RESUMO
Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.
RESUMO
BACKGROUND: Analysis of circulating tumor DNA (ctDNA) is increasingly used for clinical decision-making in oncology. However, ctDNA could represent ≤ 0.1 % of cell-free DNA in early-stage tumors and its detection requires high-sensitive techniques such as digital PCR (dPCR). METHODS: In 46 samples from patients with early-stage breast cancer, we compared two leading dPCR assays for ctDNA analysis: QX200 droplet digital PCR (ddPCR) system from Bio-Rad which is the gold-standard in the field, and Absolute Q plate-based digital PCR (pdPCR) system from Thermo Fisher Scientific which has not been reported before. We analyzed 5 mL of baseline plasma samples prior to any treatment. RESULTS: Both systems displayed a comparable sensitivity with no significant differences observed in mutant allele frequency. In fact, ddPCR and pdPCR possessed a concordance > 90 % in ctDNA positivity. Nevertheless, ddPCR exhibited higher variability and a longer workflow. Finally, we explored the association between ctDNA levels and clinicopathological features. Significantly higher ctDNA levels were present in patients with a Ki67 score > 20 % or with estrogen receptor-negative or triple-negative breast cancer subtypes. CONCLUSION: Both ddPCR and pdPCR may constitute sensitive and reliable tools for ctDNA analysis with an adequate agreement in early-stage breast cancer patients.
