MALDI imaging-based identification of prognostically relevant signals in bladder cancer using large-scale tissue microarrays.

Objective: Although most patients with urinary bladder cancer present with noninvasive and low-malignant stages of the disease, about 20% eventually develop life-threatening metastatic tumors. This study was designed to evaluate the potential of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify molecular markers predicting the clinical course of bladder cancer.

Materials And Methods: We employed MALDI-MSI to a bladder cancer tissue microarray including paraffin-embedded tissue samples from 697 patients with clinical follow-up data to search for prognostically relevant associations.

Results: Analysis of our MALDI imaging data revealed 40 signals in the mass spectra (m/z signals) associated with epithelial structures. The presence of numerous m/z signals was statistically related to one or several phenotypical findings including tumor aggressiveness (stage, grade, or nodal status; 30 signals), solid (5 signals) or papillary (3 signals) growth patterns, and increased (6 signals) or decreased (12 signals) cell proliferation, as determined by Ki-67 immunohistochemistry. Two signals were linked with tumor recurrence in noninvasive (pTa category) tumors, of which one was also related to progression from pTa-category to pT1-category disease. The absence of one m/z signal was linked with decreased survival in the subset of 102 muscle-invasive cancers.

Conclusion: Our data demonstrate the suitability of combining MSI and large-scale tissue microarrays to simultaneously identify and validate clinically useful molecular markers in urinary bladder cancer.