{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T03:40:04Z","timestamp":1747971604130,"version":"3.41.0"},"reference-count":63,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2021,4,30]],"date-time":"2021-04-30T00:00:00Z","timestamp":1619740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01DE026471","R01CA233873","R21CA223799"],"award-info":[{"award-number":["R01DE026471","R01CA233873","R21CA223799"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Predicting early in treatment whether a tumor is likely to respond to treatment is one of the most difficult yet important tasks in providing personalized cancer care. Most oropharyngeal squamous cell carcinoma (OPSCC) patients receive standard cancer therapy. However, the treatment outcomes vary significantly and are difficult to predict. Multiple studies indicate that microRNAs (miRNAs) are promising cancer biomarkers for the prognosis of oropharyngeal cancer. The reliable and efficient use of miRNAs for patient stratification and treatment outcome prognosis is still a very challenging task, mainly due to the relatively high dimensionality of miRNAs compared to the small number of observation sets; the redundancy, irrelevancy and uncertainty in the large amount of miRNAs; and the imbalanced observation patient samples.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this study, a new machine learning-based prognosis model was proposed to stratify subsets of OPSCC patients with low and high risks for treatment failure. The model cascaded a two-stage prognostic biomarker selection method and an evidential K-nearest neighbors classifier to address the challenges and improve the accuracy of patient stratification. The model has been evaluated on miRNA expression profiling of 150 oropharyngeal tumors by use of overall survival and disease-specific survival as the end points of disease treatment outcomes, respectively. The proposed method showed superior performance compared to other advanced machine-learning methods in terms of common performance quantification metrics. The proposed prognosis model can be employed as a supporting tool to identify patients who are likely to fail standard therapy and potentially benefit from alternative targeted treatments.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>\u2002<\/jats:title>\n                  <jats:p>Availability and implementation: Code is available in \u00a0https:\/\/github.com\/shenghh2015\/mRMR-BFT-outcome-prediction.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab242","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T20:30:46Z","timestamp":1618259446000},"page":"3106-3114","source":"Crossref","is-referenced-by-count":0,"title":["A novel systematic approach for cancer treatment prognosis and its applications in oropharyngeal cancer with microRNA biomarkers"],"prefix":"10.1093","volume":"37","author":[{"given":"Shenghua","family":"He","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Washington University in Saint Louis , St. Louis, MO 63130,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunfeng","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University , Xi\u2019an, 710049 Shaanxi,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wade","family":"Thorstad","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Washington University in Saint Louis , St. Louis, MO 63130,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiram","family":"Gay","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Washington University in Saint Louis , St. Louis, MO 63130,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Zhao","sequence":"additional","affiliation":[{"name":"Carle Cancer Center, Carle Foundation Hospital , Urbana, IL 61801,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Su","family":"Ruan","sequence":"additional","affiliation":[{"name":"Laboratoire LITIS (EA 4108), Equipe Quantif, University of Rouen , 76183 Rouen,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9447-4685","authenticated-orcid":false,"given":"Xiaowei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Washington University in Saint Louis , St. Louis, MO 63130,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5629-2247","authenticated-orcid":false,"given":"Hua","family":"Li","sequence":"additional","affiliation":[{"name":"Carle Cancer Center, Carle Foundation Hospital , Urbana, IL 61801,","place":["USA"]},{"name":"Department of Bioengineering, University of Illinois at Urbana-Champaign , Urbana, IL 61801,","place":["USA"]},{"name":"Cancer Center at Illinois , Urbana, IL 61801,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,4,30]]},"reference":[{"key":"2025052223014953800_btab242-B1","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1038\/nature02871","article-title":"The functions of animal MicroRNAs","volume":"431","author":"Ambros","year":"2004","journal-title":"Nature"},{"key":"2025052223014953800_btab242-B2","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/72.298224","article-title":"Using mutual information for selecting features in supervised neural net learning","volume":"5","author":"Battiti","year":"1994","journal-title":"IEEE Trans. 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