Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center case-control 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-α-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: Several proteolytically derived fragments from the proline-rich region (PRR) of human inter-α-trypsin inhibitor heavy chain 4 (ITIH4) have been identified by surface-enhanced or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS or MALDI-TOF-MS) as potential disease markers.Methods: Previously, we developed a SELDI-based immunoassay that can simultaneously distinguish and quantify multiple isoforms/variants of a protein/peptide of interest. In this study, we used this high-throughput approach to quantify and characterize the extensive fragmentation within the PRR of human serum ITIH4 and determined its association with different disease conditions. The ITIH4-related fragments were first immunocaptured by use of beads coupled with peptide-specific antibodies. The eluates were then studied by SELDI-TOF-MS. In addition, freshly collected and immediately processed serum and plasma samples were used to analyze the ex vivo stability of these ITIH4 fragments.Results: Human serum ITIH4 was shown to be extensively proteolytically processed within the PRR, and its fragmentation patterns were closely associated with different disease conditions. Fragmentation patterns were generally consistent with cleavages by endoprotease followed by exoprotease actions. Observed fragments changed little under different assay conditions or blood collection and processing procedures.Conclusions: The fragmentation patterns within the PRR of human serum ITIH4 are associated with different disease conditions and may hold important diagnostic information. These fragmentation patterns could be useful as potential biomarkers for detection and classification of cancer.

Background: Pancreatic cancer is a deadly disease for which available biomarkers, such as CA19-9, lack the desired sensitivity and specificity for early detection. Additional biomarkers are needed to improve both its sensitivity and specificity. Methods: Multiplex immunoassays were developed for selected biomarkers using a Bio-Plex 200 system, and analytical performance was optimized. All proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC; n = 188) or benign pancreatic conditions (131) and healthy controls (89). The clinical performance of these markers was evaluated individually or in combination for their ability to complement CA19-9 for the early detection of pancreatic cancer. Results: A 6-plex immunoassay was developed with negligible cross-reactivity, wide dynamic range, recovery of 89% to 104%, and intra-assay and interassay precision of 10.2% to 19.6% and 13.7% to 29.3%, respectively. Individually, the best biomarkers to separate PDAC early stage from chronic pancreatitis or intraductal papillary mucinous neoplasm (IPMN) were CA19-9 and MIA or CA19-9 and MIC-1. Logistic regression modeling selected the two-marker panels that significantly improved the individual biomarker performance in discriminating PDAC early stage from chronic pancreatitis (AUCCA19-9+MIA = 0.86 vs. AUCCA19-9 = 0.81 or AUCMIA = 0.75 only, P < 0.05) or IPMN (AUCCA19-9+MIC-1 = 0.81 vs. AUCCA19-9 = 0.75 or AUCMIC-1 = 0.73 only, P < 0.05). It was observed that osteopontin (OPN) outperformed CA19-9 in separating IPMN from chronic pancreatitis (AUCOPN = 0.80 vs. AUCCA19-9 = 0.70, P < 0.01). Conclusions: The biomarker panels evaluated by assays with high analytical performance demonstrated potential complementary values to CA19-9, warranting additional clinical validation to determine their role in early detection of pancreatic cancer. Impact: The validated biomarker panels could lead to earlier intervention and better outcomes.