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Cited by 14Advanced Proteomics Techniques and ApplicationsColorectal Cancer Treatments and StudiesMechanisms of cancer metastasis

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Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes

Open access
Zhuang, Aojia, Zhuang, Aobo, Chen, Yijiao, Qin, Zhaoyu, Zhu, Dexiang, Ren, Li, Wei, Ye, Zhou, Pengyang, Yue, Xuetong, He, Fuchu, Xu, Jianmin, Ding, Chen·2023·eLife
DOI 10.7554/elife.82959PMC PMC10234629

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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 nine proteins, and achieved an AUC of 0.824. The simplified classifier was performed excellently in two external validation cohorts. The expression patterns of 13 proteins were confirmed by immunohistochemistry, and the IHC score of five proteins was used to build an 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.

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Metadata

Authors
Zhuang, A., Zhuang, A., Chen, Y., Qin, Z., Zhu, D., Ren, L., Wei, Y., Zhou, P., Yue, X., He, F., Xu, J., & Ding, C.
Affiliations
  • Xiamen University (CN)
  • Fudan University (CN)
  • Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
Corresponding author
  • He, Fuchu
  • Xu, Jianmin
  • Ding, Chen
ORCID
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2023-05-09
Volume
12
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.82959
PMC
PMC10234629
OpenAlex
W4375954926
Cited by
14
References
3
Citations by year
2026: 2 · 2025: 6 · 2024: 5 · 2023: 1
FWCI
1.29
Type
journal article
Language
en
Open access
Licence
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Key Research and Development Program of China (2022YFA1303200, 2022YFA1303201, 2020YFE0201600, 2018YFE0201600, 2018YFE0201603, 2018YFA0507500, 2018YFA0507501, 2017YFA0505100, 2017YFA0505102, 2017YFA0505101, 2017YFC0908404, 2016YFA0502500)
  • Program of Shanghai Academic/Technology Research Leader (22XD1420100)
  • Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission (19SG02)
  • National Natural Science Foundation of China (31972933, 31700682, 31770886)
  • Major Project of Special Development Funds of Zhangjiang National Independent Innovation Demonstration Zone (ZJ2019-ZD-004)
  • Shanghai Municipal Science and Technology Major Project (2017SHZDZX01)
  • Fudan Original Research Personalized Support Project
  • Chinese Academy of Medical Sciences (Innovation Fund for Medical Sciences 2019-12M-5-063)
  • Shanghai Science and Technology Committee (Project 19511121301)
  • Clinical Research Plan of SHDC (SHDC2020CR5006)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mechanisms of cancer metastasis
Keywords
T1 colorectal cancer, lymph node metastasis, proteomic signatures, metastasis prediction, risk stratification, immunohistochemistry, cell migration and invasion
MeSH terms
Chromatography, Liquid, Humans, Lymph Nodes, Lymphatic Metastasis, Retrospective Studies, Colorectal Neoplasms, Proteomics, Tandem Mass Spectrometry

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