Epigenetics replacing single gene based disease research!

Epigenetic pathology are the one of the biggest hot spots for genome scale studies of epigenetic diseases because of its ability to reveal more than the candidate gene approaches.For example, methylation changes can affect large genomic regions in colorectal cancer, and widespread methylation changes are even more striking outside of the usually examined CpG islands (i.e., in shores and gene bodies).
Stem cells, the focus for a wide range of both basic and applied research on disease, have shown promiscuous methylation differences from somatic cells on a genome-wide scale, notably including differences at non-CpG sites.  sites of differential methylation largely overlap, with strong statistical significance, across physiological states—the same sites appear, for example, in normal cells compared with cancer cells, in stem cells compared with differentiated cells and in comparisons of tissues derived from different germ layers. Thus, the language of epigenomic organization seems to be common for normal development and for disease, just as the language of anatomy is common for normal and abnormal physiology.

The influence of epigenetic control has definitely influenced how the disease based studies are being organized.Only  2% of cancer epigenetics are published genome scale studies , the rate of increase over the past five years of cancer epigenomic studies is more than double that of conventional gene-based analyses of cancer . A similar kind of trend is also picking up in other fields of noncancer human disease epigenetics, such as epigenetics of cardiovascular, immunological and neuropsychiatric disease. These differences are driven in part by the availability of new technology, of course, but also by the growing realization that variation in both DNA methylation and chromatin are widespread across the genome and may be organized into large genomic domains.
Another important factor driving such 'disease epigenomics' is the relatively limited yield to date of conventional single-nucleotide polymorphism (SNP)–based genetic analysis in explaining most common human diseases. As has been widely described in both scientific and lay publications, it was anticipated a decade ago that genetic analysis would be much more successful at attributing risk of disease to specific genetic markers. the actual 'genome anatomy' target for disease is probably much larger than scientists previously realized—perhaps involving more than half of the genome—and because understanding of the normal function of this genome anatomy requires epigenomics, it is possible that much of what appears to be negative genetic-association data could become meaningful in an epigenomic context . For example, most genome-wide association studies (GWAS) identify not genes, but nearby regions or intergenic deserts. Yet these same regions frequently harbor differentially methylated regions that discriminate tissue types or distinguish cancer from normal cells. They are also the canonical regions for lincRNAs that help establish chromatin structure and normal gene function. Furthermore, gene deserts may promote trans associations of chromosomes in epigenetic regulation. Another way in which disease-associated DNA sequence variants might affect disease risk is through their linkage to DNA sequences that regulate DNA methylation, chromatin modification or binding factors. Substantial association of SNPs with DNA methylation has already been found.
So Epigenetics  is all set to over take single gene based disease research.

A breakthrough perosnalised medicine Biomarker in Cancer !!

Results of a new study at M.D Anderson Cancer institute have found a new diagnostic test which will set up all together a new trend in personalized  medicine.They show that a specific protein can be used as a 'biomarker' to identify which patients with a rare type of non-Hodgkin lymphoma would benefit from a new class of cancer drug.
The presence or absence of the biomarker can now be used as a diagnostic test to identify which patients will benefit from this drug.It's one of the first examples of being able to personalise cancer medicine and tailor treatment for the individual patient.
Biomarkers also have implications for reducing the cost burden of introducing new cancer drugs on the NHS, as only the subset of patients that would see a benefit would receive the treatment.
'New cancer drugs would be more likely to gain approval from the National Institute for Health and Clinical Excellence where biomarkers exist to identify the appropriate patient group,' believes Professor La Thangue, as their analyses of how well the treatment works in relation to how much it costs the NHS would improve.
Cancer drug discovery and development has changed significantly with greater understanding of what goes wrong in biological processes within cancer cells. New drugs target a variety of these cellular processes, but they will often only be effective in a subset of patients according to the profile of their particular cancer.
For example, trastuzumab (Herceptin) is an effective drug against breast cancer but only among those patients with cancers that express the protein which the drug targets. Patients without that protein see no benefit from the drug.
A biomarker is something that can be measured to predict whether a particular cancer will respond to treatment with a particular drug. Simple diagnostic tests based on the level of biomarker present can then flag up patients that will respond to that drug.
Biomarkers can also be used to identify appropriate patient groups for clinical trials. This would improve the ability of the trial to determine a drug's clinical benefits and increase the likelihood that new and effective drugs make it into clinics. Currently the failure rate for new drugs in development is estimated to be 80%.
The Oxford and Texas team focussed on a new class of cancer drug called HDAC inhibitors because they stop the action of the protein histone deacetylase. SAHA (Vorinostat or Zolinza) was the first drug of this class to gain regulatory approval, and can be used in the treatment of a rare type of non-Hodgkin lymphoma known as cutaneous T-cell lymphoma, or CTCL.
The researchers used a whole-genome screen to identify those genes active in CTCL cells that govern whether the cancer cells respond to the drug SAHA or not. The screen works by silencing each gene in turn to assess its effect on how well the drug works. HR23B was found to determine the CTCL cells' sensitivity to SAHA.
The scientists now report that HR23B works as a biomarker in a clinically relevant setting. The presence of HR23B in biopsies from patients with CTCL predicted who would respond to the treatment 71.7% of the time.
With this first demonstration of a predictive biomarker for a cancer drug, the approach using a whole-genome screen can be done again and again to find biomarkers for different cancers and different drugs. The hope is that the identification of new biomarkers can become routine.
The Oxford group has a patent on the whole-genome screen for identifying biomarkers and is looking at options for commercialising a biomarker kit using HR23B as a companion diagnostic test to go with the drug SAHA.
This will surely be the path breaker in Cancer which is itself is not one disease but an array of so many disorders clubbed together under one name.