Nicole Strittmatter

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

Significance Mass spectrometry imaging (MSI) technology represents a highly promising approach in cancer research. Here, we outline current roadblocks in translational MSI and introduce a comprehensive workflow designed to address current methodological limitations. An integrated bioinformatics platform is presented that allows intuitive histology-directed interrogation of MSI datasets. We show that this strategy permits the analysis of multivariate molecular signatures with direct correlation to morphological regions of interest, which can offer new insights into how different tumor microenvironmental populations interact with one another and generate novel region-of-interest specific biomarkers and therapeutic targets. Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.

Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry.

Breast cancer is a heterogeneous disease characterized by varying responses to therapeutic agents and significant differences in long-term survival. Thus, there remains an unmet need for early diagnostic and prognostic tools and improved histologic characterization for more accurate disease stratification and personalized therapeutic intervention. This study evaluated a comprehensive metabolic phenotyping method in breast cancer tissue that uses desorption electrospray ionization mass spectrometry imaging (DESI MSI), both as a novel diagnostic tool and as a method to further characterize metabolic changes in breast cancer tissue and the tumor microenvironment. In this prospective single-center study, 126 intraoperative tissue biopsies from tumor and tumor bed from 50 patients undergoing surgical resections were subject to DESI MSI. Global DESI MSI models were able to distinguish adipose, stromal, and glandular tissue based on their metabolomic fingerprint. Tumor tissue and tumor-associated stroma showed evident changes in their fatty acid and phospholipid composition compared with normal glandular and stromal tissue. Diagnosis of breast cancer was achieved with an accuracy of 98.2% based on DESI MSI data (PPV 0.96, NVP 1, specificity 0.96, sensitivity 1). In the tumor group, correlation between metabolomic profile and tumor grade/hormone receptor status was found. Overall classification accuracy was 87.7% (PPV 0.92, NPV 0.9, specificity 0.9, sensitivity 0.92). These results demonstrate that DESI MSI may be a valuable tool in the improved diagnosis of breast cancer in the future. The identified tumor-associated metabolic changes support theories of de novo lipogenesis in tumor tissue and the role of stroma tissue in tumor growth and development and overall disease prognosis.

Aurora kinase inhibitor nanoparticles target tumors with favorable therapeutic index in vivo

A nanoparticle formulation of an Aurora B kinase inhibitor uses ion pairing to achieve controlled release and efficacious, nontoxic target inhibition in tumors. Accurin nanoparticles dutifully deliver drug A class of drugs, called kinase inhibitors, could stop cancer in its tracks…if only these drugs could reach the tumors, stay for a while, and not be toxic. Hypothesizing that a nanoparticle formulation would solve the inhibitors’ woes, Ashton and colleagues investigated several different compositions of so-called Accurins—polymeric particles that encapsulate charged drugs through ion pairing. An Aurora B kinase, once formulated in Accurins, demonstrated a much-improved therapeutic index and preclinical efficacy compared with its parent molecule, when administered to rats and mice bearing human tumors. The Accurins allowed for sustained release of the drug over days, and did not have the same blood toxicity seen with the parent drug. A phase 1 trial is the next step for this nanomedicine, and additional preclinical studies will reveal whether such nanoformulations can improve the tolerability and efficacy of the broader class of molecularly targeted cancer therapeutics, including cell cycle inhibitors. Efforts to apply nanotechnology in cancer have focused almost exclusively on the delivery of cytotoxic drugs to improve therapeutic index. There has been little consideration of molecularly targeted agents, in particular kinase inhibitors, which can also present considerable therapeutic index limitations. We describe the development of Accurin polymeric nanoparticles that encapsulate the clinical candidate AZD2811, an Aurora B kinase inhibitor, using an ion pairing approach. Accurins increase biodistribution to tumor sites and provide extended release of encapsulated drug payloads. AZD2811 nanoparticles containing pharmaceutically acceptable organic acids as ion pairing agents displayed continuous drug release for more than 1 week in vitro and a corresponding extended pharmacodynamic reduction of tumor phosphorylated histone H3 levels in vivo for up to 96 hours after a single administration. A specific AZD2811 nanoparticle formulation profile showed accumulation and retention in tumors with minimal impact on bone marrow pathology, and resulted in lower toxicity and increased efficacy in multiple tumor models at half the dose intensity of AZD1152, a water-soluble prodrug of AZD2811. These studies demonstrate that AZD2811 can be formulated in nanoparticles using ion pairing agents to give improved efficacy and tolerability in preclinical models with less frequent dosing. Accurins specifically, and nanotechnology in general, can increase the therapeutic index of molecularly targeted agents, including kinase inhibitors targeting cell cycle and oncogenic signal transduction pathways, which have to date proved toxic in humans.

Mass Spectrometry Imaging of Cassette-Dosed Drugs for Higher Throughput Pharmacokinetic and Biodistribution Analysis

Cassette dosing of compounds for preclinical drug plasma pharmacokinetic analysis has been shown to be a powerful strategy within the pharmaceutical industry for increasing throughput while decreasing the number of animals used. Presented here for the first time is data on the application of a cassette dosing strategy for label-free tissue distribution studies. The aim of the study was to image the spatial distribution of eight nonproprietary drugs (haloperidol, bufuralol, midazolam, clozapine, terfenadine, erlotinib, olanzapine, and moxifloxacin) in multiple tissues after oral and intravenous cassette dosing (four compounds per dose route). An array of mass spectrometry imaging technologies, including matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI), liquid extraction surface analysis tandem mass spectrometry (LESA-MS/MS), and desorption electrospray ionization mass spectrometry (DESI-MS) was used. Tissue analysis following intravenous and oral administration of discretely and cassette-dosed compounds demonstrated similar relative abundances across a range of tissues indicating that a cassette dosing approach was applicable. MALDI MSI was unsuccessful in detecting all of the target compounds; therefore, DESI MSI, a complementary mass spectrometry imaging technique, was used to detect additional target compounds. In addition, by adapting technology used for tissue profiling (LESA-MS/MS) low spatial resolution mass spectrometry imaging (∼1 mm) was possible for all targets across all tissues. This study exemplifies the power of multiplatform MSI analysis within a pharmaceutical research and development (R&D) environment. Furthermore, we have illustrated that the cassette dosing approach can be readily applied to provide combined, label-free pharmacokinetic and drug distribution data at an early stage of the drug discovery/development process while minimizing animal usage.

Characterization and Identification of Clinically Relevant Microorganisms Using Rapid Evaporative Ionization Mass Spectrometry

Rapid evaporative ionization mass spectrometry (REIMS) was investigated for its suitability as a general identification system for bacteria and fungi. Strains of 28 clinically relevant bacterial species were analyzed in negative ion mode, and corresponding data was subjected to unsupervised and supervised multivariate statistical analyses. The created supervised model yielded correct cross-validation results of 95.9%, 97.8%, and 100% on species, genus, and Gram-stain level, respectively. These results were not affected by the resolution of the mass spectral data. Blind identification tests were performed for strains cultured on different culture media and analyzed using different instrumental platforms which led to 97.8-100% correct identification. Seven different Escherichia coli strains were subjected to different culture conditions and were distinguishable with 88% accuracy. In addition, the technique proved suitable to distinguish five pathogenic Candida species with 98.8% accuracy without any further modification to the experimental workflow. These results prove that REIMS is sufficiently specific to serve as a culture condition-independent tool for the identification and characterization of microorganisms.

Rapid Evaporative Ionization Mass Spectrometry Imaging Platform for Direct Mapping from Bulk Tissue and Bacterial Growth Media

Rapid evaporative ionization mass spectrometry (REIMS) technology allows real time intraoperative tissue classification and the characterization and identification of microorganisms. In order to create spectral libraries for training the classification models, reference data need to be acquired in large quantities as classification accuracy generally improves as a function of number of training samples. In this study, we present an automated high-throughput method for collecting REIMS data from heterogeneous organic tissue. The underlying instrumentation consists of a 2D stage with an additional high-precision z-axis actuator that is equipped with an electrosurgical diathermy-based sampling probe. The approach was validated using samples of human liver with metastases and bacterial strains, cultured on solid medium, belonging to the species P. aeruginosa, B. subtilis, and S. aureus. For both sample types, spatially resolved spectral information was obtained that resulted in clearly distinguishable multivariate clustering between the healthy/cancerous liver tissues and between the bacterial species.

Analysis of wastewater samples by direct combination of thin-film microextraction and desorption electrospray ionization mass spectrometry.

An analysis method for aqueous samples by the direct combination of C18/SCX mixed mode thin-film microextraction (TFME) and desorption electrospray ionization mass spectrometry (DESI-MS) was developed. Both techniques make analytical workflow simpler and faster, hence the combination of the two techniques enables considerably shorter analysis time compared to the traditional liquid chromatography mass spectrometry (LC-MS) approach. The method was characterized using carbamazepine and triclosan as typical examples for pharmaceuticals and personal care product (PPCP) components which draw increasing attention as wastewater-derived environmental contaminants. Both model compounds were successfully detected in real wastewater samples and their concentrations determined using external calibration with isotope labeled standards. Effects of temperature, agitation, sample volume, and exposure time were investigated in the case of spiked aqueous samples. Results were compared to those of parallel HPLC-MS determinations and good agreement was found through a three orders of magnitude wide concentration range. Serious matrix effects were observed in treated wastewater, but lower limits of detection were still found to be in the low ng L(-1) range. Using an Orbitrap mass spectrometer, the technique was found to be ideal for screening purposes and led to the detection of various different PPCP components in wastewater treatment plant effluents, including beta-blockers, nonsteroidal anti-inflammatory drugs, and UV filters.

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

BackgroundThree-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms.FindingsHigh-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma.ConclusionsWith the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

Repeatability and reproducibility of desorption electrospray ionization-mass spectrometry (DESI-MS) for the imaging analysis of human cancer tissue: a gateway for clinical applications

In this study, we aim to demonstrate the repeatability and reproducibility of DESI-MS for the imaging analysis of human cancer tissue using a set of optimal geometric and electrospray solvent parameters. Oesophageal cancer tissue was retrieved from four quadrants of a freshly removed tumor specimen, snap frozen, cryo-sectioned and mounted on glass slides for DESI-MS image acquisition. Prior to assessing precision, optimal geometric and electrospray solvent parameters were determined to maximize the number of detected lipid species and associated Total Ion Count (TIC). The same settings were utilized for all subsequent experiments. Repeatability measurements were performed using the same instrument, by the same operator on a total of 16 tissue sections (four from each quadrant of the tumor). Reproducibility measurements were determined in a different laboratory, on a separate DESI-MS platform and by an independent operator on 4 sections of one quadrant and compared to the corresponding measurements made for the repeatability experiments. The mean ± SD CV of lipid ion intensities was found to be 22 ± 7% and 18 ± 8% as measures of repeatability and reproducibility, respectively. In conclusion, DESI-MS has acceptable levels of reproducibility for the analysis of lipids in human cancer tissue and is suitable for the purposes of clinical research and diagnostics.

Simultaneous imaging of multiple neurotransmitters and neuroactive substances in the brain by desorption electrospray ionization mass spectrometry

With neurological processes involving multiple neurotransmitters and neuromodulators, it is important to have the ability to directly map and quantify multiple signaling molecules simultaneously in a single analysis. By utilizing a molecular-specific approach, namely desorption electrospray ionization mass spectrometry imaging (DESI-MSI), we demonstrated that the technique can be used to image multiple neurotransmitters and their metabolites (dopamine, dihydroxyphenylacetic acid, 3-methoxytyramine, serotonin, glutamate, glutamine, aspartate, γ-aminobutyric acid, adenosine) as well as neuroactive drugs (amphetamine, sibutramine, fluvoxamine) and drug metabolites in situ directly in brain tissue sections. The use of both positive and negative ionization modes increased the number of identified molecular targets. Chemical derivatization by charge-tagging the primary amines of molecules significantly increased the sensitivity, enabling the detection of low abundant neurotransmitters and other neuroactive substances previously undetectable by MSI. The sensitivity of the imaging approach of neurochemicals has a great potential in many diverse applications in fields such as neuroscience, pharmacology, drug discovery, neurochemistry, and medicine.