Large‐Scale Quantitative Morphometry of Platelet α‐Granules via SIM Super‐Resolution Microscopy for Cancer Liquid Biopsy
Year: 2026
Type: article
Study design: Observational Study
Abstract: Blood-based liquid biopsies hold transformative potential for non-invasive cancer management, but current approaches relying on rare circulating tumor components limit their broad clinical utility. Platelets, abundant in blood and mediating diverse cancer-associated responses, represent a compelling yet largely unexplored alternative. Using SIM super-resolution microscopy, we analyzed α-granule distributions in platelets from a multicenter cohort (n = 1,556) encompassing nine cancer types and twelve non-malignant diseases. We identified robust cancer-associated alterations, particularly a marked increase in the "Circle" pattern, which exhibits excellent multi-cancer diagnostic potential. This method, termed PAID (Platelet Alpha-granule Imaging-based Diagnostic assay), achieved 85.0% accuracy in prostate cancer within the diagnostically challenging PSA "gray zone". PAID combined with PSA improved diagnostic accuracy to 94.2%, 38.4% over PSA alone, suggesting significant synergy. In ovarian cancer, PAID combined with HE4 enhanced diagnostic accuracy from 73.8% to 88.3%. Furthermore, PAID outperformed CA125 in sensitivity (90.3% vs 60.0%) for detecting ovarian cancer recurrence. We also observed that tumor cells may utilize both tumor-derived exosomes and proteins to remodel platelet α-granule distributions, suggesting the increased "Circle" pattern arises from synergistic rather than singular triggers. The non-invasive, highly accurate PAID shows great promise in advancing liquid biopsy for cancer management.
Source: Advanced Science
DOI: 10.1002/advs.75094
Authors: Yan Ma, Huan Deng, Zelin Liu, Simei Zhong, Liangliang Wang, Mu He, Ning Jing, Lihua Dai, Yuzhen Basang, Xiao‐Yu Hu, Changyi Zhang, Huimin Zeng, Haoren Shao, Zhe Yang, Shanshan Zhao, Xiaohai Hu, Chuanjie Zhang, Xiaowei Wu, Jing Xu, Shaoqun Zeng, Jing Yuan, Qiang Li, Ziwei Qu, Zhenya Hong, Lingjuan Chen, Hanhua Dong, Jia Guo, Zhiqiang Han, Yu‐Hui Zhang
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $6,730
Awards: G4372715596, G747099067, G7526603168
OpenAlex ID: W7153241962
