The genetic adaptions identified were similar to those made by SARS-CoV – which caused the 2002-2003 SARS epidemic – when it adapted from bats to infect humans. This suggests that there may be a common mechanism by which this family of viruses mutates in order to jump from animals to humans. This understanding can be used in future research to identify viruses circulating in animals that could adapt to infect humans (known as zoonoses) and which potentially pose a pandemic threat.

“This study used a non-infectious, safe platform to probe how spike protein changes affect virus entry into the cells of different wild, livestock and companion animals, something we will need to continue monitoring closely as additional SARS-CoV-2 variants arise in the coming months,” said Dr Stephen Graham in the University of Cambridge’s Department of Pathology, who was involved in the study.

In the 2002-2003 SARS epidemic, scientists were able to identify closely related isolates in both bats and civets – in which the virus is thought to have adapted to infect humans. However, in the current COVID-19 outbreak scientists do not yet know the identity of the intermediate host or have similar samples to analyse. But they do have the sequence of a related bat coronavirus called RaTG13 which shares 96 percent similarity to the SARS-CoV-2 genome. The new study compared the spike proteins of both viruses and identified several important differences.

SARS-CoV-2 and other coronaviruses use their spike proteins to gain entry to cells by binding to their surface receptors, for example ACE2. Like a lock and key, the spike protein must be the right shape to fit the cell’s receptors, but each animal’s receptors have a slightly different shape, which means the spike protein binds to some better than others.

To examine whether these differences between SARS-CoV-2 and RaTG13 were involved in the adaptation of SARS-CoV-2 to humans, scientists swapped these regions and examined how well these resulting spike proteins bound human ACE2 receptors – using a method that does not involve using live virus.

The results, published in the journal PLOS Biology, showed SARS-CoV-2 spikes containing RaTG13 regions were unable to bind to human ACE2 receptors effectively, while the RaTG13 spikes containing SARS-CoV-2 regions could bind more efficiently to human receptors – although not to the same level as the unedited SARS-CoV-2 spike protein. This potentially indicates that similar changes in the SARS-CoV-2 spike protein occurred historically, which may have played a key role in allowing the virus to jump the species barrier.

Researchers also investigated whether the SARS-CoV-2 spike protein could bind to the ACE2 receptors from 22 different animals to ascertain which of these, if any, may be susceptible to infection. They demonstrated that bat and bird receptors made the weakest interactions with SARS-CoV-2. The lack of binding to bat receptors adds weight to the evidence that SARS-CoV-2 likely adapted its spike protein when it jumped from bats into people, possibly via an intermediate host.

Dog, cat, and cattle ACE2 receptors were identified as the strongest interactors with the SARS-CoV-2 spike protein. Efficient entry into cells could mean that infection may be more easily established in these animals, although receptor binding is only the first step in viral transmission between different animal species.

“As we saw with the outbreaks in Danish mink farms last year, it’s essential to understand which animals can be infected by SARS-CoV-2 and how mutations in the viral spike protein change its ability to infect different species,” said Graham.

An animal’s susceptibility to infection and its subsequent ability to infect others is reliant on a range of factors – including whether SARS-CoV-2 is able to replicate once inside cells, and the animal’s ability to fight off the virus. Further studies are needed to understand whether livestock and companion animals could be receptive to COVID-19 infection from humans and act as reservoirs for this disease.

This research was funded by the Medical Research Council, the Biotechnology and Biological Sciences Research Council and Innovate UK – all part of UK Research and Innovation; the Royal Society and Wellcome.

Reference
Conceicao, C. et.al: ‘The SARS-CoV-2 Spike protein has a broad tropism for mammalian ACE2 proteins’. PLOS Biology, Dec 2020. DOI:10.1371/journal.pbio.3001016

Adapted from a press release by the Pirbright Institute

The research published in European Radiology shows that combining computed tomography (CT) scans with ultrasound images creates a visual guide for doctors to ensure they sample the full complexity of a tumour with fewer targeted biopsies.

Capturing the patchwork of different types of cancer cell within a tumour – known as tumour heterogeneity – is critical for selecting the best treatment because genetically-different cells may respond differently to treatment.

Most cancer patients undergo one or several biopsies to confirm diagnosis and plan their treatment. But because this is an invasive clinical procedure, there is an urgent need to reduce the number of biopsies taken and to make sure biopsies accurately sample the genetically-different cells in the tumour, particularly for ovarian cancer patients.

High grade serous ovarian (HGSO) cancer, the most common type of ovarian cancer, is referred to as a ‘silent killer’ because early symptoms can be difficult to pick up. By the time the cancer is diagnosed, it is often at an advanced stage, and survival rates have not changed much over the last 20 years.

But late diagnosis isn’t the only problem. HGSO tumours tend to have a high level of tumour heterogeneity and patients with more genetically-different patches of cancer cells tend to have a poorer response to treatment.

Professor Evis Sala from the Department of Radiology, co-lead CRUK Cambridge Centre Advanced Cancer Imaging Programme, leads a multi-disciplinary team of radiologists, physicists, oncologists and computational scientists using innovative computing techniques to reveal tumour heterogeneity from standard medical images. This new study, led by Professor Sala, involved a small group of patients with advanced ovarian cancer who were due to have ultrasound-guided biopsies prior to starting chemotherapy.

For the study, the patients first had a standard-of-care CT scan. A CT scanner uses x-rays and computing to create a 3D image of the tumour from multiple image ‘slices’ through the body.

The researchers then used a process called radiomics – using high-powered computing methods to analyse and extract additional information from the data-rich images created by the CT scanner – to identify and map distinct areas and features of the tumour. The tumour map was then superimposed on the ultrasound image of the tumour and the combined image used to guide the biopsy procedure.

By taking targeted biopsies using this method, the research team reported that the diversity of cancer cells within the tumour was successfully captured.

Co-first author Dr Lucian Beer, from the Department of Radiology and CRUK Cambridge Centre Ovarian Cancer Programme, said of the results: “Our study is a step forward to non-invasively unravel tumour heterogeneity by using standard-of-care CT-based radiomic tumour habitats for ultrasound-guided targeted biopsies.”

Co-first author Paula Martin-Gonzalez, from the Cancer Research UK Cambridge Institute and CRUK Cambridge Centre Ovarian Cancer Programme, added: “We will now be applying this method in a larger clinical study.”

Professor Sala said: “This study provides an important milestone towards precision tissue sampling. We are truly pushing the boundaries in translating cutting edge research to routine clinical care.”

Fiona Barve (56) is a science teacher who lives near Cambridge. She was diagnosed with ovarian cancer in 2017 after visiting her doctor with abdominal pain. She was diagnosed with stage 4 ovarian cancer and immediately underwent surgery and a course of chemotherapy. Since March 2019 she has been cancer free and is now back to teaching three days a week.

“I was diagnosed at a late stage and I was fortunate my surgery, which I received within four weeks of being diagnosed, and chemotherapy worked for me. I feel lucky to be around,” said Barve.

“When you are first undergoing the diagnosis of cancer, you feel as if you are on a conveyor belt, every part of the journey being extremely stressful. This new enhanced technique will reduce the need for several procedures and allow patients more time to adjust to their circumstances. It will enable more accurate diagnosis with less invasion of the body and mind. This can only be seen as positive progress.”

This feasibility study, involving researchers from the Department of Radiology, CRUK Cambridge Institute, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, and collaborators at Cannon, was facilitated through the CRUK Cambridge Centre Integrated Cancer Medicine programme.

The goal of Integrated Cancer Medicine is to revolutionise cancer treatment using complex data integration. Combining and integrating patient data from multiple sources – blood tests, biopsies, medical imaging, and genetic tests – can inform and predict the best treatment decisions for each individual patient.

The study was funded by Cancer Research UK and The Mark Foundation for Cancer Research.

Reference
Lucian Beer, Paula Martin-Gonzalez et al. Ultrasound-guided targeted biopsies of distinct CT based radiomic tumour habitats: proof of concept. European Radiology; 14 Dec 2020; DOI: 10.1007/s00330-020-07560-8