Microenvironment‐Guided Evolution of ssDNA‐SWCNT Probes for Selective Recognition of Aggressive Prostate Cancer Phenotypes

Despite advances in prostate cancer detection, distinguishing indolent from aggressive phenotypes remains challenging. We report a microenvironment-guided strategy for evolving phenotype-specific molecular probes using single-stranded DNA-functionalized single-walled carbon nanotubes (ssDNA-SWCNTs). Our approach employs 3D tumor models that recapitulate complex cancer microenvironments, enabling identification of ssDNA sequences with differential binding properties. We developed two distinct probes for prostate cancer cells: PC3D2, which preferentially binds hypoxia-adapted stem-like cells associated with treatment resistance, and PC2D2, which shows enhanced binding to mesenchymal-like cells. These probes exhibit characteristic second near-infrared (NIR-II, 1000-1700 nm) fluorescence, enabling non-invasive detection of aggressive phenotypes in heterogeneous tumors using NIR-II optical imaging. We demonstrate their utility for selective drug delivery to prostate cancer spheroids, resulting in enhanced therapeutic efficacy. This platform represents a significant advancement in precision diagnostics and theranostics, potentially transforming prostate cancer management through phenotype-specific targeting. The methodology offers a generalizable approach for developing nanoprobes that recognize clinically relevant cancer phenotypes based on their unique microenvironmental signatures rather than individual biomarkers.

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Publication Details

Journal
Advanced Science
Published
2026-01-21
DOI
https://doi.org/10.1002/advs.202518582
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
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article

Microenvironment‐Guided Evolution of ssDNA‐SWCNT Probes for Selective Recognition of Aggressive Prostate Cancer Phenotypes

Seong-Hyo Oh, Dakyeon Lee, Seulgi Lee, YS Jung et al.
Advanced Science
Advanced biosensing and bioanalysis techniques
article

Microenvironment‐Guided Evolution of ssDNA‐SWCNT Probes for Selective Recognition of Aggressive Prostate Cancer Phenotypes

Seong-Hyo Oh, Dakyeon Lee, Seulgi Lee, YS Jung, Byoung Soo Kim, Sungjee Kim, Min‐Seo Choi, Sanghwa Jeong, Seok‐Hyeon Lee
article en

Abstract

Despite advances in prostate cancer detection, distinguishing indolent from aggressive phenotypes remains challenging. We report a microenvironment-guided strategy for evolving phenotype-specific molecular probes using single-stranded DNA-functionalized single-walled carbon nanotubes (ssDNA-SWCNTs). Our approach employs 3D tumor models that recapitulate complex cancer microenvironments, enabling identification of ssDNA sequences with differential binding properties. We developed two distinct probes for prostate cancer cells: PC3D2, which preferentially binds hypoxia-adapted stem-like cells associated with treatment resistance, and PC2D2, which shows enhanced binding to mesenchymal-like cells. These probes exhibit characteristic second near-infrared (NIR-II, 1000-1700 nm) fluorescence, enabling non-invasive detection of aggressive phenotypes in heterogeneous tumors using NIR-II optical imaging. We demonstrate their utility for selective drug delivery to prostate cancer spheroids, resulting in enhanced therapeutic efficacy. This platform represents a significant advancement in precision diagnostics and theranostics, potentially transforming prostate cancer management through phenotype-specific targeting. The methodology offers a generalizable approach for developing nanoprobes that recognize clinically relevant cancer phenotypes based on their unique microenvironmental signatures rather than individual biomarkers.

Advanced ScienceVol. 13(17)
Pohang University of Science and Technology (KR), Pusan National University Yangsan Hospital (KR), Pusan National University (KR)
Openalex Percentile: Top 81%
Advanced biosensing and bioanalysis techniques
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Microenvironment‐Guided Evolution of ssDNA‐SWCNT Probes for Selective Recognition of Aggressive Prostate Cancer Phenotypes — Seong-Hyo Oh, Dakyeon Lee, et al. · Advanced Science (2026) | TGRS Research Map | TGRS