USA – A cutting-edge pathology tool developed at Yale University, Patho-DBiT (pathology-compatible deterministic barcoding in tissue), is set to transform cancer diagnostics by using barcode technology to analyze tissue samples with unprecedented detail.
The tool, which was recently featured in Cell, provides molecular-level insights into RNA and protein spatial relationships within tissue, promising significant advancements in personalized cancer treatments.
Patho-DBiT, designed in the lab of Rong Fan, PhD, at Yale’s School of Medicine, maps out the spatial organization of RNA and proteins in tissue samples, revealing their regulatory roles in cancer.
The technology is uniquely equipped with microfluidic devices that deliver barcodes into tissue from two directions, forming a 2D “mosaic” of data points.
This spatial mapping could serve as a foundation for developing targeted, patient-specific therapies.
“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 Dr. Fan, who is a professor of Biomedical Engineering and Pathology at Yale and a senior author of the study.
“Using this tool, we’re able to better understand the fascinating biology of each RNA molecule. It’s going to completely transform how we study the biology of humans in the future.”
The Power of Deep Molecular Analysis
As co-author and Yale Cancer Center member Dr. Mina Xu, MD, explains, the power of Patho-DBiT lies in its ability to reveal new insights into tumor biology.
Dr. Xu, who is a professor of Pathology and the director of Hematopathology at Yale, emphasized the diagnostic potential of the tool, stating, “As a physician who has been diagnosing cancer, I was surprised by how much more I can see using this pathology tool.
“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.”
The technology is already licensed to AtlasXomics, a Yale spin-out, signaling a move toward commercializing the innovation for broader applications in cancer treatment.
Advancing cancer treatment and diagnostics
Traditional pathology methods are often limited in their ability to capture the full molecular picture in tissue samples.
The researchers at Yale believe Patho-DBiT could bridge this gap, unlocking what the study’s first author, Dr. Zhiliang Bai, PhD, called a “wealth of information” preserved in laboratory biopsies.
Dr. Bai explained, “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 a spatial level.
“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.”
With its ability to track RNA and proteins precisely, Patho-DBiT has potential applications in mapping the mechanisms behind tumor progression, offering hope for early intervention in cases where low-grade tumors transform into more aggressive forms.
This spatial data could enable researchers to better understand—and possibly prevent—tumor development.
Yale’s collaborative approach to innovation
The development of Patho-DBiT involved a collaborative team from Yale’s Biomedical Engineering, Pathology, and Genetics departments.
Dr. Jun Lu, associate professor of genetics and co-author of the study, praised Patho-DBiT’s capability to generate spatial maps of noncoding RNA expression, shedding light on regions of the genome once thought to be “junk DNA.”
“It is very exciting that Patho-DBiT-seq is also capable of generating spatial maps of noncoding RNA expression,” Dr. Lu remarked.
“Noncoding RNAs are often in regions of our genomes that were previously thought of as junk DNA, but now they are recognized as treasured players in biology and diseases such as cancer.”
Next steps and future potential
While the technology holds considerable promise, the research team emphasizes that more studies are required to test and validate Patho-DBiT with patient samples before it can be used in clinical settings.
With additional research, Patho-DBiT could potentially become a vital tool in pathology diagnostics, making it possible to create highly personalized cancer treatments.
Supported by the National Institutes of Health (NIH), this research marks a critical step toward integrating advanced molecular analysis into everyday clinical pathology.
