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

Lipid profiling of RON and DEK-dependent signaling in breast cancer guides discovery of gene networks predictive of poor outcomes

Recurrent and metastatic breast cancer is frequently treatment resistant. A wealth of evidence suggests that reprogrammed lipid metabolism supports cancer recurrence. Overexpression of the RON and DEK oncoproteins in breast cancer is associated with poor outcome. Both proteins promote cancer metastasis in laboratory models, but their influence on lipid metabolite levels remain unknown. To measure RON- and DEK-dependent steady-state lipid metabolite levels, a nuclear magnetic resonance (NMR)-based approach was utilized. The observed differences identified a lipid metabolism-related gene expression signature that is prognostic of overall survival (OS), distant metastasis-free survival (DMFS), post-progression survival (PPS), and recurrence-free survival (RFS) in patients with breast cancer. RON loss led to decreased cholesterol and sphingomyelin levels, whereas DEK loss increased total fatty acid levels and decreased free glycerol levels. Lipid-related genes were then queried to define a signature that predicts poor outcomes for patients with breast cancer patients. Taken together, RON and DEK differentially regulate lipid metabolism in a manner that predicts and may promote breast cancer metastasis and recurrence.

Tumor Lipid Signatures Are Descriptive of Acquisition of Therapy Resistance in an Endocrine-Related Breast Cancer Mouse Model

The lipid metabolism adaptations of estrogen and progesterone receptor-positive breast cancer tumors from a mouse syngeneic model are investigated in relation to differences across the transition from hormone-dependent (HD) to hormone-independent (HI) tumor growth and the acquisition of endocrine therapy (ET) resistance (HIR tumors). Results are articulated with reported polar metabolome results to complete a metabolic picture of the above transitions and suggest markers of tumor progression and aggressiveness. Untargeted nuclear magnetic resonance metabolomics was used to analyze tumor and mammary tissue lipid extracts. Tumor progression (HD-HI-HIR) was accompanied by increased nonesterified cholesterol forms and phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens) and decreased relative contents of triglycerides and fatty acids. Predominating fatty acids became shorter and more saturated on average. These results were consistent with gradually more activated cholesterol synthesis, β-oxidation, and phospholipid biosynthesis to sustain tumor growth, as well as an increase in cholesterol (possibly oxysterol) forms. Particular compound levels and ratios were identified as potential endocrine tumor HD-HI-HIR progression markers, supporting new hypotheses to explain acquired ET resistance.

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies

Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

Platelet-mimetic nano-sensor for combating postoperative recurrence and wound infection of triple-negative breast cancer

Tumor recurrence mainly triggered by tumor residual cells significantly contributes to mortality following breast tumor resection, and meanwhile post-surgical bacterial wound infections may accelerate tumor recurrence due to a series of infection-related complications. In this study, a nano-sensor system, Van-ICG@PLT, is constructed by a membrane camouflage and small molecule drug self-assembly strategy. This nano-sensor harnesses the innate tropism of platelets (PLT) to deliver vancomycin (Van) and indocyanine green (ICG) to surgical incisions, effectively eliminating both residual tumor cells and bacterial infections. Our findings demonstrate that Van-ICG@PLT preferentially accumulates at surgical wound. Under near-infrared (NIR) laser irradiation, Van-ICG@PLT exhibits significant cytotoxicity against 4T1 cells. Additionally, it is found to significantly promote ROS production thus inhibiting Staphylococcus aureus (S. aureus) growth, underscoring the synergistic benefits of phototherapy in combination with antibiotic treatment. In the 4T1 post-surgery recurrence mice model, Van-ICG@PLT is shown to efficiently ablate tumors in tumor-bearing mice (tumor inhibition rate of about 83%), and it demonstrates an excellent anti-infective effect in mice abscess models. Taken together, Van-ICG@PLT represents a promising paradigm in post-surgical adjuvant therapy (PAT). Its dual benefit in inhibiting cancer growth and promoting antibacterial activity makes Van-ICG@PLT a valuable addition to the existing arsenal of therapeutic options available for breast cancer patients.

Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview

Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.

Lipid biomarkers that reflect postoperative recurrence risk in lung cancer patients who smoke: a case-control study

BACKGROUND

The risk of postoperative recurrence is higher in lung cancer patients who smoke than non-smokers. However, objective evaluation of the postoperative recurrence risk is difficult using conventional pathological prognostic factors because of their lack of reproducibility. Consequently, novel objective biomarkers that reflect postoperative risk in lung cancer patients who smoke must be identified. Because cigarette smoking and oncogenesis alter lipid metabolism in lung tissue, we hypothesized that the lipid profiles in lung cancer tissues are influenced by cigarette smoking and can reflect the postoperative recurrence risk in smoking lung cancer patients. This study aimed to identify lipid biomarkers that reflect the smoking status and the postoperative recurrence risk.

METHODS

Primary tumor tissues of lung adenocarcinoma (ADC) (n = 26) and squamous cell carcinoma (SQCC) (n = 18) obtained from surgery were assigned to subgroups according to the patient's smoking status. The ADC cohort was divided into never smoker and smoker groups, while the SQCC cohort was divided into moderate smoker and heavy smoker groups. Extracted lipids from the tumor tissues were subjected to liquid chromatography-tandem mass spectrometry analysis. Lipids that were influenced by smoking status and reflected postoperative recurrence and pathological prognostic factors were screened.

RESULTS

Two and 12 lipid peaks in the ADC and SQCC cohorts showed a significant positive correlation with the Brinkman index, respectively. Among them, in the ADC cohort, a higher lipid level consisted of three phosphatidylcholine (PC) isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), was associated with a shorter recurrence free period (RFP) and a greater likelihoods of progressed T-factor (≥ pT2) and pleural invasion. In the SQCC cohort, a lower m/z 736.5276 level was associated with shorter RFP and greater likelihood of recurrence.

CONCLUSIONS

From our data, we propose three PC isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), and a lipid peak of m/z 736.5276 as novel candidate biomarkers for postoperative recurrence risk in lung ADC and SQCC patients who are smokers.

Lipidomics-based tissue heterogeneity in specimens of luminal breast cancer revealed by clustering analysis of mass spectrometry imaging: A preliminary study

Cancer tissues reflect a greater number of pathological characteristics of cancer compared to cancer cells, so the evaluation of cancer tissues can be effective in determining cancer treatment strategies. Mass spectrometry imaging (MSI) can evaluate cancer tissues and even identify molecules while preserving spatial information. Cluster analysis of cancer tissues' MSI data is currently used to evaluate the phenotype heterogeneity of the tissues. Interestingly, it has been reported that phenotype heterogeneity does not always coincide with genotype heterogeneity in HER2-positive breast cancer. We thus investigated the phenotype heterogeneity of luminal breast cancer, which is generally known to have few gene mutations. As a result, we identified phenotype heterogeneity based on lipidomics in luminal breast cancer tissues. Clusters were composed of phosphatidylcholine (PC), triglycerides (TG), phosphatidylethanolamine, sphingomyelin, and ceramide. It was found that mainly the proportion of PC and TG correlated with the proportion of cancer and stroma on HE images. Furthermore, the number of carbons in these lipid class varied from cluster to cluster. This was consistent with the fact that enzymes that synthesize long-chain fatty acids are increased through cancer metabolism. It was then thought that clusters containing PCs with high carbon counts might reflect high malignancy. These results indicate that lipidomics-based phenotype heterogeneity could potentially be used to classify cancer for which genetic analysis alone is insufficient for classification.

Lipidomic and Membrane Mechanical Signatures in Triple-Negative Breast Cancer: Scope for Membrane-Based Theranostics

Triple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer associated with poor prognosis, higher grade, and a high rate of metastatic occurrence. Limited therapeutic interventions and the compounding issue of drug resistance in triple-negative breast cancer warrants the discovery of novel therapeutic targets and diagnostic modules. To this view, in addition to proteins, lipids also regulate cellular functions via the formation of membranes that modulate membrane protein function, diffusion, and their localization; thus, orchestrating signaling hot spots enriched in specific lipids/proteins on cell membranes. Lipid deregulation in cancer leads to reprogramming of the membrane dynamics and functions impacting cell proliferation, metabolism, and metastasis, providing exciting starting points for developing lipid-based approaches for treating TNBC. In this review, we provide a detailed account of specific lipidic changes in breast cancer, link the altered lipidome with membrane structure and mechanical properties, and describe how these are linked to subsequent downstream functions implicit in cancer progression, metastasis, and chemoresistance. At the fundamental level, we discuss how the lipid-centric findings in TNBC are providing cues for developing lipid-inspired theranostic strategies while bridging existing gaps in our understanding of the functional involvement of lipid membranes in cancer.

Endocrine Therapy-Resistant Breast Cancer Cells Are More Sensitive to Ceramide Kinase Inhibition and Elevated Ceramide Levels Than Therapy-Sensitive Breast Cancer Cells

Simple Summary

Endocrine therapy (ET) resistance is a major problem in estrogen receptor-positive breast cancer patients. Since there have been few lipidomic studies in ET resistance and sphingolipids are heavily implicated in multidrug-resistant and chemotherapy-resistant cancers, we aimed to investigate the sphingolipidome of tamoxifen-resistant breast cancer cells in search of a unique sphingolipid profile that can potentially be exploited therapeutically. We found that ET-resistant breast cancer cells maintain a lower level of ceramides for their survival. In order to achieve this, they are dependent on ceramide kinase (CERK), the activity of which helps maintain low endogenous ceramide levels, therefore promoting tamoxifen-resistant cell survival. Targeting CERK can therefore represent an opportunity to target therapy-resistant breast tumors and improve the patient outcome for women with ET-resistant disease.

Abstract

ET resistance is a critical problem for estrogen receptor-positive (ER+) breast cancer. In this study, we have investigated how alterations in sphingolipids promote cell survival in ET-resistant breast cancer. We have performed LC-MS-based targeted sphingolipidomics of tamoxifen-sensitive and -resistant MCF-7 breast cancer cell lines. Follow-up studies included treatments of cell lines and patient-derived xenograft organoids (PDxO) with small molecule inhibitors; cytometric analyses to measure cell death, proliferation, and apoptosis; siRNA-mediated knockdown; RT-qPCR and Western blot for gene and protein expression; targeted lipid analysis; and lipid addback experiments. We found that tamoxifen-resistant cells have lower levels of ceramides and hexosylceramides compared to their tamoxifen-sensitive counterpart. Upon perturbing the sphingolipid pathway with small molecule inhibitors of key enzymes, we identified that CERK is essential for tamoxifen-resistant breast cancer cell survival, as well as a fulvestrant-resistant PDxO. CERK inhibition induces ceramide-mediated cell death in tamoxifen-resistant cells. Ceramide-1-phosphate (C1P) partially reverses CERK inhibition-induced cell death in tamoxifen-resistant cells, likely through lowering endogenous ceramide levels. Our findings suggest that ET-resistant breast cancer cells maintain lower ceramide levels as an essential pro-survival mechanism. Consequently, ET-resistant breast cancer models have a unique dependence on CERK as its activity can inhibit de novo ceramide production.

Tissue sample preparations for preclinical research determined by molecular imaging mass spectrometry using MALDI

Matrix-assisted laser desorption/ionization - imaging mass spectrometry is an alternative tool, which can be implemented in order to obtain and visualize the "omic" signature of tissue samples. Its application to clinical study enables simultaneous imaging-based morphological observations and mass spectrometry analysis. Application of fully informative material like tissue, allows to obtain the complex and unique profile of analyzed samples. This knowledge leads to diagnose disease, study the mechanism of cancer development, select the potential biomarkers as well as correlating obtained image with prognosis. Nevertheless, it is worth to notice that this method is found to be objective but the result of analysis is mainly influenced by the sample preparation protocol, included collection of biological material, its preservation and processing. However, application of this approach requires a special sample preparation procedure. The main goal of the study is to present the current knowledge on the clinical application of matrix-assisted laser desorption/ionization - imaging mass spectrometry in cancer research, with particular emphasis on the sample preparation step. For this purpose, several protocols based on cryosections and formalin-fixed paraffin embedded tissue were compiled and compared, taking into account the measured metabolites of potential diagnostic importance for a given type of cancer. This article is protected by copyright. All rights reserved.

Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients

Malignant cells differ from benign ones in their metabolome and it is largely unknown whether this difference is reflected in the metabolic profile of their microvesicles (MV), which are secreted into the blood of cancer patients. Here, they are present together with MV from the various blood and endothelial cells. Harvesting MV from 78 breast cancer patients (BC) and 30 controls, we characterized the whole blood MV metabolome using targeted and untargeted mass spectrometry. Especially (lyso)-phosphatidylcholines and sphingomyelins were detected in a relevant abundance. Eight metabolites showed a significant discriminatory power between BC and controls. High concentrations of lysoPCaC26:0 and PCaaC38:5 were associated with shorter overall survival. Comparing BC subtype-specific metabolome profiles, 24 metabolites were differentially expressed between luminal A and luminal B. Pathway analysis revealed alterations in the glycerophospholipid metabolism for the whole cancer cohort and in the ether lipid metabolism for the molecular subtype luminal B. Although this mixture of blood-derived MV contains only a minor number of tumor MV, a combination of metabolites was identified that distinguished between BC and controls as well as between molecular subtypes, and was predictive for overall survival. This suggests that these metabolites represent promising biomarkers and, moreover, that they may be functionally relevant for tumor progression.

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.

Decreased sphingomyelin (t34:1) is a candidate predictor for lung squamous cell carcinoma recurrence after radical surgery: a case-control study

Background

To reduce disease recurrence after radical surgery for lung squamous cell carcinomas (SQCCs), accurate prediction of recurrent high-risk patients is required for efficient patient selection for adjuvant chemotherapy. Because treatment modalities for recurrent lung SQCCs are scarce compared to lung adenocarcinomas (ADCs), accurately selecting lung SQCC patients for adjuvant chemotherapy after radical surgery is highly important. Predicting lung cancer recurrence with high objectivity is difficult with conventional histopathological prognostic factors; therefore, identification of a novel predictor is expected to be highly beneficial. Lipid metabolism alterations in cancers are known to contribute to cancer progression. Previously, we found that increased sphingomyelin (SM)(d35:1) in lung ADCs is a candidate for an objective recurrence predictor. However, no lipid predictors for lung SQCC recurrence have been identified to date. This study aims to identify candidate lipid predictors for lung SQCC recurrence after radical surgery.

Methods

Recurrent (n = 5) and non-recurrent (n = 6) cases of lung SQCC patients who underwent radical surgery were assigned to recurrent and non-recurrent groups, respectively. Extracted lipids from frozen tissue samples of primary lung SQCC were analyzed by liquid chromatography-tandem mass spectrometry. Candidate lipid predictors were screened by comparing the relative expression levels between the recurrent and non-recurrent groups. To compare lipidomic characteristics associated with recurrent SQCCs and ADCs, a meta-analysis combining SQCC (n = 11) and ADC (n = 20) cohorts was conducted.

Results

Among 1745 screened lipid species, five species were decreased (≤ 0.5 fold change; P < 0.05) and one was increased (≥ 2 fold change; P < 0.05) in the recurrent group. Among the six candidates, the top three final candidates (selected by AUC assessment) were all decreased SM(t34:1) species, showing strong performance in recurrence prediction that is equivalent to that of histopathological prognostic factors. Meta-analysis indicated that decreases in a limited number of SM species were observed in the SQCC cohort as a lipidomic characteristic associated with recurrence, in contrast, significant increases in a broad range of lipids (including SM species) were observed in the ADC cohort.

Conclusion

We identified decreased SM(t34:1) as a novel candidate predictor for lung SQCC recurrence. Lung SQCCs and ADCs have opposite lipidomic characteristics concerning for recurrence risk.

Trial registration

This retrospective study was registered at the UMIN Clinical Trial Registry (UMIN000039202) on January 21, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08948-5.

Investigation of the lipidomic changes in differentiated glioblastoma cells after drug treatment using MALDI-MS

Lipids differences between tumor and normal tissue have been proved to be of diagnostic and therapeutic significance. The research of lipidomics in tumor is more and more important. Mass spectrometry like matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) can be more convenient and informative for lipids researching in biological and clinical researches. Most of malignant tumors like glioblastoma are characterized by incomplete differentiation, so differentiation therapy has made important progress in tumor treatment. Lipid profiles changes after therapy are worthy investigating. In our study, glioblastoma cell line U87-MG cells were treated by inducers of sodium phenylbutyrate (SPB) and all-trans retinoic acid (ATRA). The changes in lipids on cell membrane were profiled by MALDI-MS. The differentiation degree was assessed by cell proliferation, cell cycle, morphology and protein expression before MALDI-MS analysis. Comparing the inducer treated and untreated U87-MG cells, reduced proliferation rate, blocked cell cycle, benign nucleus morphology and changed expression of protein CD133 and glial fibrillary acidic protein (GFAP), were found after drug treatment. Moreover, the lipids of cell membrane presented distinguished differences in the drug treated cells. Most of the glycerophosphocholines (PC) with an increasing abundance are unsaturated PCs (PC (38:1), 816 m/z; PC (36:1), 788 m/z; PC (31:1), 725 m/z), and those decreasing are saturated PCs (PC (32:0), 734 m/z). These results provide the lipidomic differentiation which may be a significant guidance for evaluating the therapeutic effect of tumor therapy.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Mass spectrometry-based phospholipid imaging: methods and findings

Introduction: Imaging is a technique used for direct visualization of the internal structure or distribution of biomolecules of a living system in a two-dimensional or three-dimensional fashion. Phospholipids are important structural components of biological membranes and have been reported to be associated with various human diseases. Therefore, the visualization of phospholipids is crucial to understand the underlying mechanism of cellular and molecular processes in normal and diseased conditions. Areas covered: Mass spectrometry imaging (MSI) has enabled the label-free imaging of individual phospholipids in biological tissues and cells. The commonly used MSI techniques include matrix-assisted laser desorption ionization-MSI (MALDI-MSI), desorption electrospray ionization-MSI (DESI-MSI), and secondary ion mass spectrometry (SIMS) imaging. This special report described those methods, summarized the findings, and discussed the future development for the imaging of phospholipids. Expert opinion: Phospholipids imaging in complex biological samples has been significantly benefited from the development of MSI methods. In MALDI-MSI, novel matrix that produces homogenous crystals exclusively with polar lipids is important for phospholipids imaging with greater efficiency and higher spatial resolution. DESI-MSI has the potential of live imaging of the biological surface while SIMS is expected to image at the subcellular level in the near future.

Proteomic identification of tumor- and metastasis-associated galectin-1 in claudin-low breast cancer

BACKGROUND

Metastasis and mortality remain high among breast cancer patients with the claudin-low subtype because these tumors are aggressive, chemoresistant, and lack targeted therapies. Our objective was to utilize discovery-based proteomics to identify proteins associated with claudin-low primary and metastatic tumors to gain insight into pathways and mechanisms of tumor progression.

METHODS

We used nano-LC-MS/MS proteomics to analyze orthotopic and metastatic tumors from the syngeneic murine T11 tumor model, which displays gene expression profiles mirroring human claudin-low tumors. Galectin-1 identity, expression and spatial distribution were investigated by biochemical and immunochemical methods and MALDI/IMS. RNA seq data from mouse and human tumors in our study and publicly available microarray data were analyzed for differential galectin-1 expression across breast cancer subtypes.

RESULTS

Galectin-1, an N-acetyllactosamine-binding protein, exhibited the highest sequence coverage and high abundance rank order among nano-LC-MS/MS-identified proteins shared by T11 claudin-low tumors but not normal tissue. Label-free quantitation, Western immunoblot and ELISA confirmed galectin-1 identity and significant differential expression. MALDI/IMS spatial mapping and immunohistochemistry detected galectin-1 in T11 metastatic lung foci. Immunohistochemistry of human claudin-low tumors demonstrated intermediate-to-high intensity galectin-1 staining of tumor and stroma. Gene expression analysis of mouse and human tumors found the highest galectin-1 levels in the claudin-low breast cancer subtype.

CONCLUSIONS

Proteomics and genomics reveal high expression of galectin-1 protein and RNA in primary and metastatic claudin-low breast cancer.

GENERAL SIGNIFICANCE

This work endorses proteomic approaches in cancer research and supports further investigations of the function and significance of galectin-1 overexpression in claudin-low tumor progression.

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.

The lysophospholipase D enzyme Gdpd3 is required to maintain chronic myelogenous leukaemia stem cells

Although advanced lipidomics technology facilitates quantitation of intracellular lipid components, little is known about the regulation of lipid metabolism in cancer cells. Here, we show that disruption of the Gdpd3 gene encoding a lysophospholipase D enzyme significantly decreased self-renewal capacity in murine chronic myelogenous leukaemia (CML) stem cells in vivo. Sophisticated lipidomics analyses revealed that Gdpd3 deficiency reduced levels of certain lysophosphatidic acids (LPAs) and lipid mediators in CML cells. Loss of Gdpd3 also activated AKT/mTORC1 signalling and cell cycle progression while suppressing Foxo3a/β-catenin interaction within CML stem cell nuclei. Strikingly, CML stem cells carrying a hypomorphic mutation of Lgr4/Gpr48, which encodes a leucine-rich repeat (LRR)-containing G-protein coupled receptor (GPCR) acting downstream of Gdpd3, displayed inadequate disease-initiating capacity in vivo. Our data showing that lysophospholipid metabolism is required for CML stem cell maintenance in vivo establish a new, biologically significant mechanism of cancer recurrence that is independent of oncogene addiction.

How lipid metabolism can affect cancer recurrence is still unclear. Here, the authors show that the lysophospholipase D Gdpd3 maintains self-renewal capacity of CML stem cells by regulating the quiescence, and AKT/mTORC1 and Foxo3a/β-catenin signalling in an oncogene-independent manner.

Sphingomyelin(d35:1) as a novel predictor for lung adenocarcinoma recurrence after a radical surgery: a case-control study

Background

To improve the postoperative prognosis of patients with lung cancer, predicting the recurrence high-risk patients is needed for the efficient application of adjuvant chemotherapy. However, predicting lung cancer recurrence after a radical surgery is difficult even with conventional histopathological prognostic factors, thereby a novel predictor should be identified. As lipid metabolism alterations are known to contribute to cancer progression, we hypothesized that lung adenocarcinomas with high recurrence risk contain candidate lipid predictors. This study aimed to identify candidate lipid predictors for the recurrence of lung adenocarcinoma after a radical surgery.

Methods

Frozen tissue samples of primary lung adenocarcinoma obtained from patients who underwent a radical surgery were retrospectively reviewed. Recurrent and non-recurrent cases were assigned to recurrent (n = 10) and non-recurrent (n = 10) groups, respectively. Extracted lipids from frozen tissue samples were subjected to liquid chromatography-tandem mass spectrometry analysis. The average total lipid levels of the non-recurrent and recurrent groups were compared. Candidate predictors were screened by comparing the folding change and P-value of t-test in each lipid species between the recurrent and non-recurrent groups.

Results

The average total lipid level of the recurrent group was 1.65 times higher than that of the non-recurrent group (P < 0.05). A total of 203 lipid species were increased (folding change, ≥2; P < 0.05) and 4 lipid species were decreased (folding change, ≤0.5; P < 0.05) in the recurrent group. Among these candidates, increased sphingomyelin (SM)(d35:1) in the recurrent group was the most prominent candidate predictor, showing high performance of recurrence prediction (AUC, 9.1; sensitivity, 1.0; specificity, 0.8; accuracy, 0.9).

Conclusion

We propose SM(d35:1) as a novel candidate predictor for lung adenocarcinoma recurrence. Our finding can contribute to precise recurrence prediction and qualified postoperative therapeutic strategy for lung adenocarcinomas.

Trial registration

This retrospective study was registered at the UMIN Clinical Trial Registry (UMIN000039202) on 21st January 2020.

Distribution and clinical relevance of phospholipids in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common liver cancer and featured with prominent disparity in incidence and mortality rate between male and female. It remains unclear whether alterations of phospholipids (PL) in hepatic tissues contribute to the pathogenesis, progression, and disparity of HCC.

Methods

Using electrospray ionization mass spectrometry (ESI–MS), PL profiles including 320 individual phospholipid species in 13 PL classes were determined in paired samples from HCC and adjacent benign hepatic tissues (BHT).

Results

(1) Concentrations of PLs in most of individual species, in subgroups and in total were decreased in HCC than in BHT in all studied population; (2) the number of individual PL species significantly different between HCC and BHT, and the number of PLs in six subgroups and in total decreased in HCC were more in male population than in female population; (3) panels of PL parameters (more in male population than in female population) were identified as biomarkers in differentiation of HCC from BHT, and in the prediction of pathological grade and clinical stage of HCC with high sensitivity, specificity, and accuracy.

Conclusion

It is concluded that alterations of PLs in hepatic tissues play important roles in pathogenesis, progression, and gender disparity of HCC.

Electronic supplementary material

The online version of this article (10.1007/s12072-020-10056-8) contains supplementary material, which is available to authorized users.

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).

Identification of novel biomarkers of hepatocellular carcinoma by high-definition mass spectrometry: Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry and desorption electrospray ionization mass spectrometry imaging

RATIONALE

Hepatocellular carcinoma (HCC) is a highly malignant disease for which the development of prospective or prognostic biomarkers is urgently required. Although metabolomics is widely used for biomarker discovery, there are some bottlenecks regarding the comprehensiveness of detected features, reproducibility of methods, and identification of metabolites. In addition, information on localization of metabolites in tumor tissue is needed for functional analysis. Here, we developed a wide-polarity global metabolomics (G-Met) method, identified HCC biomarkers in human liver samples by high-definition mass spectrometry (HDMS), and demonstrated localization in cryosections using desorption electrospray ionization MS imaging (DESI-MSI) analysis.

METHODS

Metabolic profiling of tumor (n = 38) and nontumor (n = 72) regions in human livers of HCC was performed by an ultrahigh-performance liquid chromatography quadrupole time-of-flight MS (UHPLC/QTOFMS) instrument equipped with a mixed-mode column. The HCC biomarker candidates were extracted by multivariate analyses and identified by matching values of the collision cross section and their fragment ions on the mass spectra obtained by HDMS. Cryosections of HCC livers, which included both tumor and nontumor regions, were analyzed by DESI-MSI.

RESULTS

From the multivariate analysis, m/z 904.83 and m/z 874.79 were significantly high and low, respectively, in tumor samples and were identified as triglyceride (TG) 16:0/18:1(9Z)/20:1(11Z) and TG 16:0/18:1(9Z)/18:2(9Z,12Z) using the synthetic compounds. The TGs were clearly localized in the tumor or nontumor areas of the cryosection.

CONCLUSIONS

Novel biomarkers for HCC were identified by a comprehensive and reproducible G-Met method with HDMS using a mixed-mode column. The combination analysis of UHPLC/QTOFMS and DESI-MSI revealed that the different molecular species of TGs were associated with tumor distribution and were useful for characterizing the progression of tumor cells and discovering prospective biomarkers.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.

Dietary Intake of Green Nut Oil or DHA Ameliorates DHA Distribution in the Brain of a Mouse Model of Dementia Accompanied by Memory Recovery

Docosahexaenoic acid (DHA), an omega-3 polyunsaturated fatty acid, has significant healthbenefits. Previous studies reported decreased levels of DHA and DHA-containing phosphatidylcholines inthe brain of animals suffering from Alzheimer's disease, the most common type of dementia; furthermore,DHA supplementation has been found to improve brain DHA levels and memory efficiency in dementia. Oilextracted from the seeds of Plukenetia volubilis (green nut oil; GNO) is also expected to have DHA like effectsas it contains approximately 50% α-linolenic acid, a precursor of DHA. Despite this, changes in the spatialdistribution of DHA in the brain of animals with dementia following GNO or DHA supplementation remainunexplored. In this study, desorption electrospray ionization imaging mass spectrometry (DESI-IMS) wasapplied to observe the effects of GNO or DHA supplementation upon the distribution of DHA in the brain ofmale senescence-accelerated mouse-prone 8 (SAMP8) mice, a mouse model of dementia. DESI-IMS revealedthat brain DHA distribution increased 1.85-fold and 3.67-fold in GNO-fed and DHA-fed SAMP8 mice,respectively, compared to corn oil-fed SAMP8 mice. Memory efficiency in SAMP8 mice was also improvedby GNO or DHA supplementation. In summary, this study suggests the possibility of GNO or DHAsupplementation for the prevention of dementia.

Analysis of potential anti-aging beverage Pru, a traditional Cuban refreshment, by desorption electrospray ionization-mass spectrometry and FTICR tandem mass spectrometry

Aging has been established as a major risk factor for prevalent diseases and hence, the development of anti-aging medicines is of great importance. Recently, herbal fermented beverages have emerged as a promising source of potential anti-aging drug. Pru, a traditional Cuban refreshment produced by decoction and fermentation of multispecies plants with sugar, has been consumed for many years and is claimed to have multiple medicinal properties. Besides the traditional method, Pru is also manufactured industrially. The present study analyzed the major components of both traditional Pru (TP) and industrial Pru (IP) to reveal their potential application in promoting the health span. We performed desorption electrospray ionization-mass spectrometry (DESI-MS) and acquired mass spectra by scanning over the 50–1200 m/z range in both positive and negative ion modes. Fourier transform ion cyclotron resonance (FTICR) tandem mass spectrometry (MS/MS) was performed for validating the compound assignments. Three important compounds were identified by comparing the MS and MS/MS spectra with reported literature and the online database. One of the identified compounds, gluconic acid, was found to be the most abundant shared metabolite between TP and IP whereas the other two compounds, magnoflorine and levan were exclusively detected in TP. The present study is the first report of component profiling in Cuban traditional and industrial Pru using DESI-MS and FTICR MS/MS, and reveals the potential application of Pru as a health-promoting agent.

Down-regulated HSDL2 expression suppresses cell proliferation and promotes apoptosis in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Hydroxysteroid dehydrogenase like 2 (HSDL2) can regulate lipid metabolism and take part in cell proliferation. The purpose of the present study was to explore functional role of HSDL2 gene in PTC. The expression of HSDL2 protein in PTC tissues was estimated using immunohistochemistry analysis (IHC). HSDL2 mRNA level was detected through quantitative real-time polymerase chain reaction (qRT-PCR). Effects of HSDL2 gene on cell proliferation and apoptosis were assessed using the shRNA method for both in vitro and in vivo experiments. Potential target genes of HSDL2 were determined via bioinformatics analyses and Western blotting. HSDL2 was up-regulated in PTC tissues and cell lines compared with the controls (all P<0.05). Inhibiting HSDL expression could suppress PTC cell proliferation and cycle, and promote apoptosis in vitro. In vivo, the knockdown of HSDL2 gene could significantly suppress tumor growth (all P<0.05). Furthermore, AKT3, NFATc2 and PPP3CA genes might be potential targets of HSDL2 in PTC. HSDL2 expression was increased in PTC tissues and cells, which could promote tumor progression in vitro and in vivo.

Discovery of lipid biomarkers correlated with disease progression in clear cell renal cell carcinoma using desorption electrospray ionization imaging mass spectrometry

Clear cell renal cell carcinoma (ccRCC) often results in recurrence or metastasis, and there are only a few clinically effective biomarkers for early diagnosis and personalized therapy. Metabolic changes have been widely studied using mass spectrometry (MS) of tissue lysates to identify novel biomarkers. Our objective was to identify lipid biomarkers that can predict disease progression in ccRCC by a tissue-based approach. We retrospectively investigated lipid molecules in cancerous tissues and normal renal cortex tissues obtained from patients with ccRCC (n = 47) using desorption electrospray ionization imaging mass spectrometry (DESI-IMS). We selected eight candidate lipid biomarkers showing higher signal intensity in cancerous than in normal tissues, with a clear distinction of the tissue type based on the images. Of these candidates, low maximum intensity ratio (cancerous/normal) values of ions of oleic acid, m/z 389.2, and 391.3 significantly correlated with shorter progression-free survival compared with high maximum intensity ratio values (P = 0.011, P = 0.022, and P < 0.001, respectively). This study identified novel lipid molecules contributing to the prediction of disease progression in ccRCC using DESI-IMS. Our findings on lipid storage may provide a new diagnostic or therapeutic strategy for targeting cancer cell metabolism.

Integrated landscape of copy number variation and RNA expression associated with nodal metastasis in invasive ductal breast carcinoma

Background

Lymph node metastasis (NM) in breast cancer is a clinical predictor of patient outcomes, but how its genetic underpinnings contribute to aggressive phenotypes is unclear. Our objective was to create the first landscape analysis of CNV-associated NM in ductal breast cancer. To assess the role of copy number variations (CNVs) in NM, we compared CNVs and/or associated mRNA expression in primary tumors of patients with NM to those without metastasis.

Results

We found CNV loss in chromosomes 1, 3, 9, 18, and 19 and gains in chromosomes 5, 8, 12, 14, 16-17, and 20 that were associated with NM and replicated in both databases. In primary tumors, per-gene CNVs associated with NM were ten times more frequent than mRNA expression; however, there were few CNV-driven changes in mRNA expression that differed by nodal status. Overlapping regions of CNV changes and mRNA expression were evident for the CTAGE5 gene. In 8q12, 11q13-14, 20q1, and 17q14-24 regions, there were gene-specific gains in CNV-driven mRNA expression associated with NM.

Methods

Data on CNV and mRNA expression from the TCGA and the METABRIC consortium of breast ductal carcinoma were utilized to identify CNV-based features associated with NM. Within each dataset, associations were compared across omic platforms to identify CNV-driven variations in gene expression. Only replications across both datasets were considered as determinants of NM.

Conclusions

Gains in CTAGE5, NDUFC2, EIF4EBP1, and PSCA genes and their expression may aid in early diagnosis of metastatic breast carcinoma and have potential as therapeutic targets.

Visualizing phosphatidylcholine via mass spectrometry imaging: relevance to human health

INTRODUCTION

Mass spectrometry imaging (MSI) techniques are nowadays widely used to obtain spatially resolved metabolite information from biological tissues. Since (phospho)lipids occur in all animal tissues and are very sensitively detectable, they are often in the focus of such studies. This particularly applies for phosphatidylcholines (PC) which are very sensitively detectable as positive ions due to the permanent positive charge of their choline headgroup. Areas covered: After a short introduction of lipid species occurring in biological systems and approaches normally used to obtain spatially resolved mass spectra (with the focus on matrix-assisted laser desorption/ionization coupled to time-of-flight (MALDI-TOF) MSI) a survey will be given which diseases have so far been characterized by changes of the PC composition. Expert commentary: Since PC species are very sensitively detectable by MS, sensitivity is not a major issue. However, spatial resolution is still limited and cellular dimensions can be hardly resolved by MALDI-TOF MSI, which is a critical point of the available approaches. Due to lacks of reproducibility and standardization further development is required.

Selective delivery of laser energy to ester bonds of triacylglycerol in lipid droplets of adipocyte using a quantum cascade laser

The recent development of quantum cascade lasers (QCLs) has facilitated the irradiation of a mid-infrared laser beam that is specifically absorbed by a target molecular bond. Aiming for a selective delivery of laser energy to a specific absorption at 1,738 cm^-1 by the ester bonds of triacylglycerol (TAG), a QCL beam with a wavenumber of 1,710 cm^-1 was irradiated to 3T3-L1 adipocytes and preadipocytes. Neutral red staining, and FITC-labeled annexin V and ethidium homodimer-III assays revealed the occurrence of adipocyte-specific cell death 24 h after QCL irradiation. The selective delivery of laser energy to endogenous molecules can affect biological processes in a living organism.

Novel Strategies on Personalized Medicine for Breast Cancer Treatment: An Update

Breast cancer is the most common cancer type among women worldwide. With breast cancer patients and survivors being reported to experience a repertoire of symptoms that are detrimental to their quality of life, the development of breast cancer treatment strategies that are effective with minimal side effects is therefore required. Personalized medicine, the treatment process that is tailored to the individual needs of each patient, is recently gaining increasing attention for its prospect in the development of effective cancer treatment regimens. Indeed, recent studies have identified a number of genes and molecules that may be used as biomarkers for predicting drug response and severity of common cancer-associated symptoms. These would provide useful clues not only for the determination of the optimal drug choice/dosage to be used in personalized treatment, but also for the identification of gene or molecular targets for the development of novel symptom management strategies, which ultimately would lead to the development of more personalized therapies for effective cancer treatment. In this article, recent studies that would provide potential new options for personalized therapies for breast cancer patients and survivors are reviewed. We suggest novel strategies, including the optimization of drug choice/dosage and the identification of genetic changes that are associated with cancer symptom occurrence and severity, which may help in enhancing the effectiveness and acceptability of the currently available cancer therapies.