The immunogenic nature of cancer can be explored to distinguish pancreatic cancer from related non-cancer conditions. We describe a liquid-based microarray approach followed by statistical analysis and confirmation for discovery of auto-immune biomarkers for pancreatic cancer. Proteins from the Panc-1 pancreatic cancer cell line were fractionated using a 2-D liquid separation method into over 1052 fractions and spotted onto nitrocellulose coated glass slides. The slides were hybridized with 37 pancreatic cancer sera, 24 chronic pancreatitis sera and 23 normal sera to detect elevated levels of reactivity against the proteins in spotted fractions. The response data obtained from protein microarrays was first analyzed by Wilcoxon Rank-Sum Tests to generate two lists of fractions that positively responded to the cancer sera and showed p-values less than 0.02 in the pairwise comparison between cancer specimens and normal and chronic pancreatitis specimens. The top 3 fractions with the lowest correlations were combined in receiver operating characteristic analyses. The area-under-the-curve (AUC) values are 0.813 and 0.792 for cancer vs. normal and cancer vs. pancreatitis respectively. Outlier-Sum statistics were then applied to the microarray data to determine the existence of outliers exclusive in cancer sera. The selected fractions were identified by LC-MS/MS. We further confirmed the occurrence of outliers with three proteins among cancer samples in a confirmation experiment using a separate dataset of 165 serum samples containing 48 cancer sera and 117 non-cancer controls. Phosphoglycerate kinase 1 (PGK1) elicited greater reactivity in 20.9% (10 in 48) of the samples in the cancer group, while no outlier was present in the non-cancer groups.