Purpose: There is evidence that therapeutic cancer vaccines can lengthen survival for some cancer patients, but responses vary widely from one person to another. Methods to predict clinical outcomes will advance the field and provide new insights into critical determinants of in vivo efficacy. This study uses a high-throughput glycan microarray to assess correlations between a subject's overall survival after receiving PROSTVAC-VF and his baseline serum anti-glycan antibody levels. Results: Pre-vaccination antibody levels to blood group A trisaccharide (BG-Atri) were found to have a statistically significant correlation with survival. Long-term survival was approximately doubled in subjects with abundant anti-BG-Atri IgM relative to subjects with little or no pre-existing IgM for BG-Atri. This survival correlation was specific to vaccine treatment, as no correlation was observed in control patients immunized with wild-type poxviruses lacking the key tumor antigen, prostate specific antigen (PSA). Moreover, anti-BG-Atri IgM levels were not correlated with general measures of disease severity, such as PSA levels, Gleason score, or Halabi predicted survival. Conclusion: In addition to reporting a new potentially predictive biomarker for PROSTVAC-VF, this study highlights the potential of glycan microarray technology for personalized medicine. The overall study was a retrospective analysis of 141 subjects from phase II trials of PROSTVAC-VF, a poxvirus based cancer vaccine currently in phase III clinical trials for advanced prostate cancer. The subjects were divided into a training set (n=28) and a validation set (n=113). A glycan microarray was used to profile pre-vaccination anti-glycan antibody populations in sera as potential biomarkers for PROSTVAC-VF. For both the training set and validation set, the anti-glycan profiles were measured using four variations of serum dilution and isotype specific secondary antibody (IgM at 1:50, IgG at 1:50, total Ig at 1:50, and total Ig at 1:200). Total immunoglobin (IgM + IgG + IgA) levels for the training set measured at serum dilution of 1:50 are detailed here. The screen for predictive biomarkers identified anti-glycan antibodies that consistently stratified subjects into groups with different Kaplan Meier survival estimates. Due to the potential for overfitting, a permutation test was used to estimate the false discovery rate. Raw data on superSeries GSE42184 record.