any case, it won't shock me completely -- but a lot -- if someone can find a paper in that timeframe that I missed. So don't gloat too much if you find one -- but please post here if you find any!

Of course, any constructive criticism is welcome. There are bits I would be tempted to rewrite if I went through the exercise again and the part on predicting the functional implications of mutations could easily be blown out into a review of its own. I don't have time to commit to that, but if anyone wants to draft one I'd help shepherd it at Briefings. I'm actually on the Editorial Board there and this review erases my long-term guilt over being on the masthead for a number of years without actually contributing anything.

As I state in the intro, in a field such as this a printed review is doomed to made incomplete very quickly. I'm actually a bit surprised that there has been only one major cancer genomics paper between my cutoff and the preprint emerging -- the breast cancer quartet paper from Wash U. I fully expect many more papers to appear before the physical issue shows up (probably in the fall) and certainly a year from now much should have happened. But, it is useful to mark off the state of a field at a certain time. In some fields it is common to publish annual or semi-annual reviews which update on all the major events since the last review; perhaps I should start logging papers with that sort of concept in mind.

One last note: now I can read "the competition". Seriously, another review on the subject by Elaine Mardis and Rick Wilson came out around the time I had my first crude set of paragraphs (it would be stretch to grant it the title of draft). At that time, I had two small targeted projects in process and they had already published two leukemia genome sequences. It was tempting to read it, but I feared I would be overly influenced by it or worse would be paranoid about plagiarizing bits, so I decided not to read it until my review published.

A Doublet of Solid Tumor Genomes

Nature this week published two papers describing the complete sequencing of a cancer cell line (small cell lung cancer (SCLC) NCI-H209 and melanoma COLO-829) each along with a "normal" cell line from the same individual. I'll confess a certain degree of disappointment at first as these papers are not rich in the information of greatest interest to me, but they have grown on me. Plus, it's rather churlish to complain when I have nothing comparable to offer myself.

Both papers have a good deal of similar structure, perhaps because their author lists share a lot of overlap, including the same first author. However, technically they are quite different. The melanoma sequencing used the Illumina GAII, generating 2x75 paired end reads supplemented with 50x2 paired end reads from 3-4Kb inserts, whereas the SCLC paper used 2x25 mate pair SOLiD libraries with inserts between 400 and 3000 bp.

The papers have estimates of the false positive and false negative rates for the detection of various mutations, in comparison to Sanger data. For single base pair substitutions on the Illumina platform in the melanoma sample, 88% of previously known variants were found and 97% of a sample of 470 newly found variants confirmed by Sanger. However, on small insertion/deletion (indel) there was both less data and much less success. Only one small deletion was previously known, a 2 base deletion which is key to the biology. This was not found by the automated alignment and analysis, though reads containing this indel could be found in the data. A sample of 182 small indels were checked by Sanger and only 36% were confirmed. On large rearrangements, 75% of those tested confirmed by PCR.

The statistics for the SOLiD data in SCLC were comparable. 76% of previously known single nucleotide variants were found and 97% of newly found variants confirmed by Sanger. Two small indels were previously known and neither was found and conversely only 25% of predicted indels confirmed by Sanger. 100% of large rearrangements tested by PCR validated. So overall, both platforms do well for detecting rearrangements and substitutions and are very weak for small indels.

The overall mutation hauls were large, after filtering out variants found in the normal cell line. 22,910 substitutions for the SCLC line and 33,345 in the melanoma line. Both of these samples reflect serious environmental abuse; melanomas often arise from sun exposure and the particular cancer morphology the SCLC line is derived from is characteristic of smokers (the smoking history of the patient was unknown). Both lines showed mutation spectra in agreement with what is previously known about these environmental insults. 92% of C>T single substitutions occured at the second base of a pyrimidne dimers (CC or CT sequences). CC>TT double substitutions were also skewed in this manner. CpG dinucleotides are also to be hotspots and showed elevated mutation frequencies. Transcription-coupled repair repairs the transcribed strand more efficiently than the non-transcribed strand, and in concordance with this in transcribed regions there was nearly a 2:1 bias of C>T changes on the non-transcribed strand. However, the authors state (but I still haven't quite figured out the logic) that transcription-coupled repair can account for only 1/3 of the bias and suggest that another mechanism, previously suspected but not characterized, is at work. One final consequence of transcription-coupled repair is that the more expressed a gene is in COLO-829, the lower its mutational burden. A bias of mutations towards the 3' end of transcribed regions was also observed, perhaps because 5' ends are transcribed at higher levels (due to abortive transcription). A transcribed-strand bias was also seen in G>T mutations, which may be oxidative damage.

An additional angle on mutations in the COLO-829 melanoma line is offered by the observation of copy-neutral loss of heterozygosity (LOH) in some regions. In other words, one copy of a chromosome was lost but then replaced by a duplicate of the remaining copy. This analysis is enabled by having the sequence of the normal DNA to identify germline heterozygosity. Interestingly, in these regions heterzyogous mutations outnumber homozygous ones, marking that these substitutions occurred after the reduplication event. 82% of C>T mutations in these regions show the hallmarks of being early mutations, suggesting they occured late, perhaps after the melanoma metastasized and was therefore removed from ultraviolet exposure.

In a similar manner, there is a rich amount of information in the SCLC mutational data. I'll skip over a bunch to hit the evidence for a novel transcription-coupled repair pathway that operates on both strands. The key point is that highly expressed genes had lower mutation rates on both strands than less expressed genes. A>G mutations showed a bias for the transcribed strand whereas G>A mutations occured equally on each strand.

Now, I'll confess I don't generally get excited about looking a mutation spectra. A lot of this has been published before, though these papers offer a particulary rich and low-bias look. What I'm most interested in are recurrent mutations and rearrangements that may be driving the cancer, particularly if they suggest therapeutic interventions. The melanoma line contained two missense mutations in the gene SPDEF, which has been associated with multiple solid tumors. A truncating stop mutation was found by sequencing SPDEF out of 48 additional tumors. A missense change was found in a metalloprotease (MMP28) which has previously been observed to be mutated in melanoma. Another missense mutation was found in agene which may play a role in ultraviolet repair (though it has been implicated in other processes), suggesting a tumor suppressor role. The sequencing results confirmed two out of three known driver mutations in COLO-829: the V600E activating mutation in kinase BRAF and deletion of the tumor suppressor PTEN. As noted above, the know 2 bp deletion in CDKN2A was not found through the automated process.

The SCLC sample has a few candidates for interestingly mutated genes. A fusion gene in which one partner (CREBBP) has been seen in leukemia gene fusions was found. An intragenic tandem duplication within the chromatin remodelling gene CHD7 was found which should generate an in-frame duplication of exons. Another SCLC cell line (NCI-H2171) was previously known to have a fusion gene involving CHD7. Screening of 63 other SCLC cell lines identified another (LU-135) with internal exon copy number alterations. Lu-135 was further explored by mate pair sequencing witha 3-4Kb library, which identified a breakpoint involving CHD7. Expression analysis showed high expression levels of CHD7 in both LU-135 and NCI-H2171 and a general higher expression of CHD7 in SCLC lines than non-small cell lung cancer lines and other tumor cell lines. An interesting twist is that the fusion partner in NCI-H2171 abd KY-135 is a non-coding RNA gene called PVT1 -- which is thought to be a transcriptional target of the oncogene MYC. MYC is amplified in both these cell lines, suggesting multiple biological mechanisms resulting in high expression of CHD7. It would seem reasonable to expect some high profile functional studies of CHD7 in the not too distant future.

For functional point mutations, the natural place to look is at coding regions and splice junctions, as here we have the strongest models for ranking the likelihood that a mutation will have a biological effect. In the SCLC paper an effort was made to push this a bit further and look for mutations that might affect transcription factor binding sites. One candidate was found but not further explored.

In general, this last point underlines what I believe will be different about subsequent papers. Looking mostly at a single cancer sample, one is limited at one can be inferred. The mutational spectrum work is something which a single tumor can illustrate in detail, and such in depth analyses will probably be significant parts of the first tumor sequencing paper for each tumor type, particularly other types with strong environmental or genetic mutational components. But, in terms of learnign what make cancers tick and how we can interfere with that, the real need is to find recurrent targets of mutation. Various cancer genome centers have been promising a few hundred tumors sequenced over the next year. Already at the recent ASH meeting (which I did not attend), there were over a half dozen presentations or posters on whole genome or exome sequencing of leukemias, lymphomas and myelomas -- the first ripples of the tsunami to come. But, the raw cost of targeted sequencing remains at most a 10th of the cost of an entire genome. The complete set of mutations found in either one of these papers could have been packed onto a single oligo based capture scheme and certainly a high-priority subset could be amplified by PCR without breaking the bank on oligos. I would expect that in the near future tumor sequencing papers will check their mutations and rearrangements on validation panels of at least 50 and preferable hundreds of samples (though assembling such sample collections is definitely not trivial). This will allow the estimation of the population frequency of those mutations which may recur at the level of 5-10% or more. With luck, some of those will suggest pharmacologic interventions which can be tested for their ability to improve patients' lives.


Pleasance, E., Stephens, P., O’Meara, S., McBride, D., Meynert, A., Jones, D., Lin, M., Beare, D., Lau, K., Greenman, C., Varela, I., Nik-Zainal, S., Davies, H., Ordoñez, G., Mudie, L., Latimer, C., Edkins, S., Stebbings, L., Chen, L., Jia, M., Leroy, C., Marshall, J., Menzies, A., Butler, A., Teague, J., Mangion, J., Sun, Y., McLaughlin, S., Peckham, H., Tsung, E., Costa, G., Lee, C., Minna, J., Gazdar, A., Birney, E., Rhodes, M., McKernan, K., Stratton, M., Futreal, P., & Campbell, P. (2009). A small-cell lung cancer genome with complex signatures of tobacco exposure Nature DOI: 10.1038/nature08629

Pleasance, E., Cheetham, R., Stephens, P., McBride, D., Humphray, S., Greenman, C., Varela, I., Lin, M., Ordóñez, G., Bignell, G., Ye, K., Alipaz, J., Bauer, M., Beare, D., Butler, A., Carter, R., Chen, L., Cox, A., Edkins, S., Kokko-Gonzales, P., Gormley, N., Grocock, R., Haudenschild, C., Hims, M., James, T., Jia, M., Kingsbury, Z., Leroy, C., Marshall, J., Menzies, A., Mudie, L., Ning, Z., Royce, T., Schulz-Trieglaff, O., Spiridou, A., Stebbings, L., Szajkowski, L., Teague, J., Williamson, D., Chin, L., Ross, M., Campbell, P., Bentley, D., Futreal, P., & Stratton, M. (2009). A comprehensive catalogue of somatic mutations from a human cancer genome Nature DOI: 10.1038/nature08658

The genomic history of a breast cancer revealed

Today's Nature contains a great paper which is one more step forward for cancer genomics. Using Illumina sequencing a group in British Columbia sequenced both the genome and transcriptome of a metastatic lobular (estrogen receptor positive) breast cancer. Furthermore, they searched a sample of the original tumor for mutations found in the genome+transcriptome screen in order to identify those that may have been present early vs. those which were acquired later.

From the combined genome sequence and RNA-Seq data they found 1456 non-synonymous changes which was then trimmed to 1178 after removing pseudogenes and HLA sequences. 1120 of these could be re-assayed by Sanger sequencing of PCR amplicons from both normal DNA and the metastatic samples -- 437 of these were confirmed. Most of these (405) were found in the normal sample. Of the 32 remaining, 2 were found only in the RNA-Seq data, a point to be addressed later below. Strikingly, none of the mutated genes were found in the previous whole-exome sequencing (by PCR+Sanger) of breast cancer, though those samples were of a different subtype (estrogen receptor negative).

There are a bunch of cool tidbits in the paper, which I'm sure I won't give full justice to here but I'll do my best. For example, several other papers using RNA-Seq on solid cancers have identified fusion proteins, but in this paper none of the fusion genes suggested by the original sequencing came through their validation process. Most of the coding regions with non-synonymous mutations have not been seen to be mutated before in breast cancer, though ERBB2 (HER2, the target of Herceptin) is in the list along with PALB2, a gene which when mutated predisposes individuals to several cancers (and is also associated with BRCA2). The algorithm (SNVMix) used for SNP identification & frequency estimation is a good example of an easter egg, a supplementary item that could easily be its own paper.

One great little story is HAUS3. This was found to have a truncating stop codon mutation and the data suggests that the mutation is homozygous (but at normal copy number) in the tumor. A further screen of 192 additional breast cancers (112 lobular and 80 ductal) for several of the mutations found no copies of the same hits seen in this sample, but two more truncating mutations in HAUS3 were found (along with 3 more variations in ERBB2 within the kinase domain, a hotspot for cancer mutations). HAUS3 is particularly interesting because until about a year ago it was just C4orf15, an anonymous ORF on chromosome 15. Several papers have recently described a complex ("augmin") which plays a role in genome stability, and HAUS3 is a component of this complex. This starts smelling like a tumor suppressor (truncating mutations seen repeatedly; truncating mutation homozygous in tumor; protein in function often crippled in cancer), and I'll bet HAUS3 will be showing up in some functional studies in the not too distant future.

Resequencing of the primary tumor was performed using amplicons targeting the mutations found in the metastatic tumor. These amplicons were small enough to be spanned directly by paired-end Illumina reads, obviating the need for library construction (a trick which has shown up in some other papers). By using Illumina sequencing for this step, the frequency of the mutation in the sample could be estimated. It is also worth noting that the primary tumor sample was a Formalin Fixed Paraffin Embedded slide, a way to preserve histology which is notoriously harsh on biomolecules and prone to sequencing artifacts. Appropriate precautions were made, such as sequencing two different PCR amplifications from two different DNA extractions. The sequencing of the primary tumor suggests that only 10 of the mutations were present there, with only 4 of these showing a frequency consistent with being present in the primary clone and the others probably being minor components. This is another important filter to suggest which genes are candidates for being involved in early tumorigenesis and which are more likely late players (or simply passengers).

One more cool bit I parked above: the 2 variants seen only in the RNA-Seq library. This suggested RNA editing and also consistent with this an RNA editase (ADAR) was found to be highly represented in the RNA-Seq data. Two genes (COG3 and SRP9) showed high frequency editing. RNA editing is beginning to be recognized as a widespread phenomenon in mammals (e.g. the nice work by Jin Billy Li in the Church lab); the possibility that cancers can hijack this for nefarious purposes should be an interesting avenue to explore. COG3 is a Golgi protein & links of the Golgi to cancer are starting to be teased out. SRP9 is part of the signal recognition particle involved in protein translocation into the ER -- which of course feeds the Golgi. Quite possibly this is coincidental, but it certainly rates investigating.

One final thought: the next year will probably be filled with a lot of similar papers. Cancer genomics is gearing up in a huge way, with Wash U alone planning 150 genomes well before a year from now. It seems unlikely that those 150 genomes will end up as 150 distinct papers and more so it will be a challenge to do the level of follow-up in this paper on such a grand scale. A real challenge to the experimental community -- and the funding establishment -- is converting the tantalizing observations which will come pouring out of these studies into validated biological findings. With a little luck, biotech & pharma companies (such as my employer) will be able to convert those findings into new clinical options for doctors and patients.



Sohrab P. Shah, Ryan D. Morin, Jaswinder Khattra, Leah Prentice, Trevor Pugh, Angela Burleigh, Allen Delaney, Karen Gelmon, Ryan Guliany, Janine Senz, Christian Steidl, Robert A. Holt, Steven Jones, Mark Sun, Gillian Leung, Richard Moore, Tesa Severson, Greg A. Taylor, Andrew E. Teschendorff, Kane Tse, Gulisa Turashvili, Richard Varhol, René L. Warren, Peter Watson, Yongjun Zhao, Carlos Caldas, David Huntsman, Martin Hirst, Marco A. Marra, & Samuel Aparicio (2009). Mutational evolution in a lobular breast tumor profiled at single nucleotide resolution Nature, 461, 809-813 : 10.1038/nature08489

Cancer Genome Sequencing--A (Pessimistic) Interim Analysis

The current issue of Cancer Research carries a very brief (3 pages, with one page mostly tables & figures) review of the first pulse of cancer genome sequencing papers (sub required to read article). While sub-titled 'An Interim Analysis', perhaps a better subtitle would be 'A Uniformly Negative Analysis'.

A full-press cancer genomics project has been a controversial drive, with many bemoaning the huge amount of resources devoted it and believing other avenues would be better suited for enhancing our ability to help cancer patients. But it has gone forward, and a spate of papers over the last year have reported the early results.

The initial papers have covered 4 of the big cancers in terms of incidence and mortality (lung, breast, colorectal and pancreatic) as well as glioblastoma and leukemia. Different studies have taken different tacks. In leukemia, we have the first parallel complete sequencing of a patient and their tumor. Papers in breast, colorectal (together covered in two papers here and here), pancreatic and glioblastoma looked at huge numbers of coding exons in small numbers of patients (11 patients x 18.2Kgenes for breast and colorectal; 21 patients x 20.6Kgenes for glioblastoma; 24 patients x 20.6Kgenes for pancreatic). A lung paper and the other glioblastoma paper looked at ~600 genes, but in larger numbers of patients (188 in lung and 91 in glioblastoma).

Personally, I would take a more nuanced view of the results. I think it is hard to argue that these papers have had a shortage of fireworks there have been some important observations made, which curiously the Cancer Research review ignore completely. In the lung study (which I have studied the closest) these include important exclusion and cooperativity relationships between mutations and a number of novel, druggable candidate driver genes (protein kinases) not previously suspected in lung cancer. In the many genes few patients glioblastoma study, it was the identificaiton of a mutational hotspot in isocitrate dehydrogenase 1 (later found to be present, though less frequently mutated, in isocitrate dehydrogenase 2).

Of course, one thing which is changing rapidly is the cost of doing these studies. Most of these papers used conventional PCR amplification and Sanger sequencing, which I would lowball estimate at $1/well (very lowball, but Sandra Porter caught some serious flak suggesting [as I have] a number much higher than this for the sequencing part, and I don't have the accounting experience to argue -- but I do know people who calculated it at Codon and this would be a very low estimate) -- so those studies looking at nearly every coding exon were at least a quarter million per patient (those 20+K genes explode out to about a quarter million exons). Clearly this isn't how things will tend to be done going forward; Illumina will now blow away genomes for $48K each and other companies are now quoting even lower. This is still well in excess of the per patient estimate for the very focused studies, and I believe these (particularly the lung study) demonstrate the value of lots of patients, since this started to give the numbers required to look at interactions between mutations.

One of the reasons the Cancer Research authors aren't terribly pleased with the progress is clear: they feel the experiments aren't the correct ones. But whereas some of the flak I had seen directed at the cancer genome sequence concept was instead promoting more functional approaches (such as RNAi library screening), what these authors want (or at least set as the minimum bar of for interesting) is cancer genome screening on an almost monomaniacal scale: thousands if not millions of individual cells from the same tumor! Clearly this would be fascinating, as there is plenty of evidence that tumors are a motley collection of genetically variant cells (but clonal -- all the tumor cells have the same ancestor, but they also are all sloppy DNA copyists). And, as they note, no DNA sequencing technology here now or on the immediate horizon has any shot at a project of this scale.

While I do believe this would be interesting, I'm not as certain it would be informative for patient care. Since many of these mutations are under very little selection, the spectrum of observed mutations is likely to be enormous. Given that there is already a horrendous backlog of characterizing mutations seen in the studies to date (though there has been a paper already functionally characterizing the isocitrate dehydrogenase mutations)

What is particularly strange about this view is that a more reasonable intermediate step would be to look at those cells that do escape the primary tumor (most of the cancer genome papers so far have focused on primary tumors, though the IDH mutations are primarily found in secondary glioblastomas) -- sequence the metastases. Ideally, this would mean finding multiple patients willing to consent to their genome, their primary's genome, and multiple metastases' genomes being sequenced -- the latter quite likely coming from autopsies (otherwise it is a lot of painful biopsying without much hope of helping the patient, an ethically questionable activity). Or, in leukemias one could more easily resequence after each relapse. Such studies would be doable technically and not cost ridiculous (though clearly not chump change either).

There's also the open question as to whether the real fireworks will come from sequencing less studied cancers, such as the recent success in using transcriptome sequencing to identify the probable causative mutation in a rare type of ovarian cancer (see also the News and Views piece). Perhaps we've mined the rich ore out of some of these veins, and it is the less worked seams which will yield fine genomic insights. Time will tell.