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. 2011 Feb 15;17(4):805-16.
doi: 10.1158/1078-0432.CCR-10-0248.

Serum biomarker panels for the detection of pancreatic cancer

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Serum biomarker panels for the detection of pancreatic cancer

Randall E Brand et al. Clin Cancer Res. .

Abstract

Purpose: Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.

Experimental design: Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.

Results: Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.

Conclusions: The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations.

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Figures

Figure 1
Figure 1. Receiver operator characteristic curves (ROC) for diagnosis of PDAC vs. Healthy controls and Benign cases
A,B, The diagnostic performance of the CA 19-9, ICAM-1, OPG combination (solid line) and CA 19-9 alone (dotted line) for the discrimination of PDAC vs. Healthy in the training set (A) and in the independent validation set (B). C,D, The diagnostic performance of the CA 19-9, CEA, TIMP-1 combination (solid line) and CA 19-9 alone (dotted line) for the discrimination of PDAC vs. Benign disease in the training set (A) and in an independent validation set (B). Areas under curve (AUC) with 95% CI are presented.

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