In a groundbreaking advancement poised to transform breast cancer management, researchers at Lund University have developed a novel blood test capable of detecting the recurrence of breast cancer long before conventional imaging or symptoms emerge. This pioneering approach leverages the detection of minute fragments of tumor-derived DNA circulating in the bloodstream, heralding a new era in early cancer relapse diagnostics and personalized treatment monitoring.
The technology, known as Pathlight, is founded on the principle that each tumor possesses a unique genetic fingerprint. By performing comprehensive genetic profiling of the tumor tissue, the test identifies specific DNA alterations characteristic of the patient’s malignancy. These tumor-specific DNA fragments, released into the circulation, serve as highly sensitive biomarkers that can be tracked longitudinally to monitor disease presence and treatment response with remarkable precision.
Traditionally, monitoring breast cancer recurrence has relied on imaging techniques or symptom-based evaluations, both of which detect disease only when tumor masses reach a size sufficient for visualization or patient discomfort. This delayed detection often limits the effectiveness of interventions aimed at preventing metastatic progression. Pathlight’s ability to identify circulating tumor DNA (ctDNA) empowers clinicians to detect residual disease at a molecular level, well before clinical signs develop, thereby enabling earlier therapeutic strategies.
In an extended prospective study involving 136 breast cancer patients undergoing neoadjuvant chemotherapy and surgical resection, the research team systematically collected and analyzed serial blood samples across multiple time points: at diagnosis, during chemotherapy, shortly after surgery, and during follow-up intervals extending up to six years. This methodical approach illuminated the dynamics of ctDNA levels in relation to treatment phases and disease outcomes.
Remarkably, the test detected tumor DNA in nearly 90% of patients before commencing chemotherapy, underscoring its high sensitivity. Moreover, approximately 21% of patients exhibited persistent ctDNA even after completion of preoperative chemotherapy, indicating potential residual disease. This finding is particularly significant, as the presence of ctDNA in the perioperative window was robustly correlated with a higher risk of cancer recurrence.
The study further demonstrated that in a subset of patients, ctDNA levels failed to decline clearly during treatment, a molecular signature strongly predictive of relapse. This pattern proved to offer superior prognostic value compared to pathological complete response (pCR), the current standard histopathological measure used to evaluate chemotherapy effectiveness before surgery. These insights portend a shift away from purely tissue-based assessments towards real-time molecular monitoring.
One of the most striking revelations was the temporal lead this technology provides in detecting metastatic disease. For patients who eventually developed metastatic relapse, the blood test identified signs of recurrence at a median of 13.8 months prior to clinical or radiological discovery, with some cases revealing recurrence signals nearly four years earlier. Such an extended lead-time offers a critical window for intervention, potentially improving survival outcomes.
The underlying methodology benefits from being less complex than exhaustive genomic sequencing but is optimized for rapid turnaround and cost-effectiveness without compromising analytic fidelity. This balance is crucial for integrating molecular liquid biopsy techniques into routine clinical workflows, making personalized cancer surveillance accessible on a broader scale.
From a clinical perspective, the implications of this approach are manifold. Beyond early relapse detection, the technology could stratify patients based on molecular risk profiles, guiding escalation of intensive therapies for high-risk cases while sparing low-risk individuals from overtreatment and its attendant toxicities. This precision tailoring of therapy promises to enhance quality of life and reduce healthcare burdens.
Furthermore, the ability to continuously monitor treatment response through longitudinal ctDNA quantification offers dynamic insights into tumor biology and therapeutic efficacy. Such feedback loops can inform adaptive treatment modifications in real time, a significant step toward truly personalized oncology.
Pioneering this research, Dr. Lao Saal and colleagues underscore that while the technology entails trade-offs between depth of genetic information and pragmatic clinical utility, the gains in speed, cost, and prognostic accuracy mark significant progress in breast cancer care. The team envisions expanding studies to refine the test’s predictive capabilities and explore applications across other tumor types.
The test, developed in collaboration with SAGA Diagnostics—a company co-founded by Dr. Saal and acquired recently by Roche—represents the culmination of years of translational research aimed at bridging molecular science and patient outcomes. The study’s publication in EMBO Molecular Medicine signifies recognition by the scientific community of its potential paradigm-shifting impact.
As the field of oncology embraces liquid biopsies for non-invasive cancer detection and monitoring, innovations like Pathlight exemplify the forefront of precision medicine. With future validation and integration, this method could revolutionize how clinicians detect, track, and treat breast cancer, ultimately improving longevity and quality of life for millions worldwide.
Subject of Research: People
Article Title: NeoCircle: pre- and post-operative circulating tumor DNA dynamics predicts survival in neoadjuvant-treated early breast cancer
News Publication Date: 26-May-2026
Image Credits: Credit: Ingemar Hultquist
Keywords: breast cancer, circulating tumor DNA, liquid biopsy, early detection, cancer recurrence, neoadjuvant chemotherapy, tumor genetics, personalized medicine, molecular monitoring, cancer relapse prediction, precision oncology, diagnostic innovation
