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Minimally Invasive Biopsies Provide Maximum Pathology Data

September 19, 2019


Current pathology techniques for analyzing biopsy tissues are lacking in their ability to detect cancer in small samples. Being able to rapidly study the distribution of protein expression within cells, gathered from minuscule samples, could be an important tool for early diagnosis and monitoring of cancer.


Now, researchers at National University of Singapore have reported in Nature Biomedical Engineering that they have been able to use programmable DNA barcodes to measure and localize billions of protein markers within just a couple of hours.

Called STAMP (Sequence-Topology Assembly for Multiplexed Profiling), the technology requires only a small sample from a fine needle aspiration biopsy. Implemented on a small microfluidic device, and with each test expected to cost roughly $50, the technology will hopefully find space inside every hospital lab.

The researchers showed that STAMP has a near 95% diagnostic accuracy and provides pathology data that currently can only be gathered once extensive lesion tissue is removed during surgery.

“To label diverse protein markers in cells, STAMP uses DNA barcodes which are folded as compact nanostructures. These 3D barcodes achieve a high labeling efficiency and remain stable against biological degradation. Each 3D barcode is further given a localization label to encode protein marker location and distribution within the cell,” explained Mr Noah Sundah, a doctoral student from NUS iHealthtech as well as NUS Biomedical Engineering, and first author of the study, in a press release. “To perform analysis, these 3D barcodes are unfolded on-demand through heating to release a pool of linear DNA, which can be easily analyzed using established technologies such as PCR and DNA sequencing. In this way, the expression of a very large number of protein markers and their distribution in cells can be sensitively measured in a single test”.

See Full Article: Minimally Invasive Biopsies Provide Maximum Pathology Data | Medgadget

Written by: Medgadget Editors

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