CASIA OpenIR  > 中国科学院分子影像重点实验室
Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer
Liu, Zhenyu1,2,3; Meng, Xiaochun4; Zhang, Hongmei5; Li, Zhenhui6; Liu, Jiangang7; Sun, Kai1,8; Meng, Yankai5; Dai, Weixing9; Xie, Peiyi4; Ding, Yingying6; Wang, Meiyun10,11; Cai, Guoxiang9; Tian, Jie1,7,8
Source PublicationNATURE COMMUNICATIONS
ISSN2041-1723
2020-08-27
Volume11Issue:1Pages:11
Corresponding AuthorWang, Meiyun(mywang@ha.edu.cn) ; Cai, Guoxiang(gxcai@fudan.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
AbstractDistant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Adjuvant chemotherapy is usually used for distant control. However, not all patients can benefit from adjuvant chemotherapy, and particularly, some patients may even get worse outcomes after the treatment. We develop and validate an MRI-based radiomic signature (RS) for prediction of DM within a multicenter dataset. The RS is proved to be an independent prognostic factor as it not only demonstrates good accuracy for discriminating patients into high and low risk of DM in all the four cohorts, but also outperforms clinical models. Within the stratified analysis, good chemotherapy efficacy is observed for patients with pN2 disease and low RS, whereas poor chemotherapy efficacy is detected in patients with pT1-2 or pN0 disease and high RS. The RS may help individualized treatment planning to select patients who may benefit from adjuvant chemotherapy for distant control. Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Here, the authors developed and validated a radiomic signature (RS) for prediction of DM within a multicenter dataset, and suggest that it may help with stratification of patients who might benefit from adjuvant chemotherapy for DM.
DOI10.1038/s41467-020-18162-9
WOS KeywordPREOPERATIVE CHEMORADIOTHERAPY ; NEOADJUVANT CHEMORADIATION ; RADIOMIC SIGNATURE ; FOLLOW-UP ; SURVIVAL ; RADIOTHERAPY ; MULTICENTER ; BIOMARKER ; BRIDGE ; PET/CT
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[81922040] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81971589] ; National Natural Science Foundation of China[81720108021] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[7182109] ; National Key Research and Development Plan of China[2017YFA0205200] ; National Key Research and Development Plan of China[2017YFE0103600] ; Youth Innovation Promotion Association CAS[2019136] ; Zhongyuan Thousand Talents Plan Project-Basic Research Leader Talent[ZYQR201810117]
Funding OrganizationNational Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Research and Development Plan of China ; Youth Innovation Promotion Association CAS ; Zhongyuan Thousand Talents Plan Project-Basic Research Leader Talent
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000567932900007
PublisherNATURE PUBLISHING GROUP
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/41950
Collection中国科学院分子影像重点实验室
Corresponding AuthorWang, Meiyun; Cai, Guoxiang; Tian, Jie
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging,Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100080, Peoples R China
4.Sun Yat Sen Univ, Affiliated Hosp 6, Dept Radiol, Guangzhou 510655, Peoples R China
5.Chinese Acad Med Sci & Peking Union Med Coll, Natl Clin Res Ctr Canc, Dept Diagnost Radiol, Natl Canc Ctr,Canc Hosp, Beijing 100021, Peoples R China
6.Kunming Med Univ, Dept Radiol, Affiliated Hosp 3, Yunnan Canc Hosp, Kunming 650031, Yunnan, Peoples R China
7.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing 100191, Peoples R China
8.Xidian Univ, Sch Life Sci & Technol, Engn Res Ctr Mol & Neuro Imaging, Minist Educ, Xian 710126, Peoples R China
9.Fudan Univ, Dept Colorectal Surg, Shanghai Canc Ctr, Shanghai 200032, Peoples R China
10.Zhengzhou Univ, Henan Prov Peoples Hosp, Dept Radiol, Zhengzhou 450003, Peoples R China
11.Zhengzhou Univ, Peoples Hosp, Zhengzhou 450003, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Zhenyu,Meng, Xiaochun,Zhang, Hongmei,et al. Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer[J]. NATURE COMMUNICATIONS,2020,11(1):11.
APA Liu, Zhenyu.,Meng, Xiaochun.,Zhang, Hongmei.,Li, Zhenhui.,Liu, Jiangang.,...&Tian, Jie.(2020).Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer.NATURE COMMUNICATIONS,11(1),11.
MLA Liu, Zhenyu,et al."Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer".NATURE COMMUNICATIONS 11.1(2020):11.
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