British researchers develop a blood test at the nanoscale for discoveries of cancer



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Researchers at the University of Manchester in the UK have developed a new nano-scale blood test technique that provides more information using blood collected from cancer patients.

The latest discovery could potentially accelerate early diagnosis, drug discovery and lead to advances in personalized medicines.

University scientists took blood samples from women with advanced ovarian cancer who had been treated with a type of chemotherapy called CAELYX for 90 minutes as part of their treatment.

"The blood test at the nanoscale could potentially accelerate early diagnosis, drug discovery and lead to advances in personalized medicines."

The drug is contained in a lipid-based soft nanoparticle called liposome that helps reduce the side effects of chemotherapy by acting as a vessel.

In the study funded by Cancer Research UK, scientists extracted the injected liposomes and were able to detect different biomolecules glued to the surface of the liposome, called "biomolecule corona".

Manchester University senior author professor Kostas Kostarelos said: "We hope this technique can serve as a springboard for further research, ranging from monitoring the evolution of the disease to its recurrence. identifying the most appropriate treatment for each patient and the potential discovery of new biomarkers for early diagnosis. "

The discovery will also help develop a better technique for collecting information from patients' blood.

Marilena Hadjidemetriou, author of the University of Manchester study, said: "Blood is a potential mine of information, but it is difficult to amplify cancer signals that would otherwise be buried in" noise ". "

Caroline Dive, an expert professor of liquid biopsies at Cancer Research UK, said, "Liquid biopsies are faster, less expensive, and less invasive than many other tests, and this technique is an important step in the development of a such test. "

It is planned to use the technique in mice to help find the best models of biomarkers to identify cancers in the early stages of the disease.

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