Prostate Cancer Update: New Gene

A genetic pattern (variation) found on human chromosome 8 has been found to have an association with a 5x risk increase for developing prostate cancer. It is thought to cause 2/3 of African-American cases and 1/3 of Caucasian-American cases of the disease.

Another biomarker might be coming! Pharmacogenomics companies: ready … go!

Full story at

Gene Therapy: Eye-Eye Doc!

Twelve patients are in the middle of a first-of-its-kind trial in the UK. They are undergoing gene therapy to correct a genetic gene deficiency; a gene called RPE65. It is supposed to be expressed at the beack of the eye, in the retina, and without that gene expression the eye won’t interpret images.

Currently in one patient, Robert Johnson, he can now see outlines during the day, but little at night – he has had genes inserted into one eye. The procedure itself requires extensive precision, including a risk of tearing the retina. (See image to the right; Source: Moorfields Eye Hospital)
Story adapted from BBC.
See full story here.

Harvesting Bioenergy from Switchgrass

Recently, scientists have made progress on finding the key genetic elements responsible for controlling lignin production in swtichgrass though monitoring of mRNA transcripts. This discovery brings switchgrass one step closer to being used as a source of bioethanol. See full story at Scientists Turn Genetic Keys To Unlock Bioenergy In Switchgrass.

Genotyping Becomes More Affordable

A new machine called OpenArray(TM) from BioTrove, Inc. now allows genomic research to conduct genotyping (SNP) analysis across much larger patient groups.

As described on Traditional Medicine:

Unlike other technologies, which can genotype hundreds of thousands of SNPs in a few patient samples, OpenArray allows researchers to analyze SNPs across tens of thousands of patient samples – dramatically expanding study size and data significance. OpenArray SNP genotyping is also more efficient than previous technology because of its flexible design. A single OpenArray plate holds as few as 16 or as many as 3072 separate assays, which can be run against 48-144 samples per plate. Since the OpenArray NT Imager can process three OpenArray plates at once, it can generate more than 9000 data points in less than 10 minutes, ultimately generating over 100,000 data points per day with a single employee.

This is a huge step forward in genetics research, but we are still awaiting the $1 genomic sequence. Right now we are bordering on the $1000 dollar genome, which was talked about by Michael J. Heller, Ph.D., Departments of Bioengineering/Electrical and Computer Engineering, University of California, San Diego – yesterday at the Cambridge Healthtech Institute’s “Next Generation Sequencing Applications and Cast Studies” conference in San Diego, CA.

If you’re wondering just how competitive this space is, there is a $10 million X-Prize for Genomics that was issued by Craig Venter, for the first team to successfully sequence 100 human genomes in 10 days. Details of the prize are as follows:

The $10 million X PRIZE for Genomics prize purse will be awarded to the first
Team that can build a device and use it to sequence 100 human genomes within 10
days or less, with an accuracy of no more than one error in every 100,000 bases
sequenced, with sequences accurately covering at least 98% of the genome, and at
a recurring cost of no more than $10,000 per genome.

As it seems, the race is on!

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Scientists Rejoice as Google Solves Data Management Crisis

Okay … so maybe “rejoice” is going a little too far, but scientists in the astronomy world are quite happy with Google’s innovative solution to managing their massive amounts of data received from imaging done in space, whether its infrared, gamma-ray, x-ray, etc…

The processes has been coined “FedExNet” by scientists who have already adopted and are using the new service. So what is this new service? I have highlighted some of the main points from the originating Wired article below:

  • Google acts as both a repository and courier for large data sets
  • Google ships both the PC and array to teams of scientists at various research institutions, which then connect their local servers to the array via an eSATA connection. Once the data transfer is complete, the drives get sent straight back to Mountain View, where the data is copied to Google’s servers for archival purposes. The idea then is that if other scientists around the world needed access to such a large quantity of data, Google would simply reverse the process.
  • Chris DiBona, the open-source program manager at Google, says “We make a copy of [the data], and then we can use the hard drives for something else. They’ll get banged around a little bit too much (to store the data directly on the drives). They’re not intended to be a long-term storage medium — they’re like envelopes to us.”
  • With a set of Google drives, Gorelick (who came up with the FedExNet moniker) can copy his team’s data in about 24 hours or less, something that can make a big difference when the time comes to collaborate with other research groups.

    See full article at Wired: Google’s Next-Gen of Sneakernet

Think of all the separate databases out there that manage genetic information. There are many independently operated bioinformatic databases and if they can all be centralized and indexed in a way that only Google can do, think of the potential implications for the scientific community working to progress the knowledge of DNA, RNA and protein interactions. This might be an essential step working towards the completion of the proteome and transcriptome …

Genetic Goldmine Found by Global Ocean Sampling Expedition

Craig J. Venter has accomplished yet another feat in his conquest to sequence everything under the sun. Venter is best known for leading Celera in their challenge to beat the National Institute of Health (NIH) in a race to sequence the human genome. Since then he has lead numerous sequencing projects including the genetic analysis of New York City’s air [or the Nature publication], searching to discover the minimum genome at his company Synthetic Genomics, and most recently the Sorcerer II Global Ocean Sampling Expedition.

Results from the oceanic voyage that traveled from Halifax, Nova Scotia to the Eastern Tropical Pacific during the two year circumnavigation by the Sorcerer II Expedition have finally been released. The announcement from the J. Craig Venter Institute (JCVI) detailed several publications that were made in PLoS Biology. Highlights of the publication include:

Rusch et al. describe the results of metagenomic analysis of 37 samples taken aboard Sorcerer II during its voyage between Halifax, Nova Scotia and French Polynesia in 2003 to 2004, combined with seven samples collected during the pilot study in the Sargasso Sea. To capture the DNA, scientists onboard the Sorcerer II collected water every 200 nautical miles and then filtered it through progressively smaller filters to collect bacteria and then viruses. The DNA extracted for these publications were from the filter that collects mostly bacteria.

The group analyzed a massive dataset consisting of 7.7 million DNA sequences totaling 6.3 billion base pairs. Following from the Sargasso Sea pilot study, they continued to find a great degree of diversity both within and across the sampling sites. Researchers identified 60 highly abundant ribotypes (roughly equivalent to species) however, the inter-species variation and the variation of organisms within the same environment suggests that while the microbes might be similar at an rRNA level they can differ greatly at a biochemical and genomic level.

Yooseph et al. report on the 6.12 million new proteins uncovered from 7.7 million GOS sequences by using a novel sequence clustering approach. This nearly doubles the number of known proteins. The researchers found that the GOS dataset covered almost all of the known prokaryote (bacterial and archaeal) protein families and that there were 1,700 totally unique large protein families in the GOS dataset, not matching any known families. A surprising number of the new protein families discovered are in viruses. Researchers were also able to match 6,000 previously unmatched sequences in current protein databases to proteins found in the GOS dataset.

Previously, it was thought that different families of kinases were responsible for these types of cell regulation in prokaryotes (bacteria) versus eukaryotes (animals and other non-bacteria). Eukaryote protein kinases (ePK) were most common in eukaryotes, histidine kinases in bacteria. However, in their PloS Biology publication Kennan et al. show that with the scope and diversity of the GOS data that ePK-like kinases (ELKs) are indeed very prevalent in bacteria, in fact, more so than histidine kinases. This finding is even shedding some light on human kinases.

The research team has shown that the ePK is just one family in a diverse superfamily of enzymes that all share a common protein kinase-like (PKL) fold (shape). Using sensitive profile methods, the researchers discovered more than 45,000 kinase sequences from the GOS and other public data sources and grouped these into 20 diverse families, of which ePKs were just one. The GOS data doubles the size of most PKL families and triples the number of known ePK-like kinases (ELK). Many of these families exhibited eukaryote-like structure and function of their proteins and thus the researchers conclude that several of these protein families existed before the divergence of the three domains of life.

For more information, please see the press release at the J. Craig Venter Institute.

The data recovered from this mission is likely to yield a number of findings, and will be the focus of much scientific research from years to come. Kudos to you and your team Dr. Venter, and it was nice seeing you in Toronto last fall!

Pharmacogenetics Era: Cancer and Opiate Updates

Pharmacogenetics has “been around since the 1950’s” but, practically speaking, is a new player in clinical diagnosis and treatment, but it is changing the way that healthcare systems, pharmaceutical companies and even small biotechs position themselves in terms of developing new ways to combat disease. With DNA sequencing dropping in price by orders of magnitude, approaches to medicine are in the process of change. Now we are able to start at the genetic level, find out your genotype for a given gene and then recommend certain drugs to you based on your personal genetic profile.

Traditionally, most pharmacogenomic profiling existed with patients needed blood thinners, specifically warfarin, where the Cytochrome P450 gene was tested to determine its presence, mutations and copy number. These features let the physician know your relative rate of metabolism to see how you will respond to the drug and what dosage you should be taking. There are a number of other cytochrome genes that are often included in pharmacogenomic tests now, such as Cytochrome P450 2C9, which is an enzyme that metabolizes coumadin.

I found two examples recently that speak to some advances made in pharmacogenetics:

The first article discusses a new diagnostic called Oncotype DX which looks at DNA of the breast cancer cells to determine if the cells are benign, malignant, or metastatic. The test is commercially available and looks at 16 tumourigenic genes to determine how the cancer is going to behave. This is the tip of the iceberg for the cancer diagnostic market. Look out for more of these test as they are bound to pop up all over the place within the next 2 years. Mark my words.

The second advance is a Nature paper from Clinical Pharmacology & Therapeutics titled Pharmacogenetics of Opioids. They are looking at a number of genes, that, when present or absent, affect a persons dosage requirements. A selection of the article abstract is seen here that speaks to what the paper’s findings indicate:

The polymorphic CYP2D6 regulates the O-demethylation of codeine and other weak opioids to more potent metabolites with poor metabolizers having reduced antinociception in some cases. Some opioids are P-glycoprotein substrates, whereas, ABCB1 genotypes inconsistently influence opioid pharmacodynamics and dosage requirements. Single-nucleotide polymorphisms in the mu opioid receptor gene are associated with increasing morphine, but not methadone dosage requirements and altered efficacy of mu opioid agonists and antagonists. As knowledge regarding the interplay between genes affecting opioid pharmacokinetics including cerebral kinetics and pharmacodynamics increases, our understanding of the role of pharmacogenomics in mediating interpatient variability in efficacy and side effects to this important class of drugs will be better informed.

The pain market is large and vast, with 100-150 million Americans (~57%) having acute and/or chronic pain within the past year. Beyond America, over 500 million cases of pain are diagnosed worldwide each year, and most patients are unsatisfied with current treatment options. The worldwide pain management market symbolizes an escalating trend, having a value of $27 billion in 2004, with an expected increase to $35 billion by 2009. The number of people affected by pain, and have access to pain treatment is likely to escalate with the “baby boomer” generation approaching older age. Also, there is a trend indicating higher incidences of cancer, arthritis, HIV as well as surgeries[1].

There will undoubtedly be the need for advanced pharmacogenetic testing platforms that can determine the drugs that will work best for each individual’s pain need. Be sure to see these diagnostics enter hospitals and genetic labs in a few years!

[1] Frost and Sullivan. (2002) U.S. Pain Management Pharmaceuticals Markets.