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Novel technology to determine classification of cancer cells through DNA barcodes
A team of researchers form the National University of Singapore (NUS) have developed a novel technology that could sensitively and accurately detect and classify cancer cells from a small clinical sample.

This new technology, STAMP (Sequence-Topology Assembly for Multiplexed Profiling) will provide quicker and more comprehensive disease information at an earlier stage of the clinical workflow, allowing doctors to decide and administer treatments earlier and more effectively.

The STAMP technology uses programmable DNA barcodes to measure billions of protein markers in a single test – the amount as well as the distribution of these protein markers in a cell – from a small clinical sample.

Led by Assistant Professor Shao Huilin from the NUS Institute for Health Innovation & Technology (NUS iHealthtech), the 10-member research team spent over two years to develop STAMP.

“Current pathology techniques only measure a small subset of protein markers and require several days of extensive processing. In comparison, STAMP is a million times more sensitive, provides highly informative analysis from scarce samples, and can be completed in as little as two hours,” said Asst Prof Shao.

To facilitate clinical processing and measurement, the research team implemented the STAMP technology on a small microfluidic chip that is about half the size of a credit card. Test results could be generated from small amounts of clinical samples, and each test is estimated to cost US$36.

To validate STAMP’s performance, the research team conducted a clinical study involving 69 breast cancer patients. FNA (fine needle aspiration) biopsies were collected from each patient and analysed using STAMP. For comparison, gold-standard pathology analysis was performed on post-surgery tissues for all patients.

The STAMP analysis of the FNA samples demonstrated a high level of accuracy of more than 94 percent for cancer diagnosis and subtyping, making it equally accurate as pathology analysis of surgical tissues. Importantly, based on its comprehensive protein marker analysis, STAMP was also able to accurately identify disease aggressiveness from the scarce biopsy samples.

A provisional patent has been filed for STAMP. Asst Prof Shao and her team are currently in discussions with industry partners to further develop and commercialise this technology. The technology is expected to reach the market within the next five years. The research team hopes to expand the applications of STAMP to other types of cancer, such as brain, lung, and gastric cancer, as well as validate the technology in other samples, such as blood and ascites.

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