From Blood to Bedside: A Review of Liquid Biopsy for Minimal Residual Disease and Recurrence Prediction in Early-Stage Breast Cancer

Background Early-stage breast cancer carries a significant risk of recurrence due to undetectable minimal residual disease (MRD). Conventional surveillance lacks sensitivity for early relapse detection. Liquid biopsy, particularly circulating tumor DNA (ctDNA), offers a promising non-invasive strategy to detect MRD and predict recurrence.  Methods This review synthesizes recent evidence on liquid biopsy applications in early-stage breast cancer, with emphasis on MRD detection and recurrence monitoring. We evaluate key assay platforms—including digital droplet PCR (ddPCR), next- generation sequencing (NGS), and cancer personalized profiling by deep sequencing (CAPP-Seq)—and examine their clinical integration.  Results Liquid biopsy demonstrates high sensitivity and specificity in detecting ctDNA at subclinical levels, enabling earlier relapse prediction compared to imaging or serum markers. ddPCR offers affordability and precision for targeted mutations, while NGS and CAPP-Seq provide broader genomic coverage and adaptability. Integration into clinical pathways enables dynamic monitoring from diagnosis through treatment and surveillance. However, challenges remain, including assay standardization, cost, and validation across diverse populations.  Conclusion Liquid biopsy represents a paradigm shift in early-stage breast cancer management, enabling proactive monitoring and individualized treatment. Future priorities include global assay harmonization, large-scale validation trials, and in tegration of multi-omic and AI-based approaches to enhance predictive accuracy and clinical adoption.

Authors

Publication Details

Published
2025-11-11
DOI
https://doi.org/10.38124/ijisrt/25oct1032
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Blood to Bedside: A Review of Liquid Biopsy for Minimal Residual Disease and Recurrence Prediction in Early-Stage Breast Cancer

Ransome Msughve Labe, S. A. Otene, Bamidele Omolabake, B Ojo et al.
Cancer Genomics and Diagnostics
article

From Blood to Bedside: A Review of Liquid Biopsy for Minimal Residual Disease and Recurrence Prediction in Early-Stage Breast Cancer

Ransome Msughve Labe, S. A. Otene, Bamidele Omolabake, B Ojo, Z. L. Gbaa, A. J. Onyewuchi, A. F. Gbaa, L. J. Tsegha
article en

Abstract

Background Early-stage breast cancer carries a significant risk of recurrence due to undetectable minimal residual disease (MRD). Conventional surveillance lacks sensitivity for early relapse detection. Liquid biopsy, particularly circulating tumor DNA (ctDNA), offers a promising non-invasive strategy to detect MRD and predict recurrence.  Methods This review synthesizes recent evidence on liquid biopsy applications in early-stage breast cancer, with emphasis on MRD detection and recurrence monitoring. We evaluate key assay platforms—including digital droplet PCR (ddPCR), next- generation sequencing (NGS), and cancer personalized profiling by deep sequencing (CAPP-Seq)—and examine their clinical integration.  Results Liquid biopsy demonstrates high sensitivity and specificity in detecting ctDNA at subclinical levels, enabling earlier relapse prediction compared to imaging or serum markers. ddPCR offers affordability and precision for targeted mutations, while NGS and CAPP-Seq provide broader genomic coverage and adaptability. Integration into clinical pathways enables dynamic monitoring from diagnosis through treatment and surveillance. However, challenges remain, including assay standardization, cost, and validation across diverse populations.  Conclusion Liquid biopsy represents a paradigm shift in early-stage breast cancer management, enabling proactive monitoring and individualized treatment. Future priorities include global assay harmonization, large-scale validation trials, and in tegration of multi-omic and AI-based approaches to enhance predictive accuracy and clinical adoption.

Openalex Percentile: Top 59%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.