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Structural characterization of glycerophospholipids beyond the fatty acid level has become a major endeavor in lipidomics, presenting an opportunity to advance the understanding of the intricate relationship between lipid metabolism and disease state. Distinguishing subtle lipid structural features, however, remains a major challenge for high-throughput workflows that implement traditional tandem mass spectrometry (MS/MS) techniques, stunting the molecular depth of quantitative strategies. Here, reversed phase liquid chromatography is coupled to parallel reaction mass spectrometry utilizing the double bond localization capabilities of ultraviolet photodissociation (UVPD) mass spectrometry to produce double bond isomer specific responses that are leveraged for relative quantitation. The strategy provides lipidomic characterization at the double bond level for phosphatidylcholine phospholipids from biological extracts. In addition to quantifying monounsaturated lipids, quantitation of phospholipids incorporating isomeric polyunsaturated fatty acids is also achieved. Using this technique, phosphatidylcholine isomer ratios are compared across human normal and tumor breast tissue to reveal significant structural alterations related to disease state.

Minimally invasive robotic-assisted surgeries have been increasingly used as a first-line of treatment for patients undergoing oncologic surgeries. In-situ tissue identification is critical to guide tissue resection and assist decision-making. Traditional intraoperative histopathologic analysis of frozen tissue sections can be time-consuming and present logistical challenges which interrupt surgical workflows. We report the development and implementation of a laparoscopic, drop-in version of the MasSpec Pen device integrated into the da Vinci Xi Surgical system for in vivo tissue analysis in a robotic-assisted porcine surgery. We evaluated the performance of the drop-in MasSpec Pen during surgery by introducing the device into the animal upper gastrointestinal system and performing in vivo analyses of the stomach and liver, including charred and bloody tissues after electrocauterization. The molecular profiles obtained included ions tentatively identified as metabolites and lipids typically observed with MasSpec Pen analysis, without causing observable tissue damage. Statistical classifiers built to distinguish porcine liver and stomach tissues using the in vivo data yielded an overall tissue identification accuracy of 98% (n = 53 analyses). The results provide evidence that the drop-in MasSpec Pen developed can be used to acquire mass spectra in vivo during a robotic-assisted surgery and might be used as an in vivo tissue assessment tool to help guide surgical resections and streamline surgical workflows.

Free fatty acids (FA) are a vital component of cells and are critical to cellular structure and function, so much so that alterations in FA are often associated with cell malfunction and disease. Analysis of FA from biological samples can be achieved by mass spectrometry (MS), but these analyses are often not capable of distinguishing the fine structural alterations within FA isomers and often limited to global profiling of lipids without spatial resolution. Here, we present the use of ultraviolet photodissociation (UVPD) for the characterization of double bond positional isomers of charge inverted dication·FA complexes and the subsequent implementation of this method for online desorption electrospray ionization (DESI) MS imaging of FA isomers from human tissue sections. This method allows relative quantification of FA isomers from heterogeneous biological tissue sections, yielding spatially resolved information about alterations in double bond isomers within these samples. Applying this method to the analysis of the monounsaturated FA 18:1 within breast cancer subtypes uncovered a correlation between double bond positional isomer abundance and the hormone receptor status of the tissue sample, an important factor in the prognosis and treatment of breast cancer patients. This result further validates similar studies that suggest FA synthase activity and FA isomer abundances are significantly altered within breast cancer tissue.

Intraoperative delineation of tumor margins is critical for effective pancreatic cancer surgery. Yet, intraoperative frozen section analysis of tumor margins is a time-consuming and often challenging procedure that can yield confounding results due to histologic heterogeneity and tissue-processing artifacts. We have previously described the development of the MasSpec Pen technology as a handheld mass spectrometry–based device for nondestructive tissue analysis. Here, we evaluated the usefulness of the MasSpec Pen for intraoperative diagnosis of pancreatic ductal adenocarcinoma based on alterations in the metabolite and lipid profiles in in vivo and ex vivo tissues. We used the MasSpec Pen to analyze 157 banked human tissues, including pancreatic ductal adenocarcinoma, pancreatic, and bile duct tissues. Classification models generated from the molecular data yielded an overall agreement with pathology of 91.5%, sensitivity of 95.5%, and specificity of 89.7% for discriminating normal pancreas from cancer. We built a second classifier to distinguish bile duct from pancreatic cancer, achieving an overall accuracy of 95%, sensitivity of 92%, and specificity of 100%. We then translated the MasSpec Pen to the operative room and predicted on in vivo and ex vivo data acquired during 18 pancreatic surgeries, achieving 93.8% overall agreement with final postoperative pathology reports. Notably, when integrating banked tissue data with intraoperative data, an improved agreement of 100% was achieved. The result obtained demonstrate that the MasSpec Pen provides high predictive performance for tissue diagnosis and compatibility for intraoperative use, suggesting that the technology may be useful to guide surgical decision-making during pancreatic cancer surgeries.

Endometriosis is a pathologic condition affecting approximately 10% of women in their reproductive years. Characterized by abnormal growth of uterine endometrial tissue in other body areas, endometriosis can cause severe abdominal pain and/or infertility. Despite devastating consequences to patients’ quality of life, the causes of endometriosis are not fully understood and validated diagnostic markers for endometriosis have not been identified. Molecular analyses of ectopic and eutopic endometrial tissues could lead to enhanced understanding of the disease. Here, we apply desorption electrospray ionization (DESI) mass spectrometry (MS) imaging to chemically and spatially characterize the molecular profiles of 231 eutopic and ectopic endometrial tissues from 89 endometriosis patients. DESI-MS imaging allowed clear visualization of endometrial glandular and stromal regions within tissue samples. Statistical models built from DESI-MS imaging data allowed classification of endometriosis lesions with overall accuracies of 89.4%, 98.4%, and 98.8% on training, validation, and test sample sets, respectively. Further, molecular markers that are significantly altered in ectopic endometrial tissues when compared to eutopic tissues were identified, including fatty acids and glycerophosphoserines. Our study showcases the value of MS imaging to investigate the molecular composition of endometriosis lesions and pinpoints metabolic markers that may provide new knowledge on disease pathogenesis.

BACKGROUND Accurate tissue diagnosis during ovarian cancer surgery is critical to maximize cancer excision and define treatment options. Yet, current methods for intraoperative tissue evaluation can be time intensive and subjective. We have developed a handheld and biocompatible device coupled to a mass spectrometer, the MasSpec Pen, which uses a discrete water droplet for molecular extraction and rapid tissue diagnosis. Here we evaluated the performance of this technology for ovarian cancer diagnosis across different sample sets, tissue types, and mass spectrometry systems. METHODS MasSpec Pen analyses were performed on 192 ovarian, fallopian tube, and peritoneum tissue samples. Samples were evaluated by expert pathologists to confirm diagnosis. Performance using an Orbitrap and a linear ion trap mass spectrometer was tested. Statistical models were generated using machine learning and evaluated using validation and test sets. RESULTS High performance for high-grade serous carcinoma (n = 131; clinical sensitivity, 96.7%; specificity, 95.7%) and overall cancer (n = 138; clinical sensitivity, 94.0%; specificity, 94.4%) diagnoses was achieved using Orbitrap data. Variations in the mass spectra from normal tissue, low-grade, and high-grade serous ovarian cancers were observed. Discrimination between cancer and fallopian tube or peritoneum tissues was also achieved with accuracies of 92.6% and 87.9%, respectively, and 100% clinical specificity for both. Using ion trap data, excellent results for high-grade serous cancer vs normal ovarian differentiation (n = 40; clinical sensitivity, 100%; specificity, 100%) were obtained. CONCLUSIONS The MasSpec Pen, together with machine learning, provides robust molecular models for ovarian serous cancer prediction and thus has potential for clinical use for rapid and accurate ovarian cancer diagnosis.

Intraoperative tissue analysis is critical to guide surgical procedures and improve patient outcomes. Here, we describe the clinical translation and intraoperative use of the MasSpec Pen technology for direct molecular analysis of in vivo and freshly excised tissues in the operating room. In this study, the MasSpec Pen was used by surgeons and surgical staff during 100 surgeries over a 12-month period, allowing rapid detection of rich mass spectral profiles from 715 in vivo and ex vivo analyses performed on thyroid, parathyroid, lymph node, breast, pancreatic, and bile duct tissues during parathyroidectomies, thyroidectomies, breast, and pancreatic neoplasia surgeries. The MasSpec Pen enabled gentle extraction and sensitive detection of various molecular species including small metabolites and lipids using a droplet of sterile water without causing apparent tissue damage. Notably, effective molecular analysis was achieved while no limitations to sequential histologic tissue analysis were identified and no device-related complications were reported for any of the patients. Collectively, this study shows that the MasSpec Pen system can be successfully incorporated into the operating room, allowing direct detection of rich molecular profiles from tissues with a seconds-long turnaround time that could be inform surgical and clinical decisions without disrupting tissue analysis workflows.

Minimally invasive robotic-assisted surgeries have been increasingly used as a first-line of treatment for patients undergoing oncologic surgeries. In-situ tissue identification is critical to guide tissue resection and assist decision-making. Traditional intraoperative histopathologic analysis of frozen tissue sections can be time-consuming and present logistical challenges which interrupt surgical workflows. We report the development and implementation of a laparoscopic, drop-in version of the MasSpec Pen device integrated into the da Vinci Xi Surgical system for

Desorption electrospray ionization (DESI) mass spectrometry imaging has become a powerful strategy for analysis of tissue sections, enabling differentiation of normal and diseased tissue based on changes in the lipid profiles. The most common DESI workflow involves collection of MS1 spectra as the DESI spray is rastered over a tissue section. Relying on MS1 spectra inherently limits the ability to differentiate isobaric and isomeric species or evaluate variations in the relative abundances of key isomeric lipids, such as double-bond positional isomers which may distinguish normal and diseased tissues. Here, 193 nm ultraviolet photodissociation (UVPD), a technique capable of differentiating double-bond positional isomers, is coupled with DESI to map differences in the double-bond isomer composition in tissue sections in a fast, high throughput manner compatible with imaging applications.

Tissues present complex biochemical and morphological composition associated with their various cell types and physiological functions. Mass spectrometry (MS) imaging technologies are powerful tools to investigate the molecular information from biological tissue samples and visualize their complex spatial distributions. Coupling of gas-phase ion mobility spectrometry (IMS) technologies to MS imaging has been increasingly explored to improve performance for biological tissue imaging. This approach allows improved detection of low abundance ions and separation of isobaric molecular species, thus resulting in more accurate determination of the spatial distribution of molecular ions. In this review, we highlight recent advances in the field focusing on promising applications of these technologies for metabolite, lipid and protein tissue imaging.

Nonporous, hydrophobic organosiloxane (OSX) polymers with surface reservoirs were developed as sampling supports in polymer-spray mass spectrometry (polyS-MS) for the detection and quantification of hydrophilic drugs, ethyl glucuronide (logP -1.8) and vancomycin (logP -4.4), and a slightly hydrophobic drug, phenobarbital (logP 1.5). OSX polymers with surface reservoirs were prepared by solvent evaporation-induced patterning in the presence of an ionic liquid during sol-gel polymerization of a methylalkoxysilane. The surface reservoir provides a continuous supply of spray solvent, enhancing both signal stability and signal duration when conducting analysis by polyS-MS. Using OSX polymer substrates with surfaces reservoirs, calibration curves were generated with good linearity (R2>0.99) and reproducibility and low data spread over the concentration ranges used to screen each of the drugs tested as compared to paper substrates: ethyl glucuronide, 5 – 1000 ng/mL (methanol) and 50 – 10,000 ng/mL (synthetic urine); vancomycin, 2 – 100 μL/mL (plasma); phenobarbital, 50 – 50,000 ng/mL (methanol) and 50 – 5000 ng/mL (synthetic urine). Quantitative analysis by polyS-MS of phenobarbital samples in synthetic urine at concentrations of 250 ng/mL and 2,500 ng/mL showed good recoveries of 90.2% (RSD 3.51%) and 95.7% (RSD 2.57%), respectively. Compared to paper substrates, OSX polymers gave calibration curves with better linearity and reproducibility, especially at low concentrations, as well as longer signal durations, improved signal stabilities, and increased signal intensities. Little to no sample pretreatment is necessary and the required sample volume is small (1 μL to 2 μL), making polyS-MS easy to use for high throughput sample processing.

Precise removal of pancreatic ductal adenocarcinoma (PDAC) with microscopically negative margins, commonly assessed by frozen section analysis, is associated with longer disease-free survival. However, histologic complexities and tissue-processing artifacts can render frozen section analysis of PDAC margins a challenging and time-consuming task, with reported accuracies dependent on the skillset and subspecialty of the pathologist on call. We developed the MasSpec Pen, a handheld device coupled to a mass spectrometer, for rapid (~15 s) and nondestructive molecular analysis and diagnosis of tissues. The MasSpec Pen supplies a discrete water droplet onto a tissue's surface, allowing diagnostic metabolites and lipids to be extracted into the droplet and then transmitted into a mass spectrometer for analysis. Here, we evaluate the performance of the MasSpec Pen for intraoperative diagnosis of PDAC in human pancreatic and bile duct margins. Pancreatic and bile duct tissue samples (N=157) were obtained from the Cooperative Human Tissue Network and Baylor College of Medicine and stored at -80°C prior to analysis. A Q Exactive mass spectrometer (Thermo Scientific) coupled to the MasSpec Pen was used for analysis of thawed samples in the negative ion mode. Tissues were then cryo-sectioned, H&E stained, and blindly evaluated by a pathologist. Based on the distinct molecular profiles acquired, we generated two statistical classifiers using lasso penalized logistic regression for distinguishing PDAC from healthy pancreas and bile duct tissue based on a sparse set of molecular features indicative of disease state. For distinguishing normal pancreas from PDAC, an overall accuracy of 91.5%, sensitivity of 95.5%, and specificity of 89.7% was achieved for training, validation, and test sets. Classification results for discriminating normal bile duct from PDAC had an overall accuracy of 95%, sensitivity of 92%, and specificity of 100% in training and validation. We have begun clinical testing of the MasSpec Pen in human surgeries following its successful translation to an operating room at Texas Medical Center. To date, the MasSpec Pen has been used to analyze in vivo and fresh ex vivo tissue in 19 pancreatic surgeries. When predicting on 64 intraoperative analyses using classification models built on banked data, 93.8% agreement with final postoperative pathology reports was achieved. While further validation studies are needed, our results show that the MasSpec Pen can distinguish PDAC from normal pancreas and bile duct tissues with high accuracy and is compatible for in vivo use, suggesting this technology may be valuable for near real-time margin evaluation during pancreatic oncologic surgeries. Citation Format: Mary E. King, Jialing Zhang, John Q. Lin, Kyana Y. Garza, Rachel J. DeHoog, Clara L. Feider, Alena V. Bensussan, Marta Sans, Anna Krieger, Sunil Badal, Michael F. Keating, Sadhna Dhingra, Wendong Yu, George Van Buren, Christopher Pirko, Kirtan Brahmbhatt, William E. Fisher, James W. Suliburk, Livia S. Eberlin. Clinical evaluation of the MasSpec Pen technology for rapid diagnosis and margin assessment in pancreatic cancer surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 624.

Ambient ionization mass spectrometry has been widely applied to image lipids and metabolites in primary cancer tissues with the purpose of detecting and understanding metabolic changes associated with cancer development and progression. Here, we report the use of desorption electrospray ionization mass spectrometry (DESI-MS) to image metastatic breast and thyroid cancer in human lymph node tissues. Our results show clear alterations in lipid and metabolite distributions detected in the mass spectra profiles from 42 samples of metastatic thyroid tumors, metastatic breast tumors, and normal lymph node tissues. 2D DESI-MS ion images of selected molecular species allowed discrimination and visualization of specific histologic features within tissue sections, including regions of metastatic cancer, adjacent normal lymph node, and fibrosis or adipose tissues, which strongly correlated with pathologic findings. In thyroid cancer metastasis, increased relative abundances of ceramides and glycerophosphoinisitols were observed. In breast cancer metastasis, increased relative abundances of various fatty acids and specific glycerophospholipids were seen. Trends in the alterations in fatty acyl chain composition of lipid species were also observed through detailed mass spectra evaluation and chemical identification of molecular species. The results obtained demonstrate DESI-MSI as a potential clinical tool for the detection of breast and thyroid cancer metastasis in lymph nodes, although further validation is needed. Graphical Abstract Desorption electrospray ionization mass spectrometry imaging is used to differentiate metastatic cancer from adjacent lymph node tissue.

Ambient ionization mass spectrometry imaging (MSI) has been increasingly used to investigate the molecular distribution of biological tissue samples. Here, we report the integration and optimization of desorption electrospray ionization (DESI) and liquid-microjunction surface sampling probe (LMJ-SSP) with a chip-based high-field asymmetric waveform ion mobility spectrometry (FAIMS) device to image metabolites, lipids, and proteins in biological tissue samples. Optimized FAIMS parameters for specific molecular classes enabled semitargeted detection of multiply charged molecular species at enhanced signal-to-noise ratios (S/N), improved visualization of spatial distributions, and, most importantly, allowed detection of species which were unseen by ambient ionization MSI alone. Under static DESI-FAIMS conditions selected for transmission of doubly charged cardiolipins (CL), for example, detection of 71 different CL species was achieved in rat brain, 23 of which were not observed by DESI alone. Diagnostic CL were imaged in a human thyroid tumor sample with reduced interference of isobaric species. LMJ-SSP-FAIMS enabled detection of 84 multiply charged protein ions in rat brain tissue, 66 of which were exclusive to this approach. Spatial visualization of proteins in substructures of rat brain, and in human ovarian cancerous, necrotic, and normal tissues was achieved. Our results indicate that integration of FAIMS with ambient ionization MS allows improved detection and imaging of selected molecular species. We show that this methodology is valuable in biomedical applications of MSI for detection of multiply charged lipids and proteins from biological tissues.

Developing alternative MS/MS strategies to distinguish isomeric lipids has become a high impact goal in shotgun lipidomics. Novel approaches have been developed to resolve structural features that are not discernible by traditional shotgun methods and have consequently promoted the discovery of new disease biomarkers. However, these methods have largely been limited to characterizing lipids with low structural complexity. Here, ultraviolet photodissociation (UVPD) strategies for phospholipid characterization are expanded for analysis of cardiolipins (CL), a class of phospholipids that exhibits a higher degree of structural complexity. A hybrid collision induced dissociation/193 nm UVPD (CID/UVPD) approach was implemented to pinpoint the location of both double bond and cyclopropyl unsaturations on the four acyl chains of CLs. This strategy was complemented with CID for the de novo elucidation of unknown CLs in biological extracts.

Ambient ionization mass spectrometry (MS) techniques, such as desorption electrospray ionization (DESI), have been increasingly used due to their simplicity, minimal sample preparation requirements, and potential applications in the field and the clinic. However, due to their intrinsic nature, the performance of these methods is susceptible to variations in ambient conditions. Here, we present data that suggests DESI-MS analysis becomes inconsistent below a relative humidity (RH) level of ~ 35%. At low RH, we hypothesize that the DESI spray is subjected to frequent electrical discharges, resulting in unstable ionization and atypical mass spectra. Consequentially, poor image quality is observed when used for tissue imaging. Our results suggest that RH control should be considered in DESI-MS experiments to assure data quality. Graphical Abstract ᅟ.

Functionalized nanoparticles for photoluminescence (PL) applications are a promising technology for biomedical imaging and as sensors for small molecules. This work presents a new method to modify silica nanoparticles (SNP) using the bifunctional linker 1,1'-carbonyldiimidazole (CDI) with a series of polyamidoamine (PAMAM) dendrimer molecules followed by grafting of fluorescein isothiocyanate (FITC) or rhodamine B isothiocyanate (RITC) to create platforms for photoluminescence (PL) sensors. A dendrimer size and charge-variable response to only copper(II) ions confirmed the prediction of a selective turn-off sensor via proximity quenching. Both dye density and Cu(2+) quenching efficiency peaked with SNP-dendrimer generation 4 (64 terminal amines). In addition, changing the terminal dendrimer arms to carboxylic acid end groups increased the copper quenching suggesting that more metal ion binding sites were created in close proximity to the dyes. Of the small anions tested for a turn-off sensor, only cyanide ion fully restored the PL when reaching a 2:1 CN(-):Cu(2+) ratio, while EDTA was not as effective at the same ratio. Therefore, dendrimer size and surface charge on the nanoparticles controlled the dye loading and copper quenching efficiency, while creating multiple binding sites for cyanide over other metal binding anions.