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Two clinical academic research partnerships awarded to Oxford researchers

Dr Karthik Ramasamy and Dr John Jacob are both Oxford clinical researchers that have been awarded a Clinical Academic Research Partnership (CARP) by the MRC. Both have been awarded upwards of £200,000 to fund projects investigating myeloma early detection & brain cancer modelling, respectively. Find out more about the projects being funded with this award below.

Dr Karthik Ramasamy

Earlier diagnosis of the bone marrow cancer myeloma is a high priority for patients since it can both improve survival and allow for better control of symptoms. Every case of myeloma is preceded by a condition called Monoclonal Gammopathy of Undetermined Significance (MGUS) and individuals with MGUS are regularly monitored so that progression to myeloma can be caught early.

While this approach is benefitting some patients, there are two main issues that still need to be overcome to improve earlier myeloma diagnosis:

  1. MGUS is largely symptomless and often undiagnosed, meaning that 80-90% of myeloma patients are diagnosed without first receiving an MGUS diagnosis that would have prompted monitoring for myeloma.
  2. Only 1% of patients with MGUS progress to myeloma every year and the risk of progression is not well defined, placing a large resource burden for monitoring on healthcare providers and creating anxiety for patients.

In this MRC CARP award, Dr Karthik Ramasamy will address both of these challenges. Firstly, working with Professor Kassim Javaid, Professor Daniel Prieto-Alhambra, Dr Constantinos Koshiaris and data from primary care health records, Dr Ramasamy will identify specific clinical signs/symptom clusters associated with MGUS to enable a greater proportion of individuals with MGUS to be diagnosed and monitored. Secondly, additionally collaborating with Dr Ross Sadler, Professor Chris Schofield and Professor James McCullagh, Dr Ramasamy will seek to identify routinely recorded clinical characteristics and additional protein biomarkers that improve prediction of progression from MGUS to myeloma in a cohort of patients undergoing monitoring at Oxford University Hospitals NHS Trust. This latter work is bolstered by a recently awarded CRUK Oxford Centre Development Fund award, which will enable the research team additionally to pilot protein glycosylation analysis in blood samples collected as part of a current study investigating serological markers in plasma cell dyscrasias (BLOOM).

Dr Karthik Ramasamy is Lead Clinician for myeloma and other plasma dyscrasias in Thames Valley Strategic Clinical Network and Divisional Lead of Cancer Research across Thames Valley and South Midlands Research Network.

Learn more about myeloma early detection research in Oxford.

Dr John Jacob

Brain cells that originate in the cerebellum give rise to the most common childhood brain tumour, known as medulloblastoma, which can also affect adults. Although it can be cured, it is often a devastating disease, with common treatment options resulting in an increased risk of adverse side effects such as strokes and seizures.

Like most cancers, the development of new treatment options that improve survival rate and reduce side effects is reliant on researchers establishing models that reflect the human tumours, in order to test the efficacy of new therapeutics before these are tested in patients. Existing models for medulloblastoma have shortcomings making the discovery of new treatment options slow. This is due to:

  1. Growing medulloblastoma cells outside of a patient is hard, due to the change in environmental factors. Growing cells outside the body usually does not accurately reflect the microenvironment that cells are derived from, and so the cells will behave differently and unlike a real tumour. As a result, only a few cell lines from medulloblastoma patients have been successfully grown ex vivo.
  2. Models can be costly, and these include mouse-based models, which pose limitations due to the difference in species
  3. Medullobastoma tumours are genetically different between patients – there is no ‘one size fits all’ model and there is a need to develop more treatment options that target specific genetic subtypes in order to improve survival.

In this CARP award, Dr John Jacob (Nuffield Department of Clinical Neurosciences) aims to investigate a specific genetic subtype of medulloblastoma (known as sonic hedgehog medulloblastoma) – and test if the presence of the tumour microenvironment, which consists of non-cancerous cerebellar tissue, is necessary to better simulate the typical tumour growth conditions.

Working alongside Associate Professor Esther Becker (Nuffield Department of Clinical Neurosciences) and Dr Benjamin Schuster-Boeckler (Big Data Institute & Oxford Ludwig Cancer Institute), the team hope to recreate the in vivo tumour microenvironment more accurately compared to existing models. The Becker group previously established a methodology to grow human cerebellar neurons from human induced pluripotent stem cells (hiPSC). By using hiPSCs to form miniature cerebellar structures, termed cerebellar organoids, the tumour microenvironment can be recreated in a dish.

The team hope to overcome the existing modelling difficulties by growing medulloblastoma cells on these organoids. Dr Jacob, aided by the computational biology expertise of Dr Schuster-Boeckler will then investigate the growth of individual tumour cells, in a more physiological context. The resulting outcomes could mean the development of a new model to test patient-specific therapies on, in order to assess their toxicities and efficacy more accurately.

Dr John Jacob is a consultant neurologist who is interested in better understanding the genetic complexity of cancer and what it means for personalised treatment. Through this award and collaboration, Dr Jacob hopes to improve the success of therapy development and ultimately improve the repertoire of therapies of this cancer.

The Medical Research Council Clinical Academic Research Partnership scheme allows NHS consultants with a PhD or MD to participate in collaborative high-quality research partnerships with established leading biomedical researchers.

 

New prostate cancer risk tool

Each year in the UK around 48,500 men are diagnosed with prostate cancer and 11,900 die from the disease. To improve survival, Professor Julia Hippisley-Cox (Nuffield Department of Primary Care and Health Sciences) and Professor Carol Coupland (University of Nottingham) have developed a tool to calculate personalised risk of prostate cancer using the health records of 1.45 million men in the QResearch database. The new risk prediction algorithm aims to diagnose more tumours earlier when they are easier to treat.

The tool is designed to be used for asymptomatic individuals and combines the prostate specific antigen (PSA) blood test result with factors such as age, ethnicity, body mass index, smoking status, social deprivation and family history. Compared to using the PSA test alone, the new algorithm is more accurate at predicting prostate cancer cases (68.2% compared to 43.9% using PSA-only), high-grade aggressive tumours (49.2 % versus 40.3%) and prostate cancer deaths (67% versus 31.5%).

The decision in most primary care practices to refer men who are asymptomatic is based on binary PSA thresholds, although this can lead to too many false-negative and false-positive results. Furthermore, a binary threshold does not give any indication for the patient as to their absolute risk of developing prostate cancer and/or clinically significant disease requiring immediate intervention. The results show that the risk equation provides a valid measure of absolute risk and is more efficient at identifying incident cases of prostate cancer, high-grade cancers and prostate cancer deaths than an approach based on a PSA threshold. The intended use is to provide a better evidence base for the GP and patient to improve decision-making regarding the most appropriate action, for example, reassurance, repetition of PSA test, referral for MRI, regular monitoring, referral to a urologist, or use of preventative interventions should any become available.

 – Professor Julia Hippisley-Cox (Nuffield Department of Primary Care and Health Sciences)

More research is now required to assess the best way to implement the algorithm and evaluate the health economics and the impact on prostate cancer diagnosis and subsequent survival.

Read the full publication in the British Journal of General Practice.

Read the feature in the Daily Mail

Understanding mutation progression to detect ovarian cancer earlier

High grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer, and is one of the deadliest. Over 80% of these ovarian cancers are detected at an advanced stage, such as stage III or IV, when cancers are much harder to treat. As a result, 10-year survival rates are less than 30% in the UK.

This is despite the fact that HGSOC has a latency period predicted to be between 6.5 and 40 years, whereby a precancerous lesion in the fallopian tube has developed and will go on to become a cancerous tumour. So, despite being present in the body for a long time, current methods are poor at detecting this type of ovarian cancer at an early stage once it has progressed.

This is due in part to a lack of screening techniques for ovarian cancer, such as the very successful screening programmes for other cancers like cervical or colorectal cancer, which have had a considerable impact on patient outcomes over the last decade. Ovarian cancer symptoms are also very non-specific and so make early diagnosis even more challenging, with women often presenting with bloating, abdominal pain, weight loss or weight gain. The precancerous lesions of the fallopian tubes that could develop into serous ovarian cancer are also hard to find due to their small size, and thus are hard to study. There is therefore an urgent need to find new methods of early detection.

Nina Wietek from the Ahmed Lab at the Nuffield Department of Women’s & Reproductive Health is investigating potential avenues for early detection through sequencing tumours and precancerous tissue to explore tumour initiation. To do this Nina is interrogating highly relevant samples obtained directly from patients to gain important insights into tumour development using the power of genomics. Through enhancing our understanding of these early changes, they hope to devise methods of looking for them in order to diagnose ovarian cancer at an early stage, which will have a direct impact on patient survival.

About Nina & the Ahmed lab

Nina Wietek is investigating methods of early detection and prevention of ovarian cancer at the Ahmed Lab. Publications and results from this work is expected later in 2021.

Led by Prof Ahmed Ahmed, the Ovarian Cancer Cell Laboratory in The Weatherall Institute of Molecular Medicine uses cutting-edge innovative technologies to gain deep understanding of mechanistic drivers of ovarian cancer initiation and progression. Find out more about this group here.

New study investigates how growth factors in our gut could initiate cancer

The cells that make up our tissues are strictly organised, and various differentiated cell types do different jobs in specific locations. The cell composition of tissues and the way the cells are organised is often different in pre-cancerous conditions, or even severely disrupted when they progress to tumours.

Understanding the molecular signals that cause cell differentiation and prompt the cells to find their location within the tissue, may explain the morphological changes observed in patients with pre-cancerous conditions. Ultimately, the alteration of these signals might be a driving force in tumour development and progression.

A recent paper from the Boccellato Lab at the Ludwig Institute for Cancer Research, University of Oxford, has investigated how the epithelial cell lining of our gastrointestinal tract differentiates based on different growth factors, and how this could ultimately determine how a patient progresses to precancerous conditions that could lead to stomach cancer.

Image: A picture from the published paper showing how normal gastric pits can change shape and functionality if EGF levels are altered, and eventually lead to the pre-cancerous condition Atrophic Gastritis

The team exposed healthy human gut tissue (the mucosoid cultures, patented) to a variety of growth factors, including EGF, BMP and NOGGIN. What they found is that different combinations of these factors help to determine which cells differentiate to form the gastric glands. These glands line the stomach, and contain a variety of different cells that produce digestive enzymes and gastric acid to help to digest our food, or mucus to protect the stomach lining.

For example, exposure to growth factors including EGF and BMP formed the foveolar cells that produce the mucus to line our gut, whereas inhibition of EGF induces the differentiation of cells producing gastric acid and digestive enzymes.

Patient with the pre-cancerous condition called Atrophic Gastritis have a problem with digestion due to the lack of digestive enzymes and gastric acid producing cells. In the biopsies of this pre-cancerous condition, the team have found elevated levels of EGF, which correlated with the lack of those gastric acid producing cells and with a flattened shape of the stomach tissue.

What this study has shown is that specific localisation of growth factors in the tissue microenvironment may be responsible for the differentiation process. So changing the relative quantities or localisation of these growth factors could trigger a change in the epithelium structure and cellular composition over time, potentially leading to cancer.

Building a high-resolution, dynamic map of the growth factors during cancer progression is the next step in this research. The team will also be investigating causes for these growth factor level changes. For example, long-term infection with  Helicobacter pylori bacteria is associated with increased risk of gastric cancer. Investigating how infection alters the growth factor microenvironment is essential to understand the response of the tissue and its potential aberration leading to cancer.

Dr Francesco Boccellato says:

“By better understanding the role of growth factors underlying the epithelial structures in pre-cancerous conditions, we can detect when cancers may appear and thus treat them earlier.

“This study has allowed us to draw up a new, detailed map of the signalling microenvironment in the healthy human gastric glands, which we can now draw upon in future studies as we investigate how growth factors influence cancer occurrence.”

About the Boccellato lab

The Boccellato lab is investigating oncogenic pathogens and how they contribute to cancer.  Patients infected with those pathogens have a higher chance of developing cancer, but the malignancy arises many years after the initial infection event. Cancer may develop as a result of a long battle between the pathogen that persists, hides and damages the tissue, and the host that attacks the pathogen and continuously repairs the damage caused by the infection.

Oxford success at the early detection sandpit on pancreatic cancer

Pancreatic cancer is a devastating disease with low survival rates that have hardly improved in the last 40 years. These cancers are very challenging to treat, in part due to their frequently late diagnosis when the cancer is already advanced.

To address this need for earlier detection, Cancer Research UK, Pancreatic Cancer UK and the Engineering and Physical Sciences Research Council convened a 3-day virtual workshop in November 2020. Multidisciplinary teams worked together to generate innovative research ideas for detecting pancreatic cancer earlier. At the end of the workshop, the teams pitched their ideas to receive seed funding for feasibility testing from a Cancer Research UK Early Detection Innovation Award. Two successful teams involved Oxford researchers.

Team ReTHOMS: Real-time high-sensitivity optrode metabolic sensor for pancreatic cyst fluids

Team ‘ReTHOMS’ includes Oxford’s Professor Eric O’Neill (Department of Oncology) who is working with Dr Paolo Bertoncello (Swansea University), Dr David Chang (University of Glasgow) and Dr George Gordon (University of Nottingham). The team aims to develop a new sensor device to detect malignant transformation in people with pancreatic cysts, a condition that puts them at higher risk of pancreatic cancer.

Pancreatic cysts are fluid-filled sacs on or in the pancreas that are mostly benign. However, 2-3% are precancerous and can develop into pancreatic cancer. Cysts are often identified incidentally and are then monitored for malignant transformation using either clinical imaging or analysis of the cyst fluid for cancer biomarkers such as mucins. Despite this surveillance regime, early cancers are still being missed since these methods have limited sensitivity and specificity.

To improve the early detection of malignant cyst transformation, the team aims to develop real-time and highly sensitive detection of an expanded range of cancer biomarkers. In addition to mucin, raised cellular levels of the chemical hydrogen peroxide are associated with cancer. So-called optrode technology will be used to detect hydrogen peroxide and mucin in cyst fluid. Optrodes are optical sensor devices that detect light emitted as a result of an electrochemical reaction with the biomarkers being analysed.

During this short project, the team will build the optrode device for measuring hydrogen peroxide and mucin, and undertake technical and biological validation. The longer-term aim of this research is to detect pancreatic cancer earlier by screening pancreatic cyst fluid at the point-of-care and determining further action based on the risk of cancer.

Team EDPAN: Earlier detection of pancreatic cancer through personalised assessment of risk combined with non-invasive infrared spectroscopy

Oxford’s Dr Pui San Tan (Nuffield Department of Primary Care Health Sciences) will work as part of team EDPAN with Dr Pilar Acedo Nunez (University College London), Dr Aida Santaolalla (King’s College London), Dr Paul Brennan (University of Edinburgh), Dr Lucy Oldfield (University of Liverpool), Dr Andrew Kunzmann (Queen’s University Belfast) and Dr Mohammad Golbabaee (University of Bath). This team aims to identify individuals at higher risk of pancreatic cancer for further diagnostic screening.

One of the reasons that pancreatic cancer is often diagnosed late is that symptoms are non-specific and cannot discriminate those that require investigation for pancreatic cancer. Team EDPAN will develop an approach for personalised risk stratification to identify individuals at higher risk that would benefit from more in-depth screening for pancreatic cancer.

During the project, the team will make use of existing cohorts for pancreatic cancer (ADEPTS (UCL) and PanDIA (Liverpool)) and larger cohorts for epidemiology research (UK Biobank, AMORIS). They will combine clinical and demographic information with analysis of serum and urine samples using a technique called infrared spectroscopy. They will also evaluate changes in immune components. These approaches aim to identify individuals at high-risk of pancreatic cancer and investigate whether addition of infrared spectroscopy data and immune analysis improves the accuracy of the risk prediction model.

New clinical prediction tools for myeloma

Myeloma is a cancer of the bone marrow that caused 117,077 deaths worldwide in 2020 (International Agency for Research on Cancer). Earlier diagnosis improves the rate of survival but unfortunately, delays in myeloma diagnosis are common and result in poorer patient outcomes.

One of the reasons for the diagnostic delay is that myeloma symptoms are non-specific and relatively common in people without cancer. For example, back pain is associated with myeloma yet there are many other non-myeloma causes of this symptom. Additional measures are therefore needed to highlight the possibility of myeloma in patients where GPs do not originally suspect this disease.

GPs frequently order simple laboratory tests, such as the full blood count, to investigate patients presenting with non-specific symptoms. Previous work by Dr Constantinos Koshiaris, Dr Jason Oke, Dr Brian Nicholson and colleagues from Oxford’s Nuffield Department of Primary Care Health Sciences and the University of Exeter identified certain abnormalities in blood test results that indicate a higher risk of myeloma, such as low haemoglobin which can be observed up to 2 years before a myeloma diagnosis.

In this paper published recently in the British Journal of General Practice, the Oxford researchers have developed new clinical prediction models for myeloma that incorporate both symptoms and blood test results. Using the Clinical Practice Research Datalink (GOLD version), a primary care database containing electronic health records for more than 11 million patients in the UK, the team identified the most common symptoms and full blood count results recorded for patients with myeloma. The most predictive of these were included in the models they developed and the new tools were validated against a set of test data. Decisions made using their prediction models resulted in fewer false positives and more true positives when compared to single tests or symptoms alone.

By identifying patients at highest risk of myeloma in primary care, these new prediction rules have the potential to reduce diagnostic delays by a substantial amount. Further research is now needed to understand more about the feasibility and implementation of this tool in the primary care setting and the impact it will have on the diagnostic pathway and patient outcomes.

Early Detection Award for research into the clinical application of single cell genomics

Myelodysplastic syndromes (MDS) are a group of blood cancers in which the bone marrow fails to make normal levels of blood cells. MDS can be broadly classified into two major groups: high-risk MDS, in which patients progress to acute myeloid leukaemia with a very poor survival rate; and low-risk MDS, in which the disease is less aggressive but patients still suffer from a huge burden of symptoms, often the result of anaemia.

There are a number of exciting new targeted treatment options for low-risk MDS. However, these do not work in all patients and, particularly given the high economic cost of newer treatments, current biomarkers are not sufficiently predictive of treatment response. There is a need to more precisely categorise MDS to predict the disease trajectory and the response to therapy so that the most effective treatment can be given to each patient.

Large investments in sequencing technology in clinical laboratory services are enabling precision medicine in certain cancers and revolutionising patient care. Dr Onima Chowdhury, MRC Clinical Academic Research Fellow and Consultant Haematologist (MRC Weatherall Institute of Molecular Medicine and Oxford University Hospitals) is working with Professor Adam Mead, Dr Supat Thongjuea and Dr Lynn Quek at the MRC WIMM to explore the use of single-cell genomics in the clinical diagnosis and management of MDS. Funded by a Cancer Research UK Early Detection and Diagnosis Primer Award, the team will seek to develop a simple, clinically applicable processing and analysis pipeline, as well as identifying biomarkers that correlate and can perhaps supersede current diagnostic modalities.

Long-term, the team hope that this approach will be able to improve outcomes of patients through improved diagnosis, risk prediction and targeted treatment in MDS and other haematological malignancies.

Higher testosterone levels in men linked to greater melanoma risk

1 in 36 UK males and one in 47 UK females will be diagnosed with melanoma skin cancer in their lifetime. However, 86% of melanoma cases were preventable, as many cases are caused by UV ray exposure, but other factors can also play a role in who is most at risk, such as age and genetics.

A recent study lead by Dr Eleanor Watts at the Nuffield Department of Population Health has now found that testosterone is one of these risk factors. Published in the International Journal of Cancer, the team found that men with high levels of testosterone have an increased risk of developing a potentially deadly type of skin cancer. This was a result of studying blood samples hormone data. collected by the UK Biobank from 182,600 men and 122,100 postmenopausal women aged 40 to 69.

The researchers looked both the total level of testosterone in the blood samples, as well as levels that were freely circulating. They then used national registries and NHS records to explore whether participants went on to develop or die from cancer.

The results show that by 2015-16, after being followed for an average of seven years, 9,519 men and 5,632 postmenopausal women – 5.2% and 4.6% of participants respectively – had been diagnosed with a malignant cancer. By excluding other, non-melanoma diagnoses and accounting for other factors, they found that for men, higher levels of testosterone, whether freely or in total, were associated with a greater risk of developing malignant melanoma.

Specifically, each 50 pmol/L increase in free testosterone was found to raise the chance of developing this cancer by 35%. 90% of men included in the study had free testosterone concentrations of between 130 pmol/L and 310 pmol/L.

Among other findings, higher levels of freely circulating testosterone were associated with a greater risk of prostate cancer in men, while in post-menopausal women, higher levels of testosterone, whether freely circulating or in total, were associated with a greater chance of endometrial and breast cancer.

Dr Eleanor Watts, the first author of the research from the University of Oxford, says:

“There has been indirect evidence for testosterone and melanoma before, but this is the first time we have been able to look directly at the hormones in the blood

“Although we have seen associations of prostate, breast and endometrial cancer with testosterone before, this is the first time we have seen an association with risk of melanoma in men.”

 

About Eleanor

Eleanor is an Early Career Research Fellow in the Cancer Epidemiology Unit (CEU), part of the Nuffield Department of Population Health. Her research examines the role of endogenous hormones on prostate cancer risk using UK Biobank.

New funding for early diagnosis research using platelets

It is known that the earlier a cancer is detected, the more likely a cancer patient is to have better outcomes. One of the challenges for achieving early detection is to develop a minimally invasive test to detect the signs of early cancer in the body.

Because blood tests are simple to carry out in the clinic, a lot of effort has been focused on detecting molecules released from cancer cells in blood samples – so-called ‘liquid biopsies’. However, the majority of techniques that are used currently have a low sensitivity for early-stage cancers, due to low levels of cancer cell-derived molecules being present in blood plasma.

Dr Bethan Psaila, Cancer Research UK (CRUK) Advanced Clinician Scientist, Group Leader at the Medical Research Council Weatherall Institute of Molecular Medicine (MRC WIMM) and principal investigator at the Radcliffe Department of Medicine at Oxford University, is pioneering an approach that might be able to enrich for cancer-derived molecules in the blood. Working with Professor Chris Gregory (University of Edinburgh), Professor Paul Rees (University of Swansea) and Dr Henkjan Gersen (University of Bristol), Beth is leading a multi-disciplinary team that brings together cancer cell biologists, and imaging and engineering expertise to explore the use of platelets for early cancer diagnosis.

Platelets perfuse tumours and take up cancer cell-derived biomolecules. Isolating platelets from the blood and analysing their contents will hopefully be a more sensitive method for detecting cancer-specific molecules in the blood.

In this newly funded project, the team will use state-of-the-art pre-clinical models as well as samples from patients with colorectal cancer, pancreatic cancer and oesophageal cancer as exemplar cancers to assess the utility of ‘tumour-educated’ platelets (TEPs) for early cancer diagnosis. They will use detailed imaging and biomechanical techniques to assess whether TEPs can be reliably distinguished from platelets in healthy people or those with non-malignant disorders.

This multi-institutional project is funded by a Cancer Research UK Early Detection and Diagnosis Project Award and builds on a successful CRUK Innovation Award the team received after a workshop on liquid biopsy technologies in 2018. The ~£650,000 award will run for four years and will support two DPhil studentships, a postdoctoral research scientist and a research assistant.

Oxford spin out influencing patient care world wide

Optellum, a lung health company aiming to redefine early diagnosis and treatment of lung disease, today announced it received FDA clearance for its “Virtual Nodule Clinic”.

Optellum was co-founded by Oxford cancer researcher Prof. Sir Michael Brady with the mission of seeing every lung disease patient diagnosed and treated at the earliest possible stage, and cured.

Optellum’s initial product is the Virtual Nodule Clinic, the first AI-powered Clinical Decision Support software for lung cancer management. Their platform helps clinicians identify and track at-risk patients and speed up decisions for those with cancer while reducing unnecessary procedures.

Lung cancer kills more people than any other cancer. The current five-year survival rate is an abysmal 20%, primarily due to the majority of patients being diagnosed after symptoms have appeared and the disease has progressed to an advanced stage. This much-needed platform is the first such application of AI decision support for early lung cancer diagnosis cleared by the FDA.

Physician use of Virtual Nodule Clinic is shown to improve diagnostic accuracy and clinical decision-making. A clinical study, which underpinned the FDA clearance for the Virtual Nodule Clinic, engaged pulmonologists and radiologists to assess the accuracy for diagnosing lung nodules when using the Optellum software.

Dr Václav Potěšil, co-founder and CEO of Optellum says:

“This clearance will ensure clinicians have the clinical decision support they need to diagnose and treat lung cancer at the earliest possible stage, harnessing the power of physicians and AI working together – to the benefit of patients.

Our goal at Optellum is to redefine early diagnosis and treatment of lung cancer, and this FDA clearance is the first step on that journey. We look forward to empowering clinicians in every hospital, from our current customers at academic medical centers to local community hospitals, to offer patients with lung cancer and other deadly lung diseases the most optimal diagnosis and treatment.”