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. (Cancer Res 2005; 65(22): 10613-22)

Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations

“…Despite that we found some other expression differences in both sample sets, these were not large enough for good classification of patients and controls. Furthermore, both a decrease of a 17.3-kDa peak (possibly des-glutamine apolipoprotein A-II) and glutathionylated transthyretin have been described in the sera from patients with other cancers before 24,[28][29][30] and thus they seem not specific for RCC either. Yet, these proteins might have a role as markers in disease or therapy monitoring.…”

The MALDI-TOF Mass Spectrometric View of the Plasma Proteome and Peptidome

“…However, these peptides have very low concentrations and were characterized through the analysis of thousands of liters of plasma ultrafiltrate. Application of SELDI-TOF MS to analysis of serum or plasma detected low-molecular-mass components from specimens of a few microliters (71,72 ), and great interest in this technique was stimulated by the potential for patterns of small peptides to serve as diagnostic markers (5,(22)(23)(24)(25)(26)(71)(72)(73)(74)(75)(76). Most studies applying MALDI-TOF or SELDI-TOF MS to analyze small amounts of serum or plasma have resolved 100 to 1000 peaks in the m/z range Ͻ20 000.…”

Survival Prediction for Pancreatic Cancer Patients Receiving Gemcitabine Treatment

“…Invasive ductal adenocarcinoma of the pancreas is one of the most aggressive and lethal malignancies (1). It is the fifth leading cause of cancer-related death in Japan and the fourth in the United States, accounting for an estimated Ͼ23,000 deaths per year in Japan and Ͼ33,000 in the United States (2,3).…”

“…We and others have successfully applied MALDI MS-based protein profiling techniques for predicting the efficacy of chemoradiotherapy and molecular targeting therapy (14,15). Two-dimensional image converted analysis of liquid chromatography and mass spectrometry (2DICAL) 1 is a new LC-MS-based proteomics platform that was developed in our laboratory (16). 2DICAL can quantify protein content accurately across a theoretically unlimited number of samples without isotope labeling and thus has considerable advantages over conventional LC-MS-based methods for clinical studies (17).…”

“…The rates of complete and partial responses (Response Evaluation Criteria in Solid Tumors guideline) to gemcitabine mono- 1 The abbreviations used are: 2DICAL, two-dimensional image converted analysis of liquid chromatography and mass spectrometry; AIC, Akaike's information criterion; CC, correlation coefficient; CI, confidence interval; CV, coefficient of variance; ECOG, Eastern Cooperative Oncology Group; NCC, National Cancer Center; ID, identification; FDR, false discovery rate. therapy are limited to ϳ10% (20 -22), and the majority of pancreatic cancers do not show significant tumor regression.…”