Aim: To identify molecular features associated with clinico-pathological parameters in renal cell cancer.
Materials and methods: Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging was employed for a kidney cancer tissue microarray containing tissue samples from 789 patients for which clinical follow-up data were available.
Results: A comparison of mass spectrometric signals with clinico-pathological features revealed significant differences between papillary and clear cell renal cell cancer. Within the subgroup of clear cell RCC, statistical associations with tumor stage (seven signals, p<0.01 each), Fuhrman grade (seven signals, p<0.0001 each), and presence of lymph node metastases (10 signals, p<0.01 each) were found. In addition, the presence of one signal was significantly linked to shortened patient survival (p=0.0198).
Conclusion: Our data pinpoint towards various molecules with potential relevance in renal cell cancer. They also demonstrate that the combination of the MALDI mass spectrometry imaging and large-scale tissue microarray platforms represents a powerful approach to identify clinically-relevant molecular cancer features.
Keywords: MALDI mass spectrometry imaging; MALDI-MSI; biomarker; renal cell cancer; tissue microarray.