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Breakthrough: AI detects hundreds of "invisible" cancer markers

In one trial, the DOLPHIN tool analyzed single-cell data from pancreatic cancer patients and detected more than 800 disease markers that conventional tools missed.

VietnamPlusVietnamPlus02/10/2025

Researchers at McGill University (Canada) have just developed a new artificial intelligence (AI) tool capable of detecting invisible disease markers inside individual cells, opening up the prospect of earlier diagnosis and more accurate treatment options for patients.

The tool, called DOLPHIN, is described in a study published in the journal Nature Communications. According to the authors, this method could help doctors reduce the "trial and error" in treatment by identifying the most suitable therapy for each patient.

Disease markers often appear as subtle changes in RNA expression, reflecting the presence, severity, or response to treatment of disease.

Traditional analysis methods only summarize at the gene level, leaving many important signals obscured. DOLPHIN uses AI to analyze in detail how small segments called exons are connected to each other, thereby revealing genetic markers that have been overlooked.

"Genes are not just one block, but more like Lego blocks made up of many small pieces. By looking at how the pieces are connected, our tool uncovers important disease markers that have long been overlooked," said lead author Kailu Song, a PhD student.

In one trial, DOLPHIN analyzed single-cell data from pancreatic cancer patients and detected more than 800 disease markers that conventional tools missed.

Thanks to that, the system can distinguish between patients with rapidly progressing, high-risk cancer and those with milder conditions, key information that helps doctors come up with appropriate treatment regimens.

In addition to its immediate application value, the project also lays the foundation for the long-term goal of building a virtual cell model.

The detailed single cell profiles generated by DOLPHIN can serve to simulate cell behavior and drug response, before entering laboratory or clinical testing, saving significant time and costs.

The research team said the next step will be to expand the application of this tool on millions of cells, thereby creating more accurate virtual cell models in the future./.

(TTXVN/Vietnam+)

Source: https://www.vietnamplus.vn/dot-pha-ai-phat-hien-hang-tram-dau-an-ung-thu-vo-hinh-post1067476.vnp


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