Prostate cancer diagnosis and characterization with mass spectrometry imaging

Abstract

BackgroundProstate cancer (PCa), the most common cancer and second leading cause of cancer death in American men, presents the clinical challenge of distinguishing between indolent and aggressive tumors for proper treatment. PCa presents significant alterations in metabolic pathways that can potentially be measured using techniques like mass spectrometry (MS) or mass spectrometry imaging (MSI) and used to characterize PCa aggressiveness. MS quantifies metabolomic, proteomic, and lipidomic profiles of biological systems that can be further visualized for their spatial distributions through MSI.MethodsPubMed was queried for all publications relating to MS and MSI in human prostate cancer from April 2007 to April 2017. With the goal of reviewing the utility of MSI in diagnosis and prognostication of human PCa, MSI articles that reported investigations of PCa-specific metabolites or metabolites indicating PCa aggressiveness were selected for inclusion. Articles were included that covered MS and MSI principles, limitations, and applications in PCa.ResultsWe identified nine key studies on MSI in intact human prostate tissue specimens that determined metabolites which could either differentiate between benign and malignant prostate tissue or indicate prostate cancer aggressiveness. These MSI-detected biomarkers show promise in reliably identifying PCa and determining disease aggressiveness.ConclusionsMSI represents an innovative technique with the ability to interrogate cancer biomarkers in relation to tissue pathologies and investigate tumor aggressiveness. We propose MSI as a powerful adjuvant histopathology imaging tool for prostate tissue evaluations, where clinical translation of this ex vivo technique could make possible the use of MSI for personalized medicine in diagnosis and prognosis of prostate cancer. Moreover, the knowledge provided from this technique can majorly contribute to the understanding of molecular pathogenesis of PCa and other malignant diseases.

The foundations and development of lipidomics

“…In the last 20 years, development of lipidomics technologies has vastly improved by the following: i ) extensive characterization of the structures of known lipid classes and subclasses and uncovering both new classes and new molecular species of lipids (e.g., ( 4 , 74 , 134 , 135 , 136 , 137 , 138 )); ii ) sensitive quantification of lipid species at attomole to femtomole levels from a variety of biological samples (e.g., ( 132 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 )); iii ) applications for biomedical and biological studies through pathway/network analysis; iv ) biomarker development that facilitates prediction, diagnosis, and prognosis of disease states (see recent reviews for references ( 83 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 )); v ) determining the alterations of lipids in spatial distribution via mapping complex organs by MALDI imaging (see recent reviews for references ( 157 , 158 , 159 , 160 , 161 , 162 )); and vi ) advances in bioinformatics to facilitate real time data processing (e.g., ( 88 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 )).…”

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

“…This technique, although very potent in prostate cancer biomarker discovery [ 79 ], is currently not particularly high throughput and is mostly used to assess specific molecules or classes of molecules in a targeted fashion. For example, Kurreck et al [ 80 ] have performed a systematic review for MSI metabolic studies in prostate cancer for diagnostic and prognostic set-ups. Recently, MSI has been used to identify, e.g., lipids distinguishing GS (4 + 3) from GS (3 + 4) tumors [ 81 ], to find zinc and its pathway metabolites citrate and aspartate correlated with each other and showing a significant reduction in cancer compared to non-cancer epithelium [ 82 ], and to find metabolic and lipid profiles differentiating cancer, non-cancer epithelium, and stroma [ 82 ].…”

Mass Spectrometry Technologies to Advance Care for Cancer Patients in Clinical and Intraoperative Use

“…The data generated from areas of pure cancer or benign epithelial cells were used to create an algorithm based on 26 glycerophospholipids, yielding 87.5% sensitivity and 91.7% specificity when predicting cancer status on a validation set of 24 samples. Based on this and other studies (Kurreck et al, 2018), high spatial resolution MALDI imaging has been proposed as a tool for biomarker discovery that can be used to improve prostate cancer diagnosis and prediction of prognosis. These examples illustrate the importance of determining adequate MALDI-MS imaging conditions (i.e., spatial resolution, speed) to investigate a particular disease and provide relevant molecular characterization for cancer biomarker discovery.…”