title: Identification of a predictive biomarker for hematologic toxicities of gemcitabine.
abstract: OBJECTIVE
  Gemcitabine monotherapy is the current standard for patients with advanced pancreatic cancer, but the occurrence of severe neutropenia and thrombocytopenia can sometimes be life threatening. This study aimed to discover a new diagnostic method for predicting the hematologic toxicities of gemcitabine.
  
  
  METHODS
  Using quantitative mass spectrometry (MS), we compared the baseline plasma proteomes of 25 patients who had developed severe hematologic adverse events (grade 3 to 4 neutropenia and/or grade 2 to 4 thrombocytopenia) within the first two cycles of gemcitabine with those of 22 patients who had not (grade 0).
  
  
  RESULTS
  We identified 757 peptide peaks whose intensities were significantly different (P < .001, Welch t test) among a total of 60,888. The MS peak with the highest statistical significance (P = .0000282) was revealed to be derived from haptoglobin by tandem MS. A scoring system (nomogram) based on the values of haptoglobin, haptoglobin phenotype, neutrophil count, platelet count, and body-surface area was constructed to estimate the risk of hematologic adverse events (grade 3 to 4 neutropenia and/or grade 2 to 4 thrombocytopenia) with an area under curve value of 0.782 in a cohort of 166 patients with pancreatic cancer. Predictive ability of the system was confirmed in two independent validation cohorts consisting of 87 and 52 patients with area under the curve values of 0.655 and 0.747, respectively.
  
  
  CONCLUSIONS
  Although the precise mechanism responsible for the correlation of haptoglobin with the future onset of hematologic toxicities remains to be clarified, our prediction model seems to have high practical utility for tailoring the treatment of patients receiving gemcitabine.
authors.affiliation: Chemotherapy Division, National Cancer Center Research Institute, Tokyo, Japan.
authors.forename: Junichi
authors.initials: J
authors.lastname: Matsubara
authors.forename: Masaya
authors.initials: M
authors.lastname: Ono
authors.forename: Ayako
authors.initials: A
authors.lastname: Negishi
authors.forename: Hideki
authors.initials: H
authors.lastname: Ueno
authors.forename: Takuji
authors.initials: T
authors.lastname: Okusaka
authors.forename: Junji
authors.initials: J
authors.lastname: Furuse
authors.forename: Koh
authors.initials: K
authors.lastname: Furuta
authors.forename: Emiko
authors.initials: E
authors.lastname: Sugiyama
authors.forename: Yoshiro
authors.initials: Y
authors.lastname: Saito
authors.forename: Nahoko
authors.initials: N
authors.lastname: Kaniwa
authors.forename: Junichi
authors.initials: J
authors.lastname: Sawada
authors.forename: Kazufumi
authors.initials: K
authors.lastname: Honda
authors.forename: Tomohiro
authors.initials: T
authors.lastname: Sakuma
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Chiba
authors.forename: Nagahiro
authors.initials: N
authors.lastname: Saijo
authors.forename: Setsuo
authors.initials: S
authors.lastname: Hirohashi
authors.forename: Tesshi
authors.initials: T
authors.lastname: Yamada
mesh_terms: D000230:Adenocarcinoma / Q000188:drug therapy*; D000368:Aged; D000964:Antimetabolites, Antineoplastic / Q000009:adverse effects*; D015415:Biomarkers; D001798:Blood Proteins / Q000032:analysis; D021441:Carcinoma, Pancreatic Ductal / Q000188:drug therapy*; D003841:Deoxycytidine / Q000009:adverse effects / Q000031:analogs & derivatives*; D005260:Female; D006242:Haptoglobins / Q000032:analysis*; D006801:Humans; D016015:Logistic Models; D008297:Male; D013058:Mass Spectrometry; D008875:Middle Aged; D009503:Neutropenia / Q000139:chemically induced*; D010190:Pancreatic Neoplasms / Q000097:blood / Q000188:drug therapy*; D010641:Phenotype; D013921:Thrombocytopenia / Q000139:chemically induced*; D000093542:Gemcitabine
chemical_list: D000964:Antimetabolites, Antineoplastic; D015415:Biomarkers; D001798:Blood Proteins; D006242:Haptoglobins; D003841:Deoxycytidine; D000093542:Gemcitabine