title: Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling.
abstract: OBJECTIVE
  Establishment of a reliable method of predicting the efficacy of chemotherapy and radiotherapy is necessary to provide the most suitable treatment for each cancer patient. We investigated whether proteomic profiles of serum samples obtained from untreated patients were capable of being used to predict the efficacy of combined preoperative chemoradiotherapy against esophageal cancer.
  
  
  METHODS
  Proteomic spectra were obtained from a training set of 27 serum samples (15 pathologically diagnosed responders to preoperative chemoradiotherapy and 12 nonresponders) by surface-enhanced laser desorption and ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. A proteomic pattern prediction model was constructed from the training set by machine learning algorithms, and it was then tested with an independent validation set consisting of serum samples from 15 esophageal cancer patients in a blinded manner.
  
  
  RESULTS
  We selected a set of four mass peaks, at 7,420, 9,112, 17,123, and 12,867 m/z, from a total of 859 protein peaks, as perfectly distinguishing responders from nonresponders in the training set with a support vector machine algorithm. This set of peaks (i.e., the classifier) correctly diagnosed chemoradiosensitivity in 93.3% (14 of 15) of the cases in the validation set.
  
  
  CONCLUSIONS
  Recent mass spectrometric approaches have revealed that serum contains a large volume of information that reflects the microenvironment of diseased organs. Although a multi-institutional large-scale study will be necessary to confirm each component of the classifier, there is a subtle but definite difference in serum proteomic profile between responders and nonresponders to chemoradiotherapy.
authors.affiliation: Chemotherapy Division and Cancer Proteomics Project, National Cancer Center Research Institute, Tokyo Medical University, Tokyo, Japan.
authors.forename: Yasuharu
authors.initials: Y
authors.lastname: Hayashida
authors.forename: Kazufumi
authors.initials: K
authors.lastname: Honda
authors.forename: Yoshiaki
authors.initials: Y
authors.lastname: Osaka
authors.forename: Tomohiko
authors.initials: T
authors.lastname: Hara
authors.forename: Tomoko
authors.initials: T
authors.lastname: Umaki
authors.forename: Akihiko
authors.initials: A
authors.lastname: Tsuchida
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Aoki
authors.forename: Setsuo
authors.initials: S
authors.lastname: Hirohashi
authors.forename: Tesshi
authors.initials: T
authors.lastname: Yamada
mesh_terms: D000368:Aged; D001798:Blood Proteins / Q000032:analysis*; D004938:Esophageal Neoplasms / Q000097:blood* / Q000188:drug therapy / Q000532:radiotherapy; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D015203:Reproducibility of Results; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods; D016896:Treatment Outcome
chemical_list: D001798:Blood Proteins