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Peer-reviewedCC BYBiosensors

Subtype-Specific Aptamer Technologies for Breast Cancer: From Molecular Recognition to Precision Applications.

  1. 1Key Laboratory of Pharmaceutical Analysis and Medicine of Fujian Province, School of Pharmacy and Medical Technology, Putian University, Putian 351100, China.
  2. 2College of Biological and Food Engineering, Hubei MinZu University, Enshi 445000, China.

Abstract

Breast-cancer management depends on reproducible molecular classification, yet tissue-based assays provide only spatially and temporally restricted views of a heterogeneous disease. Aptamers are programmable single-stranded DNA or RNA ligands that can integrate molecular recognition with biosensing, liquid-biopsy capture and targeted delivery. This review follows the translational chain from aptamer selection and molecular recognition to subtype resolution, signal or cargo conversion, biological validation, and clinical translation. We compare HER2-directed aptamers, ERα- and PHB2-associated tools for hormone-receptor-positive disease, and phenotype-oriented ligands for triple-negative breast cancer. We further organize aptasensors by signal-conversion mechanism, distinguish analytical performance in buffer from that in clinical matrices, and clarify the complementary role of aptamers in liquid-biopsy workflows, including CTC and extracellular-vesicle enrichment alongside separate ctDNA sequence-variant analysis. For theranostic systems, affinity alone is insufficient; pharmacokinetics, receptor trafficking, endosomal escape and comparator-controlled efficacy ultimately determine functional benefit. Aptamers are therefore most compelling as modular recognition elements for multiplexing, reversible engineering, and targeted delivery. Progress will depend on transparent selection reporting, orthogonal target validation, and prospective multicenter studies.

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BibTeX
@article{wu2026subtypespecific,
  title = {{Subtype-Specific Aptamer Technologies for Breast Cancer: From Molecular Recognition to Precision Applications.}},
  author = {Huibin Wu and Zhi Zeng and Wenyi Huang and Xinyan Lin and Rui Tian and Jianmin Chen and Qiulong Zhang},
  journal = {Biosensors},
  year = {2026},
  month = oct,
  doi = {10.3390/bios16100549},
  url = {https://europepmc.org/article/MED/42930096},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Subtype-Specific Aptamer Technologies for Breast Cancer: From Molecular Recognition to Precision Applications.
AU  - Huibin Wu
AU  - Zhi Zeng
AU  - Wenyi Huang
AU  - Xinyan Lin
AU  - Rui Tian
AU  - Jianmin Chen
AU  - Qiulong Zhang
PY  - 2026
DA  - 2026/10/01
JO  - Biosensors
DO  - 10.3390/bios16100549
UR  - https://europepmc.org/article/MED/42930096
AB  - Breast-cancer management depends on reproducible molecular classification, yet tissue-based assays provide only spatially and temporally restricted views of a heterogeneous disease. Aptamers are programmable single-stranded DNA or RNA ligands that can integrate molecular recognition with biosensing, liquid-biopsy capture and targeted delivery. This review follows the translational chain from aptamer selection and molecular recognition to subtype resolution, signal or cargo conversion, biological validation, and clinical translation. We compare HER2-directed aptamers, ERα- and PHB2-associated tools for hormone-receptor-positive disease, and phenotype-oriented ligands for triple-negative breast cancer. We further organize aptasensors by signal-conversion mechanism, distinguish analytical performance in buffer from that in clinical matrices, and clarify the complementary role of aptamers in liquid-biopsy workflows, including CTC and extracellular-vesicle enrichment alongside separate ctDNA sequence-variant analysis. For theranostic systems, affinity alone is insufficient; pharmacokinetics, receptor trafficking, endosomal escape and comparator-controlled efficacy ultimately determine functional benefit. Aptamers are therefore most compelling as modular recognition elements for multiplexing, reversible engineering, and targeted delivery. Progress will depend on transparent selection reporting, orthogonal target validation, and prospective multicenter studies.
SN  - 2079-6374
ER  -