AI Blood Test Shows Promise for Early Liver Cancer Detection
Key Developments:
- Researchers validated an AI-powered blood test that accurately detects liver cancer across diverse populations.
- The test analyzes fragments of cell-free DNA and outperformed existing blood-based screening methods when combined with clinical factors.
- Scientists say the technology could eventually support earlier detection of multiple diseases using a single blood-testing platform.
(News Medical Life Sciences) — August 01, 2026: A team of researchers from the Johns Hopkins Kimmel Cancer Center has successfully validated an artificial intelligence (AI)-powered blood test capable of detecting liver cancer across geographically and biologically diverse populations, offering new hope for earlier diagnosis of one of the world’s deadliest cancers.
The findings, published on 31 July 2026 in the peer-reviewed journal Cell Press Blue, build on the researchers’ previously developed DELFI (DNA Evaluation of Fragments for Early Interception) liquid biopsy platform. The technology examines millions of fragments of cell-free DNA circulating in the bloodstream to identify biological patterns associated with liver cancer.
According to the research team, the study confirmed that the AI-driven test maintained strong performance when evaluated in independent high-risk populations from Guatemala and Romania, despite significant differences in the causes of liver disease between the two regions.
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Lead researcher Dr. Victor Velculescu, Cancer Genetics and Epigenetics Professor at Johns Hopkins, said: “Our earlier studies showed that fragmentome analyses could detect liver cancer and, more recently, chronic liver diseases that increase cancer risk. This study demonstrates that the approach works with high performance across different patient populations while revealing the biological signals in the bloodstream that make this type of detection possible.”
Existing Screening Still Faces Challenges
Liver cancer remains among the leading causes of cancer-related deaths worldwide. Medical experts note that early detection significantly improves treatment options, but current screening methods—primarily ultrasound imaging and the blood protein alpha-fetoprotein (AFP)—can fail to identify many early-stage cancers.
To evaluate the new technology, researchers analyzed blood samples from 377 individuals, including patients with and without hepatocellular carcinoma, the most common form of liver cancer.
Participants from Romania primarily developed liver disease linked to viral hepatitis or alcohol use, while many participants from Guatemala had metabolic liver disease, obesity, diabetes, and, in some cases, exposure to aflatoxin, a naturally occurring toxin associated with liver cancer.
Despite these biological differences, the AI-powered test consistently detected liver cancer across both populations.
Researchers reported that combining the DELFI blood test with AFP measurements and basic clinical information such as age and sex improved the detection of both early- and late-stage liver cancers compared with conventional blood testing alone.
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AI Detects More Than Tumor DNA
The study also introduced a new analytical method known as MethID, which enables scientists to identify the origin of DNA fragments found in the bloodstream.
Researchers discovered that the test captures biological signals not only from tumor cells but also from liver tissue, blood vessels and immune cells responding to cancer.
Co-senior author Dr. Zachariah Foda explained: “As a result, these DNA fragments contain much more information than whether cancer is present. It tells us where these fragments originate and how they change during cancer development, allowing us to better understand the biology of the disease and improve our ability to detect it.”
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Findings May Support Broader Disease Detection
Scientists also identified molecular differences between the two study populations, including genetic patterns associated with aflatoxin exposure in participants from Guatemala. However, the overall AI classifier remained effective regardless of the underlying cause of liver cancer.
The researchers believe this demonstrates that genome-wide fragmentome analysis can identify both universal and region-specific biological signatures, making the technology potentially useful across diverse populations.
The team further suggested that similar fragmentome-based approaches may eventually support non-invasive detection of multiple diseases, including cancers and chronic liver conditions, using a common testing platform.
Earlier research published in March 2026 showed that related technology could detect liver fibrosis and cirrhosis, diseases that often precede liver cancer.
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Researchers Call for Further Clinical Validation
While the results are encouraging, the authors emphasize that additional prospective clinical studies are required before the test can become part of routine healthcare.
Future research will focus on larger clinical trials and combining fragmentome analysis with protein biomarkers and patient risk factors to further improve early cancer detection.
The study was supported by several research organizations, including the U.S. National Institutes of Health, the Department of Defense, philanthropic foundations and research funding associated with DELFI Diagnostics.
Healthcare experts note that although the technology shows significant promise, it should not yet be considered a replacement for established medical screening guidelines until further clinical validation and regulatory review are completed.
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