Analysis of colorectal adenocarcinoma tissue by desorption electrospray ionization mass spectrometric imaging

Abstract

Negative ion desorption electrospray ionization (DESI) was used for the analysis of an ex vivo tissue sample set comprising primary colorectal adenocarcinoma samples and colorectal adenocarcinoma liver metastasis samples. Frozen sections (12 μm thick) were analyzed by means of DESI imaging mass spectrometry (IMS) with spatial resolution of 100 μm using a computer-controlled DESI imaging stage mounted on a high resolution Orbitrap mass spectrometer. DESI-IMS data were found to predominantly feature complex lipids, including phosphatidyl-inositols, phophatidyl-ethanolamines, phosphatidyl-serines, phosphatidyl-ethanolamine plasmalogens, phosphatidic acids, phosphatidyl-glycerols, ceramides, sphingolipids, and sulfatides among others. Molecular constituents were identified based on their exact mass and MS/MS fragmentation spectra. An identified set of molecules was found to be in good agreement with previously reported DESI imaging data. Different histological tissue types were found to yield characteristic mass spectrometric data in each individual section. Histological features were identified by comparison to hematoxylin-eosin stained neighboring sections. Ions specific to certain histological tissue types (connective tissue, smooth muscle, healthy mucosa, healthy liver parenchyma, and adenocarcinoma) were identified by semi-automated screening of data. While each section featured a number of tissue-specific species, no potential global biomarker was found in the full sample set for any of the tissue types. As an alternative approach, data were analyzed by principal component analysis (PCA) and linear discriminant analysis (LDA) which resulted in efficient separation of data points based on their histological types. A pixel-by-pixel tissue identification method was developed, featuring the PCA/LDA analysis of authentic data set, and localization of unknowns in the resulting 60D, histologically assigned LDA space. Novel approach was found to yield results which are in 95% agreement with the results of classical histology. KRAS mutation status was determined for each sample by standard molecular biology methods and a similar PCA/LDA approach was developed to assess the feasibility of the determination of this important parameter using solely DESI imaging data. Results showed that the mutant and wild-type samples fully separated. DESI-MS and molecular biology results were in agreement in 90% of the cases.

High Resolution Tissue Imaging Using the Single-probe Mass Spectrometry under Ambient Conditions

“…We were also able to validate the identifications by subjecting the metabolites to higher-energy collisional dissociation (HCD) MS/MS analysis at 60,000 (m/Δm) mass resolution with a m/z ±0.5 window. Figure 6a shows the MS/MS spectrum for m/z 798.5467, which contains the characteristic peak at m/z 162.9566 corresponding to the potassium adduct of CH 3 + was observed at low intensities, and this fragment was observed previously for both protonated species and metal ion adducts of certain PCs [40]. For the MS/MS spectrum at m/z 814.5720 ( Figure 6b …”

“…MSI involves the gathering of MS spectra in a spatially defined manner for a particular sample of interest such that the distribution of a large number of biochemicals such as metabolites and proteins can be obtained within a single experiment. The potential of MSI to improve analysis of biological samples has already been demonstrated in many previous studies, such as the ability to image metabolite distributions in mouse brain sections [2], determine tissue type in tumors [3], to image protein localizations in formalin fixed tissues [4], biomarker discovery [5], and many others.…”

XMS: Cross-Platform Normalization Method for Multimodal Mass Spectrometric Tissue Profiling

“…The best compromise between high specificity and good sensitivity (for values, see Supplemental Information Figure S-5) for matching analyte with the corresponding peak in the database was achieved with a mass deviation parameter of 8 ppm. The chosen mass range of m/z = 600 to 1000 was found to be sufficient for accurate tissue identification using REIMS and DESI [35,36]. The different ionization techniques produce complex mass spectra from biological tissue samples, especially in the lower mass range where solvent and other peaks of numerous different molecule classes are present.…”

Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer

“…With each of these described approaches, operating characteristics and experimental parameters can be modulated to suit specific analytical objectives and can be customized for the identification of particular biomolecular species. Here, we have opted to use the DESI technique as there are several practical advantages with this method for metabolome-wide imaging studies, primarily attributable to lack of requirement for matrix deposition and ambient ionization, which requires minimal sample preparation (11,12).…”

“…Together with emerging metabolomicsbased profiling approaches, MSI represents a highly promising approach in molecular systems oncology (4,5) and is increasingly being used for the discovery of next-generation cancer biomarker panels (6,7). Among the MSI techniques currently available, the three most commonly used are matrix-assisted laser desorption ionization (MALDI) (2,6), secondary ion mass spectrometry (SIMS) (8,9), and desorption electrospray ionization (DESI) (10,11). With each of these described approaches, operating characteristics and experimental parameters can be modulated to suit specific analytical objectives and can be customized for the identification of particular biomolecular species.…”