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

Abstract

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 5 0.0145). Multiple signals were associated with the ERG-fusion status of our cancers. Two of 15 epithelium-associated signals including m/z 1,013 and m/z 1,502 were associated with detectable ERG expression and five signals (m/z 644, 678, 1,044, 3,086 and 3,577) were associated with ERG negativity. These observations are in line with substantial molecular differences between fusion-type and non-fusion type prostate cancer. The signals observed in this study may characterize molecules that play a role in the development of TMPRSS2-ERG fusions, or alternatively reflect pathways that are activated as a consequence of ERG-activation. The combination of MSI and large-scale TMAs reflects a powerful approach enabling immediate prioritization of MSI signals based on associations with clinico-pathological and molecular data.Prostate cancer is a leading cause of cancer-related mortality in males. Worldwide, more than 600,000 men are diagnosed with prostate cancer each year. 1 Although the majority of prostate cancers are detected at early stages as a result of prostate specific antigen (PSA) screening, many patients present with advanced and metastatic cancer at the time of diagnosis. 2 It is hoped that a better understanding of the molecular biology of prostate cancer will help to improve prostate cancer diagnosis and therapy.Screening methods such as DNA, RNA, and protein arrays have led to the identification of multiple candidate gene alterations that occur in usually small fractions of prostate cancers. [3][4][5] Most of these alterations have not been further analyzed for clinical significance, partly because the necessary tissue samples with clinical annotation were lacking in the laboratories where the screening methods were utilized. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometric imaging (MSI) on a tissue microarray (TMA) is an interesting concept for screening for clinically relevant biomarkers. [6][7][8] This approach combines a systematic search for novel biomarkers by mass spectrometry with a simultaneous analysis of the newly found parameters on hundreds of tumors with clinical follow-up data.In this study, we applied MSI to a TMA contai...

Tumor classification with MALDI-MSI data of tissue microarrays: A case study

“…There are several ways to investigate the predictive power of the selected features. Perhaps the simplest way is to correlate individual features to the parameter of interest [1,9]. It is also possible to combine features to increase their predictive power, for example by Hierarchical Clustering [3,5,8].…”

“…So far, many studies that were successful in the identification of prognostic markers performed intact protein analysis on fresh frozen tissue sections [3,8]. In [1,9,10] TMAs with samples from more than 100 patients were used. An important step in MALDI-MSI classification studies is to select features out of the high-dimensional data.…”

“…These properties make TMAs well suited for biomarker discovery studies. Up to a thousand patient samples per study can now be analyzed in a MALDI-MSI experiment [1].…”

Mass Spectrometry Imaging of Biomolecular Information

“…FFPE samples can be analyzed and imaged after direct tryptic digestion 154 or after heat-induced antigen retrieval, dewaxing an digestion 155 . MALDI MSI of FFPE tissue has been reported in great numbers recently 10,[156][157][158][159][160][161][162][163][164][165][166][167][168][169][170][171][172][173] . To mention just one example: ovarian cancer FFPE samples were investigated to describe progression, metastases and other factors of cancer development by topographic parameters and molecular information 169 .…”

Scores for standardization of on-tissue digestion of formalin-fixed paraffin-embedded tissue in MALDI-MS imaging

“…In parallel, computational methods for MSI data pre-processing, feature extraction, (tumor) tissue classification and spatial autocorrelation have been advanced [23][24][25][26][27][28][29][30][31][32][33][34], but most of them still focus on MS imaging of non-digested human FFPE or frozen tissue [24,29,[35][36][37][38][39][40]. Classification of human tumors based on digested FFPE tissue and MALDI MSI has been described, in seminal proof-of-concept studies, for pancreatic cancer [41] and prostate cancer [42]. Successful diagnosis of disease, which may be on the verge of use in routine pathology and is based on MALDI MS imaging of digested FFPE tissue, has been suggested for some diseases less complex than cancer, e.g.…”