Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
Abstract
The presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot predict LNM accurately. In this study, we detected proteins in formalin-fixed paraffin-embedded (FFPE) tumor samples from 143 LNM-negative and 78 LNM-positive patients with T1 CRC and revealed changes in molecular and biological pathways by label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) and established classifiers for predicting LNM in T1 CRC. An effective 55-proteins prediction model was built by machine learning and validated in a training cohort (N=132) and two validation cohorts (VC1, N=42; VC2, N=47), achieved an impressive AUC of 1.00 in the training cohort, 0.96 in VC1 and 0.93 in VC2, respectively. We further built a simplified classifier with 9 proteins, and achieved an AUC of 0.824. The simplified classifier was performed excellent in two external validation cohorts. The expression patterns of 13 proteins were confirmed by immunohistochemistry, and the IHC score of 5 proteins were used to build a IHC predict model with an AUC of 0.825. RHOT2 silence significantly enhanced migration and invasion of colon cancer cells. Our study explored the mechanism of metastasis in T1 CRC and can be used to facilitate the individualized prediction of LNM in patients with T1 CRC, which may provide a guidance for clinical practice in T1 CRC.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting file; Source Data files have been provided for all figures. The proteome raw data that support the findings of this study have been deposited to the ProteomeXchange Consortium (dataset identifier: PXD041476, https://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD041476) via the iProX partner repository (https://www.iprox.cn/) under Project ID IPX0003019000 at https://www.iprox.cn/page/project.html?id=IPX0003019000.
Article and author information
Author details
Funding
National Key Research and Development Program of China
- Chen Ding
Clinical Research Plan of SHDC
- Jianming Xu
Program of Shanghai Academic Research Leader
- Chen Ding
Shuguang Program og Shanghai Education Development Foundation and Shanghai Municipal Education Commission
- Chen Ding
National Natural Science Foundation of China
- Chen Ding
the Major Project of Special Development Funds of Zhangjiang National Independent Innovation Demonstration Zone
- Chen Ding
Shanghai Municipal Science and Technology Major Project
- Chen Ding
the Fudan original research personalized support project
- Chen Ding
CAMS Innovation Fund for Medical Sciences
- Fuchu He
Shanghai Science and Technology Committee Project
- Jianming Xu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The present study was carried out comply with the ethical standards of Helsinki Declaration II and approved by the Institution Review Board of Fudan University Zhongshan Hospital (B2019-166).
Copyright
© 2023, Zhuang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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