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A single blood sample taken before surgery may one day help doctors identify colorectal cancer patients at greater risk of recurrence or metastasis, according to new research from scientists at the Korea Advanced Institute of Science and Technology (KAIST), Gangnam Severance Hospital and Asan Medical Center.
The study found that as colorectal cancer progresses, it reshapes the body’s metabolism in ways that can be detected in the blood. Rather than focusing only on the levels of individual amino acids, the researchers examined how those molecules interact with each other, creating what they describe as a metabolic “network.”
Their findings suggest that these changing patterns could provide a more informative picture of cancer progression than existing approaches based on individual amino acid measurements alone.
Cancer cells require large amounts of nutrients to grow and divide. Amino acids, which are used to build proteins and support energy production and DNA synthesis, are particularly important to the process.
Previous studies have largely focused on measuring the concentrations of individual amino acids in blood samples. The new research instead examined the relationships among 18 circulating amino acids measured from a small serum sample.
Using fluorine-19 nuclear magnetic resonance spectroscopy, the team found that the amino acid network became progressively reorganized as colorectal cancer advanced. The researchers said the changes reflect broader metabolic alterations occurring throughout the body during tumor progression.
Among the shifts observed, branched-chain amino acids such as valine and leucine, which play important roles in muscle and energy metabolism, became less prominent as disease progressed. At the same time, glycine and serine—amino acids used by cancer cells for DNA synthesis and rapid growth—became more prominent.
One of the study’s most notable findings involved glycine. Although rapidly growing cancer cells actively consume the amino acid, the researchers found its relative abundance in the bloodstream increased as colorectal cancer advanced.
They also identified a glycine-centered interaction pattern within the amino acid network, which they interpreted as additional evidence of widespread metabolic remodeling.
The team then incorporated these amino acid interaction features into machine-learning models designed to identify patients who experienced recurrence or metastasis.
According to the study, a model based on amino acid interactions outperformed one using only carcinoembryonic antigen (CEA), a commonly used blood marker in colorectal cancer. The strongest performance came from a model that combined CEA, individual amino acid levels and interaction-derived features. It also performed better than a model built solely on individual amino acid measurements.
The findings suggest that understanding how amino acids change together may provide information about cancer progression that would be missed by looking at each amino acid independently.
Professor Ji Min Lee, who led the study, said the researchers hope the approach could support more precise treatment decisions in the future.
“We hope this will lead to new precision medicine technologies that can predict recurrence risk more accurately using a blood sample alone and help establish personalized treatment strategies,” Lee said.
Outside experts say the results are intriguing but caution that further validation is needed before the method could affect how patients are treated.
“The approach needs to be validated in larger studies since it’s difficult to draw a definitive conclusion from such a small population-based study,” Dr. Michael F. Driscoll, director of the Gastrointestinal Malignancy Program at Norton Healthcare, told Newsweek. “This approach could be used as an add-on to other tests if it were validated in larger studies.”
Driscoll said one obstacle facing many blood-based biomarker tests is gaining widespread adoption in clinical practice.
“The challenge of incorporating blood-based biomarker assays into clinical practice is often related to insurance coverage, as many of these tests are considered ‘experimental’,” he said.
Additional evidence would also be required before doctors could rely on the approach when making treatment decisions, he added.
For now, he noted that many gastrointestinal oncologists already use another blood-based method after surgery to assess recurrence risk.
“Currently most gastrointestinal oncologists use CT-DNA (circulating tumor DNA) in the postoperative setting to determine risk of recurrence,” Driscoll said. “This is currently the most sensitive test we have for predicting recurrence and has been validated in multiple large studies.”
While the new findings do not establish a clinical test ready for routine use, they provide evidence that the interactions among circulating amino acids could serve as a promising blood-based biomarker for tracking colorectal cancer progression and identifying patients who may face a higher risk of the disease returning or spreading.
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The study’s co-first authors are Ji-Yeon Lee, a student in the integrated master’s and doctoral program at the Graduate School of Medical Science and Engineering, and Dr. Jumi Kim, a postdoctoral researcher in the Department of Chemistry. Professors Ji Min Lee and Hyunwoo Kim of KAIST and Professor Eun Jung Park, affiliated with Gangnam Severance Hospital and Asan Medical Center, served as co-corresponding authors. The findings were published online in Advanced Science, which has a Journal Impact Factor of 14.1, on June 9, 2026.
“Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis,” DOI: 10.1002/advs.76044
Contact Newsweek editors on this story: Kara Dolman and Gray R. Thomas
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