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A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis

Purpose: To build and validate a predictive model of outcome for patients with locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy. Materials and methods: We developed a LARCassigner3 classifier based on tumor and paired normal tissues of patients treated with neoadjuvan...

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Autores principales: Zhang, Jing, Shen, Lijun, Deng, Yun, Sun, Xiaoyang, Wang, Yaqi, Yao, Ye, Zhang, Hui, Zou, Wei, Zhang, Zhiyuan, Wan, Juefeng, Yang, Lifeng, Zhu, Ji, Zhang, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6511254/
https://www.ncbi.nlm.nih.gov/pubmed/31123421
http://dx.doi.org/10.2147/CMAR.S196662
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author Zhang, Jing
Shen, Lijun
Deng, Yun
Sun, Xiaoyang
Wang, Yaqi
Yao, Ye
Zhang, Hui
Zou, Wei
Zhang, Zhiyuan
Wan, Juefeng
Yang, Lifeng
Zhu, Ji
Zhang, Zhen
author_facet Zhang, Jing
Shen, Lijun
Deng, Yun
Sun, Xiaoyang
Wang, Yaqi
Yao, Ye
Zhang, Hui
Zou, Wei
Zhang, Zhiyuan
Wan, Juefeng
Yang, Lifeng
Zhu, Ji
Zhang, Zhen
author_sort Zhang, Jing
collection PubMed
description Purpose: To build and validate a predictive model of outcome for patients with locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy. Materials and methods: We developed a LARCassigner3 classifier based on tumor and paired normal tissues of patients treated with neoadjuvant chemoradiation and surgery from January 2007 to December 2012 in Fudan University Shanghai Cancer Center. Excluding 23 pairs of tissues failed in the RNA quality test, rested 197 patients were divided into discovery (n=98) and validation (n=99) cohorts randomly. Median follow-up time was 58 months. We used the Kaplan–Meier method to estimate disease-free survival (DFS), overall survival (OS), local recurrent, and distant metastatic rate We constructed a multivariate Cox model to identify the variables independently associated with progression-free and OS. Results: We identified three classifier genes related to relevant colorectal cancer features (CXCL9, SFRP2, and CD44) that formed the LARCassigner3 classifier assay. In the discovery set, the median DFS was 48.1 months (95% confidence interval (CI) 47.3–49.5) in the low-risk group and 23.4 months (95% CI 22.1–24.8) in the high-risk group (p=0.0134); the median OS was 39.2 months (95% CI 38.4–40.3) in the high-risk group and 19.1 months (95% CI 18.3–20.7) in the low-risk group (p=0.0134); 5-year distant metastasis was 13.9% (95% CI 9.0–21.3) in the low-risk group and 49.8% (95% CI 38.7–60.9) in the high-risk group (p=0.0072). Additionally, the different responses to neoadjuvant chemoradiotherapy and the LARCassigner3 low-risk and high-risk groups was statistically significant (p=0.004) in the discovery cohort. Similar results were obtained in the internal evaluation cohort. Conclusions: Patients with LARCassigner3 low-risk tumors were associated with a good prognosis. The clinical utility of using LARCassigner3 subtyping for the identification of patients for neoadjuvant chemoradiotherapy requires validation in dependent clinical trial cohorts.
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spelling pubmed-65112542019-05-23 A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis Zhang, Jing Shen, Lijun Deng, Yun Sun, Xiaoyang Wang, Yaqi Yao, Ye Zhang, Hui Zou, Wei Zhang, Zhiyuan Wan, Juefeng Yang, Lifeng Zhu, Ji Zhang, Zhen Cancer Manag Res Original Research Purpose: To build and validate a predictive model of outcome for patients with locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy. Materials and methods: We developed a LARCassigner3 classifier based on tumor and paired normal tissues of patients treated with neoadjuvant chemoradiation and surgery from January 2007 to December 2012 in Fudan University Shanghai Cancer Center. Excluding 23 pairs of tissues failed in the RNA quality test, rested 197 patients were divided into discovery (n=98) and validation (n=99) cohorts randomly. Median follow-up time was 58 months. We used the Kaplan–Meier method to estimate disease-free survival (DFS), overall survival (OS), local recurrent, and distant metastatic rate We constructed a multivariate Cox model to identify the variables independently associated with progression-free and OS. Results: We identified three classifier genes related to relevant colorectal cancer features (CXCL9, SFRP2, and CD44) that formed the LARCassigner3 classifier assay. In the discovery set, the median DFS was 48.1 months (95% confidence interval (CI) 47.3–49.5) in the low-risk group and 23.4 months (95% CI 22.1–24.8) in the high-risk group (p=0.0134); the median OS was 39.2 months (95% CI 38.4–40.3) in the high-risk group and 19.1 months (95% CI 18.3–20.7) in the low-risk group (p=0.0134); 5-year distant metastasis was 13.9% (95% CI 9.0–21.3) in the low-risk group and 49.8% (95% CI 38.7–60.9) in the high-risk group (p=0.0072). Additionally, the different responses to neoadjuvant chemoradiotherapy and the LARCassigner3 low-risk and high-risk groups was statistically significant (p=0.004) in the discovery cohort. Similar results were obtained in the internal evaluation cohort. Conclusions: Patients with LARCassigner3 low-risk tumors were associated with a good prognosis. The clinical utility of using LARCassigner3 subtyping for the identification of patients for neoadjuvant chemoradiotherapy requires validation in dependent clinical trial cohorts. Dove 2019-05-07 /pmc/articles/PMC6511254/ /pubmed/31123421 http://dx.doi.org/10.2147/CMAR.S196662 Text en © 2019 Zhang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Zhang, Jing
Shen, Lijun
Deng, Yun
Sun, Xiaoyang
Wang, Yaqi
Yao, Ye
Zhang, Hui
Zou, Wei
Zhang, Zhiyuan
Wan, Juefeng
Yang, Lifeng
Zhu, Ji
Zhang, Zhen
A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title_full A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title_fullStr A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title_full_unstemmed A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title_short A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
title_sort novel larcassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6511254/
https://www.ncbi.nlm.nih.gov/pubmed/31123421
http://dx.doi.org/10.2147/CMAR.S196662
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