Today at Golden Helix, we are proud to announce our collaboration with MedGenome through an integration of OncoMD into our VarSeq software. Now VarSeq’s streamlined process of annotating and filtering variants will offer an added dimension.
OncoMD is a comprehensive knowledge base of cancer-specific genetic alterations, and by incorporating it into VarSeq, users can access to 2 million plus annotated cancer variants. Not only does this addition allow users to quickly prioritize actionable variants, but also make clinical decisions based on the sensitivity of variants to approved drugs and enrollment to open clinical trials.
We are excited to provide our users with a tool that is moving precision medicine forward, and meets clinician’s needs of better tailored diagnostics and therapeutic strategies. The full press release can be read on our website here.
There’s a strong desire in the genetics community for a set of canonical transcripts. It’s a completely understandable and reasonable thing to want since it would simplify many aspects of analysis and especially the downstream communicating and reporting of variants. Unfortunately, biology isn’t so tidy as to provide a clear answer for which transcript is the important one. Consequently, there isn’t a single resource that lists the “canonical” transcript for each gene. And while there have been some attempts to label important transcripts, like Ensembl’s “Gold” identifier, ultimately the issue is punted downstream to the lab (see: Which transcript should I use?).
Genes like HK1 contain many coding transcripts which differ greatly in structure. These differences can cause the same variant to have dramatically different names.
What’s a Good Name?
One of the most important reasons to develop a set of canonical transcripts is to provide a common basis on which to name variants. With that common basis in mind, a variant should ideally have a name that is:
- Contains a functional tie to the underlying biology
Regulatory bodies such as the Federal Drug Administration (FDA) already have a full plate. In the US, FDA-regulated products account for 20 percent of each dollar spent by American consumers each year. More specifically, the work of the regulatory authorities include the following:
- Carefully considering benefits and risks when evaluating medical products
- Staying on top of rapidly advancing scientific innovations
- Providing industry guidance to encourage the development of new therapies in promising areas
- Ensuring the appropriate usage of the most recent science and technology in appropriate ways
- Advising in clinical trial design, drug and device development and clinical practice
- Coordinating the dialog between key constituents such as scientists, government agencies, standards organizations and clinicians to evaluate new diagnostics and therapeutics
We anticipate more targeted therapies in the area of Precision Medicine. This means more drugs that need to be approved and more therapies that need to be evaluated. Does this mean that this will very quickly overwhelm organizations such as the FDA that are already stretched thin?
Well, not so fast!
Since its early release in early 2012, the population frequencies from the GO Exome Sequencing Project (ESP) – from the National Heart, Lung and Blood Institute (NHLBI) have been a staple of the genomic community. With the recent release of ExAC exome variant frequencies, the ESP has been surpassed as the largest cohort of publicly available variant frequencies (by nearly an order of magnitude). Yet, the NHLBI cohort, with its years of maturity and many citations, is still a staple annotation source.
Over the years, we have kept up to date with the latest version of the ESP catalog’s public releases. Recently, with their ESP6500SI-V2-SSA137 release, NHLBI has also provided mappings for the new human reference genome, making it the first major frequency catalog available for GRCh38!
While updating to this release, the Golden Helix data curation team has also made a number of improvements over the raw released data to make our ESP6500 track vastly more useful:
- Break out the monolithic genotype counts fields into individual numeric fields for heterozygous and homozygous counts.
- Compute an Alt Allele Frequency field, along with the provided Minor Allele Frequency to easily spot the “ref-is-minor” cases and be comparable to other catalogs such as 1000 genomes and ExAC.
- Support multi-allelic sites, using our genotype aware allelic splitting and left-align technique to provide focused records with relevant allele and genotype counts for the variants present in your data.
Precision medicine will fundamentally change how health care is practiced. Of course, we have a long way to go. For most practitioners today, their knowledge of the human genome was established many years ago. However, new therapies and diagnostic methods are pouring in on a daily basis. So, how do we make sure that the current and future health care workforce understands the complexities and intricate details of this field?
A starting point is a better understanding of how to use an individual’s genomic information to determine targeted treatment options, tailored to the individual patient. This requires:
- a baseline knowledge of genomics
- an understanding of the clinical applications of genomic medicine
- the capability to evaluate the clinical validity of new tests
- a comprehension of the ethical and social issues associated with this type of approach
Several of our customers have published recently, using our SVS and VarSeq software, and we love sharing their work with you. Congrats to all!
The genetics industry is undergoing a fundamental shift from a clinical science focus to a bioinformatics focus. Genetic services require a greater level of data analytics sophistication than is required for other laboratory testing. Currently, data generated by new tests overwhelms current information technology systems and human interpretation capabilities. This is one of the reasons that we at Golden Helix strive to simplify the process of analyzing and interpreting the data, so that it is possible for a wider group of users to conduct work in this space.
Ultimately, the output of the NGS pipeline needs to be integrated into the electronic health record and to be aggregated across a patient population. Robust informatics systems and trained bioinformaticians are critical new additions to the clinical team. Servant et al. (2014) covered this issue in detail. I agree with their findings. Here is the upshot.
Precision Medicine leverages the most innovative technology advances in the field of genetics. The concept is “en vouge”! We know that the science will give us increasingly better treatment options. I have covered this in my previous blog post. But does it really matter? Precision medicine only will become a reality if both patients and the health care professionals treating them will act on the information at hand.
So, where do we stand currently on this issue?