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.

MALDI imaging on large-scale tissue microarrays identifies molecular features associated with tumour phenotype in oesophageal cancer.

Aims: Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) and tissue microarray (TMA) technologies were jointly utilized to search for molecular features associated with clinicopathological parameters in oesophageal cancer.

Methods And Results: Two TMAs from formalin-fixed tissue samples, including 300 adenocarcinomas and 177 squamous cell carcinomas with clinical follow-up data, were analysed. MALDI-MSI analysis revealed 72 distinct mass per charge (m/z) signals associated with tumour cells, 48 of which were found in squamous cell carcinomas only, and 12 of which were specific for adenocarcinomas.

MALDI mass spectrometric imaging based identification of clinically relevant signals in prostate cancer using large-scale tissue microarrays.

To identify molecular features associated with clinico-pathological parameters and TMPRSS2-ERG fusion status in prostate cancer, we employed MALDI mass spectrometric imaging (MSI) to a prostate cancer tissue microarray (TMA) containing formalin-fixed, paraffin-embedded tissues samples from 1,044 patients for which clinical follow-up data were available. MSI analysis revealed 15 distinct mass per charge (m/z)-signals associated to epithelial structures. A comparison of these signals with clinico-pathological features revealed statistical association with favorable tumor phenotype such as low Gleason grade, early pT stage or low Ki67 labeling Index (LI) for four signals (m/z 700, m/z 1,502, m/z 1,199 and m/z 3,577), a link between high Ki67LI for one signal (m/z 1,013) and a relationship with prolonged time to PSA recurrence for one signal (m/z 1,502; p = 0.