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Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential

Medicine and Health

Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential

W. Zhang, F. Xu, et al.

Explore groundbreaking research by Wenjun Zhang and colleagues as they unveil a molecular typing system predicting the metastatic potential of colorectal cancer through unique metabolic fingerprints of circulating tumor cells. Their findings highlight how specific tumor cell populations may significantly impact cancer progression.

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Playback language: English
Abstract
This study develops a molecular typing system to predict colorectal cancer metastasis potential based on single circulating tumor cell (CTC) metabolic fingerprints. Using mass spectrometry-based untargeted metabolomics, a home-built single-cell quantitative mass spectrometry platform, and a machine learning method, CTCs are divided into two subgroups (C1 and C2). In vitro and in vivo experiments show that C2 CTC count strongly correlates with metastasis incidence, suggesting a specific CTC population with distinct metastatic potential.
Publisher
Nature Communications
Published On
Apr 29, 2023
Authors
Wenjun Zhang, Feifei Xu, Jiang Yao, Changfei Mao, Mingchen Zhu, Motiq Qian, Jun Hu, Huilin Zhong, Junsheng Zhou, Xiaoyu Shi, Yun Chen
Tags
colorectal cancer
circulating tumor cells
metastasis
metabolomics
machine learning
mass spectrometry
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