New Liquid Biopsy Approach Shows Promise for Detecting Breast Cancer Recurrence

Researchers are evaluating whether additional features of circulating cell-free DNA (cfDNA) can better reflect tumor biology tied to treatment resistance and relapse. At Kumamoto University, investigators analyzed nucleosome patterns and fragment-size signatures in cfDNA from patients with primary and recurrent disease. New findings demonstrate that a nucleosome-focused approach can differentiate recurrent from primary breast cancer in a retrospective cohort.

Kumamoto University researchers developed a “transcriptionally informed” nucleosome profiling strategy that examines how DNA is packaged around histone proteins within nucleosomes. Because nucleosome positioning reflects gene regulation and chromatin accessibility, patterns in blood-derived cfDNA can capture regulatory changes occurring within cancer cells rather than sequence mutations alone. The team focused on 26 genomic regions previously associated with transcriptional changes that emerge as breast cancer cells develop resistance to hormone therapy, reasoning that these loci could provide insight into recurrence biology.

The study analyzed cfDNA from 150 breast cancer samples, including 105 from primary tumors and 45 from recurrent or metastatic disease. Compared with primary samples, recurrent disease showed a greater number of genetic variants and shorter cfDNA fragments. Two genomic regions, RERE and SYNPO2, were particularly discriminative, and a nucleosome-based score derived from these loci distinguished primary from recurrent disease with an area under the curve (AUC) of 0.826. Combining nucleosome metrics with other cfDNA features through machine learning further improved recurrence prediction within the dataset.

The authors note that cfDNA may provide insights beyond mutation snapshots by reflecting gene regulatory and chromatin changes associated with therapeutic resistance and relapse. Because cfDNA is obtained from a blood sample, the approach could contribute to minimally invasive monitoring during and after treatment, potentially enabling earlier detection of recurrence and more personalized decisions. The retrospective nature of the analysis and differences in breast cancer subtypes and patient backgrounds underscore the need for larger, prospective studies to clarify generalizability. The research, involving the Institute of Molecular Embryology and Genetics (IMEG) and Kumamoto University Hospital, was published in Cancer Research Communications on June 15, 2026.

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