A Digital Score Based on Circulating-Tumor-Cells-Derived mRNA Quantification and Machine Learning for Early Colorectal Cancer Detection.

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Tác giả: Ruidong Chen, Pi Ding, Yunyun Hu, Cheng Li, Renjun Pei, Wei Peng, Na Sun, Zhili Wang, Xiaodong Yang, Kui Zhao, Zeyang Zhou

Ngôn ngữ: eng

Ký hiệu phân loại: 512.24 Algebras based on group properties

Thông tin xuất bản: United States : ACS nano , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 745390

Circulating tumor cells (CTCs) serve as valuable biomarkers in tumor circulation, carrying essential primary tumor information. The purification of CTCs from peripheral blood samples and the analysis of their characteristic molecules enable the detection of tumors at an early stage. The noninvasive, continuous, real-time dynamic monitoring provides a promising solution for the timely diagnosis of colorectal cancer (CRC). In this study, we developed a minimally invasive method for CRC early detection to enable accurate screening in a friendly manner for individuals who generally require colonoscopy. The dual-antibody (i.e., anti-EpCAM and anti-EGFR) modified antifouling hydrogel-coated magnetic nanoparticles (pSBMA-MNPs) were prepared for efficient and specific CTC purification. Then, the quantification of 6 RNA transcripts in purified CRC CTCs was performed via droplet digital PCR (ddPCR), and a CRC score was calculated using an extreme gradient boosting model to distinguish CRC from colon polyps and adenomas. A pilot study was conducted to evaluate the clinical potential of the CRC CTC RNA assay in a training cohort (
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