NTRK Fusion Testing for new therapies: Detecting & managing rare pediatric & adult cancers

Neurotrophic tyrosine receptor kinases (NTRK) can become abnormally fused to other genes resulting in growth signals that can lead to cancer in many organs of the human body. TRK gene fusion-based cancers are rare but present in pediatric and adult cancers such as lung, thyroid, colon, etc. (see, e.g., Figure 1). Anti-tumor drugs that target NTRK fusions have been shown to be largely effective across many tumor types regardless of patient age (adult or pediatric).

Figure 1: Estimated frequency of NTRK gene fusion in specific tumor types.[1]

New selective and targeted tyrosine kinase receptor inhibitor of the tropomyosin receptor kinases TrkA, TrkB, and TrkC are either in developmental stage (Entrectinib)[2] or recently approved Vitrakvi® (Larotrectinib)[3] for treatment of locally advanced or metastatic solid tumors with NTRK fusions without a known resistance mutation.[4] However, there is a dearth of NTRK fusion genes in many traditional solid tumor-based NGS targeted assays, which makes identifying patients that will benefit from these drugs by NGS testing a challenge. It also means that patient samples harboring NTRK fusions are extremely rare, thus hampering IVD development and compromising analytical validation according to CAP and CLIA guidelines.

NGS IVD vendors such as Illumina, Thermo Fisher, Archer, and others are expanding their NGS assays to incorporate RNA fusion analysis for NTRK genes. These new NGS assays will require analytical and clinical validation to support patient testing and eligibility for these anti-tropomyosin TKIs.  The use of highly multiplexed, patient-like reference samples containing NTRK fusion genes will be critical in the development, validation and clinical testing by NGS assays of solid tissue biopsies (FFPE) of metastatic solid tumor patients potentially harboring NTRK gene fusions in clinical trial stratification and targeted therapeutic treatments. The availability of designed NTRK quality control materials will immediately help overcome the lack of NTRK patient samples.

Today, the key need is designing and manufacturing solid tumor FFPE RNA NTRK fusion reference standards under ISO 13485 (cGMP) to support clinical testing laboratories looking to bring on board NTRK fusion testing assays as companion diagnostic or complementary tests for these classes of anti-tropomyosin TKIs.

SeraCare, in partnership with Bayer, has recently developed a panel of 15 RNA-based NTRK fusion genes in an FFPE format.[5] This reference standard contains NTRK1, NTRK2, and NTRK3 fusion genes with known actionable fusion partners in the TRK pathway.

Figure 2: List of NTRK fusions in the newly released Seraseq® FFPE NTRK RNA Fusion reference standard.5

In conclusion, anti-tropomyosin tyrosine kinase receptor drugs targeting NTRK genes have moved expeditiously from developmental stage all the way to the market. This has opened up new opportunities for cancer patients harboring these fusions to have access to therapeutic drugs that may ultimately address their diseases. To facilitate this, labs require highly-multiplexed FFPE NTRK RNA fusion reference standards for end-to-end evaluation of NGS assays from development to validation, and routine QC runs of patient samples. These reference standards provide readily available materials for rapid assay development and provide confidence to regulators and clinicians that an assay can detect the fusions pairs it claims to detect.

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Genomic selection: methods in crop and animal breeding

Genomic selection NGS blog 2 photoGenomic selection: 6 factors to consider when choosing between targeted GBS and microarrays

Genomic selection through genotyping is more accurate than conventional breeding methods and promises to revolutionise crop and animal breeding. Gel-based technologies such as restriction fragment length polymorphism (RFLP) analysis and Sanger sequencing were used during the development of this field, followed by microarrays and PCR-based genotyping.

Next generation sequencing (NGS) is now powering the development of more targeted genotyping by sequencing (tGBS) methods, including capture-based enrichment followed by analysis using NGS. The question is, which genotyping solution is right for the challenges you face? Let’s compare the main contenders, arrays and targeted genotyping by sequencing (tGBS), by looking at some key factors that will affect the efficiency of your breeding program.

Can you implement the flexible and scalable marker strategy you need?

The number of markers you need to screen for genomic selection depends on the species and the stage in your breeding cycle. Single nucleotide polymorphism (SNP) discovery involves 10,000–100,000 markers on perhaps as little as 5 samples, whereas the sweet spot for genomic selection is around 1,000–25,000 assays run on approximately 1,000 samples (see Figure 1). Being able to apply different levels of multiplexing using the same technology adds efficiency and consistency to your breeding program.

NGS Blog 2 Figure 1 updated

Figure 1. A typical breeding program involves moving from high coverage of a few samples in SNP discovery to medium multiplex levels for genomic selection.

Certainly arrays of different densities can deliver high and medium capacity SNP analysis, but this technology is very rigid, making it difficult to adapt marker density and composition based on the stage in your breeding program. There are, on the other hand, tGBS methods that can be used to screen up to 100,000 markers per sample but also function efficiently in that mid-plex sweet spot of 500 to 25,000 markers. This gives you the flexibility you need for genomic selection, even when you are working with multiple populations that have different genetic backgrounds.

 

Certainly arrays of different densities can deliver high and medium capacity SNP analysis, but this technology is very rigid, making it difficult to adapt marker density and composition based on the stage in your breeding program. There are, on the other hand, tGBS methods that can be used to screen up to 100,000 markers per sample but also function efficiently in that mid-plex sweet spot of 500 to 25,000 markers. This gives you the flexibility you need for genomic selection, even when you are working with multiple populations that have different genetic backgrounds.

Can you be cost-effective?

The effective application of genomic selection means screening a large number of samples quickly and efficiently, which can reduce breeding cycles by years. This speeds up time to market for new varieties, giving you that competitive edge. To achieve this requires the right technology and also cost efficiency. Array technology is lagging behind in terms of flexibility, and the high setup cost can also be daunting. On the other hand, data output and efficiency of NGS platforms is continually being improved, dramatically reducing the cost of NGS (Figure 2). Already today we can multiplex thousands of samples for tGBS on a single flow cell of even a medium throughput NGS system.

So basing sample selection on NGS analysis will inevitably drive up throughput while reducing costs. Added to that, highly efficient enrichment methods can reduce day-to-day operation costs even further.

 

NGS Blog 2 Figure 2

Figure 2. The cost of NGS is falling rapidly. Source: nature.com

Can you stay on target?

 

Using NGS for whole genome sequencing will deliver a relatively low cost per data point, but there are strong arguments for ensuring that analysis is limited to the specific genomic regions relevant to your study. For example, in most crop genomes, the exome corresponds to only 1–2% of the entire genome. Specifically targeting the regions of interest through capture and sequencing significantly reduces the cost of sequencing and data analysis (see 1).

Can you make the most of imputation?

One way to reduce genotyping cost is imputation, which is the statistical inference of unobserved alleles by using known haplotypes based on database information progenitors and sequenced parental lines. Imputation is cheaper in breeding programs because the numbers of markers that are used for screening are reduced. Therefore, accurate and informative imputation can make breeding strategies much more cost effective, but this can only be achieved with high-quality data from previously screened populations.

Imputation can be performed both from arrays and sequencing data. The trick is to select an optimized subset of existing markers. In the case of arrays, these design rounds can be very time consuming and prohibitively expensive. Added to that, it may be impossible to replace these markers since they are fixed on an array that may be the result of collaboration between many groups. In contrast, the lower setup costs and flexibility of tGBS make this approach much more attractive when developing imputation panels. With tGBS, any non-informative markers can be quickly and easily exchanged for others that may be more informative in further rounds of screening and imputation.

Does the technology fit into your breeding cycle?

The setup time for an array based on a new set of markers can be considerable, up to six months. In contrast, tGBS approaches can enable a turnaround time of less than 2 weeks, plus 4–6 weeks for the design of a new oligo library, which means you can fit it into a plant breeding cycle and improve selection of the accessions to be transplanted to the field and progressed. The result can be years of savings in development time.

Can you discover de novo variants?

Arrays discriminate targeted SNPs and are, by definition, fixed. Sequencing-based methods such as tGBS on the other hand enable the discovery of new SNPs and structural variants in flanking sequences of targeted SNPs. This increases the amount of genetic information you have at your fingertips, increasing the power of genomic selection. For example, in a study of 500 markers using sequences previously tested on an array, only 491 SNP sequences were originally selected to be common between the tGBS library and array data whereas tGBS discovered 5,733 de novo SNPs (2).

How to find the sweet spot with tGBS

As we have seen, exploiting genomic selection will help you produce new varieties faster. But it means finding a sequence-based genotyping solution that can meet your needs in terms of flexibility and cost-efficiency, while enabling you to carry out de novo SNP discovery, imputation, and much more. We will look at one way of achieving this in the last article in this series.

Want to learn more? Download the white paper: SeqSNP tGBS as alternative for array genotyping in routine breeding programs.

About the author: Darshna ‘Dusty’ Vyas

Dusty has been with LGC for the last 6 years working as a plant genetics specialist.

Her career began at the James Hutton Institute, formerly the Scottish Crop Research Institute, developing molecular markers for disease resistance in raspberries. From there Dusty moved on to Biogemma UK Ltd for a period of 13 years, where she worked primarily with cereal crops such as wheat, maize and barley. Through her participation in the Artemisia Project, funded by the Bill and Melinda Gates Foundation, at York University, she gained a vast understanding of the requirements by breeders for varietal development using molecular markers in MAS.

Dusty’s goal is to further breeding programs for global agricultural sustainability using high throughput methods such as SeqSNP.

References

  1. Efficient genome-wide genotyping strategies and data integration in crop plants. Torkamaneh D et al. Theor Appl Genet. Mar;131(3):499–511 (2018)
  2. White paper: SeqSNP tGBS as alternative for array genotyping in routine breeding programs.

 

This blog post was originally published on the LGC, Biosearch Technologies blog.

Our hungry planet: new tools in agrigenomics are key to food security

Our hungry planet NGS blog 1 photoFood security is a major global threat and traditional methods of plant and animal breeding will not be sufficient to increase production to the level needed to sustain the growing world population. Modern genomics-driven breeding, through analysis based on technologies such as next generation sequencing (NGS) and arrays, is revolutionizing agriculture and making genomic selection a viable approach throughout the industry. In this three series blog post find out how technology is changing global food security and what the newest tools bring to the table.

The power of genomic selection

Perhaps the biggest revolution in agriculture in the last decade is the emergence of agrigenomics to enhance traditional breeding programs. Molecular techniques, such as marker assisted selection and genomic selection, have enabled selection of improved varieties without having to rely on assessing visible characteristics. Genomic selection, in particular, addresses the key factors of the breeder’s equation (2) that increase the rate of genetic gain in plant and animal breeding:

  • Reduced breeding cycles – individuals can be progressed faster when selection is based on genotype rather than phenotype alone
  • Greater selection intensity – selecting individuals based on genotype is cheaper than selecting on phenotype, so more individuals can be evaluated (increasing ‘n’)
  • Improved accuracy – the genomic estimated breeding value (GEBV) enables prediction models to select with greater accuracy based on phenotype and previous pedigree historical data and enables prediction models to be applied with greater accuracy.
  • More efficient integration of new genetic material through the development of training population, where intensive phenotyping and genotyping can be assessed

Genomic selection has been instrumental in dairy cattle breeding where it has essentially replaced progeny testing, enabling greater and faster improvements in terms of genetic gain (see, for example, reference 3). Genomic selection has, however, had a relatively slow uptake in plant breeding. Reasons include its relative complexity compared to traditional methods, the need for expensive investments, complexity of plant genomes and ability to analyse big data using bioinformatics. The divergence of plant and animal breeding has also hindered the translation of methods between these two fields, but this problem is being addressed and hopefully both animal and plant breeding of the future will gain from common insights into genomic selection (1).

Technological development powers the agrigenomics breakthrough

Genomic selection has been made more practical by a range of methods, including next generation sequencing (NGS) and microarrays for genotyping and single nucleotide polymorphism (SNP) analysis. Massive developments in NGS technology in particular have realized the potential of genotyping by sequencing, (or GBS), and promises to revolutionize the drive to develop varieties of plant crops with, for example, desirable traits such as drought tolerance, disease resistance, and higher yield.

Despite all these advances, there are still gaps to fill in the toolbox of technologies, and finding the optimal solution for genomic selection can be a demanding process. We will be looking into these issues in the next article in this series.

Make sure you don’t miss the rest of this series by subscribing to our blog!

About the author: Darshna ‘Dusty’ Vyas

Dusty has been with LGC for the last 6 years working as a plant genetics specialist.

Her career began at the James Hutton Institute, formerly the Scottish Crop Research Institute, developing molecular markers for disease resistance in raspberries. From there Dusty moved on to Biogemma UK Ltd for a period of 13 years, where she worked primarily with cereal crops such as wheat, maize and barley. Through her participation in the Artemisia Project, funded by the Bill and Melinda Gates Foundation, at York University, she gained a vast understanding of the requirements by breeders for varietal development using molecular markers in MAS.

Dusty’s goal is to further breeding programs for global agricultural sustainability using high throughput methods such as SeqSNP.

References

  1. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery. J M Hickey, T Chiurugwi, I Mackay, W Powell & Implementing Genomic Selection in CGIAR Breeding Programs Workshop Participants. Nature Genetics volume 49, pages 1297–1303 (2017)
  2. Animal breeding plans 2nd J L Lush. The Iowa State College Press (1943)
  3. Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit. J R Thomasen et al, J. Dairy Sci. 97:458–470. http://dx.doi.org/10.3168/jds.2013-6599 (2014).

 

This blog originally appeared on the LGC, Biosearch Technologies blog.

How genotyping is aiding in the fight against malaria

mosquitoe-1548975_19203.2 billion people across 106 countries and territories, live in areas at risk of malaria transmission. The serious and sometime fatal mosquito-borne disease is caused by the Plasmodium parasite – in 2015, malaria caused 212 million clinical episodes, and 429,000 deaths.

Malaria has been a public health problem in Brazil ever since it was brought to the region during its colonization. By the 1940s it is estimated that six to eight million infections and 80,000 malaria-related deaths occurred every year in the country.

Due to a concerted series of malaria control policies, Brazil has recorded a 76.8% decrease in malaria incidence between 2000 and 2014 – and effort which the country was praised by the WHO.  In 2014, there were 143,910 of microscopically confirmed cases of malaria and 41 malaria-related deaths.

Part of Brazil’s malaria control policy involves the use of primaquine – a medication first made in 1946, to treat and prevent malaria. It is particularly effective against the Plasmodium vivax parasite that is prevalent in the Brazil.

Unfortunately primaquine can induce haemolytic anaemia in glucose-6-phosphate dehydrogenase (G6PD)-deficient individuals and may lead to severe and fatal complications. 330 million people worldwide are affected with G6PD deficiency, with recent studies suggesting the prevalence of the deficiency could be as high as 10% in Brazil.

Recently, molecular biologists from LGC enabled a cutting edge study in collaboration with researchers from Brazil and the London School of Hygiene and Tropical Medicine.

The researchers looked for mutations in a sample of 516 male volunteers that could be used as clinical indicators for G6PD deficiency that could lead to complications in people prescribed with primaquine.

Blood samples were collected from around Brazil at hospitals during surgeries, as well as using the local Brazilian radio stations to ask people to come and submit blood.

Needing a fast and efficient way to generate results in high throughput, the team turned to LGC’s integrated genomics toolkit to facillitate the research. Each sample was screened against 24 KASP assays to assess the genetic bases of G6PD deficiency. In combination with the IntelliQube®,a fully automated point and click PCR system;  the team collected the data in roughly three hours of instrument time and one hour hands on time.

KASP is a flexible, highly specific genotyping technology, which can be used to determine SNPs and InDels.  KASP uses unlabelled oligonucleotide primers, which gives the technology a cost advantage and allows more data to be generated, increasing data quality.

The data indicates that approximately one in 23 males from the Alto do Juruá could be G6PD deficient and at risk of haemolytic anaemia if treated with primaquine. The authors conclude that routine G6PDd screening to personalize primaquine administration should be considered – particularly as complete treatment of patients with vivax malaria using chloroquine and primaquine, is crucial for malaria elimination.

The teams are continuing their collaboration to help further research in to treatments for malaria, and we can’t wait to see more!

To access the paper, please click here, or to see the IntelliQube in action and learn more about this automated PCR instrument click here.

 

 

Sources:

Malaria. (2017, July 13). Retrieved August 8, 2017, from https://www.cdc.gov/malaria/about/index.html

Maia, U. M., Batista, D. C., Pereira, W. O., & Fernandes, Thales Allyrio Araújo de Medeiros. (n.d.). Prevalence of glucose-6-phosphate dehydrogenase deficiency in blood donors of Mossoró, Rio Grande do Norte. Retrieved August 8, 2017, from http://www.scielo.br/scielo.php?pid=S1516-84842010000500017&script=sci_arttext&tlng=en

 

This blog post was originally published on the Biosearch Technologies blog.

Accelerating rice improvement in South Asia

WP_20180515_009Diversity is the spice of life and is also key to breeding rice that delivers increased yields. Rice is a crucial staple food for about half a billion people in Asia, but it suffers from diseases that reduce yields, destroy harvests and put food security and livelihoods at risk. But there is hope – by tracking DNA markers of natural genetic variants through generations of crosses, breeders can identify better combinations that enrich crop vitality and resilience leading to more reliable and sustainable rice production.

collaborative project between Bangor University and LGC with a university partner in India (SKUAST), a research institute in Pakistan (NIBGE) and, in Nepal, a government research centre (NARC) and a private seed company (Anamolbiou) is addressing this challenge and has already identified over a million new markers in rice. They can reveal linkage to genes and patterns of diversity that help rice breeders select for a wide range of resistance genes to improve many different varieties. The project continues to develop these markers into more KASP assays that will be made available in publicly searchable databases.

Modern disease-resistant varieties are not always well adapted to specific environments, so breeders aim to incorporate markers for both biotic and abiotic stress resistance as well as yield components into locally accepted varieties that may already possess value traits, such as aroma. Molecular markers such as Simple Sequence Repeats (SSRs) in rice were developed in the 1990s for marker-assisted selection (MAS) and these are still used by some rice breeders in Asia to improve selection efficiency. Smaller breeding companies do not have all the resources (i.e. trained personnel, instrumentation for extraction or genotyping) to use such markers in-house. They can benefit from a service-based approach such as LGC Genomics’ genotyping service using KASP technology that offers a lower cost per data point and is faster to implement or use in their own lab. KASP assays offer greater sensitivity, speed, and safety than the older techniques, such as SSRs, when carried out in breeders’ own labs.

WP_20180515_007The collaboration with Bangor University and partners has already developed new methods to identify suitable SNP and InDel markers that can replace existing SSRs in target breeding crosses which have been adopted by Nepalese breeders. Now, a broader survey of suitable SNPs and InDel markers, across a set of 130 publically available rice genome sequences selected for geographic diversity, is discovering novel markers that are relevant to both Indica and Japonica rice backgrounds.

Before the research team started this project there was a choice of 2055 useful KASP assays that breeders could use, depending on their breeding strategy, but this project has increased the choice to over 245,000 potential markers that should benefit a wider range of rice breeding programs. This increase in the number of KASP assays enables the project and research community to utilize KASP technology on a scale that was only available to big breeding companies before this project. It’s exciting times for rice breeding!

Bangor University and partners plan to make thousands of the rice markers from this project available in the form of a searchable database so that rice breeders can easily find the most suitable options to replace their target SSRs in existing programs or to identify the appropriate loci for a range of possible new crosses. LGC will also offer them as validated KASP assays on its website. The large database of validated KASP assays produced by this project will thus give rice breeders the ability to carry out genomic selection (GS) with many thousands of loci across their populations, enabling smaller breeders to benefit from the same genomic scale technologies that generally require significant resource investment to develop on their own. The availability of this marker set to the public sector, and the services provided by LGC Genomics, will enable rice breeders of all sizes to apply genomic tools to accelerate their MAS and GS breeding programs to develop new rice varieties that will improve food security.

To learn more about our KASP genotyping services click here.

 

This blog originally appeared on the Biosearch Technologies blog.

Revolutionising cancer treatment one Array at a time

While the science of pharmacogenomics has been around for years, its popularity is starting to pick up steam as precision medicine and how we treat individual patients becomes more and more common place in the medical world. Geneticists and doctors are fully embracing the fact that our individual genes make us all unique and that these genes hold clues to how each patient’s body will metabolise medications.

Pharmacogenetics, or the study of how people respond differently to medicines due to their genetics, is making a splash lately thanks to companies like Minneapolis, MN-based OneOme, which co-developed its RightMed test with Mayo Clinic. The company collects a patient’s DNA sample using a simple cheek swab that is then analysed at OneOme’s lab with PCR – in this case on LGC’s IntelliQube® – to determine the patient’s genetics.  This information is then used to determine whether the patient has any genetic variations that may cause them to have a certain reaction to a medication. These results give doctors “graphic genetic pinpoint accuracy” on the medications that should work and those likely to be less effective. In simplest terms, these tests, combined with PCR instruments are empowering patients and doctors with information that may not only make their lives better, but also safer. Or as we like to say, science for a safer world.

Take a look at just how much pharmacogenomics is impacting and “revolutionizing” patient care by watching the video here, or visit our website.

 

This story was originally published on the Biosearch Technologies blog.