Tag Archives: whole-genome sequencing

New Breast Cancer Study Underscores the Need for More Sequencing

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Gene sequencing for breast cancer. More than the usual suspects at play.

Ever since actress Angelina Jolie’s highly publicized preventive mastectomy ignited discussion about BRCA 1 and BRCA2, almost everyone has heard about these genes and how they can increase risk of breast cancer.  Some people even refer to them as “the breast cancer genes.” But how genes cause this disease is much more complicated than just through the most well known BRCA mutations, as a recent study in JAMA of Ashkenazi Jewish women has demonstrated. http://jamanetwork.com/journals/jamaoncology/fullarticle/2644652

This intriguing study raises a crucial question: How much sequencing is enough when diagnosing breast cancer in the age of targeted therapies? The number of these therapies keeps growing, as does our knowledge of the links between what drugs work for women with particular mutations. But at what point should we say we have uncovered enough mutations to make a proper diagnosis? And in a field in which we know there’s a lot we don’t know, is there such a thing as enough?

The good thing is that sequencing costs are going down. “It used to be that just testing for a single gene cost several thousand dollars,” says Jim Lund, Director of Tumor Product Development at WuXi NextCODE.  “Now a panel of genes costs that and whole exome sequencing is slightly more.” At the same time, the number of mutations that are discovered and studied is increasing – in the genomes of patients and the genomes of their tumors.

The data here has a message about data itself: in principle, we should be generating as much sequencing data as possible. By generating it, storing it for vast numbers of patients and their healthy relatives, creating more comprehensive databases of all disease-linked variants, and then reanalyzing patient and tumor samples as more is learned, we can improve the risk assessment and the speed and accuracy of diagnosis for patients everywhere. Since we can do this, the question isn’t whether we can afford to do more sequencing, but why anyone would argue that we can afford not to.

The researchers who led the recent JAMA study used multiplex genomic sequencing on breast tumor samples from 1007 patients. They tested for a total of 23 known and candidate genes.  It has been well documented that women of Ashkenazi descent have a higher risk of breast and ovarian cancer, and that is at least in part because of three particular BRCA1 and BRCA2 mutations. These are called founder mutations, because they probably originated among some of the earliest members of this ethnic group, and have been propagated because of a strong history of marriage within the same community.

But the researchers working on this study wanted to know if there were mutations in other genes besides BRCA that made it more likely these particular women would develop breast cancer. The patients were from 12 major cancer centers; had a first diagnosis of invasive breast cancer; self-identified as having Ashkenazi Jewish ancestry; and had all participated in the New York Breast Cancer Study (NYBCS).

Surprisingly, only 104 of the patients were carrying one of the infamous founder alleles. Seven patients had non-founder mutations in BRCA1 or BRCA2, and 31 had mutations in other genes linked to increased risk of breast cancer, including CHEK2. The vast majority of these women carried none of the mutations that are “obvious suspects” for breast cancer. “We do not know why those women got breast cancer,” says Shannon T. Bailey, Associate Director of Cancer Genetics at WuXi NextCODE.

It’s important to note that thousands of different cancer-predisposing mutations have been found in BRCA1 and BRCA2 alone. Every population studied to date includes people with such mutations.  The three founder mutations that have been established as being common among Ashkenazis are estimated to account for about 10% of breast cancers in this group. The rest of BRCA1 and BRCA2 mutations are considered extremely rare under any circumstances.

“If you look at the genes on the panel used in this study, it looks as if they are mostly associated with DNA damage and there are no cell cycle regulating genes included,” says Bailey. “But there are all kinds of mutations that cause breast cancer, even in noncoding regulatory zones.” As a result, even the best designed panel may fall short.

That’s why this study is so important. It tells us that even with founder mutations, family history matters but it doesn’t yet always tell you everything you’d like to know. Of the women with the founder BRCA mutations, only about half had a mother or sister with breast or ovarian cancer.  It’s also already well known that just carrying a BRCA1 or BRCA2 mutation is no guarantee the patient will get cancer. For reasons we don’t yet understand, these mutations raise overall risk, but not everyone who carries one will develop the disease. So while BRCA mutations are important, we need lots more information about other genes too.

The authors of this JAMA report suggest that Ashkenazi patients with breast cancers should have “comprehensive sequencing,” including, perhaps, complete sequencing of BRCA1 and BRCA2 and possibly testing for other breast cancer genes as well.

And what about other patients?  WuXi NextCODE’s Lund points out that even the most highly regarded recommendations for breast cancer testing do not cite specific panels. Those recommendations come from the U.S. Government Task Force [https://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/brca-related-cancer-risk-assessment-genetic-counseling-and-genetic-testing] and the NCCN Clinical Practice Guidelines. Women with a family history will likely get more comprehensive testing, but beyond that it is not clear exactly how to proceed in every case.

At WuXi NextCODE we believe that this is clear evidence pointing to the value of doing more sequencing across all ethnic groups – for healthy individuals, patients, and their tumors, and pushing towards sequencing as standard of care. This would expand our knowledge of the genetic risk factors for breast and other cancers; provide vast new cohorts for research; and deliver the most actionable insights to patients, from risk assessment through diagnosis and then ongoing as new discoveries are made.

All of the participants in this JAMA study consented to have their sequence data used to advance research. They are already helping to do that, and this is just one study of thousands that are now underway and that are helping us to expand our data- and knowledgebases with the ultimate aim of delivering even better outcomes for all people and patients everywhere.

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Let’s Speed the Genomic Revolution, UK CMO Says

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Sally Davies genomics

Whatever path various societies take to tap the power of the genome to improve human health, a recent report from England’s Chief Medical Officer, Dame Sally Davies, calls out key elements for realizing that future sooner rather than later.

England’s Chief Medical Officer wants to build on the success of Genomics England’s 100,000 Genomes Project and take her country swiftly into the age of precision medicine. The goal is to get patients optimal treatment more quickly and with fewer side effects. That means using genomics to more accurately guide prescribing—initially for cancer, infections, and rare diseases—but increasingly for all conditions and overall wellness and prevention.

Dame Sally Davies’ vision is anchored in the work that Genomics England is engaged in today and to which WuXi NextCODE and other leading genomics organizations have contributed. It’s a rallying cry that many voices are joining and underpins our work not only in England, but also similar efforts we are helping to advance in countries near and far, from Ireland to Singapore.

Her call is particularly forceful in three areas that she rightly singles out as critical to realizing the potential of precision medicine to revolutionize healthcare:

  • Industrial scale: Genomics has in many ways been treated and developed as a “cottage industry,” yielding important advances. But the need is massive scale in the era of population health (e.g., whole-genome sequencing, or WGS).
  • Privacy AND data sharing: Dame Sally wants to provide and ensure high standards of privacy protection for genomic data but is adamant that this should not come at the price of stifling the data sharing and large-scale collaboration that will transform medical care and many patients’ lives. She wants to move beyond “genetic exceptionalism,” which holds that genomic data is fundamentally different or more valuable than other data. Like other sensitive data, we can protect genomic data well and use it for public benefit.
  • Public engagement: She calls for a new “social contract” in which we, as individuals and members of society, recognize that all of us will benefit if we allow data about our genomes to be studied. That holds whether we are talking within our own countries or globally.

In England, as elsewhere, these shifts require the input of political leaders, regulators, and a range of healthcare professionals, including researchers as well as care providers. Crucially, such a transformation also requires a level of commitment on the part of patients throughout the National Health Service (NHS) and citizenry in general. If England takes this bold step forward, it could have tremendous effects. But “NHS must act fast to keep its place at the forefront of global science,” said Davies. “This technology has the potential to change medicine forever.”

To date, more than 30,000 people have had their genomes sequenced as part of the 100,000 Genomes Project. But there are 55 million people in the UK, and Dame Sally would like to see genomic testing become as normal as blood tests and biopsies for cancer patients: She wants to “democratize” genomic medicine, making it available to every patient that needs it.

We share and are, indeed, taking part in helping to realize much of Dame Sally’s vision as we work to accelerate Genomics England’s work and engage with our partners globally. As we know, different societies have different models of healthcare and different approaches to research and care delivery. But the ability for people anywhere to tap into the power of the genome to improve their health is at the very core of our own mission as an organization, and we applaud Dame Sally for calling out some of the key elements for realizing that future sooner rather than later.

Whatever path different societies choose to follow toward precision medicine, her recent report provides one enlightening view of a starting point for making the leap.

As Cancer Databases Grow, A Global Platform Leaps the Big Data Hurdle

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cancer databases

As massive cancer databases like The Cancer Genome Atlas (TCGA) proliferate and expand worldwide, WuXi NextCODE expects to see—and to drive—a boom in discoveries of cancer biomarkers that will advance our ability to treat cancer and improve outcomes for patients.

One of the fastest-growing areas in medicine today is the creation of massive cancer databases. Their aim is to provide the scale of data required to unravel the complexity and heterogeneity of cancer—the key to getting patients more precise diagnoses faster, and to getting them the best treatments for their particular disease.

In short, this data has the potential to save lives.

Such databases are not new, but they are now proliferating and expanding at an unprecedented pace. Driven by governments, hospitals, and pharmaceutical companies, they catalogue a growing range of genetic data and biomarkers together with clinical information about their effects on disease, therapy, and outcomes.

Only with such data can we answer the key questions: Does a certain marker suggest that a cancer will be especially aggressive? Does it signal that the tumor responds best to particular treatments? Are there new pathways involved in particular cancers that we can target to develop new drugs?

It’s the cutting edge of oncology, but to be powered to answer these questions, these databases have to be very, very big. They have to bring together whole-genome sequence data on patients and their tumors as well as a host of other ‘omics and biological data. One of the biggest challenges to realizing this potential is to manage and analyze datasets of that scale around the world. It’s one we are addressing in a unique manner through our global platform.

One of the most renowned and widely used of these is The Cancer Genome Atlas, a collaboration between the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI). TCGA data is freely available to those who qualify, and there is a lot of it. It already comprises 2.5 petabytes of data describing tumor tissue and matched normal tissues for 33 tumor types from more than 11,000 patients. Researchers all over the world can apply to use this data for their own studies, and many have.

Yet asking questions of TCGA alone can take months for most groups and requires sophisticated tools. At Boston’s recent Bio-IT World conference, WuXi NextCODE’s director of tumor product development, Jim Lund, explained how we have put TCGA on our global platform—providing a turnkey solution with integrated analytics to transform the data into valuable findings.

Jim and his team have imported into WuXi NextCODE’s cloud platform virtually all key TCGA data: raw whole exome sequence data from patients and tumors, as well as variant calls using MuTect2 and Varscan2; RNA and microRNA sequence and expression data; and data on copy number variation, methylation arrays, and some 150 different clinical attributes. But this data isn’t just hosted in the cloud: it can all now be queried directly and at high speed online, enabling researchers to quickly ask and answer highly complex questions without having to download any data or provide their own bioinformatics software.

To demonstrate the power of this approach, Jim’s team decided to run the same queries in a recent published study that looked at sequence data from the exons of 173 genes in 2,433 primary breast tumors (Pereira et al., Nature 2016). They were specifically looking for driver mutations of cancer’s spread and growth. In a matter of minutes, rather than months, they were able to replicate key mutations identified in the study. That analysis was then extended to all cancer genes, and additional driver genes were found. More important, because they were able to correlate these mutations with clinical outcomes data, they were also able to begin systematically matching specific mutation patterns to patient outcomes.

Next, Jim’s team looked at the genomics of lung adenocarcinoma, the leading cause of death from cancer worldwide. Following up on the findings in another published study (Collison et al., Nature 2014), they profiled the 230 samples examined in the paper and immediately made several observations. Eighteen genes were mutated in a significant number of samples; EGFR mutations (which are well known) were more common in samples from women; and RBM10 mutations were more common in samples from men. These results were extended to 613 samples and shown to be robust. But because they had a wide range of data including mRNA, microRNA, DNA sequencing, and methylation, Jim’s team was further able to suggest some actual biological processes that may be fueling the origin and growth of lung adenocarcinomas.

What’s making this type of research possible? It’s our global platform for genomic data. The platform spans everything required to make the genome useful for helping patients around the world, from CLIA/CAP sequencing to the world’s most widely used system for organizing, mining, and sharing large genomic datasets. At its heart is our database—the Genomically Ordered Relational database (GORdb). Because it references sequence data according to its position on the genome, it makes queries of tens of thousands of samples computationally efficient, enabling the fast, online mining of vast datasets stored in multiple locations.

That’s how we are making the TCGA—and every major reference dataset in the world—available and directly minable by any researcher using our platform. Those users can combine all that data with their own to conduct original research at massive scale.

These breast and lung cancer studies are just two of more than a thousand that have been carried out so far on TCGA data. As more such datasets become available, we expect to see—and to drive—a boom in discoveries of cancer markers that will advance our ability to treat cancer and improve outcomes for patients. For those who want to go further still, our proprietary DeepCODE AI tools offer a means of layering in even more datasets to drive insights even deeper into the biology of cancer and other diseases. And that’s a topic I’ll return to in the weeks ahead.

Genomics and Rare Diseases: Hope for Solving Unanswered Questions

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genomics and rare diseases

Leading institutions around the world are leveraging the power of advanced sequencing technology to solve some of the greatest unanswered questions in medicine.

As we learn more about disease biology and uncover new insights thanks to the availability of genomic technologies, we are making meaningful progress in identifying means to address many rare diseases for which there is little medical hope today.

With these new genomic tools and insights, a wide range of opportunities has emerged to improve diagnosis and treatment of rare diseases. Over the past few years, DNA sequencing has begun to uncover the causes of rare diseases and, at the heart of each case solved is a patient and a family that has gained new understanding about their condition. With time, these success stories in diagnosis will lead to more successes in treatment.

Now more than ever, there is more hope that identifying the key mutations will lead to better understanding of the biology of disease and then to novel therapies. Better and faster technologies are being promoted by leaders in the field of genomics that are enabling much more rapid analysis and interpretation of a patient’s genome to find answers. The critical first step is to obtain sufficient data to analyze, compare it against a robust database of reference data, and gain an accurate understanding of potential mutations associated with these rare conditions.

As researchers focus on specific areas, new partnerships are extending access to data and accelerating progress with rare diseases around the world. Recently, genomic analysis collaborations were initiated by ACoRD at University College Dublin to implement NextCODE’s proprietary database and analytical tools to mine whole genome data for variants linked to autism spectrum disorders. [See blog post here]. Another genomic analysis program with ANZAC in Australia applies advanced sequencing analysis technology to better understand X-linked Charcot-Marie-Tooth Syndrome, a rare and progressively debilitating neurodegenerative disorder. [See blog post here] More collaborations are in the works and we’ll be talking about them as soon as we can.

We look forward to the results of these and other collaborations as leading institutions around the world make efforts to leverage the power of advanced sequencing technology to solve some of the greatest unanswered questions in medicine.

Pioneering Genome Sequencing Effort in England Aims to Shape the Future of Global Medicine

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£300 million in new investments for Genomics England

Genomics England 100,000 Genomes Project

Genomics England was set up by the UK Department of Health to deliver the 100,000 Genomes Project. Initially the focus will be on rare disease, cancer, and infectious disease. The project is currently in its pilot phase and will be completed by the end of 2017.

These are exciting times for large-scale sequencing projects. Last week, U.K. Prime Minister David Cameron announced over £300 million ($509.4 million) in new investments for Genomics England, which aims to sequence, analyze, and store the genomes of 100,000 UK National Health Service (NHS) patients by 2017. The investments include about £162 million ($275.1 million) from Illumina Inc. (NASDAQ:ILMN), the partner for the sequencing element of the project. In turn, Genomics England will pay Illumina about £78 million ($132.4 million) for its services.

At the same time, the Wellcome Trust will put £27 million ($45.8 million) into a new sequencing hub at its genome campus in Cambridge; the Medical Research Council, or MRC, is investing £24 million ($40.7 million) to support data analysis and interpretation, and the NHS will make £20 million ($34 million) available for the establishment of patient sequencing centers.

This is a prime example of how the implementation of sequencing technologies promises to drive a revolution in the structure of medical research. These new projects aim to capture more data on human DNA than ever before, with the goal of advancing care and solving healthcare challenges.

The 100,000 Genomes Project, developed by the NHS, has the potential to significantly influence the global community through its plans to integrate sequencing data into standard medical practice.

Genomics England plans to generate 100,000 whole genome sequences from NHS patients with cancer, rare diseases, and other conditions, and to share the resulting data for research and development purposes. In the early phases, the program will also seek to develop standards for consent, sample storage, data generation and variant analysis that may be useful for many other organizations conducting large-scale projects within public health systems.

The project is enlisting the help of organizations from around the world to undertake this significant effort. In fact, it recently selected Illumina to conduct the sequencing efforts and is evaluating technologies for storing, annotating, and interpreting the data so that it can be used  for both clinical diagnostics and drug discovery, development, and delivery to the right patients.

The challenges of analyzing data on such a large scale are formidable, but the end result carries great potential to address some of the significant unmet medical needs. NextCODE’s technology has already accomplished analytics on this scale based on its work with the Icelandic population through deCODE genetics. It’s an exciting prospect for advancing the future of genomics-driven medicine and one to watch.

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.


 

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?

Myriad and the Supreme Court: A Battle of Ownership in the Field of Genetic Testing

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Supreme Court BRCA gene patent

The unanimous decision by the Supreme Court Justices to strike down patent claims by Myriad Genetics on the BRCA gene is a milestone that will greatly shape the future of the genetic testing industry and, in fact, accelerate progress toward the use of whole-genome sequencing for patients well beyond breast cancer.

Recently the Supreme Court struck down patent claims by Myriad Genetics on the BRCA gene. The Court ruled that while synthetically produced DNA may be patentable, isolated genomic DNA (gDNA), discovered in nature and separated from its environment in the cell, is not patent-eligible.

The unanimous decision by the Supreme Court Justices has significant implications for patients, physicians, and the health care and life sciences industries. In many ways, this is a milestone that will greatly shape the future of the genetic testing industry and, in fact, accelerate progress toward the use of whole-genome sequencing for patients well beyond breast cancer.

Within a day of the Court’s verdict, 10 companies announced their intention to compete with Myriad—and more are sure to follow, as BRCA has proven to be a very relevant gene for assessing risk levels, disease targets, and potential treatments.

While this industry flurry illustrates the potentially significant commercial opportunity here, the greater implication is that the landscape is beginning to shift toward sequence analysis on a genome-wide basis rather than on individual gene testing.

Because fundamentally, the gene-by-gene approach to genetic testing that would be necessary if individual companies had patents on certain genetic tests is un-economical and wasteful, compared with the scope of knowledge and insights to be gained from a whole-genome sequencing analysis. As evidenced by Myriad’s recent announcements to abandon individual BRCA testing by 2014, it seems they also acknowledge this trend.

Ultimately, then, the future of competition in genetic testing will be driven by the ever-improving tools for sequencing, managing genomic data, and manipulating large data sets—and not simply by patents on DNA sequences discovered in nature.

Angelina Jolie: Genetic Testing in the Mainstream Spotlight

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angelina jolie genetic testing decision

Angelina Jolie is perhaps the first highly visible public figure to “endorse” the idea of gene screening and make a very personal, radical medical decision as a result.

The May 14 New York Times featured an op-ed from recognized actress Angelina Jolie, entitled “My Medical Choice.” The piece recapped why she had her genes sequenced, and why she made the decision to undergo prophylactic bilateral mastectomy upon finding that she carried a very high-risk mutation in her BRCA gene. That mutation gave her a high likelihood of getting the same type of cancer that killed her mother.

Ms. Jolie is perhaps the first highly visible public figure to “endorse” the idea of gene screening and make a very personal, radical medical decision as a result. Her decision is a poignant example of the recent trend toward consumer-driven healthcare, wherein consumers take on a partnership role with their doctor in making major decisions, informed by science, which will greatly impact their future.

This trend will only accelerate as more technologies like whole genome sequencing are developed to aid in the decision-making process. As consumers gain increased access to medical information, they are more proactively seeking solutions that work for their personal circumstances.

The challenge for all of us in the health care industry is to embrace this empowered patient—and to work with them to ensure that they are part of making the best decision for their individual situation.  Embracing patient empowerment implies new attitudes for physicians and health care providers, as well as new economic considerations for hospitals, insurance companies, and service providers.

It should be noted that Jolie was among the minority of the population who can currently afford to seek the data, information, and counsel she needed to help her make her medical choices based on her established family risks.

However, as technology evolves and expanded uses for genetic testing helps to drive industry-wide economies of scale, these types of tests will become more broadly available to everyone. Ultimately, these tests and the medical care that they enable will become a routine part of mainstream care for all.