{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T23:01:51Z","timestamp":1780614111296,"version":"3.54.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Accurate prognosis of breast cancer can spare a significant number of breast cancer patients from receiving unnecessary adjuvant systemic treatment and its related expensive medical costs. Recent studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical disease recurrence. However, these studies all attempt to develop genetic marker-based prognostic systems to replace the existing clinical criteria, while ignoring the rich information contained in established clinical markers. Given the complexity of breast cancer prognosis, a more practical strategy would be to utilize both clinical and genetic marker information that may be complementary.<\/jats:p><jats:p>Methods: A computational study is performed on publicly available microarray data, which has spawned a 70-gene prognostic signature. The recently proposed I-RELIEF algorithm is used to identify a hybrid signature through the combination of both genetic and clinical markers. A rigorous experimental protocol is used to estimate the prognostic performance of the hybrid signature and other prognostic approaches. Survival data analyses is performed to compare different prognostic approaches.<\/jats:p><jats:p>Results: The hybrid signature performs significantly better than other methods, including the 70-gene signature, clinical makers alone and the St. Gallen consensus criterion. At the 90% sensitivity level, the hybrid signature achieves 67% specificity, as compared to 47% for the 70-gene signature and 48% for the clinical makers. The odds ratio of the hybrid signature for developing distant metastases within five years between the patients with a good prognosis signature and the patients with a bad prognosis is 21.0 (95% CI:6.5\u201368.3), far higher than either genetic or clinical markers alone.<\/jats:p><jats:p>Availability: The breast cancer dataset is available at and Matlab codes are available upon request.<\/jats:p><jats:p>Contact: \u00a0sun@dsp.ufl.edu<\/jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl543","type":"journal-article","created":{"date-parts":[[2006,11,28]],"date-time":"2006-11-28T03:34:16Z","timestamp":1164684856000},"page":"30-37","source":"Crossref","is-referenced-by-count":149,"title":["Improved breast cancer prognosis through the combination of clinical and genetic markers"],"prefix":"10.1093","volume":"23","author":[{"given":"Yijun","family":"Sun","sequence":"first","affiliation":[{"name":"Interdisciplinary Center for Biotechnology Research, University of Florida 1 \u00a0 1 \u00a0 \u00a0 Gainesville, FL 32611, USA"},{"name":"Department of Electrical and Computer Engineering, University of Florida 3 \u00a0 3 \u00a0 \u00a0 Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Goodison","sequence":"additional","affiliation":[{"name":"Department of Surgery, University of Florida 2 \u00a0 2 \u00a0 \u00a0 Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Florida 3 \u00a0 3 \u00a0 \u00a0 Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Liu","sequence":"additional","affiliation":[{"name":"Interdisciplinary Center for Biotechnology Research, University of Florida 1 \u00a0 1 \u00a0 \u00a0 Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Farmerie","sequence":"additional","affiliation":[{"name":"Interdisciplinary Center for Biotechnology Research, University of Florida 1 \u00a0 1 \u00a0 \u00a0 Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2006,11,26]]},"reference":[{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1186\/1471-2164-6-37","article-title":"Gene expression signature of estrogen receptor \u03b1 status in breast cancer","volume":"6","author":"Abba","year":"2005","journal-title":"BMC Genomics"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"7350","DOI":"10.1200\/JCO.2005.03.3845","article-title":"Molecular classification and molecular forecasting of breast cancer: ready for clinical application?","volume":"23","author":"Brenton","year":"2005","journal-title":"J. Clin. Oncol."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1126\/science.1125948","article-title":"Cancer biomarkers\u2013an invitation to the table","volume":"312","author":"Dalton","year":"2006","journal-title":"Science"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/S0959-8049(97)00344-4","article-title":"Obvious peritumorous emboli: an elusive prognostic factor reappraised: multivariate analysis of 1320 node-negative breast cancers","volume":"34","author":"de Mascarel","year":"1998","journal-title":"Eur. J. Cancer"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.jmva.2004.02.012","article-title":"Finding predictive gene groups from microarray data","volume":"1","author":"Dettling","year":"2004","journal-title":"J. Multivariate Anal."},{"key":"2023041105092699200_","volume-title":"Pattern Classification","author":"Duda","year":"2000"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1198\/016214502753479248","article-title":"Comparison of discrimination methods for the classification of tumors using gene expression data","volume":"97","author":"Dudoit","year":"2002","journal-title":"J. Am. Stat. Assoc."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"1837","DOI":"10.1016\/j.ejca.2004.02.025","article-title":"\u2018Good old\u2019 clinical markers have similar power in breast cancer prognosis as microarray gene expression profilers","volume":"40","author":"Ed\u00e9n","year":"2004","journal-title":"Eur. J. Cancer"},{"key":"2023041105092699200_","first-page":"979","article-title":"National Institutes of Health consensus development conference statement: adjuvant therapy for breast cancer","volume":"93","author":"Eifel","year":"2000","journal-title":"J. Natl. Cancer Inst."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1111\/j.1365-2559.1991.tb00229.x","article-title":"Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up","volume":"19","author":"Elston","year":"1991","journal-title":"Histopathology"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1093\/bioinformatics\/btl230","article-title":"Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks","volume":"22","author":"Gevaert","year":"2006","journal-title":"Bioinformatics"},{"key":"2023041105092699200_","first-page":"43","article-title":"Margin based feature selection\u2014theory and algorithms","author":"Gilad-Bachrach","year":"2004"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.1200\/JCO.2003.04.576","article-title":"Meeting highlights: updated international expert consensus on the primary therapy of early breast cancer","volume":"21","author":"Goldhirsch","year":"2003","journal-title":"J. Clin. Oncol."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","article-title":"Molecular classification of cancer: class discovery and class prediction by gene expression monitoring","volume":"286","author":"Golub","year":"1999","journal-title":"Science"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"6042","DOI":"10.1158\/0008-5472.CAN-04-3043","article-title":"The RhoGAP protein DLC-1 functions as a metastasis suppressor in breast cancer cells","volume":"65","author":"Goodison","year":"2005","journal-title":"Cancer Res."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1006\/geno.2000.6370","article-title":"Cloning, mapping, and expression analysis of gene encoding a novel Mammalian EGF-related protein (SCUBE1)","volume":"70","author":"Grimmond","year":"2000","journal-title":"Genomics"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S1074-7613(00)80426-4","article-title":"Characterization of an antigen that is recognized on a melanoma showing partial HLA loss by CTL expressing an NK inhibitory receptor","volume":"6","author":"Ikeda","year":"1997","journal-title":"Immunity"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/S1470-2045(03)00982-3","article-title":"Cancer\/testis tumour-associated antigens: immunohistochemical detection with monoclonal antibodies","volume":"4","author":"Juretic","year":"2003","journal-title":"Lancet Oncol."},{"key":"2023041105092699200_","first-page":"249","article-title":"A practical approach to feature selection","author":"Kira","year":"1992"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. Intell."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"2429","DOI":"10.1093\/bioinformatics\/bth267","article-title":"A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression","volume":"20","author":"Li","year":"2004","journal-title":"Bioinformatics"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1200\/JCO.2005.04.6524","article-title":"Molecular forecasting of breast cancer: time to move forward with clinical testing","volume":"24","author":"Loi","year":"2006","journal-title":"J. Clin. Oncol."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1080\/1042819021000035725","article-title":"Preferentially expressed antigen of melanoma (PRAME) in the development of diagnostic and therapeutic methods for hematological malignancies","volume":"44","author":"Matsushita","year":"2003","journal-title":"Leuk. Lymphoma"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1111\/j.1365-2559.1994.tb01269.x","article-title":"Pathological prognostic factors in breast cancer. III. Vascular invasion: relationship with recurrence and survival in a large study with a long-term follow-up","volume":"24","author":"Pinder","year":"1994","journal-title":"Histopathology"},{"key":"2023041105092699200_","unstructured":"Ritz C. Comparing prognostic markers for metastases in breast cancer using artificial neural networks 2003 Master thesis, Lund University, Sweden"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1006\/geno.1997.4868","article-title":"Functional characterization of human nucleosome assembly protein-2 (NAP1L4) suggests a role as a histone chaperone","volume":"44","author":"Rodriguez","year":"1997","journal-title":"Genomics"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1093\/hmg\/5.11.1801","article-title":"Testis-specific protein, Y-encoded (TSPY) expression in testicular tissues","volume":"5","author":"Schnieders","year":"1996","journal-title":"Hum. Mol. Genet."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1093\/jnci\/95.1.14","article-title":"Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification","volume":"95","author":"Simon","year":"2003","journal-title":"J. Natl. Cancer Inst."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"7332","DOI":"10.1200\/JCO.2005.02.8712","article-title":"Roadmap for developing and validating therapeutically relevant genomic classifiers","volume":"23","author":"Simon","year":"2005","journal-title":"J. Clin. Oncol."},{"key":"2023041105092699200_","first-page":"913","article-title":"Iterative RELIEF for feature weighting","author":"Sun","year":"2006"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1109\/TPAMI.1979.4766926","article-title":"A problem of dimensionality: a simple example","volume":"1","author":"Trunk","year":"1979","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1038\/415530a","article-title":"Gene expression profiling predicts clinical outcome of breast cancer","volume":"415","author":"van't Veer","year":"2002","journal-title":"Nature"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1056\/NEJMoa021967","article-title":"A gene-expression signature as a predict of survival in breast cancer","volume":"347","author":"van De Vijver","year":"2002","journal-title":"N. Engl. J. Med."},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/S0140-6736(05)17947-1","article-title":"Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer","volume":"365","author":"Wang","year":"2005","journal-title":"Lancet"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1038\/nrc1670","article-title":"Breast cancer metastasis: markers and models","volume":"5","author":"Weigelt","year":"2005","journal-title":"Nat. Rev. Cancer"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"3755","DOI":"10.1093\/bioinformatics\/bti429","article-title":"A protocol for building and evaluating predictors of disease state based on microarray data","volume":"21","author":"Wessels","year":"2005","journal-title":"Bioinformatics"},{"key":"2023041105092699200_","doi-asserted-by":"crossref","first-page":"46364","DOI":"10.1074\/jbc.M207410200","article-title":"Identification of a novel family of cell-surface proteins expressed in human vascular endothelium","volume":"227","author":"Yang","year":"2002","journal-title":"J. Biol. Chem."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/23\/1\/30\/49816201\/bioinformatics_23_1_30.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/23\/1\/30\/49816201\/bioinformatics_23_1_30.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T14:57:57Z","timestamp":1707404277000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/23\/1\/30\/189255"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,11,26]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2007,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btl543","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2007,1,1]]},"published":{"date-parts":[[2006,11,26]]}}}