Impact of Freezing Delay Time on Tissue Samples for Metabolomic Studies

Fast processing of gynecologic cancer tissue in Danish Cancer Biobank makes them well-suited for biomarker studies

Gynecologic cancers remain a frequent and deadly diagnosis. Historically, treatment has focused on a "one size fits all" approach, but there is an urgent need for more personal medicine. Hence, to enhance personal medicine, new biomarkers are needed. Samples from the Danish Cancer Biobank (DCB) may be well-suited for biomarker studies, as the biobank contains samples from more than 100.000 cancer patients, and the samples are annotated with pre-analytical variables. The aim of this study was to investigate if the recorded pre-analytical variables indicate the gynecologic tissue in DCB are suited for biomarker studies. Data on processing time, transport time, and registration- and verification status were extracted from all patients with a gynecologic tissue sample collected between 2020 and 2022 in DCB. The mean processing time across centers was found to be 1.03 h (SD = 0.71), and the mean transport time was found to be 0.32 h (SD = 0.70). In total, 69% of the tissue samples were pathologically examined, and 91.5% of the pathologically examined samples were found to be concordant with the patient's final diagnosis. While differences were observed, 98% of the samples were processed within 3 h, indicating the majority of gynecologic tissue samples in DCB are of high quality and optimal for biomarker studies.

Impact of Cold Ischemia on the Stability of 1H-MRS-Detected Metabolic Profiles of Ovarian Cancer Specimens

Proton magnetic resonance spectroscopy (1H-MRS) of surgically collected tumor specimens may contribute to investigating cancer metabolism and the significance of the "total choline" (tCho) peak (3.2 ppm) as malignancy and therapy response biomarker. To ensure preservation of intrinsic metabolomic information, standardized handling procedures are needed. The effects of time to freeze (cold ischemia) were evaluated in (a) surgical epithelial ovarian cancer (EOC) specimens using high-resolution (HR) 1H-MRS (9.4 T) of aqueous extracts and (b) preclinical EOC samples (xenografts in SCID mice) investigated by in vivo MRI-guided 1H-MRS (4.7 T) and by HR-1H-MRS (9.4 T) of tumor extracts or intact fragments (using magic-angle-spinning (MAS) technology). No significant changes were found in the levels of 27 of 29 MRS-detected metabolites (including the tCho profile) in clinical specimens up to 2 h cold ischemia, besides an increase in lysine and a decrease in glutathione. EOC xenografts showed a 2-fold increase in free choline within 2 h cold ischemia, without further significant changes for any MRS-detected metabolite (including phosphocholine and tCho) up to 6 h. At shorter times (≤1 h), HR-MAS analyses showed unaltered tCho components, along with significant changes in lactate, glutamate, and glutamine. Our results support the view that a time to freeze of 1 h represents a safe threshold to ensure the maintenance of a reliable tCho profile in EOC specimens.

Artifacts Introduced by Sample Handling in Chemiluminescence Assays of Nitric Oxide Metabolites

We recently developed a combination of four chemiluminescence-based assays for selective detection of different nitric oxide (NO) metabolites, including nitrite, S-nitrosothiols (SNOs), heme-nitrosyl (heme-NO), and dinitrosyl iron complexes (DNICs). However, these NO species (NOx) may be under dynamic equilibria during sample handling, which affects the final determination made from the readout of assays. Using fetal and maternal sheep from low and high altitudes (300 and 3801 m, respectively) as models of different NOx levels and compositions, we tested the hypothesis that sample handling introduces artifacts in chemiluminescence assays of NOx. Here, we demonstrate the following: (1) room temperature placement is associated with an increase and decrease in NOx in plasma and whole blood samples, respectively; (2) snap freezing and thawing lead to the interconversion of different NOx in plasma; (3) snap freezing and homogenization in liquid nitrogen eliminate a significant fraction of NOx in the aorta of stressed animals; (4) A "stop solution" commonly used to preserve nitrite and SNOs leads to the interconversion of different NOx in blood, while deproteinization results in a significant increase in detectable NOx; (5) some reagents widely used in sample pretreatments, such as mercury chloride, acid sulfanilamide, N-ethylmaleimide, ferricyanide, and anticoagulant ethylenediaminetetraacetic acid, have unintended effects that destabilize SNO, DNICs, and/or heme-NO; (6) blood, including the residual blood clot left in the washed purge vessel, quenches the signal of nitrite when using ascorbic acid and acetic acid as the purge vessel reagent; and (7) new limitations to the four chemiluminescence-based assays. This study points out the need for re-evaluation of previous chemiluminescence measurements of NOx, and calls for special attention to be paid to sample handling, as it can introduce significant artifacts into NOx assays.

Lipidomic Profiling of Colorectal Lesions for Real-Time Tissue Recognition and Risk-Stratification Using Rapid Evaporative Ionization Mass Spectrometry

OBJECTIVE

Rapid evaporative ionization mass spectrometry (REIMS) is a metabolomic technique analyzing tissue metabolites, which can be applied intraoperatively in real-time. The objective of this study was to profile the lipid composition of colorectal tissues using REIMS, assessing its accuracy for real-time tissue recognition and risk-stratification.

SUMMARY BACKGROUND DATA

Metabolic dysregulation is a hallmark feature of carcinogenesis; however, it remains unknown if this can be leveraged for real-time clinical applications in colorectal disease.

METHODS

Patients undergoing colorectal resection were included, with carcinoma, adenoma and paired-normal mucosa sampled. Ex vivo analysis with REIMS was conducted using monopolar diathermy, with the aerosol aspirated into a Xevo G2S QToF mass spectrometer. Negatively charged ions over 600 to 1000 m/z were used for univariate and multivariate functions including linear discriminant analysis.

RESULTS

A total of 161 patients were included, generating 1013 spectra. Unique lipidomic profiles exist for each tissue type, with REIMS differentiating samples of carcinoma, adenoma, and normal mucosa with 93.1% accuracy and 96.1% negative predictive value for carcinoma. Neoplasia (carcinoma or adenoma) could be predicted with 96.0% accuracy and 91.8% negative predictive value. Adenomas can be risk-stratified by grade of dysplasia with 93.5% accuracy, but not histological subtype. The structure of 61 lipid metabolites was identified, revealing that during colorectal carcinogenesis there is progressive increase in relative abundance of phosphatidylglycerols, sphingomyelins, and mono-unsaturated fatty acid-containing phospholipids.

CONCLUSIONS

The colorectal lipidome can be sampled by REIMS and leveraged for accurate real-time tissue recognition, in addition to riskstratification of colorectal adenomas. Unique lipidomic features associated with carcinogenesis are described.

Impact of preanalytical freezing delay time on the stability of metabolites in oral squamous cell carcinoma tissue samples

INTRODUCTION

Metabolite stability is critical for tissue metabolomics. However, changes in metabolites in tissues over time from the operating room to the laboratory remain underexplored.

OBJECTIVES

In this study, we evaluated the effect of postoperative freezing delay time on the stability of metabolites in normal and oral squamous cell carcinoma (OSCC) tissues.

METHODS

Tumor and paired normal tissues from five OSCC patients were collected after surgical resection, and samples was sequentially quenched in liquid nitrogen at 30, 40, 50, 60, 70, 80, 90 and 120 min (80 samples). Untargeted metabolic analysis by liquid chromatography-mass spectrometry/mass spectrometry in positive and negative ion modes was used to identify metabolic changes associated with delayed freezing time. The trends of metabolite changes at 30-120 and 30-60 min of delayed freezing were analyzed.

RESULTS

190 metabolites in 36 chemical classes were detected. After delayed freezing for 120 min, approximately 20% of the metabolites changed significantly in normal and tumor tissues, and differences in the metabolites were found in normal and tumor tissues. After a delay of 60 min, 29 metabolites had changed significantly in normal tissues, and 84 metabolites had changed significantly in tumor tissues. In addition, we constructed three tissue freezing schemes based on the observed variation trends in the metabolites.

CONCLUSION

Delayed freezing of tissue samples has a certain impact on the stability of metabolites. For metabolites with significant changes, we suggest that the freezing time of tissues be reasonably selected according to the freezing schemes and the actual clinical situation.

Mouse tissue harvest-induced hypoxia rapidly alters the in vivo metabolome, between-genotype metabolite level differences, and 13C-tracing enrichments

OBJECTIVE

Metabolomics as an approach to solve biological problems is exponentially increasing in use. Thus, this a pivotal time for the adoption of best practices. It is well known that disrupted tissue oxygen supply rapidly alters cellular energy charge. However, the speed and extent to which delayed mouse tissue freezing after dissection alters the broad metabolome is not well described. Furthermore, how tissue genotype may modulate such metabolomic drift and the degree to which traced ¹³C-isotopologue distributions may change have not been addressed.

METHODS

By combined liquid chromatography (LC)- and gas chromatography (GC)-mass spectrometry (MS), we measured how levels of 255 mouse liver metabolites changed following 30-second, 1-minute, 3-minute, and 10-minute freezing delays. We then performed test-of-concept delay-to-freeze experiments evaluating broad metabolomic drift in mouse heart and skeletal muscle, differential metabolomic change between wildtype (WT) and mitochondrial pyruvate carrier (MPC) knockout mouse livers, and shifts in ¹³C-isotopologue abundances and enrichments traced from ¹³C-labled glucose into mouse liver.

RESULTS

Our data demonstrate that delayed mouse tissue freezing after dissection leads to rapid hypoxia-driven remodeling of the broad metabolome, induction of both false-negative and false-positive between-genotype differences, and restructuring of ¹³C-isotopologue distributions. Notably, we show that increased purine nucleotide degradation products are an especially high dynamic range marker of delayed liver and heart freezing.

CONCLUSIONS

Our findings provide a previously absent, systematic illustration of the extensive, multi-domain metabolomic changes occurring within the early minutes of delayed tissue freezing. They also provide a novel, detailed resource of mouse liver ex vivo, hypoxic metabolomic remodeling.

Methodological Developments for Metabolic NMR Spectroscopy from Cultured Cells to Tissue Extracts: Achievements, Progress and Pitfalls

This is a broad overview and critical review of a particular group of closely related ex vivo and in vitro metabolic NMR spectroscopic methods. The scope of interest comprises studies of cultured cells and excised tissue, either intact or after physicochemical extraction of metabolites. Our detailed discussion includes pitfalls that have led to erroneous statements in the published literature, some of which may cause serious problems in metabolic and biological interpretation of results. To cover a wide range of work from relevant research areas, we consider not only the most recent achievements in the field, but also techniques that proved to be valid and successful in the past, although they may not have generated a very significant number of papers more recently. Thus, this comparative review also aims at providing background information useful for judiciously choosing between the metabolic ex vivo/in vitro NMR methods presented. Finally, the methods of interest are discussed in the context of, and in relation to, other metabolic analysis protocols such as HR-MAS and cell perfusion NMR, as well as the mass spectrometry approach.

Interim Storage of Biospecimen at Satellite Collection Centers: Dewar and Cryotube Choice Are Important for Temporary Storage in Liquid Nitrogen

One major goal of biobanks is to provide the best possible biospecimen quality for research use. This can be achieved, notably in accredited structures, by using standardized procedures for collection, processing, and storage of biosamples and associated data. Since tissue samples of a clinical biobank are commonly collected at surgical theaters in satellite locations or hospitals in remote areas, adequate temporary storage of the biosample is mandatory to maintain optimal sample quality. In cases where immediate snap freezing of the collected material is possible, interim storage of the samples in portable dewars filled with liquid nitrogen (LN₂) is a widely used method. Therefore, the ideal dewar size and maximum storage time need to be considered to maintain an optimal biospecimen quality. In addition, the nature of the cryotube material is an important aspect for keeping the biosample safe while storing it in LN₂. The objective of this study was to test different dewar vessels with respect to LN₂ volume and consumption and to analyze the impact of LN₂ contact on cryotube material through scanning electron microscopy.

New chemical biopsy tool for spatially resolved profiling of human brain tissue in vivo

It is extremely challenging to perform chemical analyses of the brain, particularly in humans, due to the restricted access to this organ. Imaging techniques are the primary approach used in clinical practice, but they only provide limited information about brain chemistry. Solid-phase microextraction (SPME) has been presented recently as a chemical biopsy tool for the study of animal brains. The current work demonstrates for the first time the use of SPME for the spatially resolved sampling of the human brain in vivo. Specially designed multi-probe sampling device was used to simultaneously extract metabolites from the white and grey matter of patients undergoing brain tumor biopsies. Samples were collected by inserting the probes along the planned trajectory of the biopsy needle prior to the procedure, which was followed by metabolomic and lipidomic analyses. The results revealed that studied brain structures were predominantly composed of lipids, while the concentration and diversity of detected metabolites was higher in white than in grey matter. Although the small number of participants in this research precluded conclusions of a biological nature, the results highlight the advantages of the proposed SPME approach, as well as disadvantages that should be addressed in future studies.

A review of coral bleaching specimen collection, preservation, and laboratory processing methods

Under current climate warming predictions, the future of coral reefs is dire. With projected coral reef decline, it is likely that coral specimens for bleaching research will increasingly become a more limited resource in the future. By adopting a holistic approach through increased collaborations, coral bleaching scientists can maximize a specimen’s investigative yield, thus reducing the need to remove more coral material from the reef. Yet to expand a specimen’s utility for additional analytic methods, information on how corals are collected is essential as many methods are variably sensitive to upstream handling and processing. In an effort to identify common practices for coral collection, sacrifice, preservation, and processing in coral bleaching research, we surveyed the literature from the last 6.5 years and created and analyzed the resulting dataset of 171 publications. Since January 2014, at least 21,890 coral specimens were collected for bleaching surveys or bleaching experiments. These specimens spanned 122 species of scleractinian corals where the most frequently sampled were Acropora millepora, Pocillopora damicornis, and Stylophora pistillata. Almost 90% of studies removed fragments from the reef, 6% collected skeletal cores, and 3% collected mucus specimens. The most common methods for sacrificing specimens were snap freezing with liquid nitrogen, chemical preservation (e.g., with ethanol or nucleic acid stabilizing buffer), or airbrushing live fragments. We also characterized 37 distinct methodological pathways from collection to processing of specimens in preparation for a variety of physiological, -omic, microscopy, and imaging analyses. Interestingly, almost half of all studies used only one of six different pathways. These similarities in collection, preservation, and processing methods illustrate that archived coral specimens could be readily shared among researchers for additional analyses. In addition, our review provides a reference for future researchers who are considering which methodological pathway to select to maximize the utility of coral bleaching specimens that they collect.

Detection of metabolic change in glioblastoma cells after radiotherapy using hyperpolarized 13 C-MRI

Dynamic nuclear polarization (DNP) of 13 C-labeled substrates enables the use of magnetic resonance imaging (MRI) to monitor specific enzymatic reactions in tumors and offers an opportunity to investigate these differences. In this study, DNP-MRI chemical shift imaging with hyperpolarized [1-13 C] pyruvate was conducted to evaluate the metabolic change in glycolytic profiles after radiation of two glioma stem-like cell-derived gliomas (GBMJ1 and NSC11) and an adherent human glioblastoma cell line (U251) in an orthotopic xenograft mouse model. The DNP-MRI showed an increase in Lac/Pyr at 6 and 16 h after irradiation (18% ± 4% and 14% ± 3%, respectively; mean ± SEM) compared with unirradiated controls in GBMJ1 tumors, whereas no significant change was observed in U251 and NSC11 tumors. Metabolomic analysis likewise showed a significant increase in lactate in GBMJ1 tumors at 16 h. An immunoblot assay showed upregulation of lactate dehydrogenase-A expression in GBMJ1 following radiation exposure, consistent with DNP-MRI and metabolomic analysis. In conclusion, our preclinical study demonstrates that the DNP-MRI technique has the potential to be a powerful diagnostic method with which to evaluate GBM tumor metabolism before and after radiation in the clinical setting.

Evaluation of the Rotating-Frame Relaxation (T1ρ) Filter and Its Application in Metabolomics as an Alternative to the Transverse Relaxation (T2) Filter

Nuclear magnetic resonance (NMR)-based metabolomic studies commonly involve the use of T2 filter pulse sequences to eliminate or attenuate the broad signals from large molecules and improve spectral resolution. In this paper, we demonstrate that the T1ρ filter-based pulse sequence represents an interesting alternative because it allows the stability and the reproducibility needed for statistical analysis. The integrity of the samples and the stability of the instruments were assessed for different filter durations and amplitudes. We showed that the T1ρ filter pulse sequence did not induce sample overheating for a filter duration of up to 500 ms. The reproducibility was evaluated and compared with the T2 filter in serum and liver samples. The implementation is relatively simple and provides the same statistical and analytical results as those obtained with the standard filters. Regarding tissues analysis, because the duration of the filter is the same as that of the spin-lock, the synchronization of the echo delays with the magic angle spinning (MAS) rate is no longer necessary as for T2 filter-based sequences. The results presented in this article aim at establishing a new protocol to improve metabolomic studies and pave the way for future developments on T1ρ alternative filters, in liquid and HR-MAS NMR experiments.

Isolation and characterization of extracellular vesicle subpopulations from tissues

Extracellular vesicles (EVs) are lipid bilayered membrane structures released by all cells. Most EV studies have been performed by using cell lines or body fluids, but the number of studies on tissue-derived EVs is still limited. Here, we present a protocol to isolate up to six different EV subpopulations directly from tissues. The approach includes enzymatic treatment of dissociated tissues followed by differential ultracentrifugation and density separation. The isolated EV subpopulations are characterized by electron microscopy and RNA profiling. In addition, their protein cargo can be determined with mass spectrometry, western blot and ExoView. Tissue-EV isolation can be performed in 22 h, but a simplified version can be completed in 8 h. Most experiments with the protocol have used human melanoma metastases, but the protocol can be applied to other cancer and non-cancer tissues. The procedure can be adopted by researchers experienced with cell culture and EV isolation.

Metabolomic studies of breast cancer in murine models: A review

BACKGROUND

Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies.

SCOPE OF REVIEW

This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturally-occurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study.

MAJOR CONCLUSIONS

Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination.

GENERAL SIGNIFICANCE

Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.

Improved workflow for mass spectrometry-based metabolomics analysis of the heart

MS-based metabolomics methods are powerful techniques to map the complex and interconnected metabolic pathways of the heart; however, normalization of metabolite abundance to sample input in heart tissues remains a technical challenge. Herein, we describe an improved GC-MS-based metabolomics workflow that uses insoluble protein-derived glutamate for the normalization of metabolites within each sample and includes normalization to protein-derived amino acids to reduce biological variation and detect small metabolic changes. Moreover, glycogen is measured within the metabolomics workflow. We applied this workflow to study heart metabolism by first comparing two different methods of heart removal: the Langendorff heart method (reverse aortic perfusion) and in situ freezing of mouse heart with a modified tissue freeze-clamp approach. We then used the in situ freezing method to study the effects of acute β-adrenergic receptor stimulation (through isoproterenol (ISO) treatment) on heart metabolism. Using our workflow and within minutes, ISO reduced the levels of metabolites involved in glycogen metabolism, glycolysis, and the Krebs cycle, but the levels of pentose phosphate pathway metabolites and of many free amino acids remained unchanged. This observation was coupled to a 6-fold increase in phosphorylated adenosine nucleotide abundance. These results support the notion that ISO acutely accelerates oxidative metabolism of glucose to meet the ATP demand required to support increased heart rate and cardiac output. In summary, our MS-based metabolomics workflow enables improved quantification of cardiac metabolites and may also be compatible with other methods such as LC or capillary electrophoresis.

Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics

Altered metabolism is one of the key hallmarks of cancer. The development of sensitive, reproducible and robust bioanalytical tools such as Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry techniques offers numerous opportunities for cancer metabolism research, and provides additional and exciting avenues in cancer diagnosis, prognosis and for the development of more effective and personalized treatments. In this chapter, we introduce the current state of the art of metabolomics and metabolic phenotyping approaches in cancer research and clinical diagnostics.

Historical Biobanks in Breast Cancer Metabolomics- Challenges and Opportunities

Background: Metabolomic characterization of tumours can potentially improve prediction of cancer prognosis and treatment response. Here, we describe efforts to validate previous metabolomic findings using a historical cohort of breast cancer patients and discuss challenges with using older biobanks collected with non-standardized sampling procedures. Methods: In total, 100 primary breast cancer samples were analysed by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and subsequently examined by histology. Metabolomic profiles were related to the presence of cancer tissue, hormone receptor status, T-stage, N-stage, and survival. RNA integrity number (RIN) and metabolomic profiles were compared with an ongoing breast cancer biobank. Results: The 100 samples had a median RIN of 4.3, while the ongoing biobank had a significantly higher median RIN of 6.3 (p = 5.86 × 10⁻⁷). A low RIN was associated with changes in choline-containing metabolites and creatine, and the samples in the older biobank showed metabolic differences previously associated with tissue degradation. The association between metabolomic profile and oestrogen receptor status was in accordance with previous findings, however, with a lower classification accuracy. Conclusions: Our findings highlight the importance of standardized biobanking procedures in breast cancer metabolomics studies.

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

Activated choline metabolism is a hallmark of carcinogenesis and tumor progression, which leads to elevated levels of phosphocholine and glycerophosphocholine in all types of cancer tested so far. Magnetic resonance spectroscopy applications have played a key role in detecting these elevated choline phospholipid metabolites. To date, the majority of cancer-related studies have focused on phosphocholine and the Kennedy pathway, which constitutes the biosynthesis pathway for membrane phosphatidylcholine. Fewer and more recent studies have reported on the importance of glycerophosphocholine in cancer. In this review article, we summarize the recent literature on glycerophosphocholine metabolism with respect to its cancer biology and its detection by magnetic resonance spectroscopy applications.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.

Untargeted metabolic profiling of dogs with a suspected toxic mitochondrial myopathy using liquid chromatography-mass spectrometry

'Go Slow myopathy' (GSM) is a suspected toxic myopathy in dogs that primarily occurs in the North Island of New Zealand, and affected dogs usually have a history of consuming meat, offal or bones from wild pigs (including previously frozen and/or cooked meat). Previous epidemiological and pathological studies on GSM have demonstrated that changes in mitochondrial structure and function are most likely caused by an environmental toxin that dogs are exposed to through the ingestion of wild pig. The disease has clinical, histological and biochemical similarities to poisoning in people and animals from the plant Ageratina altissima (white snakeroot). Aqueous and lipid extracts were prepared from liver samples of 24 clinically normal dogs and 15 dogs with GSM for untargeted liquid chromatography-mass spectrometry. Group-wise comparisons of mass spectral data revealed 38 features that were significantly different (FDR<0.05) between normal dogs and those with GSM in aqueous extracts, and 316 significantly different features in lipid extracts. No definitive cause of the myopathy was identified, but alkaloids derived from several plant species were among the possible identities of features that were more abundant in liver samples from affected dogs compared to normal dogs. Mass spectral data also revealed that dogs with GSM have reduced hepatic phospholipid and sphingolipid concentrations relative to normal dogs. In addition, affected dogs had changes in the abundance of kynurenic acid, various dicarboxylic acids and N-acetylated branch chain amino acids, suggestive of mitochondrial dysfunction.

Impact of post-surgical freezing delay on brain tumor metabolomics

INTRODUCTION

Translational cancer research has seen an increasing interest in metabolomic profiling to decipher tumor phenotypes. However, the impact of post-surgical freezing delays on mass spectrometric metabolomic measurements of the cancer tissue remains elusive.

OBJECTIVES

To evaluate the impact of post-surgical freezing delays on cancer tissue metabolomics and to investigate changes per metabolite and per metabolic pathway.

METHODS

We performed untargeted metabolomics on three cortically located and bulk-resected glioblastoma tissues that were sequentially frozen as duplicates at up to six different time delays (0-180 min, 34 samples).

RESULTS

Statistical modelling revealed that 10% of the metabolome (59 of 597 metabolites) changed significantly after a 3 h delay. While carbohydrates and energy metabolites decreased, peptides and lipids increased. After a 2 h delay, these metabolites had changed by as much as 50-100%. We present the first list of metabolites in glioblastoma tissues that are sensitive to post-surgical freezing delays and offer the opportunity to define individualized fold change thresholds for future comparative metabolomic studies.

CONCLUSION

More researchers should take these pre-analytical factors into consideration when analyzing metabolomic data. We present a strategy for how to work with metabolites that are sensitive to freezing delays.

Whole genome amplification of single epithelial cells dissociated from snap-frozen tissue samples in microfluidic platform

Single cell sequencing is a technology capable of analyzing the genome of a single cell within a population. This technology is mostly integrated with microfluidics for precise cell manipulation and fluid handling. So far, most of the microfluidic-based single cell genomic studies have been focused on lab-cultured species or cell lines that are relatively easy to handle following standard microfluidic-based protocols without additional adjustments. The major challenges for performing single cell sequencing on clinical samples is the complex nature of the samples which requires additional sample processing steps to obtain intact single cells of interest without using amplification-inhibitive agents. Fluorescent-activated cell sorting is a common option to obtain single cells from clinical samples for single cell applications but requires >100 000 viable cells in suspension and the need for specialized laboratory and personnel. In this work, we present a protocol that can be used to obtain intact epithelial cells from snap-frozen postsurgical human endometrial tissues for single cell whole genome amplification. Our protocol includes sample thawing, cell dissociation, and labeling for genome amplification of targeted cells. Between 80% and 100% of single cell replicates lead to >25 ng of DNA after amplification with no measurable contamination, sufficient for downstream sequencing.

Accounting for biological variation with linear mixed-effects modelling improves the quality of clinical metabolomics data

Metabolite profiles from biological samples suffer from both technical variations and subject-specific variants. To improve the quality of metabolomics data, conventional data processing methods can be employed to remove technical variations. These methods do not consider sources of subject variation as separate factors from biological factors of interest. This can be a significant issue when performing quantitative metabolomics in clinical trials or screening for a potential biomarker in early-stage disease, because changes in metabolism or a desired-metabolite signal are small compared to the total metabolite signals. As a result, inter-individual variability can interfere subsequent statistical analyses. Here, we propose an additional data processing step using linear mixed-effects modelling to readjust an individual metabolite signal prior to multivariate analyses. Published clinical metabolomics data was used to demonstrate and evaluate the proposed method. We observed a substantial reduction in variation of each metabolite signal after model fitting. A comparison with other strategies showed that our proposed method contributed to improved classification accuracy, precision, sensitivity and specificity. Moreover, we highlight the importance of patient metadata as it contains rich information of subject characteristics, which can be used to model and normalize metabolite abundances. The proposed method is available as an R package lmm2met.

HR-MAS NMR Based Quantitative Metabolomics in Breast Cancer

High resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly used for profiling of breast cancer tissue, delivering quantitative information for approximately 40 metabolites. One unique advantage of the method is that it can be used to analyse intact tissue, thereby requiring only minimal sample preparation. Importantly, since the method is non-destructive, it allows further investigations of the same specimen using for instance transcriptomics. Here, we discuss technical aspects critical for a successful analysis—including sample handling, measurement conditions, pulse sequences for one- and two dimensional analysis, and quantification methods—and summarize available studies, with a focus on significant associations of metabolite levels with clinically relevant parameters.

Biomedical analysis of formalin-fixed, paraffin-embedded tissue samples: The Holy Grail for molecular diagnostics

More than a century ago in 1893, a revolutionary idea about fixing biological tissue specimens was introduced by Ferdinand Blum, a German physician. Since then, a plethora of fixation methods have been investigated and used. Formalin fixation with paraffin embedment became the most widely used types of fixation and preservation method, due to its proper architectural conservation of tissue structures and cellular shape. The huge collection of formalin-fixed, paraffin-embedded (FFPE) sample archives worldwide holds a large amount of unearthed information about diseases that could be the Holy Grail in contemporary biomarker research utilizing analytical omics based molecular diagnostics. The aim of this review is to critically evaluate the omics options for FFPE tissue sample analysis in the molecular diagnostics field.

Establishment and quality evaluation of a glioma biobank in Beijing Tiantan Hospital

BACKGROUND

We established a glioma biobank at Beijing Tiantan Hospital in November, 2010. Specialized residents have been trained to collect, store and manage the biobank in accordance with standard operating procedures.

METHODS

One hundred samples were selected to evaluate the quality of glioma samples stored in the liquid nitrogen tank during different periods (from 2011 to 2015) by morphological examination, RNA integrity determination, DNA integrity determination and housekeeping gene expression determination.

RESULTS

The majority of samples (95%) had high RNA quality for further analysis with RIN ≥6. Quality of DNA of all samples were stable without significant degradation.

CONCLUSION

Storage conditions of our biobank are suitable for long-term (at least five years) sample preservation with high molecular quality.

Linking imaging to omics utilizing image-guided tissue extraction

Imaging provides an insight into biological patho-mechanisms of diseases. However, the link between the imaging phenotype and the underlying molecular processes is often not well understood. Methods such as metabolomics and proteomics reveal detailed information about these processes. Unfortunately, they provide no spatial information and thus cannot be easily correlated with functional imaging. We have developed an image-guided milling machine and unique workflows to precisely isolate tissue samples based on imaging data. The tissue samples remain cooled during the entire procedure, preventing sample degradation. This enables us to correlate, at an unprecedented spatial precision, comprehensive imaging information with metabolomics and proteomics data, leading to a better understanding of diseases.

Phenotypic heterogeneity is commonly observed in diseased tissue, specifically in tumors. Multimodal imaging technologies can reveal tissue heterogeneity noninvasively in vivo, enabling imaging-based profiling of receptors, metabolism, morphology, or function on a macroscopic scale. In contrast, in vitro multiomics, immunohistochemistry, or histology techniques accurately characterize these heterogeneities in the cellular and subcellular scales in a more comprehensive but ex vivo manner. The complementary in vivo and ex vivo information would provide an enormous potential to better characterize a disease. However, this requires spatially accurate coregistration of these data by image-driven sampling as well as fast sample-preparation methods. Here, a unique image-guided milling machine and workflow for precise extraction of tissue samples from small laboratory animals or excised organs has been developed and evaluated. The samples can be delineated on tomographic images as volumes of interest and can be extracted with a spatial accuracy better than 0.25 mm. The samples remain cooled throughout the procedure to ensure metabolic stability, a precondition for accurate in vitro analysis.

Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1 H NMR spectroscopy

High-resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi-core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9- and 1.3-ppm signals) and metabolite quantification using HR MAS ¹ H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16-0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one-way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue.

NMR-Based Prostate Cancer Metabolomics

Prostate cancer is the second most common malignancy, and the fifth leading cause of cancer-related death among men, worldwide. A major unsolved clinical challenge in prostate cancer is the ability to accurately distinguish indolent cancer types from the aggressive ones. Reprogramming of metabolism is now a widely accepted hallmark of cancer development, where cancer cells must be able to convert nutrients to biomass while maintaining energy production. Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues, or organisms. Nuclear magnetic resonance (NMR) spectroscopy is commonly applied in metabolomics studies of cancer. This chapter provides protocols for NMR-based metabolomics of cell cultures, biofluids (serum and urine), and intact tissue, with concurrent advice for optimal biobanking and sample preparation procedures.

Metabolic Footprints and Molecular Subtypes in Breast Cancer

Cancer treatment options are increasing. However, even among the same tumor histotype, interpatient tumor heterogeneity should be considered for best therapeutic result. Metabolomics represents the last addition to promising “omic” sciences such as genomics, transcriptomics, and proteomics. Biochemical transformation processes underlying energy production and biosynthetic processes have been recognized as a hallmark of the cancer cell and hold a promise to build a bridge between genotype and phenotype. Since breast tumors represent a collection of different diseases, understanding metabolic differences between molecular subtypes offers a way to identify new subtype-specific treatment strategies, especially if metabolite changes are evaluated in the broader context of the network of enzymatic reactions and pathways. Here, after a brief overview of the literature, original metabolomics data in a series of 92 primary breast cancer patients undergoing surgery at the Istituto Nazionale dei Tumori of Milano are reported highlighting a series of metabolic differences across various molecular subtypes. In particular, the difficult-to-treat luminal B subgroup represents a tumor type which preferentially relies on fatty acids for energy, whereas HER2 and basal-like ones show prevalently alterations in glucose/glutamine metabolism.

Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases

High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.

Metabolic Portraits of Breast Cancer by HR MAS MR Spectroscopy of Intact Tissue Samples

Despite progress in early detection and therapeutic strategies, breast cancer remains the second leading cause of cancer-related death among women globally. Due to the heterogeneity and complexity of tumor biology, breast cancer patients with similar diagnosis might have different prognosis and response to treatment. Thus, deeper understanding of individual tumor properties is necessary. Cancer cells must be able to convert nutrients to biomass while maintaining energy production, which requires reprogramming of central metabolic processes in the cells. This phenomenon is increasingly recognized as a potential target for treatment, but also as a source for biomarkers that can be used for prognosis, risk stratification and therapy monitoring. Magnetic resonance (MR) metabolomics is a widely used approach in translational research, aiming to identify clinically relevant metabolic biomarkers or generate novel understanding of the molecular biology in tumors. Ex vivo proton high-resolution magic angle spinning (HR MAS) MR spectroscopy is widely used to study central metabolic processes in a non-destructive manner. Here we review the current status for HR MAS MR spectroscopy findings in breast cancer in relation to glucose, amino acid and choline metabolism.

Tissue-Based Metabolomics to Analyze the Breast Cancer Metabolome

Mass spectrometry and nuclear magnetic resonance-based metabolomics have been developed into mature technologies that can be utilized to analyze hundreds of biological samples in a high-throughput manner. Over the past few years, both technologies were utilized to analyze large cohorts of fresh frozen breast cancer tissues. Metabolite biomarkers were shown to separate breast cancer tissues from normal breast tissues with high sensitivity and specificity. Furthermore, the metabolome differed between hormone receptor positive (HR+) and hormone receptor negative (HR-) breast cancer, but was unchanged in HER2+ tumors compared to HER2- tumors. New metabolism-related biomarkers were discovered including the 4-aminobutyrate aminotransferase ABAT, where low mRNA expression led to an accumulation of beta-alanine and shortened relapse-free survival. The glutamate-to-glutamine ratio (GGR) represents another new biomarker that was increased in 88 % of HR- tumors and 56 % of HR+ tumors compared to normal breast tissues. The GGR might help to stratify patients for the treatment with specific glutaminase inhibitors that were recently developed and are currently being tested in phase I clinical studies. Surprisingly, 2-hydroxyglutarate (2-HG), initially found to accumulate in isocitrate dehydrogenase (IDH) mutated gliomas and leukemias and described as an oncometabolite, was detected to be drastically increased in several breast carcinomas in the absence of IDH mutations. In summary, metabolomics analysis of breast cancer tissues is a reliable method and has produced many new biological insights that may impact breast cancer diagnostics and treatment over the coming years.