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New breast cancer test to predict spread of the disease
The test works by identifying the presence of two proteins in cells of the original cancer
A new breast cancer test, which may be able to accurately predict those at risk of their cancer spreading, is to be trialled in the UK.
The test, which will be trialled at the University of Bradford’s Institute of Cancer Therapeutics, could mean those at low risk could avoid undergoing follow-on treatment as well as potentially save the NHS millions of pounds a year.
In pilot studies, the test has proved 98 per cent accurate in predicting which patients are at low risk of their cancer spreading or returning, referred to as metastasis, after their initial treatment.
Now, a trial funded by Innovate UK is being conducted to test whether Ran Diagnostics works in practice.
Professor Chris Twelves, clinical director of the Institute of Cancer Therapeutics, University of Bradford, who is leading the study, said: “When people are first diagnosed with breast cancer, their oncologist will want to discuss whether they may benefit from extra drug treatment to reduce the risk of the cancer returning and spreading.
“One of the ways we do that now is through a genetic test on the cancer, but that test is expensive and can be slow.
“If, as we hope, Ran Diagnostics is as good at identifying who may benefit from such extra treatment, it will be quicker and less expensive, helping us to better personalise cancer treatment for our patients.”
Dr Mohammad Isreb, associate professor in medicine development at the University of Bradford, said: “The Ran Diagnostics test has the potential to accurately predict the likelihood of someone newly diagnosed with breast cancer developing metastasis in the future more quickly and economically than current tests.
“It may help indicate who may benefit from extra treatment, and those at low risk, who may be able to be spared extra treatment and avoid its painful and unpleasant side effects.”
The test is designed for people with the most common type of breast cancer – hormone receptor positive, HER2, receptor negative. It works by identifying the presence of two proteins in cells of the original cancer, Ran GTPAse (Ran) and MMP-2.
In laboratory tests of 181 tumour samples from patients diagnosed with breast cancer in the 1990s and whose medical histories are known, the Ran Diagnostics test showed 98 per cent accuracy.
Dr Mohammad Isreb, associate professor in medicine development at the University of Bradford and Professor Sherif El-Khamisy, director of the Institute for Cancer Therapeutics at the University of Bradford
Dr Jason Jones, commercial manager, faculty of life sciences, University of Bradford, said: “We measured levels of the two biomarkers in those samples then we looked at their medical histories to see which ones later developed metastatic disease.
“There is a clear correlation between high levels of Ran and MMP-2 and patient outcomes. Tests showed 98 per cent of patients with low levels did not go on to develop secondary cancer and therefore may have been spared chemotherapy. We have not seen anything with such a strong relationship as this before.”
The trial will be conducted in collaboration with Leeds Teaching Hospitals NHS Trust and the University of Leeds.
Breast cancer is the most commonly diagnosed cancer globally. Metastatic breast cancer – also known as secondary or stage four breast cancer – can be treated but not cured.
The NHS has committed to improving cancer care in its Long Term Plan and NICE recommends tumour profiling for some people with breast cancer to guide clinicians and patients decisions on the best treatment for patients.
Ran Diagnostics could be carried out within a hospital’s own pathology lab, with results potentially available within hours.
The team has been awarded an £897,000 Innovate Biomedical Catalyst grant to test a further 600 samples with known tumour profiling results to see if Ran Diagnostics gives equivalent results.
Ran Diagnostics will comprise of two elements: the physical testing kit used to stain the biomarkers along with AI-enabled software to analyse the data.
The grant also includes funding for Carmen Diagnostic Technologies Ltd, a spin-out company of the University of Bradford that owns the Intellectual Property (IP), to develop Ran Diagnostics into a commercial product. If the new test is successful, Carmen Diagnostic Technologies could have the product available to use in clinic within two to three years.
Professor Krzysztof Poterlowicz, director of research for computational and data-driven science at the University of Bradford and co-investigator in the project, commented: “This groundbreaking project provides a unique opportunity to leverage the latest advancements in AI and data science to develop software that optimises the results of the Ran Diagnostics test.”
Everard Mascarenhas, director of Carmen Diagnostics Technology, based in Southport, Merseyside, said: “Ran Diagnostics utilises equipment and pathology expertise that already exists in the hospital and can be adopted very quickly in hospitals around the world.
“Furthermore, as the cancer tumours can be tested by the hospital, unlike genetic tests where samples have to be transported internationally, Ran Diagnostics is closely aligned to helping the NHS achieve its net zero climate change objectives.”
He added: “A further limitation of existing genetic tests is that they only work for around 70 per cent of breast cancers.
“The science behind Ran Diagnostics means it can work for all breast cancer. In the future, there is the potential for a similar test to be used on other forms of breast cancer as well as other cancers.”
Professor Sherif El-Khamisy, director of the Institute for Cancer Therapeutics at the University of Bradford, said: “Our mission at the Institute of Cancer Therapeutics is developing smarter and personalised ways to diagnose, predict and treat cancer.
“Ran Diagnostics is an important step towards achieving our aspirations by providing a cost-effective, rapid and potentially point-of care test that informs more personalised cancer treatments that help reducing the risk of the cancer coming back or spreading to other parts of the body.”
Ovarian cancer cells quickly activate survival responses after PARP inhibitor treatment, and a lung cancer drug could help block this, research suggests.
PARP inhibitors are a common treatment for ovarian cancer, particularly in tumours with faulty DNA repair. They stop cancer cells fixing DNA damage, which leads to cell death, but many tumours later stop responding.
Researchers identified a way cancer cells may survive PARP inhibitor treatment from the outset, pointing to a potential way to block that response. A Mayo Clinic team found ovarian cancer cells rapidly switch on a pro-survival programme after exposure to PARP inhibitors. A key driver is FRA1, a transcription factor (a protein that turns genes on and off) that helps cancer cells adapt and avoid death.
The team then tested whether brigatinib, a drug approved for certain lung cancers, could block this response and boost the effect of PARP inhibitors. Brigatinib was chosen because it inhibits multiple signalling pathways involved in cancer cell survival.
In laboratory studies, combining brigatinib with a PARP inhibitor was more effective than either treatment alone. Notably, the effect was seen in cancer cells but not normal cells, suggesting a more targeted approach.
Brigatinib also appeared to act in an unexpected way. Rather than working through the usual DNA repair routes, it shut down two signalling molecules, FAK and EPHA2, that aggressive ovarian cancer cells rely on. FAK and EPHA2 are proteins that relay survival signals inside cells. Blocking both at once weakened the cells’ ability to adapt and resist treatment, making them more vulnerable to PARP inhibitors.
Tumours with higher levels of FAK and EPHA2 responded better to the drug combination. Other data link high levels of these molecules to more aggressive disease, pointing to potential benefit in harder-to-treat cases.
Arun Kanakkanthara, an oncology investigator at Mayo Clinic and a senior author of the study, said: “This work shows that drug resistance does not always emerge slowly over time; cancer cells can activate survival programmes very early after treatment begins.”
John Weroha, a medical oncologist at Mayo Clinic and a senior author of the study, said: “From a clinical perspective, resistance remains one of the biggest challenges in treating ovarian cancer. By combining mechanistic insights from Dr Kanakkanthara’s laboratory with my clinical experience, this preclinical work supports the strategy of targeting resistance early, before it has a chance to take hold. This strategy could improve patient outcomes.”
Nighttime temperatures during pregnancy may be linked to a higher chance of an autism diagnosis in children, a recent study suggests.
The research tracked nearly 295,000 mother-child pairs in Southern California from 2001 to 2014 and linked warmer overnight temperatures with higher risk in early and late pregnancy.
Children of mothers exposed to higher than typical nighttime temperatures during weeks one to 10 of pregnancy had a 15 per cent higher risk of an autism diagnosis.
Exposure during weeks 30 to 37 was linked to a 13 per cent higher risk.
Lead author David Luglio, a post-doctoral fellow at Tulane University, said: “A key takeaway is that we identified specific windows when a mother and her developing child can be most affected by exposures to higher nighttime temperatures.
“This is critical and hopefully can help mothers prepare accordingly.”
The study is described as the first to examine how temperature may affect fetal neurodevelopment, the process by which a baby’s brain and nervous system form during pregnancy.
Extreme temperatures linked to increased risk were classified as above the 90th percentile, meaning 3.6°F hotter than average, and the 99th percentile, 5.6°F above average.
The association held even after researchers accounted for factors such as neighbourhood conditions, vegetation and fine-particle air pollution.
The study could not account for other factors such as access to air conditioning. Researchers did not find the same association with daytime temperatures, potentially because people spend more time away from home during the day.
“Heat waves are becoming more frequent, and people may only think of the dangers of daytime heat exposure,” said Mostafijur Rahman, assistant professor of environmental health sciences at Tulane University.
“These results indicate a strong association between high nighttime temperatures during pregnancy and autism risk in children and show that we need to think about exposure to heat around the clock.”
The study did not examine how higher temperatures at night might affect prenatal development, though Luglio said it is possible that warmer nights disrupt sleep for pregnant mothers.
Previous research has suggested insufficient sleep during pregnancy may be linked to a higher risk of neurocognitive delays in children.
“Extreme heat exposure during pregnancy has been linked to a range of adverse health outcomes, including prenatal neurodevelopment delays and complications with an embryo’s development of a central nervous system,” Luglio said.
“The goal of our study was to specifically explore the link between prenatal heat exposure and autism diagnoses for the first time.”
Kindbody has launched a fertility platform integrating AI with clinical care and patient support for employers and health plans.
The platform will enter a pilot with select Kindbody employer clients in 2026, covering over three million lives, ahead of wider availability in 2027.
Building on the company’s clinical model, the platform aims to improve outcomes and cost efficiency across family-building journeys. It connects Kindbody-owned clinics, partner clinics and an integrated clinical app.
The app offers virtual care across conception, pregnancy and reproductive health, extending through the menopause transition.
Launch features include updates in medication management, third-party reproduction, adoption, pregnancy, men’s health and global programme design.
David Stern, chief executive of Kindbody, said: “With our next-generation fertility platform, Kindbody is redefining what comprehensive, intelligent and affordable family-building care looks like for employers, health plans and patients.
“By unifying best-in-class clinical care, AI-driven intelligence and whole-person support, we are making it easier and more cost-effective for more people to build the families they envision.”
Kindbody has expanded access via its national network of IVF centres, including IVIRMA, Inception Fertility and Ivy Fertility.
A new Fertility Medication Portal is designed to streamline authorisations so medicines can be dispensed on time, giving patients visibility from prescription to coverage, pharmacy fulfilment and delivery tracking.
Through KindMan, men’s health education, digital resources and integrated clinical care are expanding, including hormone management programmes.
Services cover andropause (age-related testosterone decline), erectile dysfunction, low testosterone and other male reproductive conditions.
Specialist fertility care includes semen analysis, diagnostic testing, male hormone panels, genetic testing, surgical sperm extraction and sperm cryopreservation.
Launching in the second quarter, a pregnancy support app will act as a digital companion for expecting and new parents, with resources, interactive tools and clinical assessments to identify social drivers of health and mental health needs during pregnancy and beyond.
Kindbody’s physician-led menopause programme provides consultations with board-certified obstetricians and gynaecologists to diagnose, treat and manage menopausal symptoms, including hormone replacement therapy where appropriate, with support from nutritionists, mental health therapists and pelvic floor specialists.
AI and analytics will be embedded across the care journey. An AI care navigator will guide employees from benefit activation through intake, triage and scheduling.
Tools will track benefits and treatment plans, showing coverage and expected out-of-pocket costs at each step.
AI-supported scribing will assist clinicians with documentation, and a predictor tool will estimate a patient’s likelihood of having a baby across different treatment paths.
In 2027, Kindbody plans a savings model for eligible large employers that it says will guarantee lower total fertility spend while improving clinical efficiency and patient experience.
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