title: Tamoxifen therapy benefit predictive signature coupled with prognostic signature of post-operative recurrent risk for early stage ER+ breast cancer.
abstract: Two types of prognostic signatures for predicting recurrent risk of ER+ breast cancer patients have been developed: one type for patients accepting surgery only and another type for patients receiving post-operative tamoxifen therapy. However, the first type of signature cannot distinguish high-risk patients who cannot benefit from tamoxifen therapy, while the second type of signature cannot identify patients who will be at low risk of recurrence even if they accept surgery only. In this study, we proposed to develop two coupled signatures to solve these problems based on within-sample relative expression orderings (REOs) of gene pairs. Firstly, we identified a prognostic signature of post-operative recurrent risk using 544 samples of ER+ breast cancer patients accepting surgery only. Then, applying this drug-free signature to 840 samples of patients receiving post-operative tamoxifen therapy, we recognized 553 samples of patients who would have been at high risk of recurrence if they had accepted surgery only and used these samples to develop a tamoxifen therapy benefit predictive signature. The two coupled signatures were validated in independent data. The signatures developed in this study are robust against experimental batch effects and applicable at the individual levels, which can facilitate the clinical decision of tamoxifen therapy.
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Cai
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Xiangyu
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Lu
authors.initials: L
authors.lastname: Ao
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Haidan
authors.initials: H
authors.lastname: Yan
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Mengsha
authors.initials: M
authors.lastname: Tong
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Qingzhou
authors.initials: Q
authors.lastname: Guan
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
authors.forename: Mengyao
authors.initials: M
authors.lastname: Li
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism / Q000473:pathology / Q000628:therapy*; D017024:Chemotherapy, Adjuvant; D030541:Databases, Genetic; D018572:Disease-Free Survival; D004965:Estrogen Antagonists / Q000627:therapeutic use*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008408:Mastectomy / Q000009:adverse effects; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local; D018579:Patient Selection; D057285:Precision Medicine; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011960:Receptors, Estrogen / Q000187:drug effects / Q000378:metabolism; D018570:Risk Assessment; D012307:Risk Factors; D013629:Tamoxifen / Q000627:therapeutic use*; D013997:Time Factors; D016896:Treatment Outcome; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D004965:Estrogen Antagonists; D011960:Receptors, Estrogen; D013629:Tamoxifen
keywords: breast cancer; predictive signature; prognostic signature; relative expression ordering; tamoxifen