So researchers in the UK brought in the big guns – bioinformatics.

Cancer Research UK has set up seven British centers to start collecting 9,000 tumor samples from a wide range of cancer patients to create a DNA database. Researchers will extract DNA from these tumors and scan them for a series of key genes involved in tumor development. The results will then be cross-checked against a range of cancer treatments, to create a map of which treatments work best for cancers associated with which particular genes.

This is based on the concept of pharmacogenomics: certain genes predispose people to respond to certain drugs in certain ways. We can already test a cancer patient for a single gene, knowing how tumors with that gene respond to a particular drug. However currently we don’t have a way of testing a broad panel of genes. And to compound the problem, we don’t have a way of quickly and accurately sharing information between labs in the same city, across the country or internationally.

Again, enter the power of bioinformatics.

With the proposed cancer DNA database, a doctor might analyze a patient’s tumor sample and prescribe a tailored treatment plan within a very short period of time, perhaps as little as two weeks.

As Professor Matthew Seymour, director of the National Cancer Research Network (NCRN) in the UK, recently stated, “We have to get clever about how to target drugs. Medications for cancer have to be personalized because no two cancers are identical.”

Bioinformatics research is increasing at an exponential rate. DNA sequences are available to anyone with an Internet connection – along with free bioinformatics tools to explore sequence data, predict the presence of genes, and compare features shared between organisms.

The DNALC has been working in DNA sequencing and bioinformatics for over a decade, developing intuitive, visually appealing computer tools for teachers and students to quickly learn the rudiments of gene analysis and integrate bioinformatics with biochemistry labs.

If you want to find out more, check out:

• G2C Online Bioinformatics section
• DNAi: Applications > Genes and medicine > Genetic profiling
• Gene Boy, a fun, intuitive Flash interface to analyze DNA sequences.
• Sequence Server, a database and personal workspace for students to conduct phylogenetic analyses using their own DNA sequences.
• DNA Subway, a platform that uses the metaphor of a subway network to provide students access to various bioinformatics workflows.

Unfortunately very little is known about how this disease develops, so a new breakthrough published in Neuron (and by a second group also in Neuron) is reason for hope. Work by two independent groups uncovered a locus on chromosome 9 (actually an expansion of repetitive DNA in a non-coding region called C9ORF72) is implicated in at least a third of ALS cases. This sequence variation seems to affect the cells ability to recycle and cope with damaged proteins; when these proteins fail to be properly processed, the cell is damaged an ALS is the result. While this research may not explain all the causes of ALS, it is an important landmark in the battle against this illness, and provides a target for future research and therapeutic intervention.

To find these driver mutations, scientists look for the ones that occur frequently. Until recently, this was very difficult to do. However, new sequencing technologies now let scientists look for mutations in genes at an incredible rate. The cost of sequencing is dropping dramatically; to the point where in the near future sequencing the DNA from a cancer may be sequenced as a diagnostic. Soon, it may be the cost of computing that limits our sequencing efforts.

Improvements in technology allow scientists to look at the genomes of many tumors, and there is an international effort to look at 25000 cancer genomes. This will provide the data that will let them find the mutations that lead to cancer, even if they occur in a small proportion of tumors of a particular kind. Already, hundreds of tumors have been studied in detail, which is giving scientists a good feel for the patterns of mutations that happen in cancer cells. So far, over 400 genes directly linked to cancer have been identified in this and other studies. Figuring out how these many genes contribute to cancer is likely to lead to huge advances in diagnosis and treatment, although the task remains gargantuan.

In the emerging field of pharmacogenetics, scientists study genome variations and correlate them with drug treatment response.  For example, variations (also called polymorphisms) in genes encoding enzymes involved in drug metabolism have been found to affect the activation, deactivation, and toxicity of drugs used to treat cancer, heart disease, and psychiatric disorders.  Recently, scientists found that DNA sequence can also be used to predict responsiveness to current Hepatitis C treatment (a 48-week course of peginterferon-α-2b combined with ribavarin).

The sequence at a single DNA position (single nucleotide polymorphism, or SNP) on chromosome 19, close to the gene encoding the interferon-λ-3 protein, has a significant effect on a patient’s ability to clear Hepatitis C infection with treatment.  Patients with a C nucleotide at the critical position on both copies of chromosome 19 (CC genotype) are two to three times more likely to respond to treatment than those patients with the T nucleotide at the same position (TT genotype).

In the case of Hepatitis C, the mechanism by which one sequence is more therapeutic than the other is not yet understood.  However, sequence information can still assist doctors in selecting appropriate treatments: as alternative Hepatitis C treatments become available, doctors may bypass the current treatment for those patients with the TT genotype.

As DNA sequencing becomes cheaper and easier, and genome information becomes elucidated, the personalization of medicine may become a reality.

What did the study show?

Psychosis is a disordered cognitive state that can include disorganized thoughts, delusions, or hallucinations. It is a common symptom of schizophrenia and has been linked to a number of brain areas, including the the dorsolateral prefrontal cortex (DLPFC) and the hippocampus. Schizophrenia is also strongly associated with a number of genes, and a recent genome-wide association study identified a single nucleotide polymorphism in ZNF804A  as particularly important. Now, for the first time, a German research team has confirmed a link between ZNF804A and these brain structures. The group compared 115 participants who were either risk-allele carriers or non-risk-allele carriers and found differences in how their brains connect. For risk-allele carriers, connections were reduced within the DLPFC and also between left and right DLPFC . Conversely, risk-allele carriers showed increased connectivity between the DLPFC and hippocampal areas.

The study, primarily based at the University of Heidelberg, Germany, focused on a single nucleotide polymorphism (SNP) in ZNF804A (rs1344706)

Schizophrenia is a devastating, highly heritable brain disorder of unknown etiology. Recently, the first common genetic variant associated on a genome-wide level with schizophrenia and possibly bipolar disorder was discovered in ZNF804A (rs1344706). We show, by using an imaging genetics approach, that healthy carriers of rs1344706 risk genotypes exhibit no changes in regional activity but pronounced gene dosage–dependent alterations in functional coupling (correlated activity) of dorsolateral prefrontal cortex (DLPFC) across hemispheres and with hippocampus, mirroring findings in patients, and abnormal coupling of amygdala. , show that rs1344706 or variation in linkage disequilibrium is functional in human brain, and validate the intermediate phenotype strategy in psychiatry.

The study is important for a number of reasons. Firstly, it highlights the importance of connectivity (or dysconnectivity) as a neurobiological marker of schizophrenia. Secondly, it establishes ZNF804A as functional in the human brain. Thirdly, it is an example of how genome-wide association studies can align with anatomical data – to quote the authors, it affirms that “the pathophysiology of overt disease” can “mirror candidate gene effects”.

Functional Genomics and Big Picture Science

This third point is important to how we view science as a whole. Scientific research has traditionally relied upon reductionism as the primary means of discovery. To understand the world, reductionism tells us, we must strip it down to its barest elements. The sequencing of the human genome represents the ultimate triumph of this principle — the dis-assembly of an enormously complex living thing into its three billion molecular constituents. While unraveling the genomic structure ushered in a new era for biology and medicine, it laid bare a new problem—that of genomic function. Now that we have disassembled the machine, we have to figure out how to put it back together again.

Scientists have, in many ways, been forced to abandon reductionism and to look instead at the bigger picture – to see how things fits together. Increasingly we see large multi-disciplinary groups, each of which holds a different piece of the picture. In the current example, we have neuroimaging experts, who look at the gross structure of the brain, collaborating with geneticists, who look at m0lecules, and psychiatrists who look at behavior. These collaborations are exciting, because they integrate a number of different perspectives. Ultimately, this represents a triumph for “big picture” science.