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

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...

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Autores principales: Zhuang, Aojia, Zhuang, Aobo, Chen, Yijiao, Qin, Zhaoyu, Zhu, Dexiang, Ren, Li, Wei, Ye, Zhou, Pengyang, Yue, Xuetong, He, Fuchu, Xu, Jianmin, Ding, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234629/
https://www.ncbi.nlm.nih.gov/pubmed/37158593
http://dx.doi.org/10.7554/eLife.82959
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author Zhuang, Aojia
Zhuang, Aobo
Chen, Yijiao
Qin, Zhaoyu
Zhu, Dexiang
Ren, Li
Wei, Ye
Zhou, Pengyang
Yue, Xuetong
He, Fuchu
Xu, Jianmin
Ding, Chen
author_facet Zhuang, Aojia
Zhuang, Aobo
Chen, Yijiao
Qin, Zhaoyu
Zhu, Dexiang
Ren, Li
Wei, Ye
Zhou, Pengyang
Yue, Xuetong
He, Fuchu
Xu, Jianmin
Ding, Chen
author_sort Zhuang, Aojia
collection PubMed
description 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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spelling pubmed-102346292023-06-02 Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes Zhuang, Aojia Zhuang, Aobo Chen, Yijiao Qin, Zhaoyu Zhu, Dexiang Ren, Li Wei, Ye Zhou, Pengyang Yue, Xuetong He, Fuchu Xu, Jianmin Ding, Chen eLife Cancer Biology 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. eLife Sciences Publications, Ltd 2023-05-09 /pmc/articles/PMC10234629/ /pubmed/37158593 http://dx.doi.org/10.7554/eLife.82959 Text en © 2023, Zhuang, Zhuang, Chen et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cancer Biology
Zhuang, Aojia
Zhuang, Aobo
Chen, Yijiao
Qin, Zhaoyu
Zhu, Dexiang
Ren, Li
Wei, Ye
Zhou, Pengyang
Yue, Xuetong
He, Fuchu
Xu, Jianmin
Ding, Chen
Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title_full Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title_fullStr Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title_full_unstemmed Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title_short Proteomic characteristics reveal the signatures and the risks of T1 colorectal cancer metastasis to lymph nodes
title_sort proteomic characteristics reveal the signatures and the risks of t1 colorectal cancer metastasis to lymph nodes
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234629/
https://www.ncbi.nlm.nih.gov/pubmed/37158593
http://dx.doi.org/10.7554/eLife.82959
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