Enabling the fight against cancer
Cancer is one of the most devastating diseases in the world. In order to help clinical researchers understand it better and advance the development of new personalized treatments, QIAGEN introduced the GeneReader NGS System at the end of 2015 – the first true sample to insight workflow for next-generation sequencing that allows identification of clinically relevant cancer mutations. Shortly thereafter, the first system was installed at the research group of Prof. Kurt Zatloukal at the Austrian Competence Center for Biomarker Research in Medicine CBmed. His cooperation with QIAGEN helps to further advance the new system, fighting a scourge of humanity.
Dr. Kurt Zatloukal, professor at the Institute of Pathology at the Medical University Graz, sits slightly bent on a swivel chair looking at a row of slides on a desk in front of him. Using his glasses, he points at a small spot of lilac-colored tissue on one of the slides: “Here in the lymph node. At the edge, you can see metastases," he says. "If, as in this case, we have some time to determine the tissue more precisely, we can test the tumor cells for specific gene markers. The markers allow the physician to provide a more accurate diagnosis, and help him to understand the tumor better and make his choice of therapy."
Through the large windows, early autumn light flows into the four-meter-high rooms of the Institute of Pathology, which was built in 1911 together with other large buildings for the then new State Hospital Graz. Outside, on the facade, the Austrian monarchy’s double-headed eagle is still prominently on display to this day. Inside, on the workstations next to Zatloukal, there are plastic boxes with tissue samples, coded with yellow, white, green and purple tags and long numbers. They are samples from the liver, lung, colon and other organs – document to painful stories of sickness as well as testament to the hope of a cure.
The samples – per year no less than 100,000 – are sent to the Institute of Pathology by physicians after surgeries and biopsies to get answers, which may help to discover, e.g., how far a malignant tumor has grown or whether it has metastasized. Most of the samples are embedded in paraffin blocks, which are cut into fine slices and placed on glass slides such as the ones right under Prof. Zatloukal’s eyes. They can be structurally analyzed in detail under the microscope, stained with dyes to reveal their cellular pathology and used for genetic analysis.
Fourteen million people are newly diagnosed with cancer every year, accounting for more than eight million annual deaths.
Seamless workflow from sample to insight
In the past, traditional cancer genetics focused on single mutations in tumors. But thanks to various methods described as next-generation sequencing (NGS) that allow the massive parallel analysis of genetic material, today researchers can use gene panels testing multiple markers at once. This not only allows them to generate more genetic information, but also explore the molecular nature of a tumor more quickly and affordably. What they mostly aim for are gene markers that allow them to understand the cancer better as well as which treatments have been associated with a specific marker. What has been missing until recently is a solution that integrates all the important steps from sample preparation to insight generation in one seamless workflow: QIAGEN’s GeneReader NGS System.
Starting in spring 2016, based on the long-term research collaboration of QIAGEN with Christian-Doppler-Laboratory at the Medical University of Graz, the very first QIAGEN NGS system was installed at the recently established Competence Center for Biomarker Research in Medicine CBmed. The Christian-Doppler lab, founded in 2011 and headed by Prof. Dr. Kurt Zatloukal, focuses on testing new technologies for processing biological samples. Since its beginnings, QIAGEN has been the lab’s corporate partner, an example of the widespread practice of the company to cooperate with scientists and universities on developing novel technologies and applications. As it happens though, Prof. Zatloukal also founded one of Europe’s largest biobanks at the Medical University of Graz, providing access to the tissues needed for testing new technologies. Additionally, he works closely with CBmed Graz, an Austrian competence center developing customized solutions for biomarker research. “All that was reason enough for us to offer the GeneReader first to his team,“ says Yi Kong, Director Oncology Franchise at QIAGEN. "This way, we were able to get detailed feedback to optimize details of the workflow, such as the interface displaying the results of gene analysis.“
Prof. Zatloukal, after giving a tour of the venerable Institute of Pathology, walks across campus to a grey 90’s building, where a small room with windows to a hallway houses the new GeneReader system. He is standing in front of desks ordered in a U-shape, on top of which are several QIAGEN branded machines, all housed in silvery casings with dark blue semitransparent inserts. “I welcome any additional tool for understanding cancer better and fighting it, but this one especially,“ he says. “Over the last years it has become clear that with NGS, tumors can be analyzed, but the effort has been time consuming and difficult.“
He points out that to establish a good workflow one had to get machines from various vendors, which in turn had to undergo extensive testing in order to ensure that they meet quality standards – plus, they had to comply with various guidelines. “QIAGEN offers an integrated complete workflow. That saves time and money, helps to find answers more efficiently, and frees up time for researchers and lab staff to focus less on technical issues, but on fighting cancer.“
Most cancers have polygenetic mutations
Still, even with a fully integrated workflow to obtain reliable results from NGS, answers are not a given. Thanks to NGS, today a human genome can be sequenced for below $1,000 in a matter of days. But big data collection alone is just one, albeit essential step. In order to develop a custom tailored understanding of a patient’s illness the individual genetic markers have to be identified – and their biological role understood. To the degree that such knowledge exists, it is precious, considering that it is estimated that every human carries roughly three million individual genetic variants across their genome. Understanding these markers will allow for the ’personalized medicine‘ approach – tailoring any necessary combination of drugs, radiation and chemotherapy to a patient’s genetic profile.
In the case of monogenic diseases certain variants are fate. Anyone who has inherited only one defective variant of the cystic fibrosis gene remains healthy. If someone has two defective versions, inherited from both parents, they suffer from this disease. But most individual gene mutations, even if they have an effect, cannot be described in such straightforward causal terms. Instead, with respect to disease, they rather contribute to risk – of developing cancer, Alzheimer’s, or cardiovascular disease.
The same holds true in cancer. The rare case of a single genetic alteration as major cause of cancer and an accompanying treatment does exist – such as in chronic myelogenous leukemia. But by and large, most cancers are characterized by polygenetic mutations. To deal with this complexity, QIAGEN's GeneReader only uses panels looking for markers that have a known relevance for a tumor and its treatment. While some tumors with a specific variant may be resistant to certain agents, others can be particularly vulnerable to certain therapies, and mean that targeting a therapy specifically to a cancer and prolonging the patient’s life is possible. Currently, drugs are targeting around 50 genomic variants in cancers.
One such example is the EGFR (Epidermal Growth Factor Receptor) gene, which can harbor mutations that confer either sensitivity or resistance to a targeted therapy. “Knowing the genetic makeup of a cancer, and particularly actionable mutations, is a great benefit,“ says Prof. Zatloukal. “It can lead to a more substantive diagnosis and inform the decision which therapy to choose. But there are still many hurdles we need to overcome. This is what we work on in the Christian-Doppler-lab. For example: How do we sample and process a tumor properly in order to get an accurate information on the cancer, given that tumors happen to be very heterogeneous? This is the kind of research we pursue.“
"Most tumors are heterogeneous. They probably have different variants active either in different parts or they change throughout its evolution – or both. It is a moving target which won’t be easily shot down, certainly not by a single bullet."
Prof. Dr. Kurt Zatloukal, Chair, Institute of Pathology, Medical University Graz, Austria
Careful selection of actionable cancer mutations
Then Prof. Zatloukal turns to his team to demonstrate the GeneReader itself. It has a transparent blue flap in the middle. If one lifts it, one sees a turntable on which at any time several flow cells with multiple samples can be analyzed simultaneously or staggered. It takes around five days from obtaining a solid tumor sample to getting an interpreted result. At first, this may not sound lightning fast, but the whole workflow has now reached a capacity of 48 samples per run. That results in nearly 5,000 samples per year, even covering demands of high-throughput laboratories.
The GeneReader in Graz uses a gene assay called the ’Actionable Insights Tumor Panel,' which covers 12 targeted genes with 773 variants found in breast, ovarian, colon, lung and skin cancer – mankind’s most prevalent solid tumors. All these mutations have in common that they have been the subjects of several scientific publications, or are documented to be related to the outcome of specific therapies. They have been selected utilizing QIAGEN’s Ingenuity Knowledge Base, a unique resource for interpretation and selection of molecular content containing more than 13 million genetic findings. One example is a mutation on the ERBB2 gene, which can occur in lung, breast, ovary and bladder cancer. At the end of 2015 this variant was the topic of at least 27 scientific articles. There is one report showing that a breast cancer patient with this variant had a positive response to a targeted treatment, it appears in professional guidelines and is tied to Phase III clinical trials.
The GeneReader workflow becomes manifest in the various QIAGEN devices that can be found alongside the benchtop sequencer itself. After DNA extraction and target enrichment at the Institute of Pathology, library preparation, sequencing and interpretation including quality controls take place in this small room of CBMed. Unsurprisingly, there is also a computer screen on which the sample report is displayed with the help of QIAGEN Clinical Insight (QCI), a continually updated, cloud-based clinical decision support solution specifically designed for interpretation of NGS-based cancer test results.
"What I particularly like is that no bioinformatics specialist is needed to interpret the results."
Dr. Lisa Oberauner-Wappis, Medical University Graz, Austria
Traffic lights guide lab work
The molecular microbiologist Dr. Lisa Oberauner-Wappis, who runs the QIAGEN setup for the laboratory, is also quite taken by the system: "What I particularly like is that no bioinformatics specialist is needed to interpret the results," she says. In fact, the detected variants are marked in the color of traffic lights, indicating their relevance in a given disease context: red, orange or green. "Naturally, you first take a look at the 'red' marked results," she says. The user-friendly design, of course, is one of the goals of the GeneReader NGS System: “At QIAGEN we asked ourselves, ‘How do you address a pressing need in the clinical environment with a plug and play solution that can be adopted by any laboratory?,“ says Kong. “With an easy to use workflow, and easy to read results. For a wide spectrum of researchers the complete sample to insight solution will certainly be a game-changer.“
The system also offers other advantages yet: The DNA of paraffin embedded samples is often damaged. The sample preparation component of the QIAGEN System largely corrects this damage. Also, errors are often generated during the sample amplification steps. Once this process is completed, it is impossible to distinguish a unique DNA variant from a library construction error. The QIAGEN system can be used to detect low-frequency variants with high confidence by barcoding DNA molecules before any amplification takes place – a proprietary technology known as digital sequencing – to distinguish unique DNA variants from PCR errors.
Additionally, researchers and labs benefit from the single vendor model, says Kong: “Not only are they buying an integrated system that has been designed for fast and reliable output: if there is a problem, they can always pick up the phone and call support at QIAGEN.” In addition, commercial models such as price-per-insight options offer better cost management and low initial investment hurdles in the context of fixed-cost restraints. The success so far appears to underline the system’s attractiveness. By the end of 2016, the GeneReader NGS System had taken more than a 10% share of the estimated global annual market for new placements of bench-top sequencer used for oncology.
Continuous improvement of the GeneReader workflow
Still, as good as the system already is, QIAGEN is continuously working on further targeted enhancements and updates to increase its value for laboratories. Six months after launch, a GeneReader workflow was developed that can support analysis of liquid biopsy samples. For Prof. Zatloukal this is relevant as it allows a whole new approach to understanding the biological mechanisms of cancer: It has the potential to find traces of tumor cells or genomic molecules before a cancer shows any symptoms or shows up with imaging technology. It can also be used to develop methods for monitoring treatments and the progress of the disease, and help evaluate the genetic alterations in cancer metastases, which otherwise are not accessible in the body for molecular testing. In 2017, at least five new gene panels are being added to the GeneReader, including two for lung cancer, a panel for breast and ovarian cancer and one focusing on blood. Furthermore, customers will soon be able to opt to custom design panels according to their specific needs.
Prof. Zatloukal, now sitting comfortably next to the GeneReader and playing with his glasses in his hands, cautions that cancer is a notoriously complex disease. “Most tumors are heterogeneous. They probably have different variants active either in different parts or changing throughout its evolution – or both. It is a moving target, which won’t be easily shot down, certainly not by a single bullet. To fight it, we will most likely use panels testing more and more variants – and then attack them with a whole battery of drugs.” And to understand cancer? “We will need a systems biology approach, integrating all kinds of parameters, based on underlying principles which we don’t fully understand yet – hopefully the GeneReader can help a little with that.“
One of QIAGEN’s unique resources is its own industry leading QIAGEN Ingenuity Knowledge Base, compiled of multiple public and proprietary sources, such as drug labels, results from clinical trials, licensed external databases, professional guidelines and scientific literature. QIAGEN’s team of highly qualified Ph.D. and MD staff is dedicated to continuously conducting exhaustive curation of new primary literature and review of clinical cases to ensure the database contains the most up-to-date information. Among other applications, the knowledge base powers ‘QIAGEN Clinical Insight‘ (QCI), a cloud based bioinformatics tool to interpret and report test results generated with the Gene-Reader NGS System.
Furthermore, this knowledge base helps to design the gene panels used in combination with the GeneReader system themselves. The approach first selects tumors based on prevalence and potential health impact – such as breast, ovarian, colon, lung and skin cancer – and then turns to the knowledge base in order to look for genes and variants in these genes that are proven genetic biomarkers for these widespread tumor types, or that have evidence supporting their potential relevance to targeted therapies. The selection is conservative in so far as it only uses data from professional guidelines, drug labels and clinical trials from the knowledge base – but not e.g. scientific literature, which is not primarily connected to actionable variants. This in turn assures the relevance of the data.
The approach to conquering cancer has shifted from using chemotherapy to deploying precision-guided drugs targeted to each patient’s unique genomic characteristics. In the future, advanced gene panels and next-generation sequencing promise to deliver more victories to oncologists and their patients.
Advanced platform technologies and targeted content create valuable insights into biology and disease.