WuXi NextCODE Takes on Cancer: Breakthroughs and Innovation in Sequencing using TCGA and AI

Hannes Smarason NextCODE TCGA cancer

Sequencing reads of a sample prepared by the traditional whole-genome sequencing workflow for fresh-frozen samples and data generated using the SeqPlus whole-genome FFPE method. The green and purple indicate reads sequenced in the forward and reverse directions, respectively, and yellow represents bases with non-reference sequence. The center of the image shows a C to A mutation in each of the tumor samples.

Cancer is one of the most active fields in genomics, spurring mountains of research papers and scores of clinical trials. WuXi NextCODE (WXNC) is committed to pushing this field forward and so we had a special “Genomes for Breakfast” session devoted to this topic at the recent ASHG17 event. Featured talks addressed our pathbreaking work in how to extract impactful findings from the renowned TCGA dataset; get better sequencing results from FFPE samples; and apply deep learning to drug discovery, drug repurposing, and identifying subtypes for diagnostics and clinical trials.

The Cancer Genome Atlas (TCGA) is one of the most useful public genomic cancer databases available and has already led to numerous critical discoveries, including entirely new drug targets as well as better insights into tumor origination, development, and spread. It includes data from approximately 11,000 patients and covers 33 cancer types. Data types include WES, RNA-Seq, mi RNA, CNV, Methylation array, and clinical sample data. The data is big and complex, and can include multiple samples from one patient, which is crucial to know when doing analyses.

During his ASHG talk, Jim Lund, WXNC’s Director of Tumor Product Development, shared some insights into how we put this rich data source to work in concert with our own unique data and analytical tools, in a process he dubs “multiomics analysis.” He described how we specially process the data and use our unique analytical platform to help scientists find just what they are looking for. Researchers can search the data by cancer type, age of diagnosis, sex, ethnicity, year of diagnosis, sample type (e.g. metastatic, new primary), and more.

Multiple pivotal studies using this dataset have already been published, including some examining the prevalence of specific mutations across human cancer types as well as in-depth profiling of specific tumors, such as breast cancer and lung adenocarcinoma. Layering different types of data, such as reads from DNA and RNA, allows much more accurate detection of features such as variants with allele-specific effects on gene expression. The user-friendly but sophisticated data interface makes it easier to see such findings. Over the years, our own database and our capabilities have both grown exponentially, creating a powerful tool for multiomics cancer research. You can see Jim putting the portal through its paces in a recent webinar.

In his talk, Shannon Bailey described how Whole Genome Sequencing (WGS) can be applied to formalin-fixed paraffin-embedded (FFPE) tumor samples, which are stored by the hundreds of thousands in repositories around the world. Shannon is the Associate Director of our Cancer Genetics division. He pointed out that while these samples are abundant and often paired with extensive clinical and outcome data, there are specific hurdles to using these for the type of large-scale retrospective studies many groups are eager to carry out.

For one thing the genetic material in such samples can be degraded, crosslinked, or in low quantities. Of all these problems, the biggest issue is getting sufficient quantity of quality DNA for sequencing. Numerous studies have found that these types of samples are difficult to work with and often provide very low success rates for gene sequencing studies. Clearly, fresh frozen samples provide much better results, but they are also much harder to obtain.

In response, our team has developed the WXNC SeqPlus FFPE extraction method, which provides substantially improved coverage compared to traditional methods and even approximates the results obtained with fresh frozen samples at 10X depth, with similar numbers of heterozygous and homozygous calls.

We tested SeqPlus in a study that comprised 516 tumor-normal pairs (i.e., 1,032 samples) that had been stored for 3 to 6 years. The targeted sequencing depth was 30X for the normal tissue and 70X for tumor tissue. The starting amount of DNA was 400 ng. The results were excellent, with SeqPlus delivering a coverage analysis just about 1% below what the fresh frozen control samples achieved. Further, a comparison of our analyses to results from the TCGA, using fresh frozen samples, showed striking similarity. These study results give us confidence that SeqPlus is a new “power tool” for FFPE sequencing studies. This webinar describes the process.

Sequencing reads of a sample prepared by the traditional whole-genome sequencing workflow for fresh-frozen samples and data generated using the SeqPlus whole-genome FFPE method. The green and purple indicate reads sequenced in the forward and reverse directions, respectively, and yellow represents bases with non-reference sequence. The center of the image shows a C to A mutation in each of the tumor samples.

Another area of great interest at WXNC is artificial intelligence (AI). We have been pioneers in AI for pulling novel insights out of massive multiple datasets. Leading this effort is Tom Chittenden, our Vice President of Statistical Sciences, Founding Director of the Advanced AI Research Labs, and a Lecturer on Pediatrics and Biological Engineering at Harvard Medical School and MIT. He also spoke at the breakfast series.

Our AI capabilities improve the tools we have and expand their capabilities. For example, using our AI tools, we can improve functional annotation of missense variants to an accuracy of >99%, integrate multiple types of data to discover new genes and elaborate pathways, and improve tumor subtype and drug-response classification accuracy by combining DNA- and RNA-seq, among other data types. These tools can be used for such varied purposes as target discovery, drug repurposing, and defining responders and non-responders in clinical trials.

We’ve already helped to develop breakthrough results, such as identifying an intriguing new target for both cardiovascular and cancer drug discovery. We’ve also classified breast and lung cancer subtypes with 97% to 100% accuracy, classified 8,200 tumors of 22 TCGA cancer types with >99% accuracy, and discovered a completely novel pan-cancer molecular survival signature.

The power of our deepCODE AI tools is in part thanks to a novel, causal statistical-learning method and deep-learning classification strategy. But another advantage is that they were built on our global platform for genomic data, which underpins the majority of the world’s largest genomics efforts and includes all major global reference databases. Our database stores, manages, and integrates any type of genomic data and correlates it with phenotype, ‘omics’, biology, outcome, and virtually any other type of data that may be relevant to a particular medical challenge.

If you want to know more, I recently gave an interview to WXpress outlining WXNC’s AI strategy. As we continue to deepen our commitment to this field, I’m sure we’ll have more exciting results to share.

News Flash: Drawing a “Molecular Portrait” of Mutations in Brain Disease

WuXi NextCODE‘s AI group is helping to advance cutting-edge applications across the breadth of our platform and with partners across the life sciences. Recently, they put some of their toolkit to work supporting exciting work by our colleagues at Boston Children’s Hospital and Harvard Medical School. Together, they have generated sequence data of unprecedented accuracy from single neurons, and we’ve been able to help with the analysis and the discovery of some very compelling mechanisms underlying neurodegenerative disease. Kudos to the BCH and HMS teams and to our AI group on this latest collaborative publication. That report is described below and on our new WuXi NextCODE blog.

WuXi NextCODE AI Team Helps to Draw Molecular Portrait of How Somatic Mutations May Contribute to Neurodegenerative Disease

  • Boston Children’s Hospital and Harvard Medical School-led study in Science leverages WXNC expertise in feature selection and pathway enrichment
  • Study shows how individual neurons accumulate mutations over time and how this process differs between normally aging people and those with early-onset disease

A study published yesterday provides the most direct and detailed picture to date of how single-letter mutations accumulate in the sequence of the DNA of neurons as we age, and how different this process looks in neurologically healthy individuals as well as those with early-onset neurodegenerative disease. Entitled “Aging and neurodegeneration are associated with increased mutations in single human neurons,” the study is published in the online edition of Science.

Led by scientists from Boston Children’s Hospital, Harvard Medical School, MIT, and the Howard Hughes Medical Institute, the study analyzed sequence data from 161 single neurons taken postmortem from 15 neurologically normal people, ranged in age from four months to 82 years, and nine individuals with early-onset neurodegenerative diseases, Cockayne syndrome and Xeroderma pigmentosum. A press release from Boston Children’s on the study and its impact is available here.

At a first level, this study utilizes important advances by the authors in techniques for accurately sequencing and reading mutations in the DNA of individual neuronal cells, a hurdle that has until now prevented directly testing the theory that such somatic mutations built up in neurons over time. With this data, the lead scientists were then able for the first time to observe directly in a substantial dataset the patterns of accumulation of somatic mutations in individual neurons in relation to age, region of the brain (in the prefrontal cortex and hippocampus), and disease state. From this they developed broad signatures for these three different types of variation.

The scientists’ next question was whether they could further tease apart the associational signature for early-onset disease to discover something further about the biological processes that were contributing to neurodegeneration. For that task, they called upon the expertise of their longtime collaborators at WuXi NextCODE’s Advanced Artificial Intelligence Laboratory. Tom Chittenden, WXNC’s vice president of statistical sciences, and Chandri Yandava and Pengwei Yang, senior bioinformatician and senior computational statistician, respectively, are co-authors on the study. They used techniques developed in our AI and deep-learning program to identify the most informative mutations from the vast original datasets, to map mutations onto the most informative genes, and to identify the biological pathways those genes are involved in.

“This extraordinary group, including Chris Walsh and Mike Lodato as well as their talented teams, has enabled us to take another step forward and to see better than ever before the progressive mutational burden in individual neurons,” said Tom Chittenden. “We’ve used our toolkit and functional enrichment models to identify the pathways being most impacted by these mutations. This has pointed the group to the importance of oxidative mutations affecting DNA repair and, particularly, in genes that are heavily transcribed.”

“What Tom’s group has done is helped us to model how, as the somatic mutation burden increases, the brain loses function. What we see is that the more genes are transcribed, the more likely they are to be damaged and lose function,” said Mike Lodato of Boston Children’s Hospital and Harvard Medical School, one of the six first authors on the paper. “At the same time, because genes interact through these pathways, linear increases in the number of mutations appears to lead to exponential loss of brain function. It is essentially a scenario of use it and lose it.”

The study authors note that the identification of these pathways and the apparently important role of oxidative mutations points to potential novel therapeutic approaches for neurodegenerative diseases. This study also paves the way for the group’s next challenge: to take these discoveries in severe early-onset neurodegenerative disease and apply them to improve our understanding of the mechanisms and pathways involved in other related conditions, including Alzheimer’s disease.

Tom Chittenden says this is a challenge that is going to call on his full arsenal of AI and deep-learning capabilities. “To address Alzheimer’s disease, we are looking not only at early-onset disease but at subtler phenotypes around mild cognitive impairment. We are going to have to bring in not just sequence data but also methylation data, mRNA, and many other data types. The results we are presenting today are a step in the right direction, however—going from association to causal inference models to identify dysregulated pathways involved in disease. This is how AI is going to help to provide novel understanding of disease and progression.”



News Flash: Key Advances in Big Genomics from WuXi NextCODE Highlighted

Jeff Gulcher, CSO and co-founder of WuXi NextCODE

WuXi NextCODE‘s CSO and co-founder, Jeff Gulcher, spoke with Frontline Genomics at this year’s ASHG meeting about our recent breakthrough with FFPE sequencing, advancing toward using AI to diagnose cancer, how we are integrating complex datasets, and the importance of having a global platform. Here is a link to that article.

WuXi NextCODE Wins Scrip Award: As Reported in Our New Blog

WuXi NextCODE wins Scrip award

WuXi NextCODE was awarded the 2017 Scrip Award for Best Specialist CRO for enabling the pharmaceutical industry to take advantage of genomics. Dr Mark Hughes (middle), WuXi NextCODE’s Business Development Director for Europe, accepted the award on behalf of the company.

Below is news about our recent Scrip Award for Best Specialist CRO. This story is from our new WuXi NextCODE blog.

We’re thrilled to share that Scrip, the global biopharmaceutical industry news and analysis service, has named WuXi NextCODE as specialist contract research organization of the year for 2017.

The award, announced at the 13th annual Scrip Awards dinner in London, singled out WuXi NextCODE’s unique Contract Genomics Organization (CGO) capabilities for putting the full power of our world-leading genomics platform into the hands of biotechnology and pharmaceutical companies around the world.

WuXi NextCODE was selected from among many leading service providers and half a dozen finalists by an expert panel of judges comprised of independent, senior industry experts from around the world.

“Our aim is to enable anyone to use the genome to the benefit of people everywhere, so it is particularly gratifying to see our work recognized by the industry that creates new medicine,” said Hannes Smarason, CEO of WuXi NextCODE.

“We have built our CGO business to make it possible for organizations around the world to access our comprehensive range of best-in-class capabilities in genomics. We make it possible for biotechnology and pharmaceutical companies to take advantage of the best technology and largest global datasets, and to do so precisely according to their needs rather than a major fixed cost.”

WuXi NextCODE Solutions
WuXi NextCODE’s global platform is unique in offering truly comprehensive and integrated solutions for sequencing and querying genomic Big Data. Solutions include:

  • Sourcing global cohorts
  • Experimental and trial design
  • Research and clinical DNA sequencing
  • Access to large datasets for diagnostics and research
  • State-of-the-art genomic sequencing of FFPE samples
  • The unrivalled GOR database management system
  • Clinical interpretation and case-control research analytics
  • AI and deep learning

Pioneering Rare Disease Diagnostics in China—An Interview with Fudan Children’s Hospital Clinicians at ASHG17


The first year of WuXi NextCODE’s partnership with Fudan Children’s Hospital has delivered 11,000 clinical reports and a diagnosis rate of 33%, matching the throughput and success rate of the world’s leading laboratories.

One year ago, WuXi NextCODE (WXNC) and the Children’s Hospital of Fudan University (CHFU) launched a joint laboratory to put the global gold standard in sequence-based rare disease diagnostics at the service of patients in China. In the first year of that joint effort, the partnership delivered some 11,000 clinical reports—with more than 1,000 new reports now being generated each month—and a diagnosis rate of 33%. This matches the throughput and success rate of the leading laboratories in the world.

Dr Lin Yang of CHFU presented a summary of this remarkable progress at WXNC’s breakfast session on rare disease at the ASHG17 meeting held recently in Orlando. Afterwards, WXNC’s global communications lead, Edward Farmer, sat down to talk about this collaboration and what it means for patients, with Associate Professor and Laboratory Director Dr. Huijin Wang from the clinical team; Dr. Bing Bing Wu, director of the medical diagnostics laboratory; and Assistant Professor Dr Xinran Dong, who leads the bioinformatics team, as well as WXNC Chief Scientific Officer, Jeff Gulcher.

Edward Farmer: It’s a real pleasure to have with us our colleagues from Fudan and to be able to hear about this collaboration in rare disease diagnostics and genome-based testing in the neonatal unit. To start us off, Jeff, can you tell us how this partnership came about and how you see its importance to rare disease diagnostics in China and worldwide?

Jeff Gulcher: It’s been a fantastic partnership that started about two-and-a-half years ago, when we began discussing the possibility of creating a joint laboratory. The aim was to take advantage of WXNC’s technology and sequencing expertise together with Fudan’s expertise, both on the medical side and the interpretation side. The goal was to enable whole exome or medical exome sequencing of very sick children. In parallel, we decided to see if sequencing is useful in the neonatal ICU setting.

Through this partnership, we’ve now sequenced a large number of children and worked together to make diagnoses. Our medical genetics teams have worked closely together to interpret these cases, and in about one-third of the cases, we’ve been able to deliver diagnoses that were not suspected by the treating physician. In many cases, that has led to different treatments, with better outcomes for the children.

Together, we have now sequenced over 11,000 pediatric cases, including some 2,500 neonatal ICU cases, and we are very pleased with this partnership.

Edward Farmer: We have with us several senior people from Fudan. Huijin, let’s begin with you, as director of our joint laboratory. Can you share with us your impressions of this partnership so far and some of your results?

Huijin Wang: We have had a very good experience with this collaboration. We have many cases and, each week, we have a case meeting with the Cambridge WXNC team and we discuss the data and variant curation for the more difficult ones. The results have been impactful for the patients. In many cases, we can deliver a clinical diagnosis, and some of these offer real treatment options.

I remember one case that first came to the neurological clinic with seizures and hypoglycemia. This child had presented with recurrent hypoglycemia at a very early age and was in the NICU. We sequenced the family and found a recessive variant in the FBP1 gene, which the patient had inherited from both parents.

After this diagnosis, the doctor was able to discuss the problem with the family and advise them on how to limit the child’s diet to avoid hypoglycemia. The child is now doing well and no longer experiencing hypoglycemic episodes. And his family came back later and planned to have another child, and we referred them for prenatal diagnosis, and they were able to have another child who is healthy. This was a very successful case and is the sort of story that encourages us and shows us the value of the work we are doing.

Edward Farmer: That is an encouraging result. Lin, as an attending physician, how do you see the impact of introducing this technology into China at scale?

Lin Yang: We have more and more children at our hospital with birth defects or congenital malformations, so we really want to get a diagnosis and whatever possible treatment for them, including new treatments when available.

The collaboration between our hospital and WXNC starts with us deciding whether the case is likely to be the result of a genetic disorder. If it is, we do pre-testing counseling for the whole family before taking DNA samples. We then use WXNC’s capabilities for the sequencing and analysis of the results. Finally, we need to interpret the sequencing results and report them to the parents. It is often very difficult for parents to understand “what is a gene,” “what is a mutation,” “what is the disorder,” and “how can your child benefit from a molecular diagnosis?” So that is a critical part of our work.

But more and more patients are choosing molecular diagnosis and, if they get a correct diagnosis early, they may find a useful and more targeted treatment earlier.

In the NICU, we have some patients that have immune deficiency disorders. These can be very serious conditions, as the children suffer from repeated infections. It is very hard on the whole family. For such cases, if you have a specific diagnosis, there is often a cure. This is very good news for these families in the NICU, as they now have the possibility of getting a molecular diagnosis and then a treatment.

Edward Farmer: Are there any specific examples or cases that you can share with us?

Lin Yang: I had a newborn patient who had very low platelet counts and petachiae (red spots from small bleeds) on his face and body. We found that he has a mutation in the WAS gene, inherited from his mother’s side of the family, which means that his bone marrow is not producing enough platelets. But with a hematopoietic cell transplantation [HCT, which can include bone marrow] from a relative or closely matched donor, he has every chance of being cured of the disease and becoming a healthy boy. He is now waiting for a matched donor.

Edward Farmer: Huijin, you’ve done amazing work so far, and I know you are only getting started, but I wonder what proportion of the patients you see are able to benefit from the work of your lab and the collaboration with WXNC?

Huijin Wang: Currently, we are delivering a diagnosis to about 30% of patients, and we are able to recommend specific clinical treatment for about 20% of our patients.

And very often, we can give some guidance, if not a cure. Sometimes just knowing exactly what the diagnosis is gives patients peace of mind and new options. For example, many can go to a specialty clinic. But just knowing the diagnosis is often a comfort.

There is also a big need, and as a national center of excellence our diagnostics can help people across the country. About 80% of our patients come from outside of Shanghai, so with a diagnosis, they can go back to where they live and take some action there.

Lin Yang: There is also a difference among different diseases. I think we are now able to provide actionable results to about 50% of patients with neuromuscular disorders, and for respiratory maybe something less than that. For NICU, it’s maybe 15% that get a diagnosis, but we want to boost all of these.

We can benefit many more patients with this technology. In our hospital and with the WXNC collaboration, we can see an increasing number of patients. But there are a lot of undiagnosed patients, and in many places, there is not yet access to molecular diagnostics, so we hope this capability spreads to other parts of the country as well.

Edward Farmer: And Xinran, as we’re talking about building the scale and reach of molecular diagnostics, perhaps you can tell us a bit about how you are dealing with all of this data.

Xinran Dong: We have collected a lot of data. And from my bioinformatics perspective, one of the things that the WXNC collaboration is helping us to do is to make good use of the data, both for our clinical cases and for research.

I see part of my job as helping to build this into one of the biggest databases on rare disease in China and maybe the world. This is going to help patients today and advance the discovery of new genes.

Edward Farmer: Clearly there is no lack of ambition here. I want to thank you all for your time, and we look forward to sharing more stories of our work together.

WuXi NextCODE at ASHG17: Part IV of our “Genomes for Breakfast” Series Features Rare Disease Findings from Boston Children’s Hospital and deCODE genetics


Presenters from Boston Children’s Hospital and Iceland’s deCODE genetics detailed the impact of sequence-based diagnosis of rare disease at WuXi NextCODE’s “Genomes for Breakfast” series at ASHG17.

My last post described work on rare diseases at Children’s Hospital of Fudan University (CHFU) in China, but at our recent “Genomes for Breakfast” series at ASHG17, we also heard about the impact of sequence-based diagnosis of rare disease from colleagues in Boston and Iceland.

From our longstanding partners at Boston Children’s Hospital (BCH), we heard a detailed discussion of how sequencing hundreds of people across numerous families, and the analysis of all that data together, was accelerating our understanding of one disease: nemaline myopathy. That was presented by Alan Beggs of BCH’s Division of Genetics and Genomics, and the Manton Center for Orphan Disease Research at BCH/Harvard Medical School.

A myopathy is a disorder affecting the skeletal muscles. Typical symptoms of congenital myopathies include early onset of hypotonia and weakness, which reflect distinctive pathologic changes in the muscle fibers. There are multiple subtypes of myopathy. Nemaline myopathy is the most common subtype. It can cause painful contortions (arthrogrypothis), make patients dependent on ventilators and wheelchairs or, in less acute forms, lead to mild weakness that can still impair mobility.

One of the biggest challenges in understanding these myopathies is that they are heterogeneous in every way—clinically, pathologically, and genetically. There are multiple genes associated with different subtypes, and they are sometimes shared but can also be completely distinct. Scientists have also found multiple patterns of inheritance even for a single gene.

To try to shed light on this genetic puzzle, Beggs and colleagues have been looking in detail at the particular mutations found in certain patients and mapping those against their symptoms and inheritance patterns. Recently, the researchers sequenced 857 patients with several subtypes, including just over 300 with nemaline myopathy. The BCH researchers are using a variety of sequencing approaches, including exome analysis, RNA sequencing, and whole-genome sequencing (WGS). This is necessary, they have found, because there are unusual variants that are difficult to identify with traditional tools.

Using this array of sequencing technologies and WuXi NextCODE’s clinical interpretation and case-control research tools, they were able to identify specific genetic variants that have already been associated with certain subtypes, identify new variants, and start to predict the clinical impact of each mutation or constellation of mutations. These tools are able to instantly draw upon a wealth of data from BCH, WuXi NextCODE’s knowledge base, and public databases.

The picture that emerges is complex: a large set of variants that sometimes overlap across multiple subtypes, but sometimes are just strongly associated with a single subtype. The NEB gene is of particular interest because it is so strongly associated with nemaline myopathy and quite a bit is known about its biology. Based on these studies, Beggs and his colleagues have also suggested a more accurate approach to diagnosing nemaline myopathy. All of these are steps that benefit patients and their care, and they provide the first step toward developing new and more effective ways of treating these conditions.

The third country represented at our second breakfast was Iceland. Patrick Sulem, who leads the clinical team at deCODE genetics in Reykjavik, presented. Like our collaborators in Shanghai and Boston, but armed with a truly unique set of resources and expertise, the deCODE scientists have made significant strides in better diagnosing rare diseases in children.

The deCODE database is unique in many ways and powered to uncover rare disease-causing variants. It includes the directly sequenced whole genomes of nearly 50,000 Icelanders and 10,000 others; imputed whole genome data on some 400,000 Icelanders; and SNP data from nearly a million people around the world. This gives deCODE allelic frequency data of unrivaled detail. As we have shown, this data can be helpful in diagnosing disease around the world—but when used in Iceland itself, it can point straight to pathogenic mutations and provide a map to wherever they lie in the population.

These strengths are based on some advantages of the population approach, some that others would like to replicate, others that are tough to match. Iceland’s population participates in genetics studies at a higher rate than that of any other country; Iceland has a long, strong tradition of preserving ancestry records and so has a nearly complete national genealogy for the modern era; and a national health system with a centralized record system. These ingredients have given deCODE the right data to find important variants in diseases that have baffled others. (For more details, read my post on Kari Stefansson’s headlining talk for our breakfast series.)

Based on deCODE’s work, it is now evident that whole-genome sequencing (WGS) can greatly improve diagnosis and clinical management of infants and children with hard-to-diagnose diseases. Like their peers at BCH and CHFU, researchers in Iceland have been able to use genomic screenings not just for better diagnoses—giving parents at least the comfort of knowing what’s wrong—but also, in some cases, they have been able to offer better guidance for the children’s treatment.

One such case was the result of the early application of our technology, before NextCODE had spun out of deCODE. It involved two sisters who had undergone a diagnostic odyssey of several years. With whole-genome sequence data from them and their parents, and with the ability to filter allelic frequency data in the context of different modes of inheritance, we were able to identify the culprit variant—a previously unknown variant causing Brown Vialetto Van Laere syndrome—in a matter of minutes. Because the variant was disrupting a riboflavin transporter gene, the diagnosis immediately suggested riboflavin therapy, a course of treatment that halted the progression of their disease.

Finally, it is important to note that the identification of rare disease variants is a promising avenue for feeding drug discovery—not just for the rare conditions themselves, but also potentially for much more common conditions, of which rare diseases can be extreme versions. Solving rare disease is a challenge for us all—indeed, it is a common challenge in the truest sense. The more diagnostics we do, the bigger our databases all over the world, and with the informatics and tools to mine all this data, the more benefits we can deliver to people around the world.

WuXi NextCODE at ASHG17: Our Partnership with Fudan Children’s Hospital—Pioneering Rare Disease Diagnostics in China and Building Toward the Country’s Biggest Rare Disease Database

WuXi NextCODE and Fudan Children’s Hospital

In just one year, Fudan Children’s Hospital and WuXi NextCODE have diagnosed 11,000 pediatric patients in China and created a program that rivals the largest labs in the U.S.

Children’s Hospital of Fudan University (CHFU) in Shanghai is widely considered China’s top pediatric hospital. The doctors there see almost 2.5 million patients annually.

One short year ago, WuXi NextCODE and Fudan launched sequence-based rare disease

testing at CHFU using WuXi NextCODE’s RareCODE test and backed by our knowledgebase and the collective expertise of both organizations. In this first year, an astonishing 11,000 patients received sophisticated genomic screening tests to help guide treatment for hard-to-diagnose, or rare, diseases. One-third of those patients got a precise diagnosis, matching the best rates anywhere in the world. In short, Fudan and WuXi NextCODE have, in just one year, effectively launched the field of sequence-based rare disease diagnostics in China and created a program that rivals the largest labs in the U.S.

We had the distinct pleasure of hearing directly from doctors handling these cases and scientists building the database supporting this collaboration at our recent ASHG breakfast, “Using NGS to diagnose rare disease—experiences from three continents.” Dr Lin Yang, MD, PhD, a clinician at CHFU’s National Children’s Medical Center, presented the hospital’s experience with this rapidly expanding new program.

The service was created thanks to the unique partnership established between the hospital and WuXi NextCODE. WuXi NextCODE contributes its know-how in clinical-grade genomic sequencing, massively scalable informatics, and RareCODE test, backed the most powerful interpretation tools and clinical genetics expertise available.

CHFU, meanwhile, brings to bear the services, knowledge, and skill of its pediatric specialists and the national center of excellence in pediatric medicine housed at the hospital. Notably, CHFU’s Institute for Pediatric Research had previously developed more than 100 tests for single-gene genetic diseases, established multidisciplinary teams of clinical experts to address rare disease, and is among the very first hospitals in China to adopt next-generation sequencing.

Armed with our IT, knowledgebase, and diagnostic tools, this pioneering collaboration has advanced a national center of excellence for diagnosis, treatment, and further medical genetic research. At its core are not just the expertise of both teams, but also a rapidly growing database of mutations causing rare diseases, which the team hopes to grow into the largest in China, and perhaps the world.

Just over 5.5% of babies in China are born with some type of evident syndrome or birth defect. There, as elsewhere, these can impact the skeleton, metabolism, nervous system, circulation, respiration, digestion, and more. These can also be very complex, with multiple phenotypes or overlapping disorders. Some of these are due to causes other than genetics. But a large proportion represent genetic syndromes, of which many are de novo or have never been seen, or at least written about, by other clinical groups.

CHFU started doing single-gene sequencing to help resolve such cases as early as 2010. By 2012 the hospital was also running array CGH, and in 2013 it launched a number of panel tests and an NGS data-analysis pipeline. This history of pioneering genetic analysis put the hospital at the forefront of medical genomics. And things really moved forward fast after CHFU created a joint molecular diagnostic laboratory with WuXi NextCODE.

The two groups confer weekly on difficult cases and, as of now, they have completed some 12,000 genome analyses in just one year, providing a diagnosis in 33% of cases. These include the smallest patients, from the neonatal intensive care unit (NICU)—more than 2,200 of whom received focused exome sequencing and analysis. Just over 13% of those infants received a diagnosis. This lower rate of diagnosis among newborns reflects the greater challenge of working with patients whose signs and symptoms are just appearing. But this number is rising and, as the NICU is a first-tier clinical setting, every diagnosis can be a lifesaver.

Parents and other family members are also often sequenced to determine if the mutations are passed down or have occurred spontaneously (i.e., are de novo). All of that data is incorporated into a database, helping to grow knowledge about the mutations that cause rare diseases.

While there is no specific treatment for most of the syndromes identified, there is an improving picture for a growing number. Patients may receive a lifesaving, or life-changing, treatment plan, or referral to specialists based on their anticipated future needs. Regardless, it is important for the family and doctors to understand as much as possible about what the problem is. It is also helpful for parents and relatives to know that there are potentially pathogenic mutations that run in the family.

At ASHG, our head of communications, Edward Farmer, sat down with Dr Yang, other scientists and physicians from CHFU, and our CSO, Jeff Gulcher, to talk about the growth of the WuXi NextCODE joint rare disease lab and some of its early successes. I’ll be posting Dr Farmer’s interview with them here in the days ahead, so be sure to check back and learn more about the launch of rare disease testing in China.

WXpress News Site Highlights our AI Strategy

Hannes Smarason genomics AI

In an interview with WuXi AppTec’s WXpress news site, WuXi NextCODE CEO, Hannes Smarason, summarizes how genomics AI can make drug development better, faster, and cheaper.

How will WuXi NextCODE bring AI to the forefront of drug discovery and development? I mapped that out recently in an interview with WuXi AppTec’s WXpress news site. Below, I summarize some of the key points from the article.

Our advantage
The core of our strategy is to bring together three different things: Cutting-edge algorithms, domain expertise, and large data sets.

Executing on the strategy
Because of our history pioneering this field, we already have a wealth of samples as well as a very sophisticated and robust way of mining that data to help discover novel treatment pathways and for possibly re-purposing drugs. We are also continually developing new algorithms and other methods to distinguish between people who will respond and those who won’t when given a particular treatment.

The benefits of AI for drug development
Incorporating AI creates a much more data-driven rather than hypothesis-driven process. That improves the likelihood of identifying patterns and novel insights that may have been overlooked using conventional methods. That means finding the truly causal genes or pathways that drive disease. The goal is to have a more powerful starting point for the development of treatments.

Early validation
Our deep-learning algorithms have already been used to uncover a particular mechanism that appears to be a key driver in the development of the vascular system. That mechanism had not previously been described. Yale biologists then validated that discovery in an animal model, proving that our AI method had accurately predicted the role of this particular pathway in vascular development. So, when used correctly, AI can open up a whole new druggable pathway.

Challenges and hurdles
We must look at AI as a force-multiplier, as opposed to a replacement for independent thinking. That’s one reason having domain expertise in genetics and biology is absolutely key. The second thing is that you have to have access to a wealth of information, including cohort studies as well as genomic and phenotypic data.

The role of AI in evolving drug discovery and development?
Much like any major technological development, it’s going to start up slowly and then gather momentum. We believe that because of AI’s unique ability to bring large and complex data sets together and identify patterns within them, that in the end, it’s going to have an exponential impact in advancing and applying precision medicine. The result is going to be game-changing benefits to patients around the globe in terms of better diagnostics and better-targeted drugs.

Read the full interview.

WuXi NextCODE at ASHG17: Part II of our “Genomes For Breakfast” Series Featuring Major Precision Medicine Efforts in the US and Qatar

WuXi NextCODE ASHG2017

At the second WuXi NextCODE “Genomes for Breakfast” session at ASHG2017, Annerose Berndt, vice president of clinical genomics at University of Pittsburgh Medical Center, and Khalid Fakhro, director of genetics at Sidra Medical and Research Center in Qatar, outlined ambitious plans in large-scale genomics and precision medicine.

In my previous post, I described how Kari Stefansson started off this year’s ASHG breakfast session with a deep dive into deCODE’s toolbox and the powerful results the company has delivered.

Another of the renowned speakers at our “Genomes for Breakfast” session was Annerose Berndt, vice president of clinical genomics at UPMC (University of Pittsburgh Medical Center). She outlined UPMC’s ambitious plans in large-scale genomics and precision medicine. UPMC has a quite uniquely holistic role in underpinning the present and future healthcare of more than three million people in western Pennsylvania. It is an insurer, delivers healthcare through a rapidly growing network of dozens of hospitals, and conducts cutting-edge research in the life sciences and medicine, including through the University of Pittsburgh. It also has affiliated hospitals in nine countries apart from the U.S.

Last year, UPMC received one of the largest grants from the U.S. Precision Medicine Initiative and is investing in a large-scale genome sequencing effort that will both deliver patient care—through rare disease diagnostics and better-targeted cancer treatment—and create a major database for population-scale genomics research. Providing the integrated informatics, database, and tools for projects of such scale and combined clinical and research applications is what our platform does like no other, and we were very pleased to have UPMC present alongside and meet with our partners pursuing similar projects.

Closing out our population-focused breakfast we had the honor of hearing from our longtime collaborator Khalid Fakhro, director of genetics at our partner Sidra Medical and Research Center in Qatar. Sidra’s work, both on the Qatar Genome Programme and as the key maternity and pediatric hospital in Qatar, holds great promise for delivering higher-quality care to patients in Qatar and to advancing precision medicine around the world.

Echoing themes from Kari’s talk, Khalid outlined how Qatar’s population of 300,000, with its high consanguinity rates, is a fertile ground for identifying novel rare disease variants.

Leveraging data from 1,000 healthy Qataris and 600 families with rare disorders, Sidra has developed and published the first allelic map for any population in the Arab world. They are using WuXi NextCODE’s database and tools to drive forward with novel discoveries in a range of diseases, including congenital diarrhea and collagen disorders.

With the opening of Sidra’s hospital this year, and the integration of yet more data from the Qatar Genome Programme into our platform, Khalid emphasized that Qatar is well positioned to undertake not only a cutting-edge rare disease diagnostic testing program for pediatric patients but also drug target discovery. Much as deCODE has done with cardiovascular disease and numerous other conditions, the hope is to begin to analyze data for families and across the population in conditions such as type 2 diabetes. Such findings might well point to novel pathways that can be used to design treatments for those suffering from rare and common diseases alike.

I’ll also post soon about our second rare-disease focused breakfast session at ASHG: “Using NGS to diagnose rare disease—experiences from three continents.” Look for my next post about ASHG17.

WuXi NextCODE at ASHG17: Part I of our “Genomes for Breakfast” Series Highlights Leading Global Efforts to Understand and Diagnose Rare Disease

Kari Stefansson led the group of renowned scientists and clinicians who presented at

Hannes Smarason WuXi NextCODE ASHG2017

Kari Stefansson led the first of two sessions focused on rare diseases at WuXi NextCODE’s annual “Genomes for Breakfast” series at the ASHG 2017 meeting in Orlando, Florida.

WuXi NextCODE’s annual “Genomes for Breakfast” sessions at the ASHG meeting in Orlando, Florida last week. Two of these sessions focused specifically on rare diseases, one from a population perspective and the other from a clinical perspective.

We were honored to host all our speakers, each of whom are leaders in their fields. They included some of our distinguished longstanding and newer partners as well as some of our own WuXi NextCODE colleagues. We had near-capacity crowds of some 300 attendees for each of the breakfasts. That setting provided an inspirational showcase of progress in understanding rare disease and also how WuXi NextCODE’s global platform can help accelerate this critical work.

The goal for us all is to enable rapid and affordable diagnosis of rare diseases in as many countries as possible. And WuXi NextCODE is uniquely positioned to support this endeavor.

As only he can do, Kari kicked the population session off with a deep dive into what he has gleaned from looking at the unique genetics resources he has amassed at deCODE genetics in Iceland over the past 20 years. These resources are of astonishing scale, including the directly sequenced whole genomes of nearly 50,000 Icelanders and 10,000 others; imputed whole genome from 400,000 Icelanders; and SNP data from nearly a million people around the world.

It was an even more notable event, because this year, Kari received the William Allen Award, the ASHG’s highest honor; so the full breadth of the work he and his deCODE colleagues have achieved was featured at several points in our events and elsewhere during the three-day meeting. Underscoring the reach and global outlook of deCODE’s work, Kari pointed out that deCODE is currently collaborating with over 250 international groups and 25 consortia. And his talk was particularly significant for us, because deCODE is not only the world’s first and largest population genomics effort, it is also the crucible in which our technology was forged and the inspiration for the large-scale genomics efforts that we partner with around the world.

Leading off the first breakfast session, entitled “Using Population Genomics to Understand Common and Rare Diseases,” Kari spoke to how deCODE has set out to capture and correlate not just variation in the genome and phenome, but also how genetic diversity itself is actually generated. He pointed out that you could look at life forms as entities whose function is to protect DNA, rather than the other way around. Understanding how DNA changes through generations is a mission-critical task for applying genomics to human health. Where are the sites of the most recombination? Under what circumstances and where are you most likely to see de novo mutations arise?

A pivotal 2002 paper from deCODE provided the world with the first high-resolution recombination map of the entire genome. That map was used to complete the assembly of the Human Genome Project (HGP): Before that paper was published, the HGP’s assembly was about 91% accurate. After the data from deCODE were incorporated, the map reached 99% accuracy.

One of Kari’s observations was that all physiological function is spread across populations in an essentially normal distribution. Looking at extremes—the rare phenotypes—is important, because they often reflect rare genetic factors that can reveal important information about biochemical pathways relevant not only to those carrying the mutations, but also to the rest of the population that has more common, but less extreme, perturbations in those pathways. In this sense, rare variant identification is important for public health in two ways: to diagnose and better treat those with rare disorders, and to find drug targets that can benefit all of us. Rare disease, it turns out, is a common challenge that we all need to meet together.

Kari was followed by two other outstanding speakers and WuXi NextCODE partners: University of Pittsburgh Medical Center’s Annerose Berndt and Khalid Fakhro of the Sidra Medical and Research Center in Qatar. I will provide details about their talks in my next post.