The value of additional bevacizumab in patients with high-risk stroma-high colon cancer. A study within the QUASAR2 trial, an open-label randomized phase 3 trial.

INTRODUCTION: Patients with a high stroma percentage within the primary tumor have a poor prognosis. In this study, we investigate whether anti-angiogenic therapy might improve survival of patients with a stroma-high profile with potentially increased angiogenesis. MATERIALS AND METHODS: Tissue samples of the primary tumor of 965 colon cancer patients participating in the QUASAR2 trial were analyzed for tumor-stroma ratio (TSR). Stroma-high (>50%) and stroma-low (≤50%) groups were evaluated with respect to survival. RESULTS: Disease free survival (DFS) was significantly lower in the stroma-high group (HR 1.53, 95%CI 1.19-1.95, P = 0.001). No difference in DFS was seen with respect to treatment with capecitabine alone (CAP) or capecitabine with bevacizumab (CAPBEV) (Stroma-high HR 1.00, 95%CI 0.69-1.46, P = 0.996; stroma-low HR 1.02, 95%CI 0.75-1.41, P = 0.883). A significant difference in survival was seen comparing groups with or without vascular invasion (DFS P < 0.001). A correlation between vascular invasion and stroma-high was seen (χ2 -test P = 0.043). DISCUSSION AND CONCLUSIONS: The TSR confirmed to be a strong prognosticator for disease-free survival in a selected high-risk patient population. No benefit was found in response to treatment with bevacizumab when stratified for TSR. TSR showed to have an additional prognostic value in patients with vascular invasion present in the primary tumor.

Serum peptide signatures for pancreatic cancer based on mass spectrometry: a comparison to CA19-9 levels and routine imaging techniques.

PURPOSE: The detection of pancreatic tumors lacks a sensitive and specific diagnostic tool. Mass spectrometry (MS)-based profiling of serum proteins is a promising approach for discovery of new clinical biomarkers or biomarker signatures. METHODS: Serum samples from pancreatic cancer (PC) patients and control individuals were collected and processed using a standardized protocol. Samples were divided in a calibration set (n = 49 PC and 110 controls) and a validation set (n = 39 PC and 75 controls). Peptide profiles were obtained using a combination of automated solid-phase extraction with reversed-phase C18 paramagnetic beads and matrix-assisted laser desorption ionization time-of-flight MS. RESULTS: Linear discriminant analysis with double cross-validation resulted in a discriminating peptide signature for PC in the calibration set with a sensitivity of 78 % and a specificity of 91 % [area under the curve (AUC) of 92 %]. Classification was validated with a sensitivity of 93 % and a specificity of 100 % (AUC of 98 %), and the results were compared with carbohydrate antigen 19-9 levels and currently available clinical imaging techniques. The ten most discriminating peptide peaks were identified as fragments of proteins involved in the clotting cascade, acute phase response and immunologic response. CONCLUSIONS: In this study, it is shown that MS-based serum peptide profiles can discriminate between PC and control samples. The approach has great potential for high-throughput analysis in surveillance programs and appears to be most promising for patients with an inherited risk for PC, who benefit from more frequent screening.

Detection of pancreatic cancer using serum protein profiling.

BACKGROUND: Currently, no suitable biomarkers for the early detection of pancreatic cancer (PC) are available. Proteins present in the serum could reflect a state of the disease. In this study, these profiles as a diagnostic marker for PC were evaluated. METHODS: Serum samples were obtained from PC patients (n = 50 calibration set, n = 39 validation set) and healthy volunteers (n = 110 and n = 75 respectively) according to a uniform standardized collection and processing protocol. For peptide and protein isolation, automated solid-phase extraction (SPE) with Weak Cation Exchange (WCX) magnetic beads (MB) was performed using a 96-channel liquid handling platform. Protein profiles were obtained by mass spectrometry (MS) and evaluated by linear discriminant analysis with double cross-validation. RESULTS: A discriminating profile for PC has been identified, with a sensitivity of 78% and a specificity of 89% in the calibration set with an area under the curve (AUC) of 90%. These results were validated with a sensitivity of 74% and a specificity of 91% (AUC 90%). CONCLUSION: Serum profiles of healthy controls and PC can be discrimated between. Further research is warranted to evaluate specificity and whether this biosignature can be used for early detection in a high risk population.

Proteomic serum biomarkers and their potential application in cancer screening programs.

Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly used approach in proteomics is peptide and protein profiling. Here, we present an overview of profiling methods that have the potential for implementation in a clinical setting and in national screening programs.