Livia S. Eberlin

Mass Spectrometry Imaging under Ambient Conditions

Mass spectrometry imaging (MSI) has emerged as an important tool in the last decade and it is beginning to show potential to provide new information in many fields owing to its unique ability to acquire molecularly specific images and to provide multiplexed information, without the need for labeling or staining. In MSI, the chemical identity of molecules present on a surface is investigated as a function of spatial distribution. In addition to now standard methods involving MSI in vacuum, recently developed ambient ionization techniques allow MSI to be performed under atmospheric pressure on untreated samples outside the mass spectrometer. Here we review recent developments and applications of MSI emphasizing the ambient ionization techniques of desorption electrospray ionization (DESI), laser ablation electrospray ionization (LAESI), probe electrospray ionization (PESI), desorption atmospheric pressure photoionization (DAPPI), femtosecond laser desorption ionization (fs-LDI), laser electrospray mass spectrometry (LEMS), infrared laser ablation metastable-induced chemical ionization (IR-LAMICI), liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS), nanospray desorption electrospray ionization (nano-DESI), and plasma sources such as the low temperature plasma (LTP) probe and laser ablation coupled to flowing atmospheric-pressure afterglow (LA-FAPA). Included are discussions of some of the features of ambient MSI for example the ability to implement chemical reactions with the goal of providing high abundance ions characteristic of specific compounds of interest and the use of tandem mass spectrometry to either map the distribution of targeted molecules with high specificity or to provide additional MS information on the structural identification of compounds. We also describe the role of bioinformatics in acquiring and interpreting the chemical and spatial information obtained through MSI, especially in biological applications for tissue diagnostic purposes. Finally, we discuss the challenges in ambient MSI and include perspectives on the future of the field.

Classifying Human Brain Tumors by Lipid Imaging with Mass Spectrometry

Brain tissue biopsies are required to histologically diagnose brain tumors, but current approaches are limited by tissue characterization at the time of surgery. Emerging technologies such as mass spectrometry imaging can enable a rapid direct analysis of cancerous tissue based on molecular composition. Here, we illustrate how gliomas can be rapidly classified by desorption electrospray ionization-mass spectrometry (DESI-MS) imaging, multivariate statistical analysis, and machine learning. DESI-MS imaging was carried out on 36 human glioma samples, including oligodendroglioma, astrocytoma, and oligoastrocytoma, all of different histologic grades and varied tumor cell concentration. Gray and white matter from glial tumors were readily discriminated and detailed diagnostic information could be provided. Classifiers for subtype, grade, and concentration features generated with lipidomic data showed high recognition capability with more than 97% cross-validation. Specimen classification in an independent validation set agreed with expert histopathology diagnosis for 79% of tested features. Together, our findings offer proof of concept that intraoperative examination and classification of brain tissue by mass spectrometry can provide surgeons, pathologists, and oncologists with critical and previously unavailable information to rapidly guide surgical resections that can improve management of patients with malignant brain tumors.

Forensic analysis of inks by imaging desorption electrospray ionization (DESI) mass spectrometry

Desorption electrospray ionization mass spectrometry (DESI-MS) is employed in the forensic analysis of documents. Blue ballpoint pen inks applied to ordinary writing paper are examined under ambient conditions without any prior sample preparation. When coupled to an automated moving stage, two-dimensional molecular images are generated. Proof-of-principle experiments include characterization of a simulated forged number and examination of older written records. This application of DESI has advantages over extractive techniques in terms of speed and sample preservation. The effects of the desorbing solvent composition, in this case a mixture of methanol and water, and of flow rate, are evaluated. Results suggest that the solubility of the analyte (dyes Basic Blue 7, Basic Violet 3 and Solvent Blue 26) plays an important role in desorption from the paper surface.

Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors

The main goal of brain tumor surgery is to maximize tumor resection while preserving brain function. However, existing imaging and surgical techniques do not offer the molecular information needed to delineate tumor boundaries. We have developed a system to rapidly analyze and classify brain tumors based on lipid information acquired by desorption electrospray ionization mass spectrometry (DESI-MS). In this study, a classifier was built to discriminate gliomas and meningiomas based on 36 glioma and 19 meningioma samples. The classifier was tested and results were validated for intraoperative use by analyzing and diagnosing tissue sections from 32 surgical specimens obtained from five research subjects who underwent brain tumor resection. The samples analyzed included oligodendroglioma, astrocytoma, and meningioma tumors of different histological grades and tumor cell concentrations. The molecular diagnosis derived from mass-spectrometry imaging corresponded to histopathology diagnosis with very few exceptions. Our work demonstrates that DESI-MS technology has the potential to identify the histology type of brain tumors. It provides information on glioma grade and, most importantly, may help define tumor margins by measuring the tumor cell concentration in a specimen. Results for stereotactically registered samples were correlated to preoperative MRI through neuronavigation, and visualized over segmented 3D MRI tumor volume reconstruction. Our findings demonstrate the potential of ambient mass spectrometry to guide brain tumor surgery by providing rapid diagnosis, and tumor margin assessment in near–real time.

Three‐Dimensional Vizualization of Mouse Brain by Lipid Analysis Using Ambient Ionization Mass Spectrometry

Two-dimensional (2D) imaging mass spectrometry (MS)[1] has emerged as a powerful technique in the biological sciences. It allows direct investigation of the distribution of a variety of lipids, drugs, biological defensive agents, pigments and proteins in plant and animal tissues with high specificity and without the need of fluorescent or radioactive labelling normally used in histochemical protocols.[2, 3] In imaging MS, the chemical identity of molecules present on a surface is investigated as a function of their 2D spatial distribution (x and y coordinates).

Cholesterol Sulfate Imaging in Human Prostate Cancer Tissue by Desorption Electrospray Ionization Mass Spectrometry

Development of methods for rapid distinction between cancerous and non-neoplastic tissues is an important goal in disease diagnosis. To this end, desorption electrospray ionization mass spectrometry (DESI-MS) imaging was applied to analyze the lipid profiles of thin tissue sections of 68 samples of human prostate cancer and normal tissue. The disease state of the tissue sections was determined by independent histopathological examination. Cholesterol sulfate was identified as a differentiating compound, found almost exclusively in cancerous tissues including tissue containing precancerous lesions. The presence of cholesterol sulfate in prostate tissues might serve as a tool for prostate cancer diagnosis although confirmation through larger and more diverse cohorts and correlations with clinical outcome data is needed.

Desorption Electrospray Ionization Mass Spectrometry for Lipid Characterization and Biological Tissue Imaging

Desorption electrospray ionization mass spectrometry (DESI-MS) imaging of biological samples allows untargeted analysis and structural characterization of lipids ionized from the near-surface region of a sample under ambient conditions. DESI is a powerful and sensitive MS ionization method for 2D and 3D imaging of lipids from direct and unmodified complex biological samples. This review describes the strengths and limitations of DESI-MS for lipid characterization and imaging together with the technical workflow and a survey of applications. Included are discussions of lipid mapping and biomarker discovery as well as a perspective on the future of DESI imaging.

Multivariate statistical differentiation of renal cell carcinomas based on lipidomic analysis by ambient ionization imaging mass spectrometry.

AbstractDesorption electrospray ionization (DESI) mass spectrometry (MS) was used in an imaging mode to interrogate the lipid profiles of thin tissue sections of 11 sample pairs of human papillary renal cell carcinoma (RCC) and adjacent normal tissue and nine sample pairs of clear cell RCC and adjacent normal tissue. DESI-MS images showing the spatial distributions of particular glycerophospholipids (GPs) and free fatty acids in the negative ion mode were compared to serial tissue sections stained with hematoxylin and eosin (H&E). Increased absolute intensities as well as changes in relative abundance were seen for particular compounds in the tumor regions of the samples. Multivariate statistical analysis using orthogonal projection to latent structures treated partial least square discriminate analysis (PLS-DA) was used for visualization and classification of the tissue pairs using the full mass spectra as predictors. PLS-DA successfully distinguished tumor from normal tissue for both papillary and clear cell RCC with misclassification rates obtained from the validation set of 14.3% and 7.8%, respectively. It was also used to distinguish papillary and clear cell RCC from each other and from the combined normal tissues with a reasonable misclassification rate of 23%, as determined from the validation set. Overall DESI-MS imaging combined with multivariate statistical analysis shows promise as a molecular pathology technique for diagnosing cancerous and normal tissue on the basis of GP profiles. FigureMolecular disease diagnostics by DESI without sample preparation. a Good information is obtained by mapping the distribution of individual compounds in the tissue (e.g., PI(18:0/20:4). b Even better discrimination between tumor and healthy tissue is achieved using PLS-DA to consider all the data after having established through a training set of samples the features that correlate with disease as recognized by standard H&E stain pathological examination

Intraoperative mass spectrometry mapping of an onco-metabolite to guide brain tumor surgery

Significance The diagnosis of tumors during surgery still relies principally on an approach developed over 150 y ago: frozen section microscopy. We show that a validated molecular marker—2-hydroxyglutarate generated from isocitrate dehydrogenase 1 mutant gliomas—can be rapidly detected from tumors using a form of ambient MS that does not require sample preparation. We use the Advanced Multimodality Image Guided Operating Suite at Brigham and Women’s Hospital to demonstrate that desorption electrospray ionization MS could be used to detect residual tumor that would have been left behind in the patient. The approach paves the way for the clinical testing of MS-based intraoperative monitoring of tumor metabolites, an advance that could revolutionize the care of surgical oncology patients. For many intraoperative decisions surgeons depend on frozen section pathology, a technique developed over 150 y ago. Technical innovations that permit rapid molecular characterization of tissue samples at the time of surgery are needed. Here, using desorption electrospray ionization (DESI) MS, we rapidly detect the tumor metabolite 2-hydroxyglutarate (2-HG) from tissue sections of surgically resected gliomas, under ambient conditions and without complex or time-consuming preparation. With DESI MS, we identify isocitrate dehydrogenase 1-mutant tumors with both high sensitivity and specificity within minutes, immediately providing critical diagnostic, prognostic, and predictive information. Imaging tissue sections with DESI MS shows that the 2-HG signal overlaps with areas of tumor and that 2-HG levels correlate with tumor content, thereby indicating tumor margins. Mapping the 2-HG signal onto 3D MRI reconstructions of tumors allows the integration of molecular and radiologic information for enhanced clinical decision making. We also validate the methodology and its deployment in the operating room: We have installed a mass spectrometer in our Advanced Multimodality Image Guided Operating (AMIGO) suite and demonstrate the molecular analysis of surgical tissue during brain surgery. This work indicates that metabolite-imaging MS could transform many aspects of surgical care.

Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging

Significance Complete resection of a tumor is associated with an improved prognosis for most types of solid malignancies. In gastric-cancer surgery, surgical-margin evaluation is commonly performed intraoperatively by histopathologic evaluation of frozen sections. However, frozen-section results are subjective and can be unreliable in up to 30% of patients undergoing resection of gastrointestinal cancers. We used desorption electrospray ionization mass spectrometric imaging (DESI-MSI) and the statistical method of least absolute shrinkage and selection operator (Lasso) to classify tissue as cancer or normal based on molecular information obtained from tissue and also to select those mass-spectra features most indicative of disease state. The results obtained using margin samples from nine gastric-cancer operations suggest that DESI-MSI/Lasso may be a valuable tool for routine intraoperative assessment of surgical margins during gastric-cancer surgery. Surgical resection is the main curative option for gastrointestinal cancers. The extent of cancer resection is commonly assessed during surgery by pathologic evaluation of (frozen sections of) the tissue at the resected specimen margin(s) to verify whether cancer is present. We compare this method to an alternative procedure, desorption electrospray ionization mass spectrometric imaging (DESI-MSI), for 62 banked human cancerous and normal gastric-tissue samples. In DESI-MSI, microdroplets strike the tissue sample, the resulting splash enters a mass spectrometer, and a statistical analysis, here, the Lasso method (which stands for least absolute shrinkage and selection operator and which is a multiclass logistic regression with L1 penalty), is applied to classify tissues based on the molecular information obtained directly from DESI-MSI. The methodology developed with 28 frozen training samples of clear histopathologic diagnosis showed an overall accuracy value of 98% for the 12,480 pixels evaluated in cross-validation (CV), and 97% when a completely independent set of samples was tested. By applying an additional spatial smoothing technique, the accuracy for both CV and the independent set of samples was 99% compared with histological diagnoses. To test our method for clinical use, we applied it to a total of 21 tissue-margin samples prospectively obtained from nine gastric-cancer patients. The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery.