A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis
Jing Zhang,1,2,* Lijun Shen,1,2,* Yun Deng,1,2 Xiaoyang Sun,1,2 Yaqi Wang,1,2 Ye Yao,1,2 Hui Zhang,1,2 Wei Zou,1,2 Zhiyuan Zhang,1,2 Juefeng Wan,1,2 Lifeng Yang,1,2 Ji Zhu,1,2 Zhen Zhang1,21Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, People’s...
Main Authors: | , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Dove Medical Press
2019-05-01
|
Series: | Cancer Management and Research |
Subjects: | |
Online Access: | https://www.dovepress.com/a-novel-larcassigner3-classification-predicts-outcomes-in-patients-wit-peer-reviewed-article-CMAR |
_version_ | 1819033902354792448 |
---|---|
author | Zhang J Shen L Deng Y Sun X Wang Y Yao Y Zhang H Zou W Zhang Z Wan J Yang L Zhu J Zhang Z |
author_facet | Zhang J Shen L Deng Y Sun X Wang Y Yao Y Zhang H Zou W Zhang Z Wan J Yang L Zhu J Zhang Z |
author_sort | Zhang J |
collection | DOAJ |
description | Jing Zhang,1,2,* Lijun Shen,1,2,* Yun Deng,1,2 Xiaoyang Sun,1,2 Yaqi Wang,1,2 Ye Yao,1,2 Hui Zhang,1,2 Wei Zou,1,2 Zhiyuan Zhang,1,2 Juefeng Wan,1,2 Lifeng Yang,1,2 Ji Zhu,1,2 Zhen Zhang1,21Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, People’s Republic of China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, People’s Republic of China*These authors contributed equally to this workPurpose: 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.Keywords: prognostic marker, locally advanced rectal cancer, neoadjuvant chemoradiotherapy |
first_indexed | 2024-12-21T07:25:13Z |
format | Article |
id | doaj.art-b58b06e1614741b1b5c95ba17b69c28f |
institution | Directory Open Access Journal |
issn | 1179-1322 |
language | English |
last_indexed | 2024-12-21T07:25:13Z |
publishDate | 2019-05-01 |
publisher | Dove Medical Press |
record_format | Article |
series | Cancer Management and Research |
spelling | doaj.art-b58b06e1614741b1b5c95ba17b69c28f2022-12-21T19:11:41ZengDove Medical PressCancer Management and Research1179-13222019-05-01Volume 114153417045666A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysisZhang JShen LDeng YSun XWang YYao YZhang HZou WZhang ZWan JYang LZhu JZhang ZJing Zhang,1,2,* Lijun Shen,1,2,* Yun Deng,1,2 Xiaoyang Sun,1,2 Yaqi Wang,1,2 Ye Yao,1,2 Hui Zhang,1,2 Wei Zou,1,2 Zhiyuan Zhang,1,2 Juefeng Wan,1,2 Lifeng Yang,1,2 Ji Zhu,1,2 Zhen Zhang1,21Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, People’s Republic of China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, People’s Republic of China*These authors contributed equally to this workPurpose: 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.Keywords: prognostic marker, locally advanced rectal cancer, neoadjuvant chemoradiotherapyhttps://www.dovepress.com/a-novel-larcassigner3-classification-predicts-outcomes-in-patients-wit-peer-reviewed-article-CMARPrognostic markerLocally Advanced Rectal CancerNeoadjuvant chemoradiotherapy |
spellingShingle | Zhang J Shen L Deng Y Sun X Wang Y Yao Y Zhang H Zou W Zhang Z Wan J Yang L Zhu J Zhang Z A novel LARCassigner3 classification predicts outcomes in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a retrospective training and validation analysis Cancer Management and Research Prognostic marker Locally Advanced Rectal Cancer Neoadjuvant chemoradiotherapy |
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 | Prognostic marker Locally Advanced Rectal Cancer Neoadjuvant chemoradiotherapy |
url | https://www.dovepress.com/a-novel-larcassigner3-classification-predicts-outcomes-in-patients-wit-peer-reviewed-article-CMAR |
work_keys_str_mv | AT zhangj anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT shenl anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT dengy anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT sunx anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT wangy anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT yaoy anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangh anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zouw anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangz anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT wanj anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT yangl anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhuj anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangz anovellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangj novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT shenl novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT dengy novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT sunx novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT wangy novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT yaoy novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangh novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zouw novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangz novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT wanj novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT yangl novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhuj novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis AT zhangz novellarcassigner3classificationpredictsoutcomesinpatientswithlocallyadvancedrectalcancertreatedwithneoadjuvantchemoradiotherapyaretrospectivetrainingandvalidationanalysis |