Predicting multi-class responses to preoperative chemoradiotherapy in rectal cancer patients.
Background: Preoperative chemoradiotherapy (CRT) has become a widely used treatment for improving local control of disease and increasing survival rates of rectal cancer patients. We aimed to identify a set of genes that can be used to predict responses to CRT in patients with rectal cancer.Methods:...
| Publicado en: | Radiation Oncology Vol. 11; pp. 1 - 9 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
3/22/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=114250361&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 114250361 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1748717X 38NX jtl: Radiation Oncology issn: 1748717X maglogo: N pubinfo: dt: 3/22/2016 vid: 11 pid: 24147 pub: BioMed Central artinfo: ui: 114250361 114250361 NLM27005571 114250361 10.1186/s13014-016-0623-9 NLM27005571 PMC4804643 114250361 ppf: 1 ppct: 8 formats: tig: atl: Predicting multi-class responses to preoperative chemoradiotherapy in rectal cancer patients. aug: au: Jungsoo Gim Yong Beom Cho Hye Kyung Hong Hee Cheol Kim Seong Hyeon Yun Hong-Gyun Wu Seung-Yong Jeong Je-Gun Joung Taesung Park Woong-Yang Park Woo Yong Lee Gim, Jungsoo Cho, Yong Beom Hong, Hye Kyung Kim, Hee Cheol Yun, Seong Hyeon Wu, Hong-Gyun Jeong, Seung-Yong Joung, Je-Gun Park, Taesung affil: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710, Korea sug: subj: Rectal Neoplasms Drug Therapy Rectal Neoplasms Radiotherapy Aged Oligonucleotide Array Sequence Analysis Treatment Outcomes Male Female Algorithms Middle Age RNA Metabolism Adult Gene Expression Profiling RNA Genes Neoadjuvant Therapy Human Aged: 65+ years Middle Aged: 45-64 years Adult: 19-44 years Male Female ab: Background: Preoperative chemoradiotherapy (CRT) has become a widely used treatment for improving local control of disease and increasing survival rates of rectal cancer patients. We aimed to identify a set of genes that can be used to predict responses to CRT in patients with rectal cancer.Methods: Gene expression profiles of pre-therapeutic biopsy specimens obtained from 77 rectal cancer patients were analyzed using DNA microarrays. The response to CRT was determined using the Dworak tumor regression grade: grade 1 (minimal, MI), grade 2 (moderate, MO), grade 3 (near total, NT), or grade 4 (total, TO).Results: Top ranked genes for three different feature scores such as a p-value (pval), a rank product (rank), and a normalized product (norm) were selected to distinguish pre-defined groups such as complete responders (TO) from the MI, MO, and NT groups. Among five different classification algorithms, supporting vector machine (SVM) with the top 65 norm features performed at the highest accuracy for predicting MI using a 5-fold cross validation strategy. On the other hand, 98 pval features were selected for predicting TO by elastic net (EN). Finally we combined TO- and MI-finder models to build a three-class classification model and validated it using an independent dataset of rectal cancer mRNA expression.Conclusions: We identified MI- and TO-finders for predicting preoperative CRT responses, and validated these data using an independent public dataset. This stepwise prediction model requires further evaluation in clinical studies in order to develop personalized preoperative CRT in patients with rectal cancer. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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