New Barcode Technology Could Help Diagnose Cancer More Precisely

Newswise — A new pathology tool created at Yale harnesses barcode technology and shows potential for use in cancer diagnoses. The technology, Patho-DBiT (pathology-compatible deterministic barcoding in tissue), was discussed in a new study that published Sept. 30 in the journal Cell.

Co-corresponding author Dr. Mina Xu, a Yale Cancer Center (YCC) member, professor of pathology at Yale School of Medicine (YSM), and the YSM director of hematopathology, shared her enthusiasm for the new tool.

“As a physician who has been diagnosing cancer, I was surprised by how much more I can see using this pathology tool,” said Xu. “I think this deep molecular dive is going to advance our understanding of tumor biology exponentially. I really look forward to delivering more precise and actionable diagnoses.”

Patho-DBiT uses DNA barcoding to map the spatial relationships of RNA and proteins, allowing for a full examination of RNA (some types have regulatory roles in cancer). The technology is unique in that it has microfluidic devices that deliver barcodes into the tissue from two directions creating a unique 2D “mosaic” of pixels, providing spatial information that could be used to inform the creation of patient-specific targeted therapies. The technology, created in the lab of Yale’s Rong Fan, is now licensed to Yale spin-out AtlasXomics.

“It’s the first time we can directly ‘see’ all kinds of RNA species, where they are and what they do, in clinical tissue samples,” said Fan, the Harold Hodgkinson professor of biomedical engineering and pathology at YSM, senior author of the study, and a YCC member. “Using this tool, we’re able to better understand the fascinating biology of each RNA molecule which has a very rich life cycle beyond just knowing whether each gene is expressed or not. I think it’s going to completely transform how we study the biology of humans in the future.”

In the study’s manuscript, the researchers explain why their tool, Patho-DBiT, could be the key that unlocks a “wealth of information” preserved in laboratory tissue biopsy samples.

“There are millions of these tissues that have been archived for so many years, but up until now, we didn’t have effective tools to investigate them at spatial level,” said the study’s first author Zhiliang Bai, a postdoctoral associate in Fan’s lab. “RNA molecules in these tissues we’re looking at are highly fragmented and traditional methods can’t capture all the important information about them. It’s why we’re very excited about Patho-DBiT.”

Future potential uses for Patho-DBiT include creating targeted therapies and helping to understand the mechanism of transformation from low-grade tumors to more aggressive ones in order to find ways to prevent it. For Patho-DBiT to be included in pathology diagnostics, researchers say more studies are needed to test and validate patient samples.

This multidisciplinary research included faculty members from several Yale departments, including biomedical engineering, pathology, and genetics. Jun Lu, an associate professor in Yale’s Department of Genetics, joined Fan, Bai, and Xu as a Yale co-author.

"It is very exciting that Patho-DBiT-seq is also capable of generating spatial maps of noncoding RNA expression,” said Lu. “Noncoding RNAs are often in regions of our genomes that were previously thought as junk DNA, but now they are recognized as treasured players in biology and diseases such as cancer.”

The research was supported by the National Institutes of Health (NIH) under Award Numbers RF1MH128876, U54AG079759, UH3CA257393, U54AG076043, U54CA274509, U01CA294514, R01CA245313, RM1MH132648 (all to R.F.), R33CA246711 (to R.F. and J.L.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.