As the cost of an individual genome becomes more attainable, laboratories in North America and Europe are experimenting with offering clinical exome and genome sequencing for oncology.
In the second installment of our Advancing Clinical NGS series, Dr. Sheryl Elkin, Chief Scientific Officer at QIAGEN Digital Insights, discusses the clinical utility, cost-effectiveness, and patient impact of implementing genome sequencing as a routine part of precision oncology care
The first human genome, sequenced through the Human Genome Project, took 13 years and cost 3 billion dollars, and its completion was announced in 2003 (1). This version of the human genome was not even complete: a draft version of the human genome was published in 2000, and the genome was filled in to 92% “completion” in April 2003. The true completion of the genome, from “telomere to telomere” was not achieved until nearly twenty years later, in 2022.
The sequencing of the human genome represents an enormous step in the understanding of human biology, both in terms of normal function and disease. However, at the time that the human genome project concluded, the idea that individuals could have their genomes sequenced for routine diagnostics, in a therapeutic timeframe, was nearly inconceivable.
In 2007, the cost to sequence a single human genome was still hovering around $10,000,000, with the cost decreasing on a slope comparable to Moore’s law. However, the commercial transition from Sanger (dideoxy chain termination) DNA sequencing to next generation sequencing (NGS) technology led to a substantial reduction in the cost of DNA sequencing, and by 2015, the first “$1000 genome” was achieved. In effect, though, the true and complete cost of genome sequencing was not reflected in the $1000, which does not include any of the costs of downstream analysis. The amount of data generated by the sequencing of a genome created enormous and costly analytic challenges.
"The value of the genome sequencing in oncology depends on the ability to translate generated data into clinical applicability."
Sheryl Elkin, Ph.D.CSO, QIAGEN Digital Insights
Currently, genome sequencing as a diagnotistic tool in oncology is out of reach for the vast majority of patients. Yet, as the economics of genome sequencing continues to evolve, the technology further develops, for both the sequencing chemistry and the data analytics required to make sense of the information. As a result, laboratories in North America and Europe are starting to experiment with offering clinical exome and genome sequencing for oncology.
In a new white paper, Dr. Sheryl Elkin, CSO of QIAGEN Digital Insights, examines the opportunities and challenges of implementing exome and genome sequencing for oncology. Click the button below to read the full paper.
It’s exciting that advancements in high-throughput sequencing techniques and analysis enable us to generate whole genome (WGS) and whole exome (WES) data in bulk for many species, including humans. With new machines and chemistries, the cost of sequencing has decreased significantly. However, the total cost of ownership associated with bioinformatic analysis of the resulting files remains a bottleneck (1).
Whether you run a genome center, testing facility, core lab or provide sequencing services, you’ve got to deliver variant call files (VCFs) at an unbeatable price and with consistent quality and turnaround time, even at peak demand. Your customers, as well as your business, depend on it. Many high-speed NGS analysis solutions require purchasing expensive, highly specialized hardware, massive computers or large cloud computing contracts. The requirement for fast and consistent turnaround times, also at peak demand, can quickly translate into a need for more personnel, more processing power—and more investment. How do you keep costs down yet deliver quality results with quick turnaround in a world of shrinking budgets?
More investment in your bioinformatics infrastructure? Nope—now you don’t have to
What if there were a scalable, point-and-click solution that could handle all your WGS, WES and large panel data analysis needs without having to purchase vast amounts of specialized infrastructure? A software that could run with a GUI and be used by anyone with minimal training? What if you didn’t have to compromise between speed and quality?
Introducing a better, faster, cheaper and more flexible tool for WGS and WES analyses
Our all-in-one NGS bioinformatics software QIAGEN CLC Genomics Workbench Premium now offers you a faster, more accurate, more flexible and more affordable way to process WGS and WES files in bulk. This is made possible via QIAGEN CLC LightSpeed Module, which enables an ultra-fast and accurate FASTQ to VCF pipeline for hereditary germline mutation analysis.
What’s more, you’ll enjoy full flexibility. Our QIAGEN CLC Genomics Workbench Premium can process data from any sample, any panel and any species and run your analyses on a laptop, desktop, server or the cloud without depending on any new or specialized hardware.
Reduce cost with speed: Accelerate WGS secondary analysis down to just 25 mins
For certain licenses, you only pay an annual fee for software access, allowing you to run (and re-run) as many samples as you need. And because of our ultra-fast FASTQ to VCF pipeline, you can get more analyses done in less time. This translates into lower analysis costs, both for on-premise and cloud deployment.
In our recent benchmark study, we showed that using our ultra-fast QIAGEN CLC LightSpeed technology our FASTQ to VCF hereditary workflow analyzes 34x human WGS samples in just 25 minutes, whereas a QIAseq Exome v3 50x sample takes just 90 seconds. When run in Amazon Web Services (AWS), the incurred computing costs were about $1 per WGS and a few cents per WES. There is no other technology that can process WGS or WES this fast—or as cost-efficient.
With demonstrated high accuracy and reproducibility, and built on a scalable bioinformatics analysis platform, QIAGEN CLC LightSpeed technology will revolutionize your ability to perform high-volume whole genome sequencing.
A software that’s ‘cheaper than free’
QIAGEN CLC Genomics Workbench Premium is an NGS analysis software your core lab can’t do without. It enables you to deliver ultra-fast sequencing analysis results while controlling your costs. It does this by saving your lab time, processing capacity and energy, so you can provide affordable services. You’ll also enjoy a variety of specialized tools for all your sequencing needs. The CLC platform software QIAGEN CLC Genomics Server and QIAGEN CLC Genomics Cloud Module help you to build the scalable bioinformatics analysis architecture you need to offer a high-throughput genomics analysis service at affordable prices. In addition, our QIAGEN CLC Genomics platform is fully supported with tutorials and documentation, an excellent team of customer support professionals and dedicated trainers to ensure you have the support you need to perform your analyses. These advantages result in reduced total cost of ownership and are far cheaper than maintaining your current setup. Therefore transitioning to QIAGEN CLC Genomics Workbench Premium is a switch you’ll quickly discover is ‘cheaper than free’.
Get in touch
Learn more about the newest features of QIAGEN CLC in our latest release, check out our upcoming webinar and request a consultation from one of our experts. Ready to try it out for yourself? Request a trial of QIAGEN CLC Genomics Workbench Premium to see how this software will make it faster, easier and cheaper for you to analyze your NGS data.
Share your CLC LightSpeed results and win
Got killer runtime results using QIAGEN CLC LightSpeed? Share them with us on social media using #CLCLightSpeed. When you do, you'll enter for a chance to win one of three one-year licenses to QIAGEN CLC Genomics Workbench Premium. You may alternatively enter for a chance to win by submitting the online entry form available here. Terms and conditions apply.
References
But the upshot of the study was sobering for those who believe that genome sequencing is speeding to the clinic: there were far more disease-causing mutations discovered than people who actually had any disease. Of the 11 people who got reports saying their genomes harbored variants that should cause disease, only two of them actually had the disease. These conditions are not ones expected to have unusually late onset.
From our perspective, these results are not an indication that genomics has little to contribute to healthcare; instead, they are a stark reminder that efforts to accurately interpret the genome still have a long way to go. Programs like the Allele Frequency Community should help with this, but what we need most of all are more genome sequences and really strong phenotype/clinical data associated with them so that we can hone interpretation algorithms.
For the nine people who were expected to have a disease based on their genomic data but didn’t, it is likely that we will eventually discover protective mechanisms that offset the mutation, or perhaps environmental or dietary factors that explain the disconnect. For now, though, we are still at the earliest stages of truly understanding the human genome, and that’s the main message of the MedSeq results.
At QIAGEN Bioinformatics, we’re working hard to make sure that our genome analysis and interpretation tools incorporate the newest discoveries, rely on high-confidence findings, and help scientists see the big picture of how various mutations, pathways, and other factors fit together. We applaud the MedSeq team for drawing attention to this important topic.
It is not surprising to find mutations that are disease causing in healthy people because almost none of the known disease-causing mutations are 100% penetrant, or predictive of developing the resulting disease in all cases. If you get the disease depends on genomic context – some diseases are late onset and depend on your age, while others can manifest in a spectrum of how strong the effect is, and the effect may be below the threshold of calling it out as a disease.
That's why our software solutions allow for phenotype supported ranking: the ability to combine observed phenotypes of the patients with the genomic data for better interpretation results. Because of the insights we have in our QIAGEN Knowledge Base about mutations, genes, diseases, phenotypes and their relationships, we are able to prioritize mutations that are related to the individual phenotype, and we can show that this increases the rate of resolving causative mutations.
