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Hodgkin lymphoma (HL) represents a neoplasm primarily affecting adolescents and young adults, necessitating the development of precise diagnostic and monitoring tools. Specifically, classical Hodgkin lymphoma (cHL), comprising 90% of cases, necessitating tailored treatments to minimize late toxicities. Although positron emission tomography/computed tomography (PET/CT) has enhanced response assessment, its limitations underscore the urgency for more reliable progression predictive tools. Genomic characterisation of rare Hodgkin Reed-Sternberg (HRS) cells is challenging but essential. Recent studies employ single-cell molecular analyses, mass cytometry, and Next-Generation Sequencing (NGS) to unveil mutational landscapes. The integration of liquid biopsies, particularly circulating tumor DNA (ctDNA), extracellular vesicles (EVs), miRNAs and cytokines, emerge as groundbreaking approaches. Recent studies demonstrate ctDNA's potential in assessing therapy responses and predicting relapses in HL. Despite cHL-specific ctDNA applications being relatively unexplored, studies emphasize its value in monitoring treatment outcomes. Overall, this review underscores the imperative role of liquid biopsies in advancing HL diagnosis and monitoring., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Breast cancer (BC) is the most prevalent cancer in women. While usually detected when localized, invasive procedures are still required for diagnosis. Herein, we developed a novel ultrasensitive pipeline to detect circulating tumor DNA (ctDNA) in a series of 75 plasma samples from localized BC patients prior to any medical intervention. We first performed a tumor-informed analysis to correlate the mutations found in tumor tissue and plasma. Disregarding the tumor data next, we developed an approach to detect tumor mutations in plasma. We observed a mutation concordance between the tumor and plasma of 29.50% with a sensitivity down to 0.03% in mutant variant allele frequency (VAF). We detected mutations in 33.78% of the samples, identifying eight patients with plasma-only mutations. Altogether, we determined a specificity of 86.36% and a positive predictive value of 88.46% for BC detection. We demonstrated an association between higher ctDNA median VAF and higher tumor grade, multiple plasma mutations with a likelihood of relapse and more frequent TP53 plasma mutations in hormone receptor-negative tumors. Overall, we have developed a unique ultra-sensitive sequencing workflow with a technology not previously employed in early BC, paving the way for its application in BC screening.