Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center casecontrol study, serum proteomic expressions were analyzed on 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. Data from patients with early stage ovarian cancer and healthy women at two centers were analyzed independently and the results cross-validated to discover potential biomarkers. The results were validated using the samples from two of the remaining centers. After protein identification, biomarkers for which an immunoassay was available were tested on samples from the fifth center, which included 41 healthy women, 41 patients with ovarian cancer, and 20 each with breast, colon, and prostate cancers. Three biomarkers were identified as follows: (a) apolipoprotein A1 (down-regulated in cancer); (b) a truncated form of transthyretin (down-regulated); and (c) a cleavage fragment of inter-␣-trypsin inhibitor heavy chain H4 (up-regulated). In independent validation to detect early stage invasive epithelial ovarian cancer from healthy controls, the sensitivity of a multivariate model combining the three biomarkers and CA125 [74% (95% CI, 52-90%)] was higher than that of CA125 alone [65% (95% CI, 43-84%)] at a matched specificity of 97% (95% CI, 89 -100%). When compared at a fixed sensitivity of 83% (95% CI, 61-95%), the specificity of the model [94% (95% CI, 85-98%)] was significantly better than that of CA125 alone [52% (95% CI, 39 -65%)]. These biomarkers demonstrated the potential to improve the detection of early stage ovarian cancer.

Background:We previously selected a panel of 3 breast cancer biomarkers (BC1, BC2, and BC3) from serum samples collected at a single hospital based on their collective contribution to the optimal separation of breast cancer patients and noncancer controls by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The identities and general applicability of these markers, however, were unknown. In this study, we performed protein expression profiling on samples obtained from a second hospital, included a greater number of ductal carcinoma in situ (DCIS) cases, and performed purification and identification of the 2 confirmed markers. Methods: Using a case-control study design, we performed protein expression profiling on serum samples from the National Cancer Institute (Milan, Italy). The validation sample cohort consisted of 61 women with locally invasive breast cancer, 32 with DCIS, 37 with various benign breast diseases (including 13 atypical), and 46 age-matched apparently healthy women (age range, 44 -68 years). Validated biomarkers were purified and identified with serial chromatography, 1-dimensional gel electrophoresis, in-gel ASP-N digestion, peptide mass fingerprinting, and tandem mass peptide sequencing. Results: The BC3 and BC2 expression patterns in this sample set were consistent with the first study sample

Protein expression profiling has been increasingly used to discover and characterize biomarkers that can be used for diagnostic, prognostic or therapeutic purposes. Most proteomic studies published to date have identified relatively abundant host response proteins as candidate biomarkers, which are often dismissed because of an apparent lack of specificity. We demonstrate that 2 host response proteins previously identified as candidate markers for early stage ovarian cancer, transthyretin and inter-alpha trypsin inhibitor heavy chain 4 (ITIH4), are posttranslationally modified. These modifications include proteolytic truncation, cysteinylation and glutathionylation. Assays using Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) may provide a means to confer specificity to these proteins because of their ability to detect and quantitate multiple posttranslationally modified forms of these proteins in a single assay. Quantitative measurements of these modifications using chromatographic and antibody-based ProteinChip1 array assays reveal that these posttranslational modifications occur to different extents in different cancers and that multivariate analysis permits the derivation of algorithms to improve the classification of these cancers. We have termed this process host response protein amplification cascade (HRPAC), since the process of synthesis, posttranslational modification and metabolism of host response proteins amplifies the signal of potentially low-abundant biologically active disease markers such as enzymes. ' 2005 Wiley-Liss, Inc.

Background-Peripheral arterial disease (PAD) is common but commonly unrecognized. Improved recognition of PAD is needed. We used high-throughput proteomic profiling to find PAD-associated biomarkers. Methods and Results-Plasma was collected from PAD patients (ankle brachial index of Ͻ0.90; nϭ45) and subjects with risk factors but without PAD (nϭ43). Plasma was analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to quantify 1619 protein peaks. The peak intensity of a 12-kDa protein was higher in PAD patients. Western blot analyses and immunoaffinity studies confirmed that this protein was ␤2-microglobulin (B2M). In a validation study, B2M was measured by ELISA in plasma in age-and gender-matched PAD (nϭ20) and non-PAD (nϭ20) subjects. Finally, we studied a larger cohort of subjects (nϭ237) referred for coronary angiography but without known PAD. Plasma B2M levels were higher in PAD patients than in non-PAD patients with coronary artery disease. Plasma B2M correlated with ankle brachial index and functional capacity. Independent predictors of PAD were diabetes mellitus, age, and the combination of B2M and C-reactive protein level. Conclusions-In PAD patients, circulating B2M is elevated and correlates with the severity of disease independent of other risk factors. These findings might provide a needed biomarker for PAD and new insight into its pathophysiology. Further studies in other populations are needed to confirm the utility of measuring B2M in cardiovascular disease risk assessment.