title: Gene expression analysis of pretreatment biopsies predicts the pathological response of esophageal squamous cell carcinomas to neo-chemoradiotherapy.
abstract: BACKGROUND
  Neoadjuvant chemoradiotherapy (neo-CRT) followed by surgery has been shown to improve esophageal squamous cell carcinoma (ESCC) patients' survival compared with surgery alone. However, the outcomes of CRT are heterogeneous, and no clinical or pathological method can currently predict CRT response. In this study, we aim to identify mRNA markers useful for ESCC CRT-response prediction.
  
  
  METHODS
  Gene expression analyses were carried out on pretreated cancer biopsies from 28 ESCCs who received neo-CRT and surgery. Surgical specimens were assessed for pathological response to CRT. The differentially expressed genes identified by expression profiling were validated by real-time quantitative polymerase chain reaction (qPCR), and a classifying model was built from qPCR data using Fisher's linear discriminant analysis. The predictive power of this model was further assessed in a second set of 32 ESCCs.
  
  
  RESULTS
  The profiling of the 28 ESCCs identified 10 differentially expressed genes with more than a twofold change between patients with pathological complete response (pCR) and less than pCR (<pCR). A prediction model based on the qPCR values of three genes was generated, which provided a predictive accuracy of 86% upon leave-one-out cross-validation. Furthermore, the predictive power of this model was validated in another cohort of 32 ESCCs, among which a predictive accuracy of 81% was achieved. Importantly, the discriminant score was found to be the only independent factor that affected neo-CRT response in both the training (P = 0.015) and validation (P = 0.017) sets, respectively.
  
  
  CONCLUSIONS
  The expression levels of three genes determined by qPCR provide a possible model for ESCC CRT prediction, which will facilitate the individualization of ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou.
authors.forename: J
authors.initials: J
authors.lastname: Wen
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.
authors.forename: H
authors.initials: H
authors.lastname: Yang
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Radiotherapy.
authors.forename: M Z
authors.initials: MZ
authors.lastname: Liu
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.
authors.forename: K J
authors.initials: KJ
authors.lastname: Luo
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Radiotherapy.
authors.forename: H
authors.initials: H
authors.lastname: Liu
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.
authors.forename: Y
authors.initials: Y
authors.lastname: Hu
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.
authors.forename: X
authors.initials: X
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
authors.forename: R C
authors.initials: RC
authors.lastname: Lai
authors.affiliation: Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.
authors.forename: T
authors.initials: T
authors.lastname: Lin
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou.
authors.forename: H Y
authors.initials: HY
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology. Electronic address: fu_jianhua@hotmail.com.
authors.forename: J H
authors.initials: JH
authors.lastname: Fu
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D001706:Biopsy; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000401:mortality / Q000628:therapy*; D059248:Chemoradiotherapy; D002945:Cisplatin / Q000627:therapeutic use; D004938:Esophageal Neoplasms / Q000235:genetics* / Q000401:mortality / Q000628:therapy*; D000077277:Esophageal Squamous Cell Carcinoma; D005260:Female; D015870:Gene Expression; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D020360:Neoadjuvant Therapy; D012333:RNA, Messenger / Q000235:genetics; D016896:Treatment Outcome; D014747:Vinblastine / Q000031:analogs & derivatives / Q000627:therapeutic use; D000077235:Vinorelbine
chemical_list: D012333:RNA, Messenger; D014747:Vinblastine; D002945:Cisplatin; D000077235:Vinorelbine
keywords: esophageal squamous cell carcinoma; gene expression; neoadjuvant chemoradiotherapy; response prediction