DNA and You

Human Genetics Superimposed Upon Tragedy

I arrived in San Diego today, where I'll be attending the American Society of Human Genetics meeting. 

As I grew up in this town, the somewhat hairy airport approach cutting low over the buildings on the northern fringe of downtown always brings a smile to my face; it means that I'm almost back home.  However, this particular trip is a sad one too, as a quarter of a million people in San Diego County have been evacuated from their homes - victims of wildfires currently consuming Southern California.

Those of us who surfed while growing up here loved the "Santa Ana" winds.  The prevailing winds here are "onshore," from west to east.  However, periodically during Santa Ana's, the wind direction reverses with offshore winds bringing hot, dry air from deserts.  These winds hold up and shape the waves making the surfers very happy, but they can have a sinister side as we are seeing with the fires this week. 

After experiencing something similar a few years back, it seems like so far the city, county, and state governments have learned from their mistakes and are working fairly well together.  And this disaster seems to be bringing out the best in San Diegans, with many contributing food, shelter, and other resources to their displaced neighbors.

It's going to be a busy week at the meeting.  I'll do my best to keep up with the blogging and keep you posted on new and exciting developments.  I had intended for this post to be a rundown of exciting things to look forward to at the meeting.  However, for now, I'm hard pressed to do anything but watch the tragedy unfold for San Diego County and other areas of Southern California.   

Eye Color and Your Genes

Although it was once thought to be a classic Mendelian trait, eye color is now well known to be subject to polygenic (i.e., multiple genes are involved) inheritance.  Our current catalog of genetic variation affecting eye color is incomplete. 

However, in a paper published online today in Nature Genetics (abstract here, subscription required for full paper), Dr. Kari Stefansson and colleagues at deCode Genetics report the results of a genome-wide association study focusing on eye color (in addition to hair color and freckling) as a phenotypic trait.  This study adds considerably to our knowledge of the genetics of human eye color, in addition to hair color and freckling. 

The authors initially studied about 3,000 Icelanders and then performed replication studies in another ~2700 Icelanders and about 1200 Dutch individuals.  With respect to eye color, they found the previously reported association with OCA2 gene variants - not big news but providing confidence in the methods.  However, the authors also found association of a new gene - SLC24A4 - with both eye and hair color.  Additionally, two coding variants in the TYR gene were found to be associated with eye color and freckles. 

Interestingly, the SLC24A4 gene is similar to SLC24A5; a SLC24A5 coding single nucleotide polymorphism has previously been shown to be associated with skin color in African-Americans and African-Caribbean populations. 

The authors then went on to derive a model in which they attempted to predict eye color based on genotypes.  They showed that variants in OCA2 dominate the distinction between brown and blue eyes and that the newly reported variants can contribute significantly to the more subtle distinction between blue and green eyes. 

It will be interesting to see what deCode may have in mind with respect to commercialization of this new information.

New Blog: Cancer and Your Genes

I've started another blog, "Cancer and Your Genes," which can be found here.  It will be focused on the intersection of our genomes and cancer risk, with particular emphasis on educating the lay public about genetic risks for cancer.

Mountains Out of Molehills? Or the Real Deal?

Despite some significant challenges in bringing effective personalized medicine approaches to the clinic, cancer treatment is one area in which personalized medicine and molecularly-targeted therapies have begun to come to fruition already.  In addition to Gleevec, which effectively targets the BCR-ABL fusion protein that is characteristic of chronic myelogenous leukemia (CML) in humans, Herceptin is important in the treatment of the subset of breast cancer patients whose cancers have substantial expression of the "Her2/Neu" protein.

However, these molecularly targeted therapies that focus on specific proteins important to the causation and maintenance of a subset of cancer cases are only available for a small percentage of all cancers.  To move closer to truly targeted therapy (which hopefully would have less severe side effects than current approaches with relatively non-specific cytotoxic drugs and radiation), we must know more about the relatively complicated changes in the DNA of the cancer cell.

Although it frequently seems like the more we learn about cancer the more complex the problem becomes, a paper published in the online edition of Science today makes a significant contribution to our knowledge of what goes awry in the development of breast and colon cancers.  (Although the full paper is available only by subscription, there is a press release with more information about the findings at the HHMI website) 

In this work, groups led by Giovanni Parmigiani, Kenneth Kinzler, Victor Velculescu, and Bert Vogelstein utilized a high-throughput DNA sequencing approach to look at the coding sequences (the DNA sequence coding for protein sequence) of more than 18,000 genes in each of 11 different breast cancer cases and 11 colon cancer cases.  Utilizing a careful approach to determine that mutations occurred somatically in the development of the cancer (as opposed to being polymorphisms present in all of the DNA of the individual at birth), the study basically showed that an impressively high percentage of the genes had a non-silent mutation (i.e., one that altered the protein coding sequence) in at least 1 cancer case: 9.4% of the total number of genes analyzed.  Putative cancer-related genes were evaluated in another set of cancers.  There were a total of 280 genes (equally distributed between breast and colon cancers) in all that were validated by the presence of mutations in both the initial cancer set and the validation tumor set.  Further analyses were performed to assess the plausibility that these genes were mutated more often in the cancers than would be predicted by chance. 

Although it is not news that cancer is a genetic disease associated with the accumulation of mutations in several key genes (that presumably differ by tumor/tissue type), the high-throughput resequencing approach utilized in this work suggests much more complexity in the mutated cancer genome than was previously recognized.  By plotting a score related to gene mutation frequency for each gene on something resembling a topographical map, the authors point out that while there are certainly still several "mountains" that appear to likely to be very important in cancer development, perhaps the more striking feature is an extremely high number of "hills" (genes mutated at a much lower frequency in a given cancer type, but which still likely play a role in causation or maintenance). 

Although some may suggest that the authors are making mountains out of molehills, I believe that their interpretation is likely correct.  The ability to sequence virtually the entire coding genome of a tumor is very exciting; with the coming drop in sequencing costs, this could be more realistically applied to individual patient tumors in a clinical context.  The hard part will be devising strategies to act on this information in a way that improves clinical outcomes.  However, as the authors suggest, many of the "hills" can be grouped into one of a small number of biochemical pathways.  Future studies will no doubt assess whether drugs targeting these pathways can be applied on a rational basis based on high-throughput sequencing of patient tumor DNA. 

Despite some significant challenges in bringing effective personalized medicine approaches to the clinic, cancer treatment is one area in which personalized medicine and molecularly-targeted therapies have begun to come to fruition already.  In addition to Gleevec, which effectively targets the BCR-ABL fusion protein that is characteristic of chronic myelogenous leukemia (CML) in humans, Herceptin is important in the treatment of the subset of breast cancer patients whose cancers have substantial expression of the "Her2/Neu" protein.

However, these molecularly targeted therapies that focus on specific proteins important to the causation and maintenance of a subset of cancer cases are only available for a small percentage of all cancers.  To move closer to truly targeted therapy (which hopefully would have less severe side effects than current approaches with relatively non-specific cytotoxic drugs and radiation), we must know more about the relatively complicated changes in the DNA of the cancer cell.

Although it frequently seems like the more we learn about cancer the more complex the problem becomes, a paper published in the online edition of Science today makes a significant contribution to our knowledge of what goes awry in the development of breast and colon cancers.  (Although the full paper is available only by subscription, there is a press release with more information about the findings at the HHMI website) 

In this work, groups led by Giovanni Parmigiani, Kenneth Kinzler, Victor Velculescu, and Bert Vogelstein utilized a high-throughput DNA sequencing approach to look at the coding sequences (the DNA sequence coding for protein sequence) of more than 18,000 genes in each of 11 different breast cancer cases and 11 colon cancer cases.  Utilizing a careful approach to determine that mutations occurred somatically in the development of the cancer (as opposed to being polymorphisms present in all of the DNA of the individual at birth), the study basically showed that an impressively high percentage of the genes had a non-silent mutation (i.e., one that altered the protein coding sequence) in at least 1 cancer case: 9.4% of the total number of genes analyzed.  Putative cancer-related genes were evaluated in another set of cancers.  There were a total of 280 genes (equally distributed between breast and colon cancers) in all that were validated by the presence of mutations in both the initial cancer set and the validation tumor set.  Further analyses were performed to assess the plausibility that these genes were mutated more often in the cancers than would be predicted by chance. 

Although it is not news that cancer is a genetic disease associated with the accumulation of mutations in several key genes (that presumably differ by tumor/tissue type), the high-throughput resequencing approach utilized in this work suggests much more complexity in the mutated cancer genome than was previously recognized.  By plotting a score related to gene mutation frequency for each gene on something resembling a topographical map, the authors point out that while there are certainly still several "mountains" that appear to likely to be very important in cancer development, perhaps the more striking feature is an extremely high number of "hills" (genes mutated at a much lower frequency in a given cancer type, but which still likely play a role in causation or maintenance). 

Although some may suggest that the authors are making mountains out of molehills, I believe that their interpretation is likely correct.  The ability to sequence virtually the entire coding genome of a tumor is very exciting; with the coming drop in sequencing costs, this could be more realistically applied to individual patient tumors in a clinical context.  The hard part will be devising strategies to act on this information in a way that improves clinical outcomes.  However, as the authors suggest, many of the "hills" can be grouped into one of a small number of biochemical pathways.  Future studies will no doubt assess whether drugs targeting these pathways can be applied on a rational basis based on high-throughput sequencing of patient tumor DNA.