Low-cost lab-on-a-chip blood test detects lung cancer without DNA sequencing

Lung cancer may soon be easier to detect with a technology that sounds more like a laboratory scanner than a conventional diagnostic test. Researchers at Tel Aviv University have developed a low-cost blood test that identifies lung cancer by reading the tumor’s biological “fingerprint” in fragments of DNA circulating through the bloodstream. Unlike many liquid-biopsy systems, the method does not require DNA sequencing, potentially making it faster, less expensive, and easier to implement in standard clinical laboratories.

In an initial study, the test distinguished people with stage 2–4 lung cancer from healthy individuals with a sensitivity of 93.1% and a specificity of 90.3%. Sensitivity measures how accurately a test identifies people who have a disease, while specificity reflects how reliably it rules out disease in people who do not have it. Although the results are preliminary and will require validation in much larger populations, the performance suggests that the technology could eventually complement medical imaging in the diagnosis and monitoring of lung cancer.

The approach focuses on cell-free DNA, small fragments released into the bloodstream when cells die. Blood contains DNA from many tissues, but tumor-derived fragments can carry molecular patterns that differ from those found in healthy cells. Rather than reading the complete genetic sequence of each fragment, the researchers analyze chemical characteristics associated with specific genomic regions. These patterns can reflect changes in the way cancer cells package and regulate their DNA, creating a molecular signature that is detectable even when the fragments themselves are present in small amounts.

To measure this signature, the team first extracts cell-free DNA from a blood sample and attaches a light-emitting label to it. The labeled material is then exposed to a specially designed DNA chip containing probes corresponding to selected genomic regions. If fragments in the sample interact with particular probes, the chip produces a characteristic optical pattern. A scanner records the pattern, and analytical software compares it with profiles associated with cancer or healthy tissue. The process converts a complex molecular signal into a visual readout that can be interpreted without sequencing the entire genome.

The researchers initially identified a panel of 170 genomic regions that together formed a diagnostic signature. Their study included 103 participants: 51 people with lung cancer and 52 healthy control subjects. After training a model using part of the data, the team evaluated the signature in a separate validation group under blinded conditions, meaning the analysis was performed without revealing the participants’ clinical status. The strong results in this testing phase indicate that the signature was not simply recognizing obvious differences in the original training samples.

The chip also showed promise in distinguishing between two major forms of non-small cell lung cancer: adenocarcinoma and squamous cell carcinoma. These cancers arise from different types of cells and can respond differently to treatment. Their distinct DNA-associated patterns suggest that the technology may eventually provide more than a simple positive-or-negative result. With further research, the same platform could help characterize tumor subtypes and support more individualized decisions about diagnosis and therapy.

The researchers also explored whether the test could track how patients respond to treatment. In patients whose tumors responded according to medical imaging, the blood-based chemical fingerprint shifted toward the pattern observed in healthy individuals. Patients who did not respond showed no comparable change. This finding raises the possibility that a blood test could provide an additional, less invasive way to follow disease activity between scans. However, the monitoring analysis involved a limited number of patients and should be considered exploratory until confirmed in prospective, large-scale clinical studies.

The need for improved tools is substantial. Lung cancer remains the leading cause of cancer-related death worldwide, yet detecting it early can be difficult. Computed tomography scans can identify suspicious nodules, but many of these findings are ultimately benign. False-positive results may lead to repeated imaging, invasive biopsies, anxiety, and occasionally unnecessary surgery. Existing liquid biopsies can offer molecular information, but sequencing-based systems often require costly instruments, specialized personnel, and substantial computational resources.

According to the research team, the new test could be completed in approximately two to three days at an estimated cost of about $60 per sample. Those figures could make the platform attractive for laboratories that cannot support comprehensive sequencing workflows. Still, the test is not a replacement for CT imaging or pathological examination, and its reported accuracy does not yet establish how it would perform in routine screening, where many tested individuals would not have cancer. The next steps will include recruiting larger and more diverse patient groups, testing earlier-stage disease, and determining how the method performs alongside established clinical tools.

The Tel Aviv University study, conducted with collaborators from JaxBio Technologies, Bnai Zion Medical Center, and Sheba Medical Center, points toward a different model for liquid biopsy: instead of decoding every letter of tumor DNA, clinicians may be able to recognize cancer through a compact optical signature. If future studies confirm the findings, a simple DNA-chip assay could help reduce diagnostic delays, distinguish lung cancer subtypes, and provide a convenient way to monitor treatment response. For now, the technology remains an investigational advance, but its combination of speed, affordability, and sequencing-free molecular analysis makes it one of the more intriguing developments in the search for accessible cancer diagnostics.

Web References: https://doi.org/10.1038/s41698-026-01547-2; Study video

References: npj Precision Oncology, DOI: 10.1038/s41698-026-01547-2

Keywords

Lung cancer, cancer diagnosis, liquid biopsy, cell-free DNA, DNA chip, DNA methylation, optical scanning, precision oncology, cancer biomarkers, treatment monitoring