Ambient ionization - mass spectrometry: Advances toward intrasurgical cancer detection

My dissertation research has focused on the development of ambient ionization – mass spectrometry (MS) for clinical measurements, specifically intrasurgical cancer detection. The molecular differences between normal and cancerous tissue were detected via direct tissue analysis in vitro by touch spray ionization (TS) or by analyzing sectioned or smeared tissue using desorption electrospray ionization (DESI). The physical form of the tissue, e.g. in vitro sampling, sectioned, or smeared, was inconsequential in differentiating normal from cancerous tissue; however, the spectra acquired by TS and DESI differed due to differences in ionization processes. We envision that TS-MS and DESI-MS could impact diagnostic medicine, for example in providing surgeons with rapid, near real-time information as to tissue disease state, i.e. normal or tumor. Disease state information provided to surgeons about discrete pathologically ambiguous areas, ideally intrasurgically via TS or DESI-MS smear analysis, could improve the completeness of tumor resection while minimizing unintended damage to adjacent tissue. Touch spray ionization was developed for intrasurgical detection of cancer; TS greatly simplifies MS analysis by using the same device for in vivo sampling and subsequent ionization. Frozen tissue sections were sampled and analyzed by TS-MS providing the ability to differentiate normal from human prostate cancer, via lipid profiles, using multivariate statistics. The next proof-of-concept step for TS-MS was the analysis human kidney cancer specimens in vitro, immediately following resection. TS-MS analysis of untreated kidney tissue emulated intrasurgical use, e.g. the presence and co-sampling of biofluids such as blood. Regardless, normal renal tissue and kidney cancer was differentiated using lipid profiles and multivariate statistics. Desorption electrospray ionization (DESI) - MS imaging of tissue sections differentiated normal from tumor in all cancers studied. DESI-MS imaging of human prostate and human kidney tissue sections were performed to corroborate TS-MS results. Human brain cancer, a major focus of my dissertation research, was studied by imaging tissue sections using DESI-MS to establish the characteristic chemical features, e.g. lipid and metabolite profiles, that distinguish normal brain parenchyma from gliomas and different brain tumors. It was found that information in the negative ion mode lipid profile, positive ion mode lipid profile, and negative ion mode metabolite profile is able to discriminate brain parenchyma (grey and white matter) and gliomas, the most common form of malignant brain tumor. Further, the negative mode lipid and metabolite profiles also proved capable of discriminating different types of brain tumors (gliomas, meningiomas, and pituitary tumors) which account for ~80% of all central nervous system tumors. DESI-MS imaging of effaced or otherwise pathologically ambiguous frozen tissue sections offered the ability to determine the underlying brain parenchyma in cancerous samples – something that traditional morphologic evaluation was not able to determine. Further, DESI-MS was able to detect molecular changes resulting from varying amounts of glioma tumor cells present within infiltrated tissues. The tumor cell percentage of these samples was predicted using N-acetyl-aspartic acid, a neurometabolite which was found to decrease in cancerous tissue, and matched well with histopathologic evaluation. The transition from DESI-MS imaging of sectioned tissue to DESI-MS analysis of tissue smears was driven by the time restriction of intrasurgical application. The potential of DESI-MS analysis of smears was first demonstrated upon canine non-Hodgkin’s lymphoma fine-needle aspirate smears which provided similar sensitivity and specificity values to that of tissue section imaging but is technically less demanding and decreased analysis time. DESI-MS imaging of tissue sections established that MS profiles contained the sufficient information for diagnosis; whereas DESI-MS analysis of tissue smears made the intrasurgical analysis of human brain tumors feasible. The observed lipid or metabolite profiles were not significantly altered by the physical act of smearing and their signal intensities were comparable to those of tissue sections. Further, the chemical information obtained from tissue smears was equivalent to those of tissue sections as determined by canonical component analysis. The culmination of my dissertation research was the creation and implementation of an intrasurgical DESI-MS tissue smear analysis method for human gliomas. Preliminary results from the initial intrasurgical cases analyzed using the developed DESI-MS method are discussed

Enhanced Characterization of Drug Metabolism and the Influence of the Intestinal Microbiome: A Pharmacokinetic, Microbiome, and Untargeted Metabolomics Study.

Determining factors that contribute to interindividual and intra-individual variability in pharmacokinetics (PKs) and drug metabolism is essential for the optimal use of drugs in humans. Intestinal microbes are important contributors to variability; however, such gut microbe-drug interactions and the clinical significance of these interactions are still being elucidated. Traditional PKs can be complemented by untargeted mass spectrometry coupled with molecular networking to study the intricacies of drug metabolism. To show the utility of molecular networking on metabolism we investigated the impact of a 7-day course of cefprozil on cytochrome P450 (CYP) activity using a modified Cooperstown cocktail and assessed plasma, urine, and fecal data by targeted and untargeted metabolomics and molecular networking in healthy volunteers. This prospective study revealed that cefprozil decreased the activities of CYP1A2, CYP2C19, and CYP3A, decreased alpha diversity and increased interindividual microbiome variability. We further demonstrate a relationship between the loss of microbiome alpha diversity caused by cefprozil and increased drug and metabolite formation in fecal samples. Untargeted metabolomics/molecular networking revealed several omeprazole metabolites that we hypothesize may be metabolized by both CYP2C19 and bacteria from the gut microbiome. Our observations are consistent with the hypothesis that factors that perturb the gut microbiome, such as antibiotics, alter drug metabolism and ultimately drug efficacy and toxicity but that these effects are most strongly revealed on a per individual basis

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS

Examination of tissue sections using desorption electrospray ionization (DESI)-MS revealed phospholipid-derived signals that differ between gray matter, white matter, gliomas, meningiomas, and pituitary tumors, allowing their ready discrimination by multivariate statistics. A set of lower mass signals, some corresponding to oncometabolites, including 2-hydroxyglutaric acid and N-acetyl-aspartic acid, was also observed in the DESI mass spectra, and these data further assisted in discrimination between brain parenchyma and gliomas. The combined information from the lipid and metabolite MS profiles recorded by DESI-MS and explored using multivariate statistics allowed successful differentiation of gray matter (n = 223), white matter (n = 66), gliomas (n = 158), meningiomas (n = 111), and pituitary tumors (n = 154) from 58 patients. A linear discriminant model used to distinguish brain parenchyma and gliomas yielded an overall sensitivity of 97.4% and a specificity of 98.5%. Furthermore, a discriminant model was created for tumor types (i.e., glioma, meningioma, and pituitary), which were discriminated with an overall sensitivity of 99.4% and a specificity of 99.7%. Unsupervised multivariate statistics were used to explore the chemical differences between anatomical regions of brain parenchyma and secondary infiltration. Infiltration of gliomas into normal tissue can be detected by DESI-MS. One hurdle to implementation of DESI-MS intraoperatively is the need for tissue freezing and sectioning, which we address by analyzing smeared biopsy tissue. Tissue smears are shown to give the same chemical information as tissue sections, eliminating the need for sectioning before MS analysis. These results lay the foundation for implementation of intraoperative DESI-MS evaluation of tissue smears for rapid diagnosis

Initial Development toward Non-Invasive Drug Monitoring via Untargeted Mass Spectrometric Analysis of Human Skin.

Drug monitoring is crucial for providing accurate and effective care; however, current methods (e.g., blood draws) are inconvenient and unpleasant. We aim to develop a non-invasive method for the detection and monitoring of drugs via human skin. The initial development toward this aim required information about which drugs, taken orally, can be detected via the skin. Untargeted liquid chromatography-mass spectrometry (LC-MS) was used as it was unclear if drugs, known drug metabolites, or other transformation products were detectable. In accomplishing our aim, we analyzed samples obtained by swabbing the skin of 15 kidney transplant recipients in five locations (forehead, nasolabial area, axillary, backhand, and palm), bilaterally, on two different clinical visits. Untargeted LC-MS data were processed using molecular networking via the Global Natural Products Social Molecular Networking platform. Herein, we report the qualitative detection and location of drugs and drug metabolites. For example, escitalopram/citalopram and diphenhydramine, taken orally, were detected in forehead, nasolabial, and hand samples, whereas N-acetyl-sulfamethoxazole, a drug metabolite, was detected in axillary samples. In addition, chemicals associated with environmental exposure were also detected from the skin, which provides insight into the multifaceted chemical influences on our health. The proof-of-concept results presented support the finding that the LC-MS and data analysis methodology is currently capable of the qualitative assessment of the presence of drugs directly via human skin

Intraoperative assessment of tumor margins during glioma resection by desorption electrospray ionization-mass spectrometry

Gliomas infiltrate into surrounding healthy brain tissue. Microsurgical resection aims for maximal tumor resection while minimizing morbidity. Surgical margins are defined based on the surgeon’s experience, visual observation, and neuronavigation. Surgical margin assessment is rarely undertaken intraoperatively due to time constraints and unreliability of such evaluation. Routine, pathologic intraoperative examination provides no molecular information. Molecular measurements using mass spectrometry can be made rapidly on tissue during surgery to identify tissue types, estimate tumor infiltration, and recognize the presence of prognostic mutations by monitoring oncometabolites and phospholipids. This intraoperative study demonstrates the power of mass spectrometry in assessing diagnostic and prognostic information on discrete surgeon-defined points along the resection margins to improve tumor resection, even in regions without MRI contrast enhancement., Intraoperative desorption electrospray ionization-mass spectrometry (DESI-MS) is used to characterize tissue smears by comparison with a library of DESI mass spectra of pathologically determined tissue types. Measurements are performed in the operating room within 3 min. These mass spectra provide direct information on tumor infiltration into white or gray brain matter based on N-acetylaspartate (NAA) and on membrane-derived complex lipids. The mass spectra also indicate the isocitrate dehydrogenase mutation status of the tumor via detection of 2-hydroxyglutarate, currently assessed postoperatively on biopsied tissue using immunohistochemistry. Intraoperative DESI-MS measurements made at surgeon-defined positions enable assessment of relevant disease state of tissue within the tumor mass and examination of the resection cavity walls for residual tumor. Results for 73 biopsies from 10 surgical resection cases show that DESI-MS allows detection of glioma and estimation of high tumor cell percentage (TCP) at surgical margins with 93% sensitivity and 83% specificity. TCP measurements from NAA are corroborated by indirect measurements based on lipid profiles. Notably, high percentages (>50%) of unresected tumor were found in one-half of the margin biopsy smears, even in cases where postoperative MRI suggested gross total tumor resection. Unresected tumor causes recurrence and malignant progression, as observed within a year in one case examined in this study. These results corroborate the utility of DESI-MS in assessing surgical margins for maximal safe tumor resection. Intraoperative DESI-MS analysis of tissue smears, ex vivo, can be inserted into the current surgical workflow with no alterations. The data underscore the complexity of glioma infiltration

Ambient ionization mass spectrometric analysis of human surgical specimens to distinguish renal cell carcinoma from healthy renal tissue

Touch spray - mass spectrometry (TS-MS) is an ambient ionization technique (ionization of unprocessed samples in the open air) that may find intraoperative applications in quickly identifying the disease state of cancerous tissues and in defining surgical margins. In this study, TS-MS was performed on fresh kidney tissue (~1–5 cm3), within one hour of resection, from 21 human subjects afflicted by renal cell carcinoma (RCC). The preliminary diagnostic value of TS-MS data taken from freshly resected tissue was evaluated. Principal component analysis (PCA) of the negative ion mode (m/z 700–1000) data provided separation between RCC (16 samples) and healthy renal tissue (13 samples). Linear discriminant analysis (LDA) on the PCA compressed data estimated sensitivity (true positive rate) and specificity (true negative rate) of 98% and 95%, respectively, based on histopathological evaluation. The results indicate that TS-MS might provide rapid diagnostic information in spite of the complexity of unprocessed kidney tissue and the presence of interferences such as urine and blood. Desorption electrospray ionization imaging (DESI-MSI) in the negative ionization mode was performed on the tissue specimens after TS-MS analysis as a reference method. The DESI imaging experiments provided phospholipid profiles (m/z 700–1000) that also separated RCC and healthy tissue in the PCA space, with PCA-LDA sensitivity and specificity of 100% and 89%, respectively. The TS and DESI loading plots indicated that different ions contributed most to the separation of RCC from healthy renal tissue (m/z 794 [PC 34:1+Cl]− and 844 [PC 38:4+Cl]− for TS vs. m/z 788 [PS 36:1-H]− and 810 [PS 38:4-H]− for DESI), while m/z 885 ([PI 38:4-H]−) was important in both TS and DESI. The prospect, remaining hurdles, and future work required for translating TS-MS into a method of intraoperative tissue diagnosis is discussed.

Analysis of human gliomas by swab touch spray-mass spectrometry: applications to intraoperative assessment of surgical margins and presence of oncometabolites

Touch spray mass spectrometry using medical swabs is an ambient ionization technique (ionization of unprocessed sample in the open air) that has potential intraoperative application in quickly identifying the disease state of tissue and in better characterizing the resection margin. To explore this potential, we studied 29 human brain tumor specimens and obtained evidence that this technique can provide diagnostic molecular information that is relevant to brain cancer. Touch spray using medical swabs involves the physical sampling of tissue using a medical swab on a spatial scale of a few mm2 with subsequent ionization occurring directly from the swab tip upon addition of solvent and application of a high voltage. Using a tertiary mixture of acetonitrile, N,N-dimethylformamide, and ethanol, membrane-derived phospholipids and oncometabolites are extracted from the tissue, incorporated into the sprayed microdroplets, vacuumed into the mass spectrometer, and characterized in the resulting mass spectra. The tumor cell load was assessed from the complex phospholipid pattern in the mass spectra and also separately by measurement of N-acetylaspartate. Mutation status of the isocitrate dehydrogenase gene was determined via detection of the oncometabolite 2-hydroxyglutarate. The lack of sample pretreatment makes touch spray mass spectrometry using medical swabs a feasible intraoperative strategy for rapid surgical assessment

Feasibility of Desorption Electrospray Ionization Mass Spectrometry for Diagnosis of Oral Tongue Squamous Cell Carcinoma

Rationale Desorption electrospray ionization mass spectrometry (DESI-MS) has demonstrated utility in differentiating tumor from adjacent normal tissue in both urologic and neurosurgical specimens. We sought to evaluate if this technique had similar accuracy in differentiating oral tongue squamous cell carcinoma (SCC) from adjacent normal epithelium due to current issues with late diagnosis of SCC in advanced stages. Methods Fresh frozen samples of SCC and adjacent normal tissue were obtained by surgical resection. Resections were analyzed using DESI-MS sometimes by a blinded technologist. Normative spectra were obtained for separate regions containing SCC or adjacent normal epithelium. Principal Component Analysis and Linear Discriminant Analysis (PCA-LDA) of spectra were used to predict SCC versus normal tongue epithelium. Predictions were compared with pathology to assess accuracy in differentiating oral SCC from adjacent normal tissue. Results Initial PCA score and loading plots showed clear separation of SCC and normal epithelial tissue using DESI-MS. PCA-LDA resulted in accuracy rates of 95% for SCC versus normal and 93% for SCC, adjacent normal and normal. Additional samples were blindly analyzed with PCA-LDA pixel-by-pixel predicted classifications as SCC or normal tongue epithelial tissue and compared against histopathology. The m/z 700–900 prediction model showed a 91% accuracy rate. Conclusions DESI-MS accurately differentiated oral SCC from adjacent normal epithelium. Classification of all typical tissue types and pixel predictions with additional classifications should increase confidence in the validation model

Loss of CD4+ T cell-intrinsic arginase 1 accelerates Th1 response kinetics and reduces lung pathology during influenza infection

Arginase 1 (Arg1), the enzyme catalyzing the conversion of arginine to ornithine, is a hallmark of IL-10-producing immunoregulatory M2 macrophages. However, its expression in T cells is disputed. Here, we demonstrate that induction of Arg1 expression is a key feature of lung CD4+ T cells during mouse in vivo influenza infection. Conditional ablation of Arg1 in CD4+ T cells accelerated both virus-specific T helper 1 (Th1) effector responses and its resolution, resulting in efficient viral clearance and reduced lung pathology. Using unbiased transcriptomics and metabolomics, we found that Arg1-deficiency was distinct from Arg2-deficiency and caused altered glutamine metabolism. Rebalancing this perturbed glutamine flux normalized the cellular Th1 response. CD4+ T cells from rare ARG1-deficient patients or CRISPR-Cas9-mediated ARG1-deletion in healthy donor cells phenocopied the murine cellular phenotype. Collectively, CD4+ T cell-intrinsic Arg1 functions as an unexpected rheostat regulating the kinetics of the mammalian Th1 lifecycle with implications for Th1-associated tissue pathologies

Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics

Abstract Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data