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Four Factors for Improving Genomic Data for Personalized Medicine

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advancing the use of genomic data for personalized medicine

The pace of progress has been astounding with advances in the use of genomic information to provide faster, more accurate, and more in-depth information to enable personalized patient care.

We’ve come a long way in improving the way that a patient’s genome sequence data is analyzed and interpreted to realize the full potential of personalized medicine. Here are four factors helping to overcome barriers and achieve new milestones for using genomic data to provide faster, more accurate, and more in-depth information to guide clinicians in delivering personalized care for patients.

Factor #1: Fast database query of the genome

Problem: Relational database architectures make it possible to store large quantities of sequencing data, but querying whole genome data can be time-consuming and take days to weeks.

Solution: The GOR (Genomic Ordered Relations) database is able to query whole-genome sequences in real time. The reason is that GOR understands the genome in terms of chromosomes, its natural structure, rather than as a continuous string of sequence. That’s both intuitive and innovative. When searching for a variant, tools in the GOR architecture don’t have to scan each individual’s entire sequence; they retrieve the variant straight from its location. Annotation data – information on what diseases or conditions variants have been linked to – are also stored in the same way. The GOR database was pioneered a decade ago by deCODE genetics, one of the first organizations to manage truly large genetic datasets, and is now being used by NextCODE for clinical applications of genomic data.

Factor #2: Fast, reliable identification of disease-causing variants

Problem: Many sequencing analysis pipelines are only powered to process data in a compressed format called Variant Call Format (VCF) files. These comprise only a tiny fraction of the genome, and being working only with VCF files makes it difficult to correct common alignment and allele-calling errors. That can result in both false positive and negative results, or to missing the key causative variants altogether.

Solution: The foundation for improved sensitivity and specificity is the ability to use VCF data on top of the raw sequence data from which it was derived. NextCODE’s pipeline and clinical interfaces, powered by GOR, give users the ability to go back to and visualize raw sequence data at a click. This approach enables genomic analysis and interpretation by seeking out disease-causing genetic variants, either in specific patients, or for research studies in a clinical setting.

Factor #3: Patient genomic information at the fingertips of the clinician

Problem: Many of today’s genomic interpretation tools are too complex and difficult to use by clinicians who may have minimal experience with genetic informatics tools.

Solution: All of the complex informatics required by a clinical analysis tool should disappear at the fingertips of a clinician. It starts by having a robust foundation to the informatics platform, and using the GOR database architecture enables rapid cycling between personal sequence data and broad clinical knowledge. The result is the Clinical Sequence Analyzer (CSA) in which clinicians can simply type in a patient’s symptoms, and CSA will search the patient’s whole genome for variants that may be relevant.

Factor #4: Applying the full power of whole-genome sequencing to cancer tumor analysis

Problem: Many of today’s approaches to the analysis of cancer genomes only look at the immediate next step for a course of treatment, an important capability but only part of a holistic view of a the genetic profile of a patient’s cancer and what can be done to fight it.

Solution: The Tumor Mutation Analyzer makes a more holistic approach possible, analyzing a whole exome or whole genome sequence from a patient’s own genome and from tumor cells. Comparing the two it is possible to isolate the variants likely to be cancer drivers. The distinguishing feature of TMA is the depth of the data it stores and the unprecedented level of detail it provides to more accurately identify variations. This level of detail is especially important in cancer genetics, where the chances of finding previously unknown variants are very high, and even if a mutation is successfully targeted with a course of treatment, another potential driver is often waiting in the wings.

The pace of progress has been astounding with advances in the use of genomic information for patient care. How will the path continue in the future? Stay tuned.


 

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Early Adopters of Sequencing in the Clinic

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early adopters of sequencing in the clinic

Leaders in the medical community are actively enhancing their facilities with DNA sequencers and supercomputers—steps toward the routine sequencing of patient genomes that will inform the full spectrum of care decisions.

It is increasingly evident that sequencing and analyzing genomic information can contribute to more informed healthcare decisions, and major research institutions and medical centers around the world seem to agree.

Leaders in the medical community are actively enhancing their facilities with DNA sequencers and supercomputers, recognizing the efficiencies of having this advanced technology at their disposal for innovative research programs. And as they look to the future, they are taking steps toward the routine sequencing of patient genomes that will inform the full spectrum of care decisions, from defining risk, to diagnosing disease, to defining the ideal course of treatment for the best possible outcome.

Just a few examples of the major advances in the use of sequencing technologies that have been announced recently…

From medical centers:

  • Mount Sinai Medical Center in New York initiated a program in which 24,000 patients participate in a biobank to include their DNA sequence and research over their lifetimes. The program, called BioMe™, is among the largest in the United States.
  • Memorial Sloan-Kettering Cancer Center researchers are active in a range of collaborations that seek to understand the molecular changes that characterize cancer, the largest of which is The Cancer Genome Atlas (TCGA), a project jointly funded by the NCI and the National Human Genome Research Institute. MSK currently houses one of TCGA’s Genome Data Analysis Centers.
  • Phoenix Children’s Hospital launched a new molecular and personalized medicine research institute that will “bring genomics research to the forefront of pediatrics.” The infrastructure will include a range of capabilities, such as a biospecimen repository, DNA sequencing and analysis, and a CLIA lab for genomic profiling.

And research institutions:

  • The Wellcome Trust Sanger Institute is dramatically upgrading its storage and data management capacity.  The Institute already operates 30 DNA sequencers, each of which generates roughly a terabyte of data every day. New upgrades will double their capacity and improve data management and organization software.
  • Harvard Medical School’s Center for Biomedical Informatics, conducts informatics research with a strong emphasis on translational science informed by innovative computational strategies; the research staff use mathematical modeling to predict when genetic information could lead to more effective treatment.

By members of industry:

  • Google is jumping into the genomics industry with the launch of “Calico,” a new company that will focus on genomic sequencing and advanced analytics to identify solutions for some of the most challenging diseases today.
  • “N-of-One” is a company offering personalized cancer treatment strategies as a new employee benefit tool for innovative, health-minded employers. Through the service, the company provides interpretation of molecular profiling to employees, their family members fighting cancer and their physicians to help inform treatment decisions.

And even the U.S. government:

  • The National Institutes of Health is one of the greatest proponents of genomic sequencing for research purposes. In fact, a recently initiated program is funding research teams to examine whether sequencing newborn genomes or exomes may provide useful information beyond what is currently captured in newborn screening programs.
  • Further, in the fight against infectious diseases and “super-bugs,” the National Institute of Allergy and Infectious Diseases established the Genomic Sequencing Centers for Infectious Diseases (GSCID) to sequencing priority pathogens, microorganisms responsible for emerging and re-emerging infectious diseases and related organisms.

With such a broad array of innovative research underway within the halls of the world’s leading institutions, there is no doubt sequencing is on the verge of delivering exciting breakthroughs in medicine. In fact, we’re seeing evidence of this with NextCODE, which has engaged with several “early adopter” organizations around the globe.  Check it out here.

The Technologies That are Key to Unlocking Genome Analysis

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Lower-cost genome sequencing, genomic analysis tools support personalized medicine

Lower-cost genome sequencing, genomic analysis tools, and reference databases for human genomes are the “3-legged stool” that will help the world reach personalized medicine.

Genome sequencing technology available today can accurately sequence a whole genome from an individual’s test sample for a surprisingly low cost—a few thousand dollars (and dropping fast). As a result, the adoption of this technology is rapidly expanding as medical centers around the world embrace its utility in informing healthcare decisions—an emerging reality of personalized medicine.

Three important areas of technology progress have enabled the medical community to reach this point:

  1. Lower-Cost Genome Sequencing: Major technological advances have reduced the cost of sequencing to nearly $1,000 or less, a critical milestone to enable the use of sequencing as a mass-market product for medical care.
  2. Genomic Analysis Tools: Since the human genome was first sequenced more than a decade ago, an increasingly robust body of research has showcased the links between mutations identified in the genome and disease risk. Informatics tools have been developed by medical centers and genomics companies to apply to whole-genome samples. Increasingly, these genome analysis tools will need to adapt to the steady pace of new genomic linkages to disease and to operate at a level approaching “big data.”
  3. Reference Databases for Human Genomes: There are a growing number of robust databases of human genomes, including data for healthy people or those with certain diseases.  When properly analyzed, these databases offer the potential to provide the medical community with a reference library against which to compare genetic data. Large-scale, high-quality databases are an essential element to cross-reference a patient genome to guide more informed medical decisions.

These three technology domains represent the “3-legged stool” that will help the world reach personalized medicine. The technology is in place, and the corresponding insights and uses are expanding every day. Yet there are challenges to be resolved before implementing these tools on a universal basis.

For example, logistically, how will new DNA and supercomputing equipment be accessed by medical centers, and how will the data be stored? And more importantly, what is the most efficient way to compare an individual’s genome to the massive body of genomic information available to help inform medical decisions for that patient?

One important part of the solution: we must turn to “big data” solutions to manage and make use of the enormous amounts of data produced through sequencing. The whole-genome sequence of a single human is roughly 100GB—that’s the entire storage capacity of a single Macbook Air®.

The progress to date has been amazing. Yet the opportunities ahead are even more extraordinary to improve the speed, accuracy, and accessibility of genomic information to improve human health.

Personalized Medicine: The Future is Almost Here

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The new era of personalized medicine.

The achievement of low-cost genome sequencing and the use of genomic data to better understand diseases are advancing the exciting new era of personalized medicine.

It’s been more than a decade since the human genome was first sequenced. Since then, we have been on the journey of applying this profound new discovery to create personalized medicine and advance human health.

Two significant triumphs along this human genome journey:

  • Using genomic data to better understand diseases; and
  • Achieving low-cost genome sequencing.

Each of these accomplishments has been a stepping stone into the exciting new era that is dawning now: where genomic information is becoming integrated into medical care.

Using Genomic Data to Better Understand Diseases

Let’s take a look back at the early days of using genomic data to connect the dots between genetic mutations and disease. From 1997-2004, I was part of the leadership team at deCODE, the Icelandic genomic company. This was the period when deCODE was building the world’s most productive human genomics platform, with a database of  tens of thousands of individuals who participated in genetic studies and including the largest database of genomes to this day. deCODE’s genomic engine was able to successfully identify the genetic variations associated with human disease. This resulted in dozens of groundbreaking discoveries that were published in major, peer-reviewed journals.

The legacy of deCODE was the creation of an industrialized platform capable of massive storage and analysis capabilities. This enabled researchers to crunch genomic data to gain insights about genetic variants, or risk factors, associated with many common diseases. deCODE’s premise was that once the genetics of disease was better understood that information could be used to create new ways to diagnose, treat and prevent disease. However, when I left deCODE in 2004, there were still barriers to overcome before this genomic information could be widely applied to the level of an individual patient. Chief among them was that the cost of genome sequencing was still prohibitively high. (deCODE was subsequently acquired by Amgen).

Achieving Low-Cost Genome Sequencing

Back in 2004, the cost to sequence a single human genome was hundreds of thousands of dollars. Today that cost is a few thousand dollars (and, in fact, fast approaching $1,000) for a whole genome sequence. DNA sequencing costs continue to fall, as speed and accuracy increase.

This means we are rapidly approaching a tipping point where, as the sequencing of human genomes becomes more economical, its adoption in the medical community becomes more widespread and genomic data can become more routine in medical care. This is why personalized medicine is becoming a reality.

The Era of Genome Sequencing in Medical Care

The steep drop in the costs of sequencing, combined with the explosion of research on gene variants and disease, mean the time is fast approaching when genome sequencing will become routine in medical care. Today, pathologists perform blood cultures to decide which antibiotics will stop a patient’s bacterial infection. Soon a patient sample can be taken to perform a genome sequencing to analyze the genetic characteristics of a patient to determine ways a disease can be prevented or, if they are sick, which treatments might work best for their disease.

The body of genomic knowledge and the large databank of human genomes built by pioneers like deCODE established the key building blocks that enable genome sequencing to have predictive power for individual patients. As more human genomes are sequenced and more genetic variants are associated with disease, the predictive power of knowing about risk genes and effective treatments for each patient – a.k.a. personalized medicine – will become an essential part of medical care.

Genome Sequencing Being Implemented by Medical Centers

In preparation for the future of personalized medicine, major medical centers in the U.S., Europe and Asia are actively beginning to install DNA sequencers and supercomputers as important tools for integrating genome sequencing into medical care. These medical centers are taking initial steps toward the routine sequencing of every patient’s genome to define the ideal course of prevention and treatment based on variants found in a patient’s genes.

Evidence of this adoption of genome sequencing by medical centers appeared in an article in The New York Times in April 2013 citing that:

  • Medical centers in New York City are spending more than $1 billion on new genomic research centers;
  • Several hospitals around the U.S. are undertaking systematic genome sequencing in patients;
  • Mount Sinai Medical Center has a program in which 24,000 patients participate in a biobank to include their DNA sequence and research over their lifetimes;
  • Memorial Sloan-Kettering Cancer Center sequenced 16,000 tumors from cancer patients in 2012; and
  • Phoenix Children’s Hospital opened a new institute in December 2012 to sequence the genomes of 30 percent of their childhood cancer patients.

For now, the use of whole genome sequencing in medical practice is still in its infancy, but the pace of progress continues to accelerate. Clearly, genome sequencing will soon become part of the nucleus of medical care. This will herald a new era in personalized medicine revolutionizing healthcare as we know it and transforming our lives. When do you think genome sequencing will become a part of the medical decisions in your life?