A novel methodology for in vivo endoscopic phenotyping of colorectal cancer based on real-time analysis of the mucosal lipidome: a prospective observational study of the iKnife. Surg Endosc. 2017;31:1361-1370. [PMID: 27501728 PMCID: PMC5315709 DOI: 10.1007/s00464-016-5121-5]

Mass Spectrometry as a Clinical Integrative Tool to Evaluate Hepatocellular Carcinoma: Moving to the Mainstream

Introduction: Since the pioneering work of J. J. Thomson on magnetic deflection of charged particles, mass spectrometry (MS) has become the most progressive clinical tool by continuously providing new applications in medical research. In hepatocellular carcinoma (HCC), MS can be used from surveillance in early stages of the disease to constant evaluation of effective treatments. Areas covered: This Special Report highlights the groundbreaking possibilities of mass spectrometry clinical application in the mainstream to evaluate HCC development and progression. Expert opinon: MS has been employed to understand a myriad of liver diseases, such as the identification of early biomarkers in cirrhosis and HVB and HVC, as well as metabolic alterations of lipidic imbalance in HCC due to fatty liver disease. In an integrative point-of-view, researchers worldwide are looking for molecular signatures that may represent more faithfully the complex scenario of the onset and progression of HCC. Following the steps of MELD score (Model of End-stage Liver Disease), which evaluates biochemical dysfunction of end-stage liver diseases, the necessity to use innovative attempts to pursue a molecular-MEaLD (mMEaLD - molecular Model for Early Liver Disease), shifting MS to the upstream and from the lab facilities into the mainstream, inside the surgery room.

Evolving Technologies for Tissue Cutting

This article reviews evolving and lesser known technologies for tissue cutting and their application in oral and maxillofacial surgery.

Combination of Low-Temperature Electrosurgical Unit and Extractive Electrospray Ionization Mass Spectrometry for Molecular Profiling and Classification of Tissues

Real-time molecular navigation of tissue surgeries is an important goal at present. Combination of electrosurgical units and mass spectrometry (MS) to perform accurate molecular visualization of biological tissues has been pursued by many research groups. Determination of molecular tissue composition at a particular location by surgical smoke analysis is now of increasing interest for clinical use. However, molecular analysis of surgical smoke is commonly lacking molecular specificity and is associated with significant carbonization and chemical contamination, which are mainly related to the high temperature of smoke at which many molecules become unstable. Unlike traditional electrosurgical tools, low-temperature electrosurgical units allow tissue dissection without substantial heating. Here, we show that low-temperature electrosurgical units can be used for desorption of molecules from biological tissues without thermal degradation. The use of extractive electrospray ionization technique for the ionization of desorbed molecules allowed us to obtain mass spectra of healthy and pathological tissues with high degree of differentiation. Overall, the data indicate that the described approach has potential for intraoperative use.

Optical Technologies for Endoscopic Real-Time Histologic Assessment of Colorectal Polyps: A Meta-Analysis

OBJECTIVES

Accurate, real-time, endoscopic risk stratification of colorectal polyps would improve decision-making and optimize clinical efficiency. Technologies to manipulate endoscopic optical outputs can be used to predict polyp histology in vivo; however, it remains unclear how accuracy has progressed and whether it is sufficient for routine clinical implementation.

METHODS

A meta-analysis was conducted by searching MEDLINE, Embase, and the Cochrane Library. Studies were included if they prospectively deployed an endoscopic optical technology for real-time in vivo prediction of adenomatous colorectal polyps. Polyposis and inflammatory bowel diseases were excluded. Bayesian bivariate meta-analysis was performed, presenting 95% confidence intervals (CI).

RESULTS

One hundred two studies using optical technologies on 33,123 colorectal polyps were included. Digital chromoendoscopy differentiated neoplasia (adenoma and adenocarcinoma) from benign polyps with sensitivity of 92.2% (90.6%-93.9% CI) and specificity of 84.0% (81.5%-86.3% CI), with no difference between constituent technologies (narrow-band imaging, Fuji intelligent Chromo Endoscopy, iSCAN) or with only diminutive polyps. Dye chromoendoscopy had sensitivity of 92.7% (90.1%-94.9% CI) and specificity of 86.6% (82.9%-89.9% CI), similarly unchanged for diminutive polyps. Spectral analysis of autofluorescence had sensitivity of 94.4% (84.0%-99.1% CI) and specificity of 50.9% (13.2%-88.8% CI). Endomicroscopy had sensitivity of 93.6% (85.3%-98.3% CI) and specificity of 92.5% (81.8%-98.1% CI). Computer-aided diagnosis had sensitivity of 88.9% (74.2%-96.7% CI) and specificity of 80.4% (52.6%-95.7% CI). Prediction confidence and endoscopist experience alone did not significantly improve any technology. The only subgroup to demonstrate a negative predictive value for adenoma above 90% was digital chromoendoscopy, making high confidence predictions of diminutive recto-sigmoid polyps. Chronologic meta-analyses show a falling negative predictive value over time. A significant publication bias exists.

DISCUSSION

This novel approach to meta-analysis demonstrates that existing optical technologies are increasingly unlikely to allow safe "resect and discard" strategies and that step-change innovation may be required. A "diagnose and leave" strategy may be supported for diminutive recto-sigmoid polyps diagnosed with high confidence; however, limitations exist in the evidence base for this cohort.

Challenges and Opportunities in Cancer Metabolomics

Challenges in metabolomics for a given spectrum of disease are more or less comparable, ranging from the accurate measurement of metabolite abundance, compound annotation, identification of unknown constituents, and interpretation of untargeted and analysis of high throughput targeted metabolomics data leading to the identification of biomarkers. However, metabolomics approaches in cancer studies specifically suffer from several additional challenges and require robust ways to sample the cells and tissues in order to tackle the constantly evolving cancer landscape. These constraints include, but are not limited to, discriminating the signals from given cell types and those that are cancer specific, discerning signals that are systemic and confounded, cell culture-based challenges associated with cell line identities and media standardizations, the need to look beyond Warburg effects, citrate cycle, lactate metabolism, and identifying and developing technologies to precisely and effectively sample and profile the heterogeneous tumor environment. This review article discusses some of the current and pertinent hurdles in cancer metabolomics studies. In addition, it addresses some of the most recent and exciting developments in metabolomics that may address some of these issues. The aim of this article is to update the oncometabolomics research community about the challenges and potential solutions to these issues.

Reshaping Lipid Biochemistry by Pushing Barriers in Structural Lipidomics

Lipidomics is a rapidly growing field with numerous examples showing the importance of lipid molecules throughout biology. It has also shed light onto the vast and complex functions performed by many lipids that possess an immense diversity in molecular structures. Mass spectrometry (MS) is the tool of choice for analyzing lipids and has been the key catalyst driving the field forward. However, MS does not yet permit true molecular lipidomics wherein the identification and quantification of lipids having defined molecular structures can be routinely achieved. Here we describe recent advances in MS-based lipidomics that allow access to higher levels of molecular information in lipidomics experiments. These advances will form a key piece of the puzzle as the field moves towards systems characterization of lipids at the molecular level.

Individualized metabolomics: opportunities and challenges

The goal of advancing science in health care is to provide high quality treatment and therapeutic opportunities to patients in need. This is especially true in precision medicine, wherein the ultimate goal is to link disease phenotypes to targeted treatments and novel therapeutics at the scale of an individual. With the advent of -omics technologies, such as genomics, proteomics, microbiome, among others, the metabolome is of wider and immediate interest for its important role in metabolic regulation. The metabolome, of course, comes with its own questions regarding technological challenges. In this opinion article, I attempt to interrogate some of the main challenges associated with individualized metabolomics, and available opportunities in the context of its clinical application. Some questions this article addresses and attempts to find answers for are: Can a personal metabolome (n = 1) be inexpensive, affordable and informative enough (i.e. provide predictive yet validated biomarkers) to represent the entirety of a population? How can a personal metabolome complement advances in other -omics areas and the use of monitoring devices, which occupy our personal space?

Mass spectrometry-based intraoperative tumor diagnostics

In surgical oncology, decisions regarding the amount of tissue to be removed can have important consequences: the decision between preserving sufficient healthy tissue and eliminating all tumor cells is one to be made intraoperatively. This review discusses the latest technical innovations for a more accurate tumor margin localization based on mass spectrometry. Highlighting the latest mass spectrometric inventions, real-time diagnosis seems to be within reach; focusing on the intelligent knife, desorption electrospray ionization, picosecond infrared laser and MasSpec pen, the current technical status is evaluated critically concerning its scientific and medical practice.

Platforms for rapid cancer characterization by ambient mass spectrometry: advancements, challenges and opportunities for improvement towards intrasurgical use

Ambient Mass Spectrometry (MS) analysis is widely used to characterize biological and non-biological samples. Advancements that allow rapid analysis of samples by ambient methods such as Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) and Rapid Evaporative Ionization Mass Spectrometry (REIMS) are discussed. A short, non-comprehensive overview of ambient MS is provided that only contains example applications due to space limitations. A spatially encoded mass spectrometry analysis concept to plan cancer resection is introduced. The application of minimally destructive tissue ablation probes to survey the surgical field for sites of pathology using on-line analysis methods is discussed. The technological challenges that must be overcome for ambient MS to become a robust method for intrasurgical pathology assessments are reviewed.

Utilisation of Ambient Laser Desorption Ionisation Mass Spectrometry (ALDI-MS) Improves Lipid-Based Microbial Species Level Identification

The accurate and timely identification of the causative organism of infection is important in ensuring the optimum treatment regimen is prescribed for a patient. Rapid evaporative ionisation mass spectrometry (REIMS), using electrical diathermy for the thermal disruption of a sample, has been shown to provide fast and accurate identification of microorganisms directly from culture. However, this method requires contact to be made between the REIMS probe and microbial biomass; resulting in the necessity to clean or replace the probes between analyses. Here, optimisation and utilisation of ambient laser desorption ionisation (ALDI) for improved speciation accuracy and analytical throughput is shown. Optimisation was completed on 15 isolates of Escherichia coli, showing 5 W in pulsatile mode produced the highest signal-to-noise ratio. These parameters were used in the analysis of 150 clinical isolates from ten microbial species, resulting in a speciation accuracy of 99.4% - higher than all previously reported REIMS modalities. Comparison of spectral data showed high levels of similarity between previously published electrical diathermy REIMS data. ALDI does not require contact to be made with the sample during analysis, meaning analytical throughput can be substantially improved, and further, increases the range of sample types which can be analysed in potential direct-from-sample pathogen detection.

Changes in lipids composition and metabolism in colorectal cancer: a review

Altered metabolism of lipids is currently considered a hallmark characteristic of many malignancies, including colorectal cancer (CRC). Lipids are a large group of metabolites that differ in terms of their fatty acid composition. This review summarizes recent evidence, documenting many alterations in the content and composition of fatty acids, polar lipids, oxylipins and triacylglycerols in CRC patients' sera, tumor tissues and adipose tissue. Some of altered lipid molecules may be potential biomarkers of CRC risk, development and progression. Owing to a significant role of many lipids in cancer cell metabolism, some of lipid metabolism pathways may also constitute specific targets for anti-CRC therapy.

Metabolomics and Biomarker Discovery

Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.

Modalities for image- and molecular-guided cancer surgery

BACKGROUND

Surgery is the cornerstone of treatment for many solid tumours. A wide variety of imaging modalities are available before surgery for staging, although surgeons still rely primarily on visual and haptic cues in the operating environment. Image and molecular guidance might improve the adequacy of resection through enhanced tumour definition and detection of aberrant deposits. Intraoperative modalities available for image- and molecular-guided cancer surgery are reviewed here.

METHODS

Intraoperative cancer detection techniques were identified through a systematic literature search, with selection of peer-reviewed publications from January 2012 to January 2017. Modalities were reviewed, described and compared according to 25 predefined characteristics. To summarize the data in a comparable way, a three-point rating scale was applied to quantitative characteristics.

RESULTS

The search identified ten image- and molecular-guided surgery techniques, which can be divided into four groups: conventional, optical, nuclear and endogenous reflectance modalities. Conventional techniques are the most well known imaging modalities, but unfortunately have the drawback of a defined resolution and long acquisition time. Optical imaging is a real-time modality; however, the penetration depth is limited. Nuclear modalities have excellent penetration depth, but their intraoperative use is limited by the use of radioactivity. Endogenous reflectance modalities provide high resolution, although with a narrow field of view.

CONCLUSION

Each modality has its strengths and weaknesses; no single technique will be suitable for all surgical procedures. Strict selection of modalities per cancer type and surgical requirements is required as well as combining techniques to find the optimal balance.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Real-time oncological guidance using diffuse reflectance spectroscopy in electrosurgery: the effect of coagulation on tissue discrimination

In breast surgery, a lack of knowledge about what is below the tissue surface may lead to positive tumor margins and iatrogenic damage. Diffuse reflectance spectroscopy (DRS) is a spectroscopic technique that can distinguish between healthy and tumor tissue making it a suitable technology for intraoperative guidance. However, because tumor surgeries are often performed with an electrosurgical knife, the effect of a coagulated tissue layer on DRS measurements must be taken into account. It is evaluated whether real-time DRS measurements obtained with a photonic electrosurgical knife could provide useful information of tissue properties also when tissue is coagulated and cut. The size of the coagulated area is determined and the effect of its presence on DR spectra is studied using ex vivo porcine adipose and muscle tissue. A coagulated tissue layer with a depth of 0.1 to 0.4 mm is observed after coagulating muscle with an electrosurgical knife. The results show that the effect of coagulating adipose tissue is negligible. Using the fat/water ratio's calculated from the measured spectra of the photonic electrosurgical knife, it was possible to determine the distance from the instrument tip to a tissue transition during cutting. In conclusion, the photonic electrosurgical knife can determine tissue properties of coagulated and cut tissue and has, therefore, the potential to provide real-time feedback about the presence of breast tumor margins during cutting, helping surgeons to establish negative margins and improve patient outcome.

Analysis of the Lipid Profile in Patients with Colorectal Cancer in Advanced Stages

Backgrounds: Colorectal (CRC) is one of the main cause of cancer worldwide. The search for noninvasive markers for diagnosis and monitoring as the use of analytical technologies such as mass spectrometry (MS), which allowed the search for lipid metabolites as candidates for probable biomarkers are needed. Objective and Methods: The objective was to establish the lipid profile of patients with locally advanced, unresectable or metastatic CRC. Peripheral blood was collected from patients with CRC and controls with normal colonoscopy. After lipid extraction, the samples were processed and analyzed in the MALDI TOF / TOF equipment. From the data matrix, the statistical analyzes were performed by the principal component analysis methods and the least squares discriminant analysis. The importance of the variable in the projection was used to identify the ions that had the greatest discriminatory effect between the groups. Results: Eight lipids were identified as potential biomarkers and a multiple logistic regression model was proposed to calculate the performance of the test where we observed values of AUC 0.87, sensitivity 88.33% and specificity 83.78% and for a validation test with 1,000 permutations a p <0.001. The classes of lipids found were sphingolipids, glycerophospholipids and policetidis. The strength of the association between the peak intensities of these lipids and the presence of CRC make these metabolites candidates for possible biomarkers. The sphingolipid (m / z = 742.98869) could be a biomarker in monitoring patients with CRC. In the survival analysis, three lipids showed a prognostic value for colorectal cancer, sphingolipid (m / z = 857.11525) and policetidis (m / z = 876.20796) and glycerophospholipid (m / z = 1031.54773).

Integrative omics to detect bacteremia in patients with febrile neutropenia

BACKGROUND

Cancer chemotherapy-associated febrile neutropenia (FN) is a common condition that is deadly when bacteremia is present. Detection of bacteremia depends on culture, which takes days, and no accurate predictive tools applicable to the initial evaluation are available. We utilized metabolomics and transcriptomics to develop multivariable predictors of bacteremia among FN patients.

METHODS

We classified emergency department patients with FN and no apparent infection at presentation as bacteremic (cases) or not (controls), according to blood culture results. We assessed relative metabolite abundance in plasma, and relative expression of 2,560 immunology and cancer-related genes in whole blood. We used logistic regression to identify multivariable predictors of bacteremia, and report test characteristics of the derived predictors.

RESULTS

For metabolomics, 14 bacteremic cases and 25 non-bacteremic controls were available for analysis; for transcriptomics we had 7 and 22 respectively. A 5-predictor metabolomic model had an area under the receiver operating characteristic curve of 0.991 (95%CI: 0.972,1.000), 100% sensitivity, and 96% specificity for identifying bacteremia. Pregnenolone steroids were more abundant in cases and carnitine metabolites were more abundant in controls. A 3-predictor gene expression model had corresponding results of 0.961 (95%CI: 0.896,1.000), 100%, and 86%. Genes involved in innate immunity were differentially expressed.

CONCLUSIONS

Classifiers derived from metabolomic and gene expression data hold promise as objective and accurate predictors of bacteremia among FN patients without apparent infection at presentation, and can provide insights into the underlying biology. Our findings should be considered illustrative, but may lay the groundwork for future biomarker development.

The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)

Background

Survival from ovarian cancer (OC) is improved with surgery, but surgery can be complex and tumour identification, especially for borderline ovarian tumours (BOT), is challenging. The Rapid Evaporative Ionisation Mass Spectrometric (REIMS) technique reports tissue histology in real-time by analysing aerosolised tissue during electrosurgical dissection.

Methods

Aerosol produced during diathermy of tissues was sampled with the REIMS interface. Histological diagnosis and mass spectra featuring complex lipid species populated a reference database on which principal component, linear discriminant and leave-one-patient-out cross-validation analyses were performed.

Results

A total of 198 patients provided 335 tissue samples, yielding 3384 spectra. Cross-validated OC classification vs separate normal tissues was high (97·4% sensitivity, 100% specificity). BOT were readily distinguishable from OC (sensitivity 90.5%, specificity 89.7%). Validation with fresh tissue lead to excellent OC detection (100% accuracy). Histological agreement between iKnife and histopathologist was very good (kappa 0.84, P < 0.001, z = 3.3). Five predominantly phosphatidic acid (PA(36:2)) and phosphatidyl-ethanolamine (PE(34:2)) lipid species were identified as being significantly more abundant in OC compared to normal tissue or BOT (P < 0.001, q < 0.001).

Conclusions

The REIMS iKnife distinguishes gynaecological tissues by analysing mass-spectrometry-derived lipidomes from tissue diathermy aerosols. Rapid intra-operative gynaecological tissue diagnosis may improve surgical care when histology is unknown, leading to personalised operations tailored to the individual.

Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis

Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models.

Effect of Electrode Geometry on the Classification Performance of Rapid Evaporative Ionization Mass Spectrometric (REIMS) Bacterial Identification

The recently developed automated, high-throughput monopolar REIMS platform is suited for the identification of clinically important microorganisms. Although already comparable to the previously reported bipolar forceps method, optimization of the geometry of monopolar electrodes, at the heart of the system, holds the most scope for further improvements to be made. For this, sharp tip and round shaped electrodes were optimized to maximize species-level classification accuracy. Following optimization of the distance between the sample contact point and tube inlet with the sharp tip electrodes, the overall cross-validation accuracy improved from 77% to 93% in negative and from 33% to 63% in positive ion detection modes, compared with the original 4 mm distance electrode. As an alternative geometry, round tube shaped electrodes were developed. Geometry optimization of these included hole size, number, and position, which were also required to prevent plate pick-up due to vacuum formation. Additional features, namely a metal "X"-shaped insert and a pin in the middle were included to increase the contact surface with a microbial biomass to maximize aerosol production. Following optimization, cross-validation scores showed improvement in classification accuracy from 77% to 93% in negative and from 33% to 91% in positive ion detection modes. Supervised models were also built, and after the leave 20% out cross-validation, the overall classification accuracy was 98.5% in negative and 99% in positive ion detection modes. This suggests that the new generation of monopolar REIMS electrodes could provide substantially improved species level identification accuracies in both polarity detection modes. Graphical abstract.

Optimized Mass Spectrometry Analysis Workflow with Polarimetric Guidance for ex vivo and in situ Sampling of Biological Tissues

Spatially Targeted Mass Spectrometry (MS) analysis using survey scans with an imaging modality often requires consecutive tissue slices, because of the tissue damage during survey scan or due to incompatible sample preparation requirements between the survey modality and MS. We report two spatially targeted MS analysis workflows based on polarized light imaging guidance that use the same tissue sample for survey and targeted analysis. The first workflow is applicable for thin-slice analysis, and uses transmission-polarimetry-guided Desorption ElectroSpray Ionization Mass Spectrometry (DESI-MS), and confirmatory H&E histopathology analysis on the same slice; this is validated using quantitative digital pathology methods. The second workflow explores a polarimetry-guided MS platform for thick tissue assessment by developing reflection-mode polarimetric imaging coupled with a hand-held Picosecond InfraRed Laser (PIRL) MS ablation probe that requires minimal tissue removal to produce detectable signal. Tissue differentiation within 5–10 s of sampling with the hand-held probe is shown using multivariate statistical methods of the MS profiles. Both workflows were tasked with differentiating necrotic cancer sites from viable cancers using a breast tumour model, and their performance was evaluated. The use of the same tissue surface addresses mismatches in guidance due to intrinsic changes in tissue morphology over consecutive sections.

The metabolome 18 years on: a concept comes of age

BACKGROUND

The term 'metabolome' was introduced to the scientific literature in September 1998.

AIM AND KEY SCIENTIFIC CONCEPTS OF THE REVIEW

To mark its 18-year-old 'coming of age', two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.