Science and Steamrollers: How Research Stories Can Go Off the Rails [UPDATE]

In a blog post earlier today I did a bit of a dissection, from my personal perspective of a big story that came out of AACR this week (see earlier post here).


No sooner had I hit the "upload" button, I became aware of a wonderfully written piece that was hitting the 'blogosphere' at the same time, from one of the authors already quoted in my earlier piece - Erika Check Hayden.

From the Blog "Last Word on Nothing" she wrote a piece entitled "What the ‘limits of DNA’ story reveals about the challenges of science journalism in the ‘big data’ age.


As I did in my earlier post, I will enumerate her key messages:

1. Science consists of more and more “big data” studies whose findings depend on statistical methods that few of us reporters can understand on our own..
2. Challenges in the news business are ratcheting up pressure on all of us. 
3. We are only as good as our sources. 
4. It’s becoming more difficult to trust traditional scientific authorities. 
5. Beware the deceptively simple story line.
6. Getting the story right matters more than ever. 

As much as I am tempted to do so, good practice prohibits me from just cutting and pasting her whole blog post here, but I do encourage you to go back and read what she says on each of these. Please do; it is worth the click and the read.

As you can see, a number of her points very much parallel my own, but rather than feel smug about that, it inspires me to keep doing this blog. And I aspire to writing on a subject as cogently and eloquently as she does.

Science and Steamrollers: How Research Stories Can Go Off the Rails

Earlier this week I wrote a post about “personal genomics”. Actually I wrote 2 posts the same day (part 1 and 2) but who’s counting <smile>?

Short Recap:

In the second article (read it again, here) I talked about a new study that was announced at the Annual Meeting of the American Association for Cancer Research (AACR) in Chicago (meeting website here), and published simultaneously in the journal Science Translational Medicine.  This study, authored by a team at Johns Hopkins in Baltimore and led by world-famous researcher Dr. Bert Vogelstein, was entitled The Predictive Capacity of Personal Genome Sequencing. The researchers used disease registries from several countries, and looked at data from over 50,000 identical twins and tracked how often one twin or the other developed one of 24 different diseases.

Because twins have identical genomes, by comparing the results of one twin to the other, the question was asked: how much do their genes predict any increased chances of getting a disease. It was concluded that most of the twins were at average risk for most of the 24 diseases, pretty much the same as anyone from the general population. 

In other words, the authors suggested that widespread use of genome sequencing will likely provide very little useful information to enable  prediction of future disease.

Because of the fanfare around this paper, and not in the least because of the reputation of the research team in general and Dr. Vogelstein in particular, this study became instantly of interest in the mainstream  media, and in the social media universe, especially on Twitter.

One of the first to pick up on this story was Gina Kolata, writing for the New York Times. Ms Kolata is, to my mind, a seasoned, very well respected and well-known science journalist and her article in the Times (Study Says DNA’s Power to Predict Illness Is Limited) offered both a recap and this caveat:

“While sequencing the entire DNA of individuals is proving fantastically useful in understanding diseases and finding new treatments, it is not a method that will, for the most part, predict a person’s medical future.”

Another well-known journalist, Robert Bazell posted an article on MSNBC entitled "Gene tests: Your DNA blueprint may disappoint, scientists say" that carried pretty much the same cautionary message: 

“If everyone has a complete gene profile, a small number can learn they have a great risk for something.  But for most, the information is minimally significant.”

I confess that, given the reputations of Dr. Vogelstein and of the mainstream journalists covering this story, that I too felt a bit deflated in that moment, and said in my own blog post: 

“Bottom line, it seems to me, is that we really have to be more careful than ever about exposing ourselves to privacy, confidentiality, insurability and other legal and ethical dilemmas, especially if the risks might outweigh the gains in many, if not most, cases.”

What Happened Next?

At least I was open-minded (or prescient?) enough  to have ended my post with the caveat that:

 “Clearly there is no definitive pronouncement to be made one way or the other yet - it is far too early days for that. But it is good to have these debates with our eyes wide open.”

Indeed, as is so often the case, closer inspection with eyes wide open and sober second thought reveals that there is more to this story than meets the eye.

Actually, perhaps it might be better said that there may be “less” to this story than meets the eye...

Initially, I was rather surprised to see a very vigorous, but negative reaction from a number of other  journalists and scientists alike, especially in the ‘Twitterverse’ not only to the Vogelstein study, but to the media attention that it was getting. Some of the critiques explored how the study was flawed, or at least how its conclusions might have been flawed given the design of the study.

But the main critique that I read loud and clear from several independent sources was essentially that this result was to be 100% anticipated, and that geneticists and other molecular biologists  have been saying this for some time. In other words that ‘there is no news here’.  And so they were perplexed at why the study had been positioned to have been some brand new discovery. Worse, they were very concerned that the rush to judgment of the mainstream media, by lacking critical perspective, might seriously set back genomic research progress by unfairly damning this whole area of research without benefit of having asked many critical (and contrary) questions. 

The Other Side of the Story

I’m sure there must have been many more, but I will highlight 3 excellent pieces that have appeared since the original story broke and the original media attention flourished.

One of the very best was written by Erika Check Hayden in a blog post entitled “DNA has limits, but so does study questioning its value, geneticists say” published in Nature’s Newsblog. In that post she writes that:

 “Geneticists don’t dispute the idea that genes aren’t the only factor that determines whether we get sick; many  of them agree with that point. The problem, geneticists say, is not that the study ... arrived at a false conclusion, but that it arrived at an old, familiar one via questionable methods and is now being portrayed by the media as a new discovery that undermines the value of genetics.”

She went on to list 5 main critiques which I will enumerate here, but which you should go back to the original article to read the details:

1. This study critiques the power of genomic medicine but does not contain any genome data. 
2. This study is beating a dead horse.
3. The mathematical model used in the study is unrealistic.
4. The study doesn’t correct for errors that can affect twin studies.
5. The media coverage of the study could weaken support for genetic research.

 To me, another  very well written and compelling “rebuttal” was penned by Luke Jostins on the Blog “Genomes Unzipped” in an article entitled “Identical twins usually do not die from the same thing”. 

In his post he ponders why “a not particularly original or particularly well done attempt to answer a question that many other people have answered before, got so much press (including a feature in the [New York Times]).”

He goes on to try to answer his own question, and the insight is commendable:

But of course, the reason is relatively obvious. All of the papers I linked to there are by statistical geneticists ... and never came with a press release or an attempt to talk to the public about them. The message, to those who can read them, is clear and well established – genetic risk prediction (or any form of risk prediction) will never be able to perfectly predict disease incidence, and will never replace diagnostic tests. But the fact that the results of Bert Vogelstein’s study seems to have come as a surprise to people, when it comes as no surprise to us, shows us that we have failed in one of our primary duties to keep the public informed about the results of our research. The paper’s failure as a work of statistical genetics stands in contrast to its success as a work of public outreach. If we are annoyed that a bad paper got the message across, then we should be annoyed with ourselves that we never communicated our own results properly”

And finally, a blog post yesterday from Paul Raeburn in the Knight Science Journalism Tracker entitled “What everyone should know about genome scans”, not only provides a very nice summary of the debate, but goes one step further to pose questions about the role of the press and of journalists who cover science and research that gets exceedingly complex. In some very insightful comments, Mr. Raeburn asks, for example:

“The question here is how reporters might have suspected these criticisms and produced better stories–or how their reporting might have done a better job of uncovering the potential pitfalls of the study. Few reporters are qualified to assess the statistical soundness of the study. But why did they not find out more about this in their reporting? Perhaps some were so interested in the contrarian nature of the story–genomes aren’t all they’re cracked up to be–that they didn’t push hard enough to discover potential problems with the study.

One tip-off was the many stories that have been written questioning the value of commercial genome scans. Reporters should have asked whether the findings were new. That would not necessarily have uncovered the statistical issues, but it might have led reporters to scale back their coverage.”

 

Sober Second Thoughts?

Paul Raeburn, in the article cited above, concluded:

“If I had covered this story, I fear I, too, would have missed the issues that Hayden presents so clearly. The main lesson I can draw from this is that reporters ought to be as skeptical and vigilant as they can be, especially when writing about subjects, such as this one, that they have written about many times before–enough to have formed opinions that might be getting in their way.”

 I myself have posted before about the “good, the bad and the ugly” of public engagement in research. Science can never again be an ivory tower exercise – much of the research, including that study in question, is done at public expense, whether that be taxpayers’ dollars or charitable donations. The public has a right to be informed as to how their dollars are used, and researchers have a responsibility and accountability to inform them. Very often, it is science journalists, health reporters, broadcasters and the like who have a central and trusted role to play smack in the middle, as a critical conduit to the public to make sure that happens.

But they have to get it right if they are to hold that public trust.

Still, as Mr. Raeburn said, how many reporters have the qualifications and expertise to really dissect increasingly specialized science and increasingly complex data sets? I *HAVE* some qualifications and I certainly can NOT keep up with, nor even understand, much of the highly complex, jargon-filled science that even I try to write about.

So, while it is easy to criticize the reporters who may have rushed to judgment and perhaps overly sensationalized what for many is a non-story, on balance one surely also has to hold accountable the very scientists themselves who may have allowed this steamroller to roll down the hill, and indeed, from what I can surmise, may have even given it quite a little push to get it going downhill in the first place, whether intentionally or not.

More About "Personal" Genomics

No, I didn't make a mistake in the title. I know we talk about genomics and personalized medicine a lot, but in this case I really was referring to "personal genomics". We need more conversations, discussions and debates about how we as a society are going to deal with the inundation of personal gene and DNA information that is coming our way in the brave new world of $1000 genomes.

I have already written some on the subject in a previous post about the promise and the concerns.

I have also provided some links last week to some further information on the subject.

This week saw (at least)  two new entries into this important discussion that I thought were worthy of passing on.

The first of these was a wonderful show on the series "Nova" from WGBH Boston called "Cracking Your Genetic Code".  I thought it was a particularly good treatment of the whole science behind genomics and personalized medicine. If you missed it, or can't get it, for now the show is available online at http://www.pbs.org/wgbh/nova/body/cracking-your-genetic-code.html.

I really encourage you to invest the hour watching this show - it is excellent in my view.

The other is a particularly good article written by Christine S. Moyer of the (American Medical Association) Amednews.com staff. In this piece she writes more about the issues of what are we going to do with all of the information that we might be gleaning very soon. Entitled "Genome sequencing to add new twist to doctor-patient talks", it is written from a health care, ethical and societal point of view - exactly the debate that I have been insisting that we have not been having  nearly enough of.

I am very glad to see that these discussions are expanding and that the issues are starting to come out on the table. We owe it to ourselves to become much better informed and to steer this brave new world or else it will swamp us!

Society, Ethics and Cancer Genomics

In one of my earlier posts (you can read it here), I talked about some of the major societal issues that face us in ethics, health services and health policy arenas (to name but a few), now that we are about to turn the corner on the $1000 genome.

I know that I am not the only one (not by a long shot), who is concerned about these important issues) but it was gratifying today to learn that the US Presidential Commission for the Study of Bioethical Issues is taking up the charge. I will be following this to see what happens....

See a report from Bloomberg News.

International Cancer Genomics Efforts - Marching Forward

I previously wrote about the International Cancer Genomics Consortium (ICGC)  and the promise of the genomics approach to solving some of the mysteries of cancers.


Earlier this month the ICGC released the latest round of data from a number of international sites that can now be used by researchers around the world.

From the ICGC web site: 

This update includes first data releases from France’s Liver Cancer project, Germany’s Pediatric Brain Cancer project, and the United Kingdom’s Myelodysplastic Syndrome Project. Also included are new submissions from the Australian Pancreatic Cancer project, the Canadian Pancreatic Cancer project, the Japanese Liver Cancer project, and the United Kingdom Breast Cancer (Triple Negative) project.


This data adds to previous data releases from the Chinese Gastric Cancer project, the Spanish Chronic Lymphocytic Leukemia project and submissions from The Cancer Genome Atlas in the United States, which has contributed information on about 10 types of cancer affecting the blood, brain, breast, colon, kidney, lung, ovaries, rectum, stomach and uterus.


In total, 600 newly-available cancer datasets are provided in this release, with the ICGC data portal now containing data from 3,561 cancer genomes.

This clearly shows the power of collaboration and of open access to data generated by that collaboration.

Personalized Medicine [Part 2] - Time for a Reality Check?

Despite the enormous promise of personalized or precision medicine coming from the  genomics era, I think we need to collectively take a deep breath and also ponder the reality of just how far this new technology can take us.

Without in any way diminishing the huge potential of the "$1000 genome" era, I think there are at least two important areas where we need to do a reality check.

 The first of these I have already written about - the need for debate in society about how we want to view privacy and confidentiality, and how are we going to deal with the influx of personal, genetic information that could overwhelm and confuse us despite good intentions to the contrary.

The second area stems (no pun intended) from the reality that cancer is, at its heart, a set of diseases marked by tremendous  genetic instability. The reason that so many cancers are hard to treat is because every time you think you have it pinned down, it morphs into something a bit different.

For example, when a number of the first Gleevec patients started to relapse, the sound of people jumping OFF the bandwagon was an audible thud. Skeptics said "see, we knew it couldn't really work so easily!" Subsequent studies showed, however, that Gleevec indeed worked exactly as advertised, but in the interim, the cancers had “evolved” – they developed some secondary mutations that essentially allowed the Gleevec roadblock to be bypassed.  If  you put roadblocks up on the main highways, cancer will find a way to take a side road to get out of town. If you block the side roads, cancer often will find some other route.

So, the advent of an international consortium like ICGC  that is  so very powerful, coupled with the fact that gene sequencing costs are spiralling downward, leads us logically to anticipate a new era of personalized and precision medicine. The idea is out there that if every patient’s tumour could be biopsied and his/her cancer genome sequenced so that we can determine and understand the underlying genetic defects, then we will be able to choose a tailored therapeutic regimen to treat that patient and his/her cancer in a more targeted way than ever before possible.

But that kind of future scenario depends not only on “cheap” sequencing technologies and an enormous database of mutations associated with cancers (both of which are now or will soon be in our reach), but it also depends, at least in part, on one other crucial factor. If we do a biopsy on a patient’s cancer, are we confident that what we will learn will be sufficient to give us the depth and detail of understanding that we need so that we can put this therapeutic precision and personalization to the test?

As is so often the case with cancers, the answer is, maybe…..

Why the hedge? Because we haven’t yet fully accounted for the idea that tumours are undoubtedly NOT homogeneous, that is, they do not have a uniform structure or character. There may well  be many different types of cancer cells even in a single patient’s cancer. We call this “tumour heterogeneity” which in simple terms means that the tumour may be a “dog’s breakfast” of different kinds of cells and different kinds of mutations.

As Dr. Dan Longo wrote in an editorial entitled Tumor Heterogeneity and Personalized Medicine in the March 8, 2012 issue of the New England Journal of Medicine:  

“A new world has been anticipated in which patients will undergo a needle biopsy of a tumor in the outpatient clinic, and a little while later, an active treatment will be devised for each patient on the basis of the distinctive genetic characteristics of the tumor,” he wrote.  “But a serious flaw in the imagined future of oncology is its underestimation of tumor heterogeneity.”

This “complication” came to the fore earlier this month with the publication of a very important study, entitled IntratumorHeterogeneity and Branched Evolution Revealed by Multiregion Sequencing published in the same New England Journal of Medicine issue. 

That’s a very technical title, and indeed a very specialized and technical paper, but the bottom line of it is this: a team of researchers led by Drs. Marco Gerlinger and Charles Swanton from London, UK found that there was an astonishing degree of genetic variation in biopsies from the same tumour from the same patient. In fact, multiple biopsies taken from single patients with kidney cancer (renal carcinoma) showed that there were many different mutations in each biopsy, and that not all of them showed up in all of the biopsies. In fact, the majority (over 60% of the mutations) did NOT show up across all of the biopsies.

Even worse, the researchers found that the mutations and gene “signatures” found in one region of the tumour were consistent with what we would currently have said is a good prognosis, whereas gene “signatures” found in a different part of the very same tumour were consistent with what we would have expected to be a poor prognosis!

This study, if typical for other tumours, suggests that a simple, i.e., non-invasive biopsy of a limited region of a tumour might NOT be at all sufficient to proceed with a very targeted therapeutic regimen. What if we targeted treatment to the wrong cells, cells that maybe by chance only represented 10% of the tumour?  What if we chose not to treat aggressively based on an ostensibly great prognosis from the biopsied material, only to find out later to our detriment that we were fooled by a “sampling error” of lamentable proportions?

So, bottom line, looking at both sides of the coin of "personalized medicine" (e.g., this post and the previous post), what does this all mean?

Are genomics, DNA sequencing and the building of mutation databases of enormous proportion tantamount going to lead us single-handedly to the Holy Grail of cancer treatments? Hardly.

Does the Swanton et al. study on genetic variation in kidney cancers mean that we are wasting our time with  the pursuit of genomics and precision cancer therapies? Again, hardly.

Like all things cancer, black and white approaches are simply not the way to go. This may be a bump in the road, as some have alluded, but if it is, it is not the end of the road by any means. We will learn some breathtaking insights from genomics, but it will be only one powerful tool in the arsenal, not the whole answer.

As one blogger eloquently put it in describing the kidney cancer study (Jessica Wapner, March 9, 2012, in a PublicLibrary of Science blog)

“It’s for this reason that the idea of personalized medicine—and here we are talking specifically about drugs targeted against the genetic make-up of an individual cancer, not about a whole-person regimen for life based on your personal DNA quirks—is one that has to be held with a long-view. It took decades for the first useful chemotherapy drug to be discovered. If we absorb the notion that targeted therapy is still in its nascent stage, then this new study isn’t a bump in the road, but rather another description of the scenery.”

Personalized Medicine [Part 1] – The PROMISE...

Whether you call it personalized medicine, or precision medicine, or whatever, the promise of the $1000 (or less) genome has captured the imaginations and aspirations of the public and the research community alike.

This excitement is not ill-considered. One can assume that there are going to be vast improvements in our ability to prevent, diagnose, treat and cure cancers as we learn more and more about the mutations that drive the diseases.

As  Colin Hill contributed to Forbes on Feb 9, 2012 in his post “Beyond the $1000 Genome on the Forbes website.

“Larger availability of complete genomic data will have a profound near-term impact on cancer research. The ability to rapidly and economically sequence individual patient tumours will help us to better understand the biological mechanisms of cancer and will facilitate data-driven patient stratification. This, in turn, will facilitate more effective clinical trials and speed the development of new therapies.

The significant near-term growth of rich genomic data will impact the patient care side too. Companies ... will use this data to perform molecular analysis of tumours that will assist in pinpointing the optimal treatment strategies for individuals with cancer.”

But of course, no matter how cheaply it can be done, sequencing a single patient’s genome is not going to tell us much if we don't know what we are looking for. How will we know a “bad” mutation from a “neutral” mutation? As we saw with Craig Venter’s genome, his natural amount of genetic variability, and presumably yours and mine as well, is very high, and yet Craig Venter is by all accounts a healthy man.

Well, the supposition is that if we look at enough DNA sequences of enough cancer patients then a pattern will start to emerge and we will start to see certain mutations showing up over and over. How many will there be? Will some mutations be more directly linked to actual “causation” of the cancer (so called “driver” mutations) or will some be there as a consequence of the cancer and not actually involved in the origin or progression (so-called “passenger” mutations). Will we be able to tell the difference?

Answers to these crucial kinds of questions require a lot more data than we currently have. And that is where and how the International Cancer Genome Consortium (or ICGC) was formed.

Inaugural Meeting of Genome Scientists in Toronto 2007

Much like the Herculean world-wide effort to collaborate in determining the very first human reference genome sequence, the ICGC is also a massive consortium (website at http://icgc.org/) . The ICGC is a consortium not so much of scientists but of whole countries. The consortium was formed in 2008 after an inaugural meeting (Toronto) and report in 2007, to bring a global effort to bear in sequencing enough genomes for each of perhaps 50 or more types of important cancers so that we could start to answer some of the questions posed above. It is estimated that perhaps several hundred genome sequences derived from patients with any individual type of cancer may needed in order to be able to have statistical confidence of which mutations may indeed be the “drivers” vs. those that may simply be the “passengers”. If you consider the effort, and cost, of sequencing hundreds of genomes for each of perhaps 50 types of cancer, you start to see the enormity of the task, and why a consortium of countries in needed.

The ICGC is therefore funded in the main by governments and government agencies (federal and provincial here in Canada) of countries, along with some notable cancer charities and other funders. Each participating member country of the consortium is expected to invest at least $20 Million overall to that country’s activities. Furthermore, a commitment to fully, openly and quickly share ALL data with other qualified researchers world-wide is an absolute requirement for membership.

The secretariat of the ICGC is in Toronto, at the Ontario Institute for Cancer Research (OICR; http://oicr.on.ca), and Dr. Tom Hudson, an internationally renowned genomics researcher who is President and Scientific Director of the OICR heads the Executive.

OICR also operates the main data coordination centre for the consortium. Tom took me on a tour of the OICR server room about a year ago and I can tell you it is like something out of the movies :) The air conditioning costs alone for  just keeping the server room(s) cool must be enormous!

The goal of all of this of course is to have an international database of “signatures” of dozens of types of cancers, with enough confidence that we can start to use that data to better understand cancers at the gene and molecular levels, and be better able to determine predisposition to cancers (leading to better prevention strategies); to determine better and more pin-point diagnostic and marker mutations (leading to earlier diagnosis and better interventions), and to determine many new therapeutic targets for treating and curing more and more cancers.

In Canada, we have taken a leadership role for three different types of cancer – Pancreatic Cancer (ductal adenocarcinoma of the pancreas; collaborating and funding organizations can be found here; Brain Cancer (pediatric medulloblastoma; collaborating and funding organizations can be found here; and Prostate Cancer (adenocarcinoma of the prostate; collaborating and funding organizations can be found here.

 

Whether the ICGC actually achieves all of its lofty goals is of course yet to be fully seen. What is clear is that a major undertaking like this brings out what I consider to be the very best in science and scientists: the desire and willingness to not compete but instead to openly collaborate, to share data, and to work for the common good in ways that no single researcher or even a single country could manage.

This is so-called “big science” at its best and we should all be pleased that it is being undertaken in the international arena, and in the collegial and cooperative manner that it is.

Welcome to the World of Genomics... [Part One]

Although chronic myelogenous leukemia (CML) which is the main target of Gleevec, would not be considered one of the "major" cancers, I consider Gleevec to be the "poster child" for rational cancer drug design. I think that its importance goes far beyond CML but really creates a "proof of principle" that this kind of approach really will pay huge dividends in the future.

But as I stressed in the last post, approaches like this can only work when we understand more and more at the gene and molecular levels exactly what are the nature of the mutations that underlie particular cancer diagnoses. Which brings us to the brave new world of genomics…

With the success of drugs like Gleevec, combined with huge advances in technology, the field of cancer genomics is exploding and researchers around the globe are trying to catalogue as many cancer-causing mutations as we possibly can. So, what exactly is the study of genomics, and why should we care?

To understand cancer genomics we need to step back and understand what exactly is meant by the "human genome". Simply put, the human genome is the full collection of genetic material in each one of us.

You will recall that normal human beings have 23 pairs of chromosomes, and these chromosomes are comprised of long strands of DNA. If you remember your high school biology you will remember that DNA is comprised of four different chemical building blocks which we abbreviate as "A", "T","C", and "G". In each of our genomes there are about 3 billion(yes, that's billion with a 'B') of these building blocks arranged along each of the 23 chromosomes, but in a very particular order for each unique individual. It is this unique sequence of your DNA that defines the genes that make you an individual, different from me as an individual, different from your friend, different from your siblings etc. So, genomics is simply the study of the genome, and our attempts to understand how differences in the sequences of DNA contribute to human life and to individual variation.

So why is this important for cancer? Simply put, cancer is a disease of genes and mutations, i.e., mistakes in this “DNA alphabet”. The more and more we understand the genome alphabet and the more we learn about the different mutations that are associated with cancer, the better able we will be to understand, prevent, diagnose, treat and even cure cancers.

Now we have known about some fundamentals of DNA for a long time. The famous paper in the journal Nature by Jim Watson and Francis Crick was, after all, published on April 25, 1953! But knowing about some of the fundamentals of DNA is not nearly enough until we developed some tools to really study this in detail. Fast-forward from the famous publication by Watson and Crick about 25 years and you find me, as a postdoctoral fellow at the University of Calgary, doing some sequencing of DNA genes. In those days, in the late 70’s, I would have been able to routinely analyze a few dozen base pairs of DNA at a time, and that would have typically taken me several days to perhaps a week in order to accomplish. When you're dealing with 3 billion base pairs, this is very slow progress indeed.

Let's put the genome challenge in perspective in a different way. The human genome is comprised of about 3 billion base pairs. If your job was to read aloud your own genome starting from one end of chromosome number 1 and going all the way to the tip of chromosome 23, how long would it take you to read your own DNA sequence? Let's assume that you can read at the rate of about five bases per second, and that you work eight hours a day straight, five days per week (I'll give you your weekends off!), and you do this 50 weeks per year. How long would it take you to read your own DNA sequence?

The answer is something in the order of 84 years!! More than a lifetime for many of us…

So when I tell you that on February 15, 2001, the same prestigious scientific journal Nature (the one that published the original Watson and Crick paper in 1953, published a paper from an international consortium of scientists that reported, for the first time in history, the entire DNA sequence of a human genome, I think it's more than fair to say that this was a truly monumental accomplishment.

In fairness, this was not the full DNA sequence of a particular individual - that would come later - but rather what could be termed to be a “typical" sequence or a "reference" sequence. It was created via a precedent-setting, historic worldwide scientific effort, combining the efforts of many, many researchers and laboratories around the world, and stitching together bits and pieces of human DNA sequence to form this prototypical reference sequence.

While I personally don’t consider this accomplishment to be the absolute holy Grail of molecular biology,  I cannot over stress how pivotal, historic and important this accomplishment was. It lays the very groundwork for an unprecedented understanding of human life, genetic variation, and even human disease. And it will have a profound impact on how we view cancers, and how we deal with cancers.

In a future post, I will show you just how far we've come even since 2001 when this first reference human genome was published, and by doing so, give you a glimpse into a future filled with optimism and excitement, yet one that we may not be quite ready for…