title: Predicting multi-class responses to preoperative chemoradiotherapy in rectal cancer patients.
abstract: 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.
authors.affiliation: Institute of Health and Environment, Seoul National University, Seoul, 151-742, Korea.
authors.forename: Jungsoo
authors.initials: J
authors.lastname: Gim
authors.affiliation: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea.
authors.forename: Yong Beom
authors.initials: YB
authors.lastname: Cho
authors.affiliation: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea.
authors.forename: Hye Kyung
authors.initials: HK
authors.lastname: Hong
authors.affiliation: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea.
authors.forename: Hee Cheol
authors.initials: HC
authors.lastname: Kim
authors.affiliation: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea.
authors.forename: Seong Hyeon
authors.initials: SH
authors.lastname: Yun
authors.affiliation: Department of Radiation Oncology, College of Medicine, Seoul National University, Seoul, 110-799, Korea.
authors.forename: Hong-Gyun
authors.initials: HG
authors.lastname: Wu
authors.affiliation: Department of Surgery, College of Medicine, Seoul National University, Seoul, 110-799, Korea.
authors.forename: Seung-Yong
authors.initials: SY
authors.lastname: Jeong
authors.affiliation: Samsung Medical Center, Samsung Genome Institute, Seoul, 135-710, Korea.
authors.forename: Je-Gun
authors.initials: JG
authors.lastname: Joung
authors.affiliation: Institute of Health and Environment, Seoul National University, Seoul, 151-742, Korea. taesungp@gmail.com.|Department of Statistics, College of Natural Science, Seoul National University, Seoul, 151-742, Korea. taesungp@gmail.com.
authors.forename: Taesung
authors.initials: T
authors.lastname: Park
authors.affiliation: Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea. woongyang@gmail.com.|Samsung Medical Center, Samsung Genome Institute, Seoul, 135-710, Korea. woongyang@gmail.com.
authors.forename: Woong-Yang
authors.initials: WY
authors.lastname: Park
authors.affiliation: Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea. lwy555@skku.edu.
authors.forename: Woo Yong
authors.initials: WY
authors.lastname: Lee
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D059248:Chemoradiotherapy / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D008875:Middle Aged; D020360:Neoadjuvant Therapy; D020411:Oligonucleotide Array Sequence Analysis; D012313:RNA / Q000737:chemistry; D012333:RNA, Messenger / Q000378:metabolism; D012004:Rectal Neoplasms / Q000188:drug therapy* / Q000532:radiotherapy*; D016896:Treatment Outcome
chemical_list: D012333:RNA, Messenger; D012313:RNA
keywords: Chemoradiotherapy; Dworak classification; Microarray; Prediction model; Rectal cancer