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A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes

PURPOSE: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I–III colon cancer. METHODS: A Treg-rel...

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Autores principales: Xu, Longwen, Liu, Mengjie, Lian, Jie, Li, Enmeng, Dongmin, Chang, Li, Xuqi, Wang, Wenjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590341/
https://www.ncbi.nlm.nih.gov/pubmed/37498396
http://dx.doi.org/10.1007/s00432-023-05187-y
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author Xu, Longwen
Liu, Mengjie
Lian, Jie
Li, Enmeng
Dongmin, Chang
Li, Xuqi
Wang, Wenjuan
author_facet Xu, Longwen
Liu, Mengjie
Lian, Jie
Li, Enmeng
Dongmin, Chang
Li, Xuqi
Wang, Wenjuan
author_sort Xu, Longwen
collection PubMed
description PURPOSE: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I–III colon cancer. METHODS: A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell’s concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package “pRRophetic". RESULTS: A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy. CONCLUSIONS: We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I–III colon cancer that can identify high-risk patients for more personalized and effective therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05187-y.
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spelling pubmed-105903412023-10-23 A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes Xu, Longwen Liu, Mengjie Lian, Jie Li, Enmeng Dongmin, Chang Li, Xuqi Wang, Wenjuan J Cancer Res Clin Oncol Research PURPOSE: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I–III colon cancer. METHODS: A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell’s concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package “pRRophetic". RESULTS: A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy. CONCLUSIONS: We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I–III colon cancer that can identify high-risk patients for more personalized and effective therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05187-y. Springer Berlin Heidelberg 2023-07-27 2023 /pmc/articles/PMC10590341/ /pubmed/37498396 http://dx.doi.org/10.1007/s00432-023-05187-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Xu, Longwen
Liu, Mengjie
Lian, Jie
Li, Enmeng
Dongmin, Chang
Li, Xuqi
Wang, Wenjuan
A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title_full A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title_fullStr A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title_full_unstemmed A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title_short A prognostic nomogram for predicting recurrence-free survival of stage I–III colon cancer based on immune-infiltrating Treg-related genes
title_sort prognostic nomogram for predicting recurrence-free survival of stage i–iii colon cancer based on immune-infiltrating treg-related genes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590341/
https://www.ncbi.nlm.nih.gov/pubmed/37498396
http://dx.doi.org/10.1007/s00432-023-05187-y
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