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Cancer symptoms: Top 14 early signs to look out for
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Cancerous cells proliferate and spread – a process that can be hard to stop once it’s underway. Taking early action is the best weapon against cancer yet finding the best treatment can take time. A new test aims to tackle both these problems: providing quick results that help steer doctors towards the best drug combinations to treat an individual’s cancer.
The cutting-edge technique uses artificial intelligence (AI) to analyse data from tumour samples and can more accurately estimate a patient’s response to medication than is currently possible.
The test can be carried out in 24 to 48 hours and the rapid turnaround means it has the potential to help doctors decide which treatment is best.
Researchers believe the technology could be crucial in overcoming cancer evolution and treatment resistance by allowing doctors to analyse how drugs work in combination.
While genetic analysis of tumours can reveal mutations that are fuelling cancer’s growth – some of which can be targeted with treatment – this information alone does not provide sufficiently accurate predictions to select drug combinations.
Study leader Udai Banerji, professor of molecular cancer pharmacology at the Institute of Cancer Research, London (ICR) said: “Our test provides proof of concept for using AI to analyse changes in the way information flows within cancer cells and make predictions about how tumours are likely to respond to combinations of drugs.
“With a rapid turnaround time of less than two days, the test has the potential to guide doctors in their judgments on which treatments are most likely to benefit individual cancer patients.
“It is an important step to move forward from our current focus on using genetic mutations to predict response.
“Our findings show that our innovative approach is feasible, and makes more accurate predictions than genetic analysis for patients with non-small cell lung cancer.”
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Scientists at the ICR tested the new technique on individual cancer cells in the lab and tumour cells taken from lung fluid in people with lung cancer.
They used an algorithm to predict how sensitive cells were to individual cancer drugs, and found the technique could predict individual drug responses more accurately than genetic features.
Researchers then used the same approach to predict sensitivity to drug combinations – using 21 different two-drug combinations.
Of 252 total drug combinations, prevacid pediatrics 128 showed some level of synergy, meaning their combined effect exceeded the effect of each drug added together.
Of these, the AI test correctly identified the top five ranked combinations 57 percent of the time and the top 10 ranked combinations 83 percent of the time.
Researchers were able to confirm the effectiveness of previously promising combinations, as well as identify possible new combinations.
They suggested this is therefore the first prototype test that can offer personalised predictions of which drug combinations are likely to work in different individuals.
Their study is published in the journal Molecular Cancer Therapeutics and was funded by the National Institute for Health Research, Wellcome, Cancer Research UK and the ICR.
The new study establishes proof of concept but further trials are needed before it can be used in patients.
Cancer – general signs and symptoms
It’s important to be aware of any new or worrying symptoms.
“Although it’s unlikely to be cancer, it’s important to speak to a GP so they can investigate. Finding cancer early means it’s easier to treat,”explains the NHS.
Signs to spot include:
- Changes in bowel habits
- Bloating
- Lumps
- Moles
- Unexplained weight loss.
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