title: Possible detection of pancreatic cancer by plasma protein profiling.
abstract: The survival rate of pancreatic cancer patients is the lowest among those with common solid tumors, and early detection is one of the most feasible means of improving outcomes. We compared plasma proteomes between pancreatic cancer patients and sex- and age-matched healthy controls using surface-enhanced laser desorption/ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. Proteomic spectra were generated from a total of 245 plasma samples obtained from two institutes. A discriminating proteomic pattern was extracted from a training cohort (71 pancreatic cancer patients and 71 healthy controls) using a support vector machine learning algorithm and was applied to two validation cohorts. We recognized a set of four mass peaks at 8,766, 17,272, 28,080, and 14,779 m/z, whose mean intensities differed significantly (Mann-Whitney U test, P < 0.01), as most accurately discriminating cancer patients from healthy controls in the training cohort [sensitivity of 97.2% (69 of 71), specificity of 94.4% (67 of 71), and area under the curve value of 0.978]. This set discriminated cancer patients in the first validation cohort with a sensitivity of 90.9% (30 of 33) and a specificity of 91.1% (41 of 45), and its discriminating capacity was further validated in an independent cohort at a second institution. When combined with CA19-9, 100% (29 of 29 patients) of pancreatic cancers, including early-stage (stages I and II) tumors, were detected. Although a multi-institutional large-scale study will be necessary to confirm clinical significance, the biomarker set identified in this study may be applicable to using plasma samples to diagnose pancreatic cancer.
authors.affiliation: Chemotherapy Division and Cancer Proteomics Project, National Cancer Center Research Institute 5-1-1 Tsukiji Chuoh-ku, Tokyo, Japan.
authors.forename: Kazufumi
authors.initials: K
authors.lastname: Honda
authors.forename: Yasuharu
authors.initials: Y
authors.lastname: Hayashida
authors.forename: Tomoko
authors.initials: T
authors.lastname: Umaki
authors.forename: Takuji
authors.initials: T
authors.lastname: Okusaka
authors.forename: Tomoo
authors.initials: T
authors.lastname: Kosuge
authors.forename: Satoru
authors.initials: S
authors.lastname: Kikuchi
authors.forename: Mitsufumi
authors.initials: M
authors.lastname: Endo
authors.forename: Akihiko
authors.initials: A
authors.lastname: Tsuchida
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Aoki
authors.forename: Takao
authors.initials: T
authors.lastname: Itoi
authors.forename: Fuminori
authors.initials: F
authors.lastname: Moriyasu
authors.forename: Setsuo
authors.initials: S
authors.lastname: Hirohashi
authors.forename: Tesshi
authors.initials: T
authors.lastname: Yamada
mesh_terms: D014408:Biomarkers, Tumor / Q000097:blood*; D001798:Blood Proteins / Q000032:analysis*; D021441:Carcinoma, Pancreatic Ductal / Q000097:blood*; D002852:Chromatography, Ion Exchange; D005260:Female; D006801:Humans; D008297:Male; D013058:Mass Spectrometry; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000097:blood*; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods; D015203:Reproducibility of Results
chemical_list: D014408:Biomarkers, Tumor; D001798:Blood Proteins