Potential plasma lipid biomarkers in early-stage breast cancer

Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer

BACKGROUND

Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data.

METHODS

Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively.

RESULTS

The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance.

CONCLUSION

We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Untargeted lipidomic analysis and network pharmacology for parthenolide treated papillary thyroid carcinoma cells

BACKGROUND

With fast rising incidence, papillary thyroid carcinoma (PTC) is the most common head and neck cancer. Parthenolide, isolated from traditional Chinese medicine, inhibits various cancer cells, including PTC cells. The aim was to investigate the lipid profile and lipid changes of PTC cells when treated with parthenolide.

METHODS

Comprehensive lipidomic analysis of parthenolide treated PTC cells was conducted using a UHPLC/Q-TOF-MS platform, and the changed lipid profile and specific altered lipid species were explored. Network pharmacology and molecular docking were performed to show the associations among parthenolide, changed lipid species, and potential target genes.

RESULTS

With high stability and reproducibility, a total of 34 lipid classes and 1736 lipid species were identified. Lipid class analysis indicated that parthenolide treated PTC cells contained higher levels of fatty acid (FA), cholesterol ester (ChE), simple glc series 3 (CerG3) and lysophosphatidylglycerol (LPG), lower levels of zymosterol (ZyE) and Monogalactosyldiacylglycerol (MGDG) than controlled ones, but with no significant differences. Several specific lipid species were changed significantly in PTC cells treated by parthenolide, including the increasing of phosphatidylcholine (PC) (12:0e/16:0), PC (18:0/20:4), CerG3 (d18:1/24:1), lysophosphatidylethanolamine (LPE) (18:0), phosphatidylinositol (PI) (19:0/20:4), lysophosphatidylcholine (LPC) (28:0), ChE (22:6), and the decreasing of phosphatidylethanolamine (PE) (16:1/17:0), PC (34:1) and PC (16:0p/18:0). Four key targets (PLA2G4A, LCAT, LRAT, and PLA2G2A) were discovered when combining network pharmacology and lipidomics. Among them, PLA2G2A and PLA2G4A were able to bind with parthenolide confirmed by molecular docking.

CONCLUSIONS

The changed lipid profile and several significantly altered lipid species of parthenolide treated PTC cells were observed. These altered lipid species, such as PC (34:1), and PC (16:0p/18:0), may be involved in the antitumor mechanisms of parthenolide. PLA2G2A and PLA2G4A may play key roles when parthenolide treated PTC cells.

Untargeted serum metabolomics analysis of Trichinella spiralis-infected mouse

BACKGROUND

Trichinellosis, caused by a parasitic nematode of the genus Trichinella, is a zoonosis that affects people worldwide. After ingesting raw meat containing Trichinella spp. larvae, patients show signs of myalgia, headaches, and facial and periorbital edema, and severe cases may die from myocarditis and heart failure. The molecular mechanisms of trichinellosis are unclear, and the sensitivity of the diagnostic methods used for this disease are unsatisfactory. Metabolomics is an excellent tool for studying disease progression and biomarkers; however, it has never been applied to trichinellosis. We aimed to elucidate the impacts of Trichinella infection on the host body and identify potential biomarkers using metabolomics.

METHODOLOGY/PRINCIPAL FINDINGS

Mice were infected with T. spiralis larvae, and sera were collected before and 2, 4, and 8 weeks after infection. Metabolites in the sera were extracted and identified using untargeted mass spectrometry. Metabolomic data were annotated via the XCMS online platform and analyzed with Metaboanalyst version 5.0. A total of 10,221 metabolomic features were identified, and the levels of 566, 330, and 418 features were significantly changed at 2-, 4-, and 8-weeks post-infection, respectively. The altered metabolites were used for further pathway analysis and biomarker selection. A major pathway affected by Trichinella infection was glycerophospholipid metabolism, and glycerophospholipids comprised the main metabolite class identified. Receiver operating characteristic revealed 244 molecules with diagnostic power for trichinellosis, with phosphatidylserines (PS) being the primary lipid class. Some lipid molecules, e.g., PS (18:0/19:0)[U] and PA (O-16:0/21:0), were not present in metabolome databases of humans and mice, thus they may have been secreted by the parasites.

CONCLUSIONS/SIGNIFICANCE

Our study highlighted glycerophospholipid metabolism as the major pathway affected by trichinellosis, hence glycerophospholipid species are potential markers of trichinellosis. The findings of this study represent the initial steps in biomarker discovery that may benefit future trichinellosis diagnosis.

Serum lipidomic profiling by UHPLC-MS/MS may be able to detect early-stage endometrial cancer

Nowadays, screening for endometrial cancer (EC) primarily relies on clinical symptoms and imaging, which makes it difficult to detect early-stage disease. Here, we conducted a widely targeted lipidomic analysis of 38 human serum samples in a discovery set and 40 human serum samples in a validation set to profile the dysregulated lipid species and establish lipid biomarkers for early-stage EC. This comprehensive lipidomic determination of 616 serum lipids indicated significant differences between early-stage EC patients and healthy controls. Three phases of lipid biomarker investigation (discovery, validation, and determination of the lipid biomarker panel) were performed, which revealed the upregulation of some sphingolipid, glycerophospholipid, and glycerolipids and downregulation of some carnitine. Consistently, the perturbation of sphingolipid and glycerophospholipid metabolism was also observed from pathway enrichment analysis. Moreover, a lipid biomarker panel, including ursodeoxycholic acid, PC(O-14:0_20:4), and Cer(d18:1/18:0), was established. This panel was assessed as an effective diagnostic model to distinguish early-stage EC patients from healthy controls and atypical endometrial hyperplasia patients within the area under the receiver operating characteristic curve (AUC) reaching 0.903 and 0.928, respectively. In particular, the comparison results of the diagnostic efficacy indicated that the lipid biomarker panel was superior to clinically established indicators for EC diagnosis, including HE4, CA125, CA153, and CA199, suggesting that it could be used as an excellent supplementary method for the diagnosis of early-stage EC. In conclusion, we established a novel and non-invasive lipid biomarker for early-stage EC detection and these findings may provide new insight into the pathological mechanisms of EC.

Effective breast cancer therapy based on palmitic acid-loaded PLGA nanoparticles

Although new strategies for breast cancer treatment have yielded promising results, most drugs can lead to serious side effects when applied systemically. Doxorubicin (DOX), currently the most effective chemotherapeutic drug to treat breast cancer, is poorly selective towards tumor cells and treatment often leads to the development of drug resistance. Recent studies have indicated that several fatty acids (FAs) have beneficial effects on inhibiting tumorigenesis. The saturated FA palmitic acid (PA) showed anti-tumor activities in several types of cancer, as well as effective repolarization of M2 macrophages towards the anti-tumorigenic M1 phenotype. However, water insolubility and cellular impermeability limit the use of PA in vivo. To overcome these limitations, here, we encapsulated PA into a poly(d,l-lactic co-glycolic acid) (PLGA) nanoparticle (NP) platform, alone and in combination with DOX, to explore PA's potential as mono or combinational breast cancer therapy. Our results showed that PLGA-PA-DOX NPs and PLGA-PA NPs significantly reduced the viability and migratory capacity of breast cancer cells in vitro. In vivo studies in mice bearing mammary tumors demonstrated that PLGA-PA-NPs were as effective in reducing primary tumor growth and metastasis as NPs loaded with DOX, PA and DOX, or free DOX. At the molecular level, PLGA-PA NPs reduced the expression of genes associated with multi-drug resistance and inhibition of apoptosis, and induced apoptosis via a caspase-3-independent pathway in breast cancer cells. In addition, immunohistochemical analysis of residual tumors showed a reduction in M2 macrophage content and infiltration of leukocytes after treatment of PLGA-PA NPs and PLGA-PA-DOX NPs, suggesting immunomodulatory properties of PA in the tumor microenvironment. In conclusion, the use of PA alone or in combination with DOX may represent a promising novel strategy for the treatment of breast cancer.

Unique sphingolipid signature identifies luminal and triple-negative breast cancer subtypes

Breast cancer (luminal and triple-negative breast cancer [TNBC]) is the most common cancer among women in India and worldwide. Altered sphingolipid levels have emerged as a common phenomenon during cancer progression. However, these alterations are yet to be translated into robust diagnostic and prognostic markers for cancer. Here, we present the quantified sphingolipids of tumor and adjacent-normal tissues from patients of luminal (n = 70) and TNBC (n = 42) subtype from an Indian cohort using targeted liquid chromatography mass spectrometry. We recorded unique sphingolipid profiles that distinguished luminal and TNBC tumors in comparison to adjacent normal tissue by six-sphingolipid signatures. Moreover, systematic comparison of the profiles of luminal and TNBC tumors provided a unique five-sphingolipid signature distinguishing the two subtypes. We further identified key sphingolipids that can stratify grade II and grade III tumors of luminal and TNBC subtype as well as their lymphovascular invasion status. Therefore, we provide the right evidence to develop these candidate sphingolipids as widely acceptable marker/s capable of diagnosing luminal vs TNBC subtype of breast cancer, and predicting the disease severity by identifying the tumor grade.

Comprehensive serum lipidomic analyses reveal potential biomarkers for malignant breast cancer: A case-control study

BACKGROUND

Breast cancer is the most worldwide commonly found malignancy among women. The evidence for lipidomic studies of breast cancer in the Chinese population is relatively limited.

OBJECTIVE

Our current study aimed to identify peripheral lipids capable of distinguishing adults with and without malignant breast cancer in a Chinese population and to explore the potential lipid metabolism pathways implicated in breast cancer.

METHODS

Lipidomics was performed with an Ultimate 3000 UHPLC system coupled with a Q-Exactive HF MS platform by using the serum of 71 female patients with malignant breast cancer and 92 age-matched (± 2 years) healthy women. The data were uploaded to and processed by the specialized online software Metaboanalyst 5.0. Both univariate and multivariate analyses were carried out for potential biomarker screening. Areas under the receiver-operating characteristic (ROC) curves (AUCs) of identified differential lipids were obtained for evaluating their classification capacity.

RESULTS

A total of 47 significantly different lipids were identified by applying the following criteria: false discovery rate-adjusted P < 0.05, variable importance in projection ⩾ 1.0, and fold change ⩾ 2.0 or ⩽ 0.5. Among them, 13 lipids were identified as diagnostic biomarkers with the area under curve (AUC) greater than 0.7. Multivariate ROC curves indicated that AUCs greater than 0.8 could be achieved with 2-47 lipids.

CONCLUSIONS

Using an untargeted LC-MS-based metabolic profiling approach, our study provides preliminary evidence that extensive dysregulations of OxPCs, PCs, SMs and TAGs were involved in the pathological processes of breast cancer. We provided clues for furtherly investigating the role of lipid alterations in the pathoetiology of breast cancer.

Classic and New Markers in Diagnostics and Classification of Breast Cancer

Simple Summary

With ever-increasing incidence, breast cancer is considered a most diagnosed type of cancer among women worldwide. Breast cancer arises through malignant transformation of ductal or lobular cells in female (or male) breast and the genetic, phenotypic and morphological heterogeneity has an effect on tumour’s behaviour, thereby instigating a need for individual personalized therapy. A traditional assessment of tumour’s characteristics involves a biopsy and histological analysis of a tumour tissue, and in recent years has been accompanied by analysis of molecular biomarkers to enhance the results. In this work we aimed to thoroughly investigate the latest data in this field of study and give a comprehensive review of novel molecular biomarkers of breast cancer and methodologies used to analyse them.

Abstract

Breast cancer remains the most frequently diagnosed form of female’s cancer, and in recent years it has become the most common cause of cancer death in women worldwide. Like many other tumours, breast cancer is a histologically and biologically heterogeneous disease. In recent years, considerable progress has been made in diagnosis, subtyping, and complex treatment of breast cancer with the aim of providing best suited tumour-specific personalized therapy. Traditional methods for breast cancer diagnosis include mammography, MRI, biopsy and histological analysis of tumour tissue in order to determine classical markers such as estrogen and progesterone receptors (ER, PR), cytokeratins (CK5/6, CK14, C19), proliferation index (Ki67) and human epidermal growth factor type 2 receptor (HER2). In recent years, these methods have been supplemented by modern molecular methodologies such as next-generation sequencing, microRNA, in situ hybridization, and RT-qPCR to identify novel molecular biomarkers. MicroRNAs (miR-10b, miR-125b, miR145, miR-21, miR-155, mir-30, let-7, miR-25-3p), altered DNA methylation and mutations of specific genes (p16, BRCA1, RASSF1A, APC, GSTP1), circular RNA (hsa_circ_0072309, hsa_circRNA_0001785), circulating DNA and tumour cells, altered levels of specific proteins (apolipoprotein C-I), lipids, gene polymorphisms or nanoparticle enhanced imaging, all these are promising diagnostic and prognostic tools to disclose any specific features from the multifaceted nature of breast cancer to prepare best suited individualized therapy.

Multifunctional Role of Lipids in Modulating the Tumorigenic Properties of 4T1 Breast Cancer Cells

Tumor growth and progression are linked to an altered lipid metabolism in the tumor microenvironment (TME), including tumor cells and tumor-associated macrophages (TAMs). A growing number of lipid metabolism targeting drugs have shown efficacy in anti-tumor therapy. In addition, exogenously applied lipids and lipid analogues have demonstrated anti-tumor activities in several cancers, including breast cancer. In this study, we investigated the anti-tumor efficacies of the natural lipids palmitic acid (PA), sphingomyelin (SM), ceramide (Cer) and docosahexaenoic acid (DHA) on breast cancer cells. All tested lipids reduced the malignancy of breast cancer cells in vitro by impairing cell proliferation, migration and invasiveness. PA showed superior anti-tumor properties, as it additionally impaired cancer cell viability by inducing apoptosis, without affecting healthy cells. Co-culture experiments further demonstrated that Cer and PA reduced the immunosuppressive phenotype of M2 macrophages and the M2 macrophage-promoted the epithelial–mesenchymal transition (EMT) and migration of breast cancer cells. At the molecular level, this coincided with the up-regulation of E-cadherin. Our results highlight a powerful role for exogenously applied PA and Cer in reducing breast cancer tumorigenicity by simultaneously targeting cancer cells and M2 macrophages. Our findings support the notion that lipids represent alternative biocompatible therapeutic agents for breast cancer.

Lipidomic analysis reveals disturbances in glycerophospholipid and sphingolipid metabolic pathways in benzene-exposed mice

Benzene, a known occupational and environmental contaminant, has been recognized as the hematotoxin and human carcinogen. Lipids have a variety of important physiological functions and the abnormal lipid metabolism has been reported to be closely related to the occurrence and development of many diseases. In the present study, we aim to utilize LC-MS/MS lipidomic platform to identify novel biomarkers and provide scientific clues for mechanism study of benzene hematotoxicity. Results showed that a total of 294 differential metabolites were obtained from the comparison of benzene-treated group and control group. The glycerophospholipid pathway was altered involving the down-regulation of the levels of phosphatidylcholine and phosphatidylserine. In addition, phosphatidylethanolamine (PE) and 1-Acyl-sn-glycero-3-phosphocholine levels were increased in benzene-treated group. Based on the relationship between PE and autophagy, we then found that effective biomarker of autophagy, Beclin1 and LC3B, were increased remarkably. Furthermore, following benzene treatment, significant decreases in glucosylceramide (GlcCer) and phytosphingosine (PHS) levels in sphingolipid pathway were observed. Simultaneously, the levels of proliferation marker (PCNA and Ki67) and apoptosis regulator (Bax and Caspase-3) showed clear increases in benzene-exposed group. Based on our results, we speculate that disturbances in glycerophospholipid pathway play an important role in the process of benzene-induced hematopoietic toxicity by affecting autophagy, while sphingolipid pathway may also serve as a vital role in benzene-caused toxicity by regulating proliferation and apoptosis. Our study provides basic study information for the future biomarker and mechanism research underlying the development of benzene-induced blood toxicity.

Apolipoprotein A1 and Low-Density Lipoprotein as Risk Factors for Intraocular Metastases in Postmenopausal Breast Cancer

BACKGROUND

The outcomes of patients with postmenopausal breast cancer(PBC) can be improved through the early detection of intraocular metastases(IOMs). In this study, we investigated patients with PBC, and compared those with IOMs with those with non-intraocular metastases(NIOMs) in terms of blood lipid levels, and then differentiated the risk factors associated with IOMs.

METHODS

Student's t-test and a chi-square test were used to discriminate between the IOMs and NIOMs groups. After establishing a Poisson regression model to analyze risk factors, we plotted receiver operating characteristic curves(ROC) to assess the quality of risk factors predicting IOMs.

RESULTS

The incidence of IOMs in PBC was 1.16%. There was no significant difference in terms of histopathology between the 2 groups. The levels of total cholesterol (TC), apolipoprotein A1(APOA1) and low-density lipoprotein(LDL) in IOMs were significantly lower than in NIOMs groups. Poisson regression suggested that low levels of APOA1 and LDL were risk factors for IOMs (P = 0.002 and P < 0.001, respectively). ROC curve analysis demonstrated that the cut-off values of APOA1 and LDL were 1.025 g/L and 2.415 mmol/L. The highest prediction accuracy for IOMs involved the combination of APOA1 and LDL (AUC = 0.881, P < 0.001).

CONCLUSION

Our research demonstrates that low levels of APOA1 and LDL efficiently predict IOMs in PBC as risk factors, and the combination of APOA1 and LDL was more predictive than single factors.

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.

Phospholipase A2 superfamily in cancer

Phospholipase A2 enzymes (PLA₂s) comprise a superfamily that is generally divided into six subfamilies known as cytosolic PLA₂s (cPLA₂s), calcium-independent PLA₂s (iPLA₂s), secreted PLA₂s (sPLA₂s), lysosomal PLA₂s, platelet-activating factor (PAF) acetylhydrolases, and adipose specific PLA₂s. Each subfamily consists of several isozymes that possess PLA₂ activity. The first three PLA₂ subfamilies play important roles in inflammation-related diseases and cancer. In this review, the roles of well-studied enzymes sPLA₂-IIA, cPLA₂α and iPLA₂β in carcinogenesis and cancer development were discussed. sPLA₂-IIA seems to play conflicting roles and can act as a tumor suppressor or a tumor promoter according to the cancer type, but cPLA₂α and iPLA₂β play protumorigenic role in most cancers. The mechanisms of PLA₂-mediated signal transduction and crosstalk between cancer cells and endothelial cells in the tumor microenvironment are described. Moreover, the mechanisms by which PLA₂s mediate lipid reprogramming and glycerophospholipid remodeling in cancer cells are illustrated. PLA₂s as the upstream regulators of the arachidonic acid cascade are generally high expressed and activated in various cancers. Therefore, they can be considered as potential pharmacological targets and biomarkers in cancer. The detailed information summarized in this review may aid in understanding the roles of PLA₂s in cancer, and provide new clues for the development of novel agents and strategies for tumor prevention and treatment.

A serum lipidomic strategy revealed potential lipid biomarkers for early-stage cervical cancer

AIMS

Cervical cancer (CC) is a common tumor of women worldwide. Here, we conducted a non-targeted lipidomic study to discover novel lipid biomarkers for early-stage CC.

MAIN METHODS

The lipidomic analysis of 71 samples in discovery set and 72 samples in validation set were performed by coupling ultra-high-pressure liquid chromatography (UHPLC) with quadrupole time-of-flight tandem mass spectrometry (Q-TOF-MS). Lipids with variable importance (VIP) values greater than 1, adj. p < 0.05 (the adjusted p value obtained from false discovery rate correction) and fold change (FC) higher than 1.5 were reserved as potential biomarkers. Subsequently, receiver operating characteristic (ROC) curve and binary logistic regression were implemented to assess the diagnostic potential of these biomarkers and to acquire the best biomarker combination.

KEY FINDINGS

A lipid biomarker panel, including phosphatidylcholine (PC, PC 14:0/18:2) and phosphatidylethanolamine (PE, PE 15:1e/22:6 and PE 16:1e/18:2), was established. This panel was effective in distinguishing between CC and non-CC (squamous intraepithelial lesions [SIL] and healthy controls) within the area under the ROC curve (AUC), sensitivity, and specificity reaching 0.966, 0.952, and 0.860 for discovery set and 0.961, 0.920, and 0.915 for external validation set. Furthermore, this panel was also capable of discriminating early-stage CC from SIL with AUC, sensitivity, and specificity reaching 0.946, 0.952, and 0.800 for discovery set and 0.956, 0.960, and 0.815 for external validation set.

SIGNIFICANCE

The combination of PC 14:0/18:2, PE 15:1e/22:6, and PE 16:1e/18:2 could serve as a promising serum biomarker for discriminating early-stage CC from SIL and healthy subjects.

Multiplatform Investigation of Plasma and Tissue Lipid Signatures of Breast Cancer Using Mass Spectrometry Tools

Plasma and tissue from breast cancer patients are valuable for diagnostic/prognostic purposes and are accessible by multiple mass spectrometry (MS) tools. Liquid chromatography-mass spectrometry (LC-MS) and ambient mass spectrometry imaging (MSI) were shown to be robust and reproducible technologies for breast cancer diagnosis. Here, we investigated whether there is a correspondence between lipid cancer features observed by desorption electrospray ionization (DESI)-MSI in tissue and those detected by LC-MS in plasma samples. The study included 28 tissues and 20 plasma samples from 24 women with ductal breast carcinomas of both special and no special type (NST) along with 22 plasma samples from healthy women. The comparison of plasma and tissue lipid signatures revealed that each one of the studied matrices (i.e., blood or tumor) has its own specific molecular signature and the full interposition of their discriminant ions is not possible. This comparison also revealed that the molecular indicators of tissue injury, characteristic of the breast cancer tissue profile obtained by DESI-MSI, do not persist as cancer discriminators in peripheral blood even though some of them could be found in plasma samples.

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.

The predictive value of high-density lipoprotein for ocular metastases in colorectal cancer patients

Purpose: Colorectal cancer (CRC) is a common tumor of the digestive tract that tends to metastasize and leads to high mortality. Ocular metastases (OM) from colorectal cancer are being increasingly diagnosed, and they can lead to a poor prognosis. Serum lipids are a known risk factor for cardiovascular disease, and are also relevant to the occurrence of CRC. In this study, we examined the levels of serum lipids and tried to determine whether there were correlations with the occurrence of OM in patients with colorectal cancer, in order to determine whether serum lipid levels may be a risk factor for OM in this patient population.

Patients and methods: Records from a total of 703 patients treated for colorectal cancer from August 2005 to August 2017 were involved in this study. Student’s t-tests, nonparametric rank sum tests, and Chi-square tests were applied to describe whether there were significant differences between the OM group and non-ocular metastases (NOM) group. We used binary logistic regression analysis to determine the risk factors and receiver operating curve (ROC) analyses to assess the diagnostic value for OM in CRC patients.

Results: There were no significant differences in gender, age, histopathology type, or tumor classifications between the OM and NOM groups. The levels of serum TC, HDL, and LDL were significantly different between patients with and without lymph node metastases as well as male and female patients. The OM group had higher serum HDL levels compared to the NOM group. Binary logistic regression indicated that HDL was a risk factor for OM in colorectal cancer patients. The ROC curves showed that the AUC of HDL was 0.660. The cutoff value of HDL was 1.27 mmol/L, with a sensitivity of 0.619 and a specificity of 0.650.

Conclusion: HDL levels are correlated with ocular metastases in colorectal cancer patients.

Targeting lipid mediators in cancer biology

Bioactive lipids are essential components of human cells and tissues. As discussed in this review, the cancer lipidome is diverse and malleable, with the ability to promote or inhibit cancer pathogenesis. Targeting lipids within the tumor and surrounding microenvironment may be a novel therapeutic approach for treating cancer patients. Additionally, the emergence of a novel super-family of lipid mediators termed specialized pro-resolving mediators (SPMs) has revealed a new role for bioactive lipid mediators in the resolution of inflammation in cancer biology. The role of SPMs in cancer holds great promise in our understanding of cancer pathogenesis and can ultimately be used in future cancer diagnostics and therapy.

Lipids as Biomarkers of Cancer and Bacterial Infections

Lipids are ubiquitous molecules, known to play important roles in various cellular processes. Alterations to the lipidome can therefore be used as a read-out of the signs of disease, highlighting the importance to consider lipids as biomarkers in addition of nucleic acid and proteins. Lipids are among the primary structural and functional constituents of biological tissues, especially cell membranes. Along with membrane formation, lipids play also a crucial role in cell signalling, inflammation and energy storage. It was shown recently that lipid metabolism disorders play an important role in carcinogenesis and development. As well, the role of lipids in disease is particularly relevant for bacterial infections, during which several lipid bacterial virulence factors are recognized by the human innate immune response, such as lipopolysaccharide in Gram-negative bacteria, lipoteichoic acid in Gram-positive bacteria, and lipoglycans in mycobacteria. Compared to nucleic acids and proteins, a complete analysis of the lipidome, which is the comprehensive characterization of different lipid families, is usually very challenging due to the heterogeneity of lipid classes and their intrinsic physicoproperties caused by variations in the constituents of each class. Understanding the chemical diversity of lipids is therefore crucial to understanding their biological relevance and, as a consequence, their use as potential biomarkers for non-infectious and infectious diseases. This mini-review exposes the current knowledge and limitations of the use of lipids as biomarkers of the top global killers which are cancer and bacterial infections.

Rapid discrimination of pediatric brain tumors by mass spectrometry imaging

Purpose

Medulloblastoma, the most common primary pediatric malignant brain tumor, originates in the posterior fossa of the brain. Pineoblastoma, which originates within the pineal gland, is a rarer malignancy that also presents in the pediatric population. Medulloblastoma and pineoblastoma exhibit overlapping clinical features and have similar histopathological characteristics. Histopathological similarities confound rapid diagnoses of these two tumor types. We have conducted a pilot feasibility study analyzing the molecular profile of archived frozen human tumor specimens using mass spectrometry imaging (MSI) to identify potential biomarkers capable of classifying and distinguishing between medulloblastoma and pineoblastoma.

Methods

We performed matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry imaging on eight medulloblastoma biopsy specimens and three pineoblastoma biopsy specimens. Multivariate statistical analyses were performed on the MSI dataset to generate classifiers that distinguish the two tumor types. Lastly, the molecules that were discriminative of tumor type were queried against the Lipid Maps database and identified.

Results

In this pilot study we show that medulloblastoma and pineoblastoma can be discriminated using molecular profiles determined by MSI. The highest-ranking discriminating classifiers of medulloblastoma and pineoblastoma were glycerophosphoglycerols and sphingolipids, respectively.

Conclusion

We demonstrate proof-of-concept that medulloblastoma and pineoblastoma can be rapidly distinguished by using MSI lipid profiles. We identified biomarker candidates capable of distinguishing these two histopathologically similar tumor types. This work expands the current molecular knowledge of medulloblastoma and pineoblastoma by characterizing their lipidomic profiles, which may be useful for developing novel diagnostic, prognostic and therapeutic strategies.

Electronic supplementary material

The online version of this article (10.1007/s11060-018-2978-2) contains supplementary material, which is available to authorized users.