Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype

Lipid profile in breast cancer: From signaling pathways to treatment strategies

Breast cancer is the most prevalent cancer in women. Metabolic abnormalities, particularly increased lipid synthesis and uptake, impact the onset and progression of the disease. However, the influence of lipid metabolism in breast cancer varies according to the disease stage and patient's hormone status. In postmenopausal patients, obesity is associated with a higher risk and poor prognosis of luminal tumors, while in premenopausal individuals, it is correlated to BRCA mutated tumors. In fact, the tumor's lipid profile may be used to distinguish between HER2+, luminal and BRCA-mutated tumors. Moreover, drug resistance was associated with increased fatty acid synthesis and alterations in membrane composition, impacting its fluidity and spatial subdomains such as lipid rafts. Here, we discuss the subtype-specific lipid metabolism alterations found in breast cancer and the potentiality of its modulation in a clinical setting.

Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma

Extracellular vesicles (EVs), including exosomes and microvesicles, mediate intercellular communication in cancer, from development to metastasis. EV-based liquid biopsy is a promising strategy for cancer diagnosis as EVs can be found in cancer patients' body fluids. In this study, the lipid composition of breast cancer-derived EVs was studied as well as the potential of blood plasma EVs for the identification of lipid biomarkers for breast cancer detection. Initially, an untargeted lipidomic analysis was carried out for a panel of cancerous and non-cancerous mammary epithelial cells and their secreted EVs. We found that breast cancer-derived EVs are enriched in sphingolipids and glycerophospholipids compared to their parental cells. The initial in vitro study showed that EVs and their parental cells can be correctly classified (100% accuracy) between cancerous and non-cancerous, as well as into their respective breast cancer subtypes, based on their lipid composition. Subsequently, an untargeted lipidomic analysis was carried out for blood plasma EVs from women diagnosed with breast cancer (primary or progressive metastatic breast cancer) as well as healthy women. Correspondingly, when blood plasma EVs were analysed, breast cancer patients and healthy women were correctly classified with an overall accuracy of 93.1%, based on the EVs' lipid composition. Similarly, the analysis of patients with primary breast cancer and healthy women showed an overall accuracy of 95% for their correct classification. Furthermore, primary and metastatic breast cancers were correctly classified with an overall accuracy of 89.5%. This reveals that the blood plasma EVs' lipids may be a promising source of biomarkers for detection of breast cancer. Additionally, this study demonstrates the usefulness of untargeted lipidomics in the study of EV lipid composition and EV-associated biomarker discovery studies. This is a proof-of-concept study and a starting point for further analysis on the identification of EV-based biomarkers for breast cancer.

The journey towards clinical adoption of MALDI-MS-based imaging proteomics: from current challenges to future expectations

Among the spatial omics techniques available, mass spectrometry imaging (MSI) represents one of the most promising owing to its capability to map the distribution of hundreds of peptides and proteins, as well as other classes of biomolecules, within a complex sample background in a multiplexed and relatively high-throughput manner. In particular, matrix-assisted laser desorption/ionisation (MALDI-MSI) has come to the fore and established itself as the most widely used technique in clinical research. However, the march of this technique towards clinical utility has been hindered by issues related to method reproducibility, appropriate biocomputational tools, and data storage. Notwithstanding these challenges, significant progress has been achieved in recent years regarding multiple facets of the technology and has rendered it more suitable for a possible clinical role. As such, there is now more robust and extensive evidence to suggest that the technology has the potential to support clinical decision-making processes under appropriate circumstances. In this review, we will discuss some of the recent developments that have facilitated this progress and outline some of the more promising clinical proteomics applications which have been developed with a clear goal towards implementation in mind.

Visualization of Small Intact Proteins in Breast Cancer FFPE Tissue

Molecular visualization of metabolites, lipids, and proteins by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is becoming an in-demand analytical approach to aid the histopathological analysis of breast cancer. Particularly, proteins seem to play a role in cancer progression, and specific proteins are currently used in the clinic for staging. Formalin-fixed paraffin-embedded (FFPE) tissues are ideal for correlating the molecular markers with clinical outcomes due to their long-term storage. So far, to obtain proteomic information by MSI from this kind of tissue, antigen retrieval and tryptic digestion steps are required. In this chapter, we present a protocol to spatially detect small proteins in tumor and necrotic regions of patient-derived breast cancer xenograft FFPE tissues without employing any on-tissue digestion. This protocol can be used for other kinds of FFPE tissue following specific optimization of the sample preparation phases.

Correlations between serum lipid and Ki-67 levels in different breast cancer molecular subcategories

Breast cancer has the highest incidence rate among all cancer types worldwide, seriously threatening women's health. The present retrospective study explored differences in serum lipid contents in different breast cancer (BC) subcategories and their correlation with Ki-67 expression levels in patients with invasive BC with the aim of identifying novel diagnostic and prognostic indicators for personalized BC treatment. The study included 170 patients diagnosed with BC who were diagnosed with invasive BC by postoperative pathological examination. Data on patient age, body mass index and menopausal status were collected, in addition to estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (HER2) and antigen Ki-67 expression levels and pathological tumor type. Preoperative circulating lipid levels, specifically the levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and apolipoproteins A1 (ApoA1) and B (ApoB) were also obtained. Molecular subcategories of BC were grouped based on their immunohistochemistry. Differences in serum lipid levels between the groups were assessed, and correlations between serum lipid and Ki-67 expression levels were explored. While TC, LDL-C, HDL-C and ApoA1 levels differed significantly among molecular subcategories. TG and ApoB levels did not. Circulating TC and LDL-C levels were considerably higher in patients with triple-negative BC (TNBC) and HER2-positive [hormone receptor (HR)-negative] BC than in those with luminal A and B (HER2-negative) BC. Serum HDL-C levels were significantly diminished in the TNBC and HER2-positive (HR-negative) groups compared with the luminal A and B (HER2-negative) groups. ApoA1 levels were significantly reduced in cases of TNBC and HER2-positive (HR-negative) BC compared with luminal A and B BC. Ki-67 expression levels were positively correlated with circulating TC and LDL-C levels and inversely correlated with circulating HDL-C and ApoA1 levels but exhibited no correlation with serum ApoB and TG levels. The results indicate that elevated TC and LDL-C levels and diminished HDL-C and ApoA1 levels were high-risk factors in patients with TNBC and HER2-positive (HR-negative) BC, but not patients with luminal subcategories of BC. Abnormal serum lipid levels were correlated with Ki-67 expression levels, with elevated circulating TC and LDL-C levels and reduced circulating HDL-C and ApoA1 levels indicating a poor prognosis in patients with BC.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Cell and Tissue Imaging by TOF-SIMS and MALDI-TOF: An Overview for Biological and Pharmaceutical Analysis

The potential of mass spectrometry imaging (MSI) has been demonstrated in cell and tissue research since 1970. MSI can reveal the spatial distribution of a wide range of atomic and molecular ions detected from biological sample surfaces, it is a powerful and valuable technique used to monitor and detect diverse chemical and biological compounds, such as drugs, lipids, proteins, and DNA. MSI techniques, notably matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) and time of flight secondary ion mass spectrometry (TOF-SIMS), witnessed a dramatic upsurge in studying and investigating biological samples especially, cells and tissue sections. This advancement is attributed to the submicron lateral resolution, the high sensitivity, the good precision, and the accurate chemical specificity, which make these techniques suitable for decoding and understanding complex mechanisms of certain diseases, as well as monitoring the spatial distribution of specific elements, and compounds. While the application of both techniques for the analysis of cells and tissues is thoroughly discussed, a briefing of MALDI-TOF and TOF-SIMS basis and the adequate sampling before analysis are briefly covered. The importance of MALDI-TOF and TOF-SIMS as diagnostic tools and robust analytical techniques in the medicinal, pharmaceutical, and toxicology fields is highlighted through representative published studies.

Metabolic and lipidomic characterization of radioresistant MDA-MB-231 human breast cancer cells to investigate potential therapeutic targets

To provide preliminary insights into metabolic and lipidomic characteristics in radioresistant triple-negative breast cancer (TNBC) cells and suggest potential therapeutic targets, we performed a comprehensive metabolic and lipidomic profiling of radioresistant MDA-MB-231 (MDA-MB-231/RR) TNBC cells and their parental cells using gas chromatography-mass spectrometry and nano electrospray ionization-mass spectrometry, followed by multivariate statistical analysis. Buthionine sulfoximine (BSO) and radiation were co-treated to radioresistant TNBC cells. The level of glutathione (GSH) was significantly increased, and the levels of GSH synthesis-related metabolites, such as cysteine, glycine, and glutamine were also increased in MDA-MB-231/RR cells. In contrast, the level of lactic acid was significantly reduced. In addition, reactive oxygen species (ROS) level was decreased in MDA-MB-231/RR cells. In the lipidomic profiles of MDA-MB-231/RR cells, the levels of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) were significantly increased, whereas those of most of the phosphatidylinositol species were significantly decreased. BSO sensitized MDA-MB-231/RR cells to radiotherapy, which resulted in decreased GSH level and increased ROS level and apoptosis. Radioresistant TNBC cells showed distinct metabolic and lipidomic characteristics compared to their parental cells. We suggested activated GSH, PC, and PE biosynthesis pathways as potential targets for treating radioresistant TNBC cells. Particularly, enhanced radiosensitivity was achieved by inhibition of GSH biosynthesis in MDA-MB-231/RR cells.

Application of Intraoperative Mass Spectrometry and Data Analytics for Oncological Margin Detection, A Review

OBJECTIVE

A common phase of early-stage oncological treatment is the surgical resection of cancerous tissue. The presence of cancer cells on the resection margin, referred to as positive margin, is correlated with the recurrence of cancer and may require re-operation, negatively impacting many facets of patient outcomes. There exists a significant gap in the surgeons ability to intraoperatively delineate between tissues. Mass spectrometry methods have shown considerable promise as intraoperative tissue profiling tools that can assist with the complete resection of cancer. To do so, the vastness of the information collected through these modalities must be digested, relying on robust and efficient extraction of insights through data analysis pipelines.

METHODS

We review clinical mass spectrometry literature and prioritize intraoperatively applied modalities. We also survey the data analysis methods employed in these studies.

RESULTS

Our review outlines the advantages and shortcomings of mass spectrometry imaging and point-based tissue probing methods. For each modality, we identify statistical, linear transformation and machine learning techniques that demonstrate high performance in classifying cancerous tissues across several organ systems. A limited number of studies presented results captured intraoperatively.

CONCLUSION

Through continued research of data centric techniques, like mass spectrometry, and the development of robust analysis approaches, intraoperative margin assessment is becoming feasible.

SIGNIFICANCE

By establishing the relatively short history of mass spectrometry techniques applied to surgical studies, we hope to inform future applications and aid in the selection of suitable data analysis frameworks for the development of intraoperative margin detection technologies.

Advances in Analyzing the Breast Cancer Lipidome and Its Relevance to Disease Progression and Treatment

Abnormal lipid metabolism is common in breast cancer with the three main subtypes, hormone receptor (HR) positive, human epidermal growth factor 2 (HER2) positive, and triple negative, showing common and distinct lipid dependencies. A growing body of studies identify altered lipid metabolism as impacting breast cancer cell growth and survival, plasticity, drug resistance, and metastasis. Lipids are a class of nonpolar or polar (amphipathic) biomolecules that can be produced in cells via de novo synthesis or acquired from the microenvironment. The three main functions of cellular lipids are as essential components of membranes, signaling molecules, and nutrient storage. The use of mass spectrometry-based lipidomics to analyze the global cellular lipidome has become more prevalent in breast cancer research. In this review, we discuss current lipidomic methodologies, highlight recent breast cancer lipidomic studies and how these findings connect to disease progression and therapeutic development, and the potential use of lipidomics as a diagnostic tool in breast cancer. A better understanding of the breast cancer lipidome and how it changes during drug resistance and tumor progression will allow informed development of diagnostics and novel targeted therapies.

Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone

Objective

Prostate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4–10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4–10 ng/ml was explored.

Methods

A total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4–10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles.

Results

Several differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student’s t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4–10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG).

Conclusion

The findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4–10 ng/ml.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Peptide barcodes in dogs affected by mitral valve disease with and without pulmonary hypertension using MALDI-TOF MS and LC-MS/MS

Mitral valve disease (MVD) is an important and most frequently acquired heart disease found in dogs. MVD is classified into different stages according to its severity. There is a challenge in differentiation between asymptomatic and symptomatic stages of the MVD. Moreover, pulmonary hypertension (PH) is a common complication in dogs affected by MVD. In clinical practice, there are also some limitations to identify PH. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a technique that can characterize specific patterns of peptide mass called peptide barcodes from various samples. Besides, in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS), potential peptide sequences associated with specific conditions could be identified. The present study aimed to use MALDI-TOF coupled with LC-MS/MS to characterize specific peptide barcodes and potential peptide candidates in serum samples from healthy dogs, dogs with MVD stage B (MVD B, asymptomatic stage), MVD stage C (MVD C, symptomatic stage), MVD stage B with PH (MVD B PH), and MVD stage C with PH (MVD C PH). Discrete clusters of the 5 sample groups were identified by 3D plot analysis. Peptide barcodes also revealed differences in peptide patterns among the 5 groups. Six amino acid sequences of peptide candidates at 1,225.60, 1,363.85, 1,688.71, 1789.52, 2020.21, and 2156.42 Da were identified as part of the proteins CLCN1, CLUL1, EDNRA, PTEN, SLC39A7, and CLN6, respectively. The network interactions between these discovered proteins and common cardiovascular drugs were also investigated. These results demonstrate that MALDI-TOF MS has promise as an optional technique for diagnosing dogs affected by asymptomatic and symptomatic stages of MVD with and without PH. Further studies are required to identify peptide barcodes in dogs with other diseases to create peptide barcode databases in veterinary medicine before using this method as a novel diagnostic tool in the future.

Expanding Roles of De Novo Lipogenesis in Breast Cancer

In recent years, lipid metabolism has gained greater attention in several diseases including cancer. Dysregulation of fatty acid metabolism is a key component in breast cancer malignant transformation. In particular, de novo lipogenesis provides the substrate required by the proliferating tumor cells to maintain their membrane composition and energetic functions during enhanced growth. However, it appears that not all breast cancer subtypes depend on de novo lipogenesis for fatty acid replenishment. Indeed, while breast cancer luminal subtypes rely on de novo lipogenesis, the basal-like receptor-negative subtype overexpresses genes involved in the utilization of exogenous-derived fatty acids, in the synthesis of triacylglycerols and lipid droplets, and fatty acid oxidation. These metabolic differences are specifically associated with genomic and proteomic changes that can perturb lipogenic enzymes and related pathways. This behavior is further supported by the observation that breast cancer patients can be stratified according to their molecular profiles. Moreover, the discovery that extracellular vesicles act as a vehicle of metabolic enzymes and oncometabolites may provide the opportunity to noninvasively define tumor metabolic signature. Here, we focus on de novo lipogenesis and the specific differences exhibited by breast cancer subtypes and examine the functional contribution of lipogenic enzymes and associated transcription factors in the regulation of tumorigenic processes.

Regional Lipid Expression Abnormalities Identified Using MALDI IMS Correspond to MRI-Defined White Matter Hyperintensities within Post-mortem Human Brain Tissues

Periventricular white matter hyperintensities (pvWMHs) are a neurological feature detected with magnetic resonance imaging that are clinically associated with an increased risk of stroke and dementia. pvWMHs represent white matter lesions characterized by regions of myelin and axon rarefaction and as such likely involve changes in lipid composition; however, these alterations remain unknown. Lipids are critical in determining cell function and survival. Perturbations in lipid expression have previously been associated with neurological disorders. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is an emerging technique for untargeted, high-throughput investigation of lipid expression and spatial distribution in situ; however, the use of MALDI IMS has been previously been limited by the need for non-embedded, non-fixed, fresh-frozen samples. In the current study, we demonstrate the novel use of MALDI IMS to distinguish regional lipid abnormalities that correlate with magnetic resonance imaging (MRI) defined pvWMHs within ammonium formate washed, formalin-fixed human archival samples. MALDI IMS scans were conducted in positive or negative ion detection mode on tissues sublimated with 2,5-dihydroxybenzoic acid or 1,5-diaminonaphthalene matrices, respectively. Using a broad, untargeted approach to lipid analysis, we consistently detected 116 lipid ion species in 21 tissue blocks from 11 different post-mortem formalin-fixed human brains. Comparing the monoisotopic mass peaks of these lipid ions elucidated significant differences in lipid expression between pvWMHs and NAWM for 31 lipid ion species. Expanding our understanding of alterations in lipid composition will provide greater knowledge of molecular mechanisms underpinning ischemic white matter lesions and provides the potential for novel therapeutic interventions targeting lipid composition abnormalities.

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

Altered lipid metabolism has been associated with the progression of various cancers, and aberrant expression of enzymes involved in the lipid metabolism has been detected in different stages of cancer. Breast cancer (BC) is one of the cancer types known to be associated with alterations in the lipid metabolism and overexpression of enzymes involved in this metabolism. It has been demonstrated that inhibition of the activity of certain enzymes, such as that of phospholipase A₂ in BC cell lines sensitizes these cells and decreases the IC₅₀ values for forthcoming therapy with traditional drugs, such as doxorubicin and tamoxifen. Moreover, other phospholipases, such as phospholipase C and D, are involved in intracellular signal transduction, which emphasizes their importance in cancer development. Finally, BC is assumed to be dependent on the diet and the composition of lipids in nutrients. Despite their importance, analytical approaches that can associate the activity of phospholipases with changes in the lipid composition and distribution in cancer tissues are not yet standardized. In this review, an overview of various analytical platforms that are applied on the study of lipids and phospholipase activity in BC tissues will be given, as well as their association with cancer diagnosis and tumor progression. The methods that are applied to tissues obtained from the BC patients will be emphasized and critically evaluated, regarding their applicability in oncology.

The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer

Lipids are essential components of cell structure and play important roles in signal transduction between cells and body metabolism. With the continuous development and innovation of lipidomics technology, many studies have shown that the relationship between lipids and cancer is steadily increasing, involving cancer occurrence, proliferation, migration, and apoptosis. Breast cancer has seriously affected the safety and quality of life of human beings worldwide and has become a significant public health problem in modern society, with an especially high incidence among women. Therefore, the issue has inspired scientific researchers to study the link between lipids and breast cancer. This article reviews the research progress of lipidomics, the biological characteristics of lipid molecules, and the relationship between some lipids and cancer drug resistance. Furthermore, this work summarizes the lipid molecules related to breast cancer diagnosis and prognosis, and then it clarifies their impact on the occurrence and development of breast cancer The discussion revolves around the current research hotspot long-chain non-coding RNAs (lncRNAs), summarizes and explains their impact on tumor lipid metabolism, and provides more scientific basis for future cancer research studies.

Double Bond Characterization of Free Fatty Acids Directly from Biological Tissues by Ultraviolet Photodissociation

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.

Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling

Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early-stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific, and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls, and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least-squares discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, and specificity = 0.76 and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, and specificity = 0.79 and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier MSV000085324).

Lipidomic study of cell lines reveals differences between breast cancer subtypes

Breast cancer (BC) is the most prevalent type of cancer in women in western countries. BC mortality has not declined despite early detection by screening, indicating the need for better informed treatment decisions. Therefore, a novel noninvasive diagnostic tool for BC would give the opportunity of subtype-specific treatment and improved prospects for the patients. Heterogeneity of BC tumor subtypes is reflected in the expression levels of enzymes in lipid metabolism. The aim of the study was to investigate whether the subtype defined by the transcriptome is reflected in the lipidome of BC cell lines. A liquid chromatography mass spectrometry (LC-MS) platform was applied to analyze the lipidome of six cell lines derived from human BC cell lines representing different BC subtypes. We identified an increased abundance of triacylglycerols (TG) ≥ C-48 with moderate or multiple unsaturation in fatty acyl chains and down-regulated ether-phosphatidylethanolamines (PE) (C-34 to C-38) in cell lines representing estrogen receptor and progesterone receptor positive tumor subtypes. In a cell line representing HER2-overexpressing tumor subtype an elevated expression of TG (≤ C-46), phosphatidylcholines (PC) and PE containing short-chained (≤ C-16) saturated or monounsaturated fatty acids were observed. Increased abundance of PC ≥ C-40 was found in cell lines of triple negative BC subtype. In addition, differences were detected in lipidomes within these previously defined subtypes. We conclude that subtypes defined by the transcriptome are indeed reflected in differences in the lipidome and, furthermore, potentially biologically relevant differences may exist within these defined subtypes.

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression

Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 μm) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.

Fatty acids: Adiposity and breast cancer chemotherapy, a bad synergy?

Globally, breast cancer continues to be a major concern in women's health. Lifestyle related risk factors, specifically excess adipose tissue (adiposity) has reached epidemic proportions and has been identified as a major risk factor in the development of breast cancer. Dysfunctional adipose tissue has evoked research focusing on its association with metabolic-related conditions, breast cancer risk and progression. Adipose dysfunction in coordination with immune cells and inflammation, are responsible for accelerated cell growth and survival of cancer cells. Recently, evidence also implicates adiposity as a potential risk factor for chemotherapy resistance. Chemotherapeutic agents have been shown to negatively impact adipose tissue. Since adipose tissue is a major storage site for fatty acids, it is not unlikely that these negative effects may disrupt adipose tissue homeostasis. It is therefore argued that fatty acid composition may be altered due to the chemotherapeutic pharmacokinetics, which in turn could have severe health related outcomes. The underlying molecular mechanisms elucidating the effects of fatty acid composition in adiposity-linked drug resistance are still unclear and under explored. This review focuses on the potential role of adiposity in breast cancer and specifically emphasizes the role of fatty acids in cancer progression and treatment resistance.

Unbiased Lipidomic Profiling of Triple-Negative Breast Cancer Tissues Reveals the Association of Sphingomyelin Levels with Patient Disease-Free Survival

The reprogramming of lipid metabolism is a hallmark of many cancers that has been shown to promote breast cancer progression. While several lipid signatures associated with breast cancer aggressiveness have been identified, a comprehensive lipidomic analysis specifically targeting the triple-negative subtype of breast cancer (TNBC) may be required to identify novel biomarkers and therapeutic targets for this most aggressive subtype of breast cancer that still lacks effective therapies. In this current study, our global LC-MS-based lipidomics platform was able to measure 684 named lipids across 15 lipid classes in 70 TNBC tumors. Multivariate survival analysis found that higher levels of sphingomyelins were significantly associated with better disease-free survival in TNBC patients. Furthermore, analysis of publicly available gene expression datasets identified that decreased production of ceramides and increased accumulation of sphingoid base intermediates by metabolic enzymes were associated with better survival outcomes in TNBC patients. Our LC-MS lipidomics profiling of TNBC tumors has, for the first time, identified sphingomyelins as a potential prognostic marker and implicated enzymes involved in sphingolipid metabolism as candidate therapeutic targets that warrant further investigation.

Tissue preservation with mass spectroscopic analysis: Implications for cancer diagnostics

Surgical intervention is a common treatment modality for localized cancer. Post-operative analysis involves evaluation of surgical margins to assess whether all malignant tissue has been resected because positive surgical margins lead to a greater likelihood of recurrence. Secondary treatments are utilized to minimize the negative effects of positive surgical margins. Recently, in Science Translational Medicine, Zhang et al describe a new mass spectroscopic technique that could potentially decrease the likelihood of positive surgical margins. Their nondestructive in vivo tissue sampling leads to a highly accurate and rapid cancer diagnosis with great precision between healthy and malignant tissue. This new tool has the potential to improve surgical margins and accelerate cancer diagnostics by analyzing biomolecular signatures of various tissues and diseases.

Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system

Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.

The quest for improved reproducibility in MALDI mass spectrometry

Reproducibility has been one of the biggest hurdles faced when attempting to develop quantitative protocols for MALDI mass spectrometry. The heterogeneous nature of sample recrystallization has made automated sample acquisition somewhat "hit and miss" with manual intervention needed to ensure that all sample spots have been analyzed. In this review, we explore the last 30 years of literature and anecdotal evidence that has attempted to address and improve reproducibility in MALDI MS. Though many methods have been attempted, we have discovered a significant publication history surrounding the use of nitrocellulose as a substrate to improve homogeneity of crystal formation and therefore reproducibility. We therefore propose that this is the most promising avenue of research for developing a comprehensive and universal preparation protocol for quantitative MALDI MS analysis. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:217-228, 2018.

Enhanced coverage of lipid analysis and imaging by matrix-assisted laser desorption/ionization mass spectrometry via a strategy with an optimized mixture of matrices

In matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) analysis and imaging of lipids, comprehensive ionization of lipids simultaneously by a universal matrix is a very challenging problem. Ion suppression of readily ionizable lipids to others is common. To overcome this obstacle and enhance the coverage of MALDI MS analysis and imaging of lipids, we developed a novel strategy employing a mixture of matrices, each of which is capable of selective ionization of different lipid classes. Given that MALDI MS with either 9-aminoacridine (9-AA) or N-(1-naphthyl) ethylenediamine dihydrochloride (NEDC) yields weak in-source decay which is critical for analysis of complex biological samples and possesses orthogonal selectivity for ionization of lipid classes, we tested the mixtures of NEDC and 9-AA with different ratios for analysis of standard lipids and mouse brain lipid extracts. We determined 1.35 of NEDC/9-AA as an optimized molar ratio. It was demonstrated that an enhanced coverage with the optimized mixture was obtained, which enabled us to analyze and map all the major classes of phospholipids and sulfatide from either lipid extracts or tissue slides, respectively. We believe that this powerful novel strategy can enhance lipidomics analysis and MALDI MS imaging of lipids in a high-throughput and semi-quantitative fashion.

Recurrent triple-negative breast cancer (TNBC) tissues contain a higher amount of phosphatidylcholine (32:1) than non-recurrent TNBC tissues

Triple-negative breast cancer (TNBC) is one of the breast cancer subtype that displays a high risk of early recurrence and short overall survival. Improvement of the prognosis of patients with TNBC requires identifying a predictive factor of recurrence, which would make it possible to provide beneficial personalized treatment. However, no clinically reliable predictive factor is currently known. In this study, we investigated the predictive factor of recurrence in TNBC using matrix-assisted laser desorption/ionization-imaging mass spectrometry for lipid profiling of breast cancer specimens obtained from three and six patients with recurrent and non-recurrent TNBC, respectively. The signal for phosphatidylcholine (PC) (32:1) at m/z 732.5 was significantly higher in the recurrence group compared to the non-recurrence group (P = 0.024). PC (32:1) was more abundant in the cancer epithelial area than it was in the surrounding stroma, suggesting that abnormal lipid metabolism was associated with malignant transformation. Our results indicate PC (32:1) as a candidate predictive factor of TNBC recurrence. A future prospective study investigating whether personalized therapy based on PC (32:1) intensity improves the prognosis of patients with TNBC is recommended.

A new standard of visual data representation for imaging mass spectrometry

PURPOSE

MALDI imaging MS (IMS) is principally used for cancer diagnostics. In our own experience with publishing IMS data, we have been requested to modify our protocols with respect to the areas of the tissue that are imaged in order to comply with the wider literature. In light of this, we have determined that current methodologies lack effective controls and can potentially introduce bias by only imaging specific areas of the targeted tissue EXPERIMENTAL DESIGN: A previously imaged sample was selected and then cropped in different ways to show the potential effect of only imaging targeted areas.

RESULTS

By using a model sample, we were able to effectively show how selective imaging of samples can misinterpret tissue features and by changing the areas that are acquired, according to our new standard, an effective internal control can be introduced.

CONCLUSIONS AND CLINICAL RELEVANCE

Current IMS sampling convention relies on the assumption that sample preparation has been performed correctly. This prevents users from checking whether molecules have moved beyond borders of the tissue due to delocalization and consequentially products of improper sample preparation could be interpreted as biological features that are of critical importance when encountered in a visual diagnostic.

Advances in Lipidomics for Cancer Biomarkers Discovery

Lipids play critical functions in cellular survival, proliferation, interaction and death, since they are involved in chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions. These cellular processes are strongly related to carcinogenesis pathways, particularly to transformation, progression, and metastasis, suggesting the bioactive lipids are mediators of a number of oncogenic processes. The current review gives a synopsis of a lipidomic approach in tumor characterization; we provide an overview on potential lipid biomarkers in the oncology field and on the principal lipidomic methodologies applied. The novel lipidomic biomarkers are reviewed in an effort to underline their role in diagnosis, in prognostic characterization and in prediction of therapeutic outcomes. A lipidomic investigation through mass spectrometry highlights new insights on molecular mechanisms underlying cancer disease. This new understanding will promote clinical applications in drug discovery and personalized therapy.

Analysis of formalin-fixed, paraffin-embedded (FFPE) tissue via proteomic techniques and misconceptions of antigen retrieval

Since emerging in the late 19th century, formaldehyde fixation has become a standard method for preservation of tissues from clinical samples. The advantage of formaldehyde fixation is that fixed tissues can be stored at room temperature for decades without concern for degradation. This has led to the generation of huge tissue banks containing thousands of clinically significant samples. Here we review techniques for proteomic analysis of formalin-fixed, paraffin-embedded (FFPE) tissue samples with a specific focus on the methods used to extract and break formaldehyde crosslinks. We also discuss an error-of-interpretation associated with the technique known as “antigen retrieval.” We have discovered that this term has been mistakenly applied to two disparate molecular techniques; therefore, we argue that a terminology change is needed to ensure accurate reporting of experimental results. Finally, we suggest that more investigation is required to fully understand the process of formaldehyde fixation and its subsequent reversal.

Global changes of phospholipids identified by MALDI imaging mass spectrometry in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia; however, at the present time there is no disease-modifying drug for AD. There is increasing evidence supporting the role of lipid changes in the process of normal cognitive aging and in the etiology of age-related neurodegenerative diseases. AD is characterized by the presence of intraneuronal protein clusters and extracellular aggregates of β-amyloid (Aβ). Disrupted Aβ kinetics may activate intracellular signaling pathways, including tau hyperphosphorylation and proinflammatory pathways. We analyzed and visualized the lipid profiles of mouse brains using MALDI-TOF MS. Direct tissue analysis by MALDI-TOF imaging MS (IMS) can determine the relative abundance and spatial distribution of specific lipids in different tissues. We used 5XFAD mice that almost exclusively generate and rapidly accumulate massive cerebral levels of Aβ-42 (1). Our data showed changes in lipid distribution in the mouse frontal cortex, hippocampus, and subiculum, where Aβ plaques are first generated in AD. Our results suggest that MALDI-IMS is a powerful tool for analyzing the distribution of various phospholipids and that this application might provide novel insight into the prediction of disease.

A non-instrument-based method for the analysis of formalin-fixed paraffin-embedded human spinal cord via matrix-assisted laser desorption/ionisation imaging mass spectrometry

RATIONALE

This paper, in conjunction with a work published earlier this year by O'Rourke et al., aims to provide a comprehensive set of protocols for the analysis of formalin-fixed paraffin-embedded (FFPE) tissue via matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) in a low-cost and highly repeatable and robust way, thereby allowing other research teams to begin their own IMS-centered avenues of research.

METHODS

Samples of FFPE tissue were sectioned at 5 µm, water float mounted to specially prepared ITO glass slides and then dilipidated in a graded alcohol series. Tissue sections were then antigen retrieved under pressure in 20 mmol Tris-HCl (pH 8.8), coated with trypsin and digested O/N at 37°C. Samples were then sublimated with matrix to a final coverage of 0.2 mg/cm(2), recrystallised at 37°C with 50:50 acetonitrile (ACN)/0.1% trifluoroacetic acid (TFA) for 1 h and analysed with a MALDI TOF/TOF mass spectrometer.

RESULTS

Serial sections were imaged, revealing little to no variation with regards to image quality and corresponding spectra. We have also attempted to describe the processes that govern the various aspects of this protocol with respect to each step necessary to ensure reproducibility.

CONCLUSIONS

We are confident that this protocol in conjunction with the work published earlier by O'Rourke et al. provides the basis for a repeatable and robust protocol for the analysis of tissues from various sources via MALDI-IMS. The descriptions of key steps within allows for easy adoption of the protocol while allowing for desired modifications to be performed with minimal yet intuitive adjustment.

Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes

PURPOSE

To identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients.

METHODS

From the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell's C.

RESULTS

In the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (Prs166870 = 2.88 × 10(-7) and Prs10825036 = 3.54 × 10(-7) in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P discovery=1.18 × 10(-8) and P replication = 2.08 × 10(-5)) and HR- HRE2- subtypes (P discovery = 2.35 × 10(-4) and P replication = 2.60 × 10(-2)). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status.

CONCLUSION

Combined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.

Phosphatidylcholine alteration identified using MALDI imaging MS in HBV-infected mouse livers and virus-mediated regeneration defects

In this study, we investigated whether hepatitis B virus (HBV) causes the alteration of lipid metabolism and composition during acute infection and liver regeneration in a mouse model. The liver controls lipid biogenesis and bile acid homeostasis. Infection of HBV causes various liver diseases and impairs liver regeneration. As there are very few reports available in the literature on lipid alterations by HBV infection or HBV-mediated liver injury, we have analyzed phospholipids that have important roles in liver regeneration by using matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) in the livers of HBV model mice. As a result, we identified different phosphatidylcholines (PCs) showing significant changes in their composition as well as cationized ion adduct formation in HBV-infected mouse livers which are associated with virus-mediated regeneration defects. To find the factor of altered PCs, the expression kinetics of enzymes was also examined that regulate PC biosynthesis during liver regeneration. It is noteworthy that the expression of choline-phosphate cytidylyltransferase A (PCYT1A) was significantly delayed in wild type HBV-expressing livers. Moreover, the amount of hepatic total PC was also significantly decreased in wt HBV-expressing mice. These results suggest that infection of HBV alters the composition of PCs which may involve in HBV-mediated regeneration defects and liver disease.

Analysis of the phospholipid profile of metaphase II mouse oocytes undergoing vitrification

Oocyte freezing confers thermal and chemical stress upon the oolemma and various other intracellular structures due to the formation of ice crystals. The lipid profiles of oocytes and embryos are closely associated with both, the degrees of their membrane fluidity, as well as the degree of chilling and freezing injuries that may occur during cryopreservation. In spite of the importance of lipids in the process of cryopreservation, the phospholipid status in oocytes and embryos before and after freezing has not been investigated. In this study, we employed mass spectrometric analysis to examine if vitrification has an effect on the phospholipid profiles of mouse oocytes. Freshly prepared metaphase II mouse oocytes were vitrified using copper grids and stored in liquid nitrogen for 2 weeks. Fresh and vitrified-warmed oocytes were subjected to phospholipid extraction procedure. Mass spectrometric analyses revealed that multiple species of phospholipids are reduced in vitrified-warmed oocytes. LIFT analyses identified 31 underexpressed and 5 overexpressed phospholipids in vitrified mouse oocytes. The intensities of phosphatidylinositol (PI) {18∶2/16∶0} [M-H]- and phosphatidylglycerol (PG) {14∶0/18∶2} [M-H]- were decreased the most with fold changes of 30.5 and 19.1 in negative ion mode, respectively. Several sphingomyelins (SM) including SM {d38∶3} [M+H]+ and SM {d34∶0} [M+K]+ were decreased significantly in positive ion mode. Overall, the declining trend of multiple phospholipids demonstrates that vitrification has a marked effect on phospholipid profiles of oocytes. These results show that the identified phospholipids can be used as potential biomarkers of oocyte undergoing vitrification and will allow for the development of strategies to preserve phospholipids during oocyte cryopreservation.

Imaging mass spectrometry in papillary thyroid carcinoma for the identification and validation of biomarker proteins

Direct tissue imaging mass spectrometry (IMS) by matrix-assisted laser desorption ionization and time-of-flight (MALDI-TOF) mass spectrometry has become increasingly important in biology and medicine, because this technology can detect the relative abundance and spatial distribution of interesting proteins in tissues. Five thyroid cancer samples, along with normal tissue, were sliced and transferred onto conductive glass slides. After laser scanning by MALDI-TOF equipped with a smart beam laser, images were created for individual masses and proteins were classified at 200-µm spatial resolution. Based on the spatial distribution, region-specific proteins on a tumor lesion could be identified by protein extraction from tumor tissue and analysis using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using all the spectral data at each spot, various intensities of a specific peak were detected in the tumor and normal regions of the thyroid. Differences in the molecular weights of expressed proteins between tumor and normal regions were analyzed using unsupervised and supervised clustering. To verify the presence of discovered proteins through IMS, we identified ribosomal protein P2, which is specific for cancer. We have demonstrated the feasibility of IMS as a useful tool for the analysis of tissue sections, and identified the tumor-specific protein ribosomal protein P2.

Low C24-OH and C22-OH sulfatides in human renal cell carcinoma

Histopathologic diagnosis of renal cell carcinoma (RCC) may sometimes be difficult with small biopsy samples. We applied histology-directed matrix-assisted laser desorption/ionization mass spectrometry to RCC samples to evaluate whether and how lipid profiles are different between RCC and normal tissue. We evaluated 59 RCC samples and 24 adjacent normal tissue samples collected from patients who underwent surgery. Five peaks were significantly differently expressed (p < 10(-7)) between RCCs and adjacent normal tissue samples. C24-OH sulfatide (ST-OH {18:1/24:0}[M-H](-); m/z 906.7 in the negative ion mode) and C22-OH sulfatide (ST-OH {18:1/22:0}[M-H](-); m/z 878.6 in the negative ion mode) were most significantly underexpressed in RCC samples, compared with adjacent normal tissue samples. With 100 random training-to-test partitions within these samples, the median prediction accuracy (RCC vs. normal) ranged from 96.3% to 100% at p cutoff values for feature selection ranging from 0.001 to 10(-7). Two oncocytoma samples were predicted as normal tissue by five lipids that were differentially expressed between RCC and normal tissue at p < 10(-7). Clear-cell, papillary, and chromophobe RCCs were different in lipid profiles. Permutation p- values for 0.632+ bootstrap cross-validated misclassification rates were less than 0.05 for all the classifiers. Thus, lipid profiles differentiate RCC from normal tissue and may possibly classify the histology of RCC.

Graphene nanoflakes as an efficient ionizing matrix for MALDI-MS based lipidomics of cancer cells and cancer stem cells

This study demonstrates that graphene nanoflakes can be efficiently used as a successful, interference free matrix for matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS).

High-resolution imaging mass spectrometry reveals detailed spatial distribution of phosphatidylinositols in human breast cancer

High-resolution matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is an emerging application for lipid research that provides a comprehensive and detailed spatial distribution of ionized molecules. Recent lipidomic approach has identified several phospholipids and phosphatidylinositols (PIs) are accumulated in breast cancer tissues and are therefore novel biomarker candidates. Because their distribution and significance remain unclear, we investigated the precise spatial distribution of PIs in human breast cancer tissues using high-resolution MALDI IMS. We evaluated tissues from nine human breast cancers and one normal mammary gland by negative ion MALDI IMS at a resolution of 10 μm. We detected 10 PIs with different fatty acid compositions, and their proportions were remarkably variable in the malignant epithelial regions. High-resolution imaging enabled us to discriminate cancer cell clusters from the adjacent stromal tissue within epithelial regions; moreover, this technique revealed that several PIs were specifically localized to cancer cell clusters. These PIs were heterogeneously distributed within cancer cell clusters, allowing us to identify two different populations of cancer cells that predominantly expressed either PI(18:0/18:1) or PI(18:0/20:3). Tracing the expression level of PIs during cancer cell progression suggested that the latter population is associated with the invasion. Our study documents a novel model for phospholipid analysis of breast cancer tissues by using high-resolution MALDI IMS and identifies candidate PIs that can describe a specific phenotype of cancer cells.

A survey of useful salt additives in matrix-assisted laser desorption/ionization mass spectrometry and tandem mass spectrometry of lipids: introducing nitrates for improved analysis

RATIONALE

Matrix-assisted laser desorption/ionization (MALDI) is a powerful technique for the direct analysis of lipids in complex mixtures and thin tissue sections, making it an extremely attractive method for profiling lipids in health and disease. Lipids are readily detected as [M+H](+), [M+Na](+) and [M+K](+) ions in positive ion MALDI mass spectrometry (MS) experiments. This not only decreases sensitivity, but can also lead to overlapping m/z values of the various adducts of different lipids. Additives can be used to promote formation of a particular adduct, improving sensitivity, reducing spectral complexity and enhancing structural characterization in collision-induced dissociation (CID) experiments.

METHODS

Li(+), Na(+), K(+), Cs(+) and NH(4)(+) cations were considered as a range of salt types (acetates, chlorides and nitrates) incorporated into DHB matrix solutions at concentrations between 5 and 80 mM. The study was extended to evaluate the effect of these additives on CID experiments of a lipid standard, after optimization of collision energy parameters. Experiments were performed on a hybrid quadrupole time-of-flight (QqTOF) instrument.

RESULTS

The systematic evaluation of new and existing additives in MALDI-MS and MS/MS of lipids demonstrated the importance of additive cation and anion choice and concentration for tailoring spectral results.

CONCLUSIONS

The recommended choice of additive depends on the desired outcomes of the experiment to be performed (MS or MS/MS). Nitrates are found to be particularly useful additives for lipid analysis.