A simple blood test for early detection of breast cancer?

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Breast cancer could be detected up to five years before there are any clinical signs of it, using a blood test that identifies the body’s immune response to substances produced by tumour cells, according to new research presented at the 2019 NCRI Cancer Conference today (Sunday).

Cancer cells produce proteins called antigens that trigger the body to make antibodies against them – autoantibodies. Researchers at the University of Nottingham (UK) have found that these tumour-associated antigens (TAAs) are good indicators of cancer, and now they have developed panels of TAAs that are known already to be associated with breast cancer to detect whether or not there are autoantibodies against them in blood samples taken from patients.

In a pilot study the researchers, who are part of the Centre of Excellence for Autoimmunity in Cancer (CEAC) group at the School of Medicine, University of Nottingham, took blood samples from 90 breast cancer patients at the time they were diagnosed with breast cancer and matched them with samples taken from 90 patients without breast cancer (the control group).

They used screening technology (protein microarray) that allowed them to screen the blood samples rapidly for the presence of autoantibodies against 40 TAAs associated with breast cancer, and also 27 TAAs that were not known to be linked with the disease.

Presenting the research at the NCRI Conference, Ms Daniyah Alfattani, a PhD student in the group, said: “The results of our study showed that breast cancer does induce autoantibodies against panels of specific tumour-associated antigens. We were able to detect cancer with reasonable accuracy by identifying these autoantibodies in the blood.”

The researchers identified three panels of TAAs against which to test for autoantibodies. The accuracy of the test improved in the panels that contained more TAAs. The panel of five TAAs correctly detected breast cancer in 29% of the samples from the cancer patients and correctly identified 84% of the control samples as being cancer-free. The panel of seven TAAs correctly identified cancer in 35% of cancer samples and no cancer in 79% of control samples. The panel of nine antigens correctly identified cancer in 37% of cancer samples and no cancer in 79% of the controls.

“We need to develop and further validate this test,” said Ms Alfattani. “However, these results are encouraging and indicate that it’s possible to detect a signal for early breast cancer. Once we have improved the accuracy of the test, then it opens the possibility of using a simple blood test to improve early detection of the disease.”

The researchers are now testing samples from 800 patients against a panel of nine TAAs, and they expect the accuracy of the test to improve with these larger numbers.

“A blood test for early breast cancer detection would be cost effective, which would be of particular value in low and middle income countries. It would also be an easier screening method to implement compared to current methods, such as mammography,” said Ms Alfattani.

The researchers estimate that, with a fully-funded development programme, the test might become available in the clinic in about four to five years.

A similar test for lung cancer is currently being tested in a randomised controlled trial in Scotland, involving 12,000 people at high risk of developing lung cancer because they smoke. They have been randomised to have (or not) an autoantibody blood test called ELISA (Early CDT-Lung). Participants who test positive for the autoantibodies are then followed up with a CT scan every two years in order to detect lung cancer in its early stages when it is easier to treat.

The CEAC group is also working on similar tests for pancreatic, colorectal and liver cancers. Solid tumours like these, as well as lung and breast cancer, represent around 70% of all cancers.

“A blood test capable of detecting any of these cancers at an early stage is the over-riding objective of our work,” concluded Ms Alfattani.

Dr Iain Frame, CEO of NCRI said: “Early diagnosis using simple, non-invasive ways of detecting the first signs of cancer is a key strategic priority for NCRI and something we’d all like to see working in practice. The results from this pilot study for a blood test to detect early breast cancer are promising and build on this research group’s expertise in other cancers, such as lung cancer. It’s obviously early days but we look forward to seeing the results from the larger group of patients that are now being investigated.”

 

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Can muscle decline due to aging be suppressed or even stopped?

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Muscle decline caused by ageing and certain diseases could be dramatically slowed by stopping a chain reaction that damages cells, new research shows.

The study revealed the previously unknown steps by which dysfunction of mitochondria – the so-called “powerhouses” of cells – harms muscle health and leads to atrophy (wasting away).

The research team, from the universities of Exeter and Nottingham (UK) and Tohoku University in Japan, showed that inhibiting various stages of this process suppressed muscle atrophy.

The research was carried out on a species of worm called Caenorhabditis elegans – recently used in a muscle study on the International Space Station because their muscle cells resemble those of humans.

“Mitochondrial dysfunction is a key feature of several muscle diseases, but treatments are currently limited,” said Dr Timothy Etheridge, of the University of Exeter.

“Our research shows that mitochondrial dysfunction causes calcium to build up in cells, which in turn activates enzymes that degrade collagen.

“Collagen is vital for giving structure to the outside of cells, so degradation of collagen destabilises muscle.

“In this study, we used experimental drugs to inhibit the enzymes that degrade collagen – and the results show this suppressed muscle decline caused by dysfunctional mitochondria.

“We found the same effect in worms used to model Duchenne muscular dystrophy, which causes severe muscle weakness.”

More research is needed, but the findings raise the prospect of new therapies to delay muscle atrophy caused by ageing and conditions such as Duchenne muscular dystrophy.

Learn more: Worm study sparks hope for slowing muscle decline

 

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A new approach using 2 old drugs show promise for specific types of stroke and dementia

via Stroke Connection Magazine – American Stroke Association

Treatments that prevent recurrence of types of stroke and dementia caused by damage to small blood vessels in the brain have moved a step closer, following a small study.

The drugs – called cilostazol and isosorbide mononitrate – are already used to treat other conditions, such as heart disease and angina.

This is the first time they have been tested in the UK for the treatment of stroke or vascular dementia.

High tolerance

A study involving more than 50 stroke patients found that patients tolerated the drugs, with no serious side effects, even when the drugs were given in full dose or in combination with other medicines.

Experts say the findings pave the way for larger studies to check if the treatments can prevent brain damage and reduce risk of stroke and vascular dementia.

Damage to small blood vessels in the brain is responsible for around a quarter of strokes. It is also a common cause of memory problems and dementia.

Around 400,000 people in the UK are affected but there are no specific treatments. Currently the only way to reduce risk of the disease is by controlling blood pressure and cholesterol, stopping smoking and managing symptoms of diabetes.

Promising early signs

A team led by the Universities of Edinburgh and Nottingham recruited 57 patients who had experienced a stroke caused by damaged small blood vessels, known as a lacunar stroke.

Patients took the two medicines either individually or in combination for up to nine weeks, in addition to usual treatments aimed at preventing further strokes.

They completed health questionnaires and had regular blood pressure checks, blood tests and brain scans.

The findings suggest the drugs are safe for use in stroke patients, taken alone or in combination, at least in the short term.

There were also signs that the treatments helped improve blood vessel function in the arms and brain, and may improve thinking skills, but the researchers stress that further studies are needed to test this. A larger study, called LACI-2, is already underway.

Effective treatment

The study, published in EClinicalMedicine, was funded primarily by the Alzheimer’s Society, with support from the UK Stroke Association, British Heart Foundation, the European Union, National Institutes of Health Research, and NHS Research Scotland.

We are delighted that the results of this trial show promise for treating a common cause of stroke and the commonest cause of vascular dementia, since currently there are no effective treatments. Further trials are underway.

Professor Joanna Wardlaw Centre for Clinical Brain Sciences

There hasn’t been a new drug for dementia for 15 years, so finding evidence that these cheap existing drugs could prevent dementia after a stroke would be a huge breakthrough. It’s promising to see that these two drugs are safe to use and we’ll be excited to see the results of the next stage of testing in a couple of years, which will show whether these drugs can be an effective treatment.

Dr James PickettHead of Research at Alzheimer’s Society

Learn more: Drugs to prevent stroke and dementia show promise

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Can artificial intelligence predict premature death?

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Computers which are capable of teaching themselves to predict premature death could greatly improve preventative healthcare in the future, suggests a new study by experts at the University of Nottingham.

The team of healthcare data scientists and doctors have developed and tested a system of computer-based ‘machine learning’ algorithms to predict the risk of early death due to chronic disease in a large middle-aged population.

They found this AI system was very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts. The study is published by PLOS ONE in a special collections edition of “Machine Learning in Health and Biomedicine”.

The team used health data from just over half a million people aged between 40 and 69 recruited to the UK Biobank between 2006 and 2010 and followed up until 2016.

Leading the work, Assistant Professor of Epidemiology and Data Science, Dr Stephen Weng, said: “Preventative healthcare is a growing priority in the fight against serious diseases so we have been working for a number of years to improve the accuracy of computerised health risk assessment in the general population. Most applications focus on a single disease area but predicting death due to several different disease outcomes is highly complex, especially given environmental and individual factors that may affect them.

“We have taken a major step forward in this field by developing a unique and holistic approach to predicting a person’s risk of premature death by machine-learning. This uses computers to build new risk prediction models that take into account a wide range of demographic, biometric, clinical and lifestyle factors for each individual assessed, even their dietary consumption of fruit, vegetables and meat per day.

“We mapped the resulting predictions to mortality data from the cohort, using Office of National Statistics death records, the UK cancer registry and ‘hospital episodes’ statistics. We found machine learned algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert.”

The AI machine learning models used in the new study are known as ‘random forest’ and ‘deep learning’. These were pitched against the traditionally-used ‘Cox regression’ prediction model based on age and gender – found to be the least accurate at predicting mortality – and also a multivariate Cox model which worked better but tended to over-predict risk.

Professor Joe Kai, one of the clinical academics working on the project, said: “There is currently intense interest in the potential to use ‘AI’ or ‘machine-learning’ to better predict health outcomes. In some situations we may find it helps, in others it may not. In this particular case, we have shown that with careful tuning, these algorithms can usefully improve prediction.

“These techniques can be new to many in health research, and difficult to follow. We believe that by clearly reporting these methods in a transparent way, this could help with scientific verification and future development of this exciting field for health care.”

This new study builds on previous work by the Nottingham team which showed that four different AI algorithms, ‘random forest’, ‘logistic regression’, ‘gradient boosting’ and ‘neural networks’, were significantly better at predicting cardiovascular disease than an established algorithm used in current cardiology guidelines. This earlier study is available here.

The Nottingham researchers predict that AI will play a vital part in the development of future tools capable of delivering personalised medicine, tailoring risk management to individual patients. Further research requires verifying and validating these AI algorithms in other population groups and exploring ways to implement these systems into routine healthcare.

Learn more: Artificial intelligence can predict premature death, study finds

 

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A promising new treatment for acute myeloid leukaemia

Acute myeloid leukamia (AML) cells. Image courtesy of The Armed Forces Institute of Pathology (AFIP)

Ingredient in pre-clinical treatment for retinal neovascular disease targets gene associated with acute myeloid leukaemia

An active ingredient in eye drops that were being developed for the treatment of a form of eye disease has shown promise for treating an aggressive form of blood cancer. Scientists at the Wellcome Sanger Institute, University of Cambridge, University of Nottingham and their collaborators have found that this compound, which targets an essential cancer gene, could kill leukaemia cells without harming non-leukemic blood cells.

The results, published today (19 December) in Nature Communications reveal a potential new treatment approach for an aggressive blood cancer with a poor prognosis.

Acute myeloid leukaemia (AML) is a form of blood cancer that affects people of all ages, often requiring months of intensive chemotherapy and prolonged hospital admissions. It develops in cells in the bone marrow crowding out the healthy cells, in turn leading to life-threatening infections and bleeding.

Mainstream AML treatments have remained unchanged for over 30 years, with the current treatment being chemotherapy, and the majority of people’s cancer cannot be cured. A subtype of AML, driven by rearrangements in the MLL gene has a particularly bad prognosis.

In a previous study, researchers at the Sanger Institute developed an approach, based on CRISPR gene editing technology, which helped them identify more than 400 genes as possible therapeutic targets for different subtypes of AML. One of the genes, SRPK1, was found to be essential for the growth of MLL-rearranged AML. SRPK1 is involved in a process called RNA splicing, which prepares RNA for translation into proteins, the molecules that conduct the majority of normal cellular processes, including growth and proliferation.

In a new study, Sanger Institute researchers and their collaborators set out to work out how inhibition of SRPK1 can kill AML cells and whether it has therapeutic potential in this disease. They first showed that genetic disruption of SRPK1 stopped the growth of MLL-rearranged AML cells and then went on to study the compound SPHINX31, an inhibitor of SRPK1, which was being used to develop an eye drop treatment for retinal neovascular disease – the growth of new blood vessels on the retinal surface that bleed spontaneously and cause vision loss.

The team found that the compound strongly inhibited the growth of several MLL-rearranged AML cell lines, but did not inhibit the growth of normal blood stem cells. They then transplanted patient-derived human AML cells into immunocompromised mice and treated them with the compound. Strikingly, the growth of AML cells was strongly inhibited and the mice did not show any noticeable side effects.

“We have discovered that inhibiting a key gene with a compound being developed for an eye condition can stop the growth of an aggressive form of acute myeloid leukaemia without harming healthy cells. This shows promise as a potential approach for treating this aggressive leukaemia in humans.”

Dr George Vassiliou, joint leader of the research from the Wellcome Sanger Institute and the Wellcome-MRC Cambridge Stem Cell Institute

SRPK1 controls the splicing* of RNA in the production of new proteins. An example of a gene that is affected when SRPK1 is blocked is BRD4, a well-known gene that maintains AML. Inhibiting SRPK1 causes the main form of BRD4 to switch to another form, a change that is detrimental to AML growth.

“Our study describes a novel mechanism required for leukaemia cell survival and highlights the therapeutic potential of SRPK1 inhibition in an aggressive type of AML. Targeting this mechanism may be effective in other cancers where BRD4 and SRPK1 play a role, such as metastatic breast cancer.”

Dr Konstantinos Tzelepis, joint lead author from the Wellcome Sanger Institute and University of Cambridge

“When Dr Vassiliou told me that SRPK1 was required for the survival of a form of AML, I immediately wanted to work with him to find out if our inhibitors could actually stop the leukaemia cells growing. The fact that the compound worked so effectively bodes well for its potential development as a new therapy for leukaemia. It will take some time, but there is real promise for a new treatment on the horizon for patients with this aggressive cancer.”

Professor David Bates, from the University of Nottingham and co-founder of biotech company Exonate, which develops eye drops for retinal diseases

Learn more: From eye drops to potential leukaemia treatment

 

 

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