Comprehensive lipid profiling of plasma in patients with benign breast tumor and breast cancer reveals novel biomarkers

Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers

Aberrant lipid metabolism is increasingly recognized as a hallmark of cancer, contributing to tumor growth, metastatic dissemination, and resistance to therapy. Cancer cells reprogram key metabolic pathways-including de novo lipogenesis, lipid uptake, and phospholipid remodeling-to sustain malignant progression and adapt to microenvironmental demands. This review summarizes current insights into the role of lipid metabolic reprogramming in oncogenesis and highlights recent advances in lipidomics that have revealed cancer type- and stage-specific lipid signatures with diagnostic and prognostic relevance. We emphasize the dual potential of lipid metabolic pathways-particularly those involving phospholipids-as sources of clinically relevant biomarkers and therapeutic targets. Enzymes and transporters involved in these pathways have emerged as promising candidates for both diagnostic applications and pharmacological intervention. We also examine persistent challenges hindering the clinical translation of lipid-based approaches, including analytical variability, insufficient biological validation, and the lack of standardized integration into clinical workflows. Furthermore, the review explores strategies to overcome these barriers, highlighting the importance of incorporating lipidomics into multi-omics frameworks, supported by advanced computational tools and AI-driven analytics, to decipher the complexity of tumor-associated metabolic networks. We discuss how such integrative approaches can facilitate the identification of actionable metabolic targets, improve the specificity and robustness of lipid-based biomarkers, and enhance patient stratification in the context of precision oncology.

Endoplasmic Reticulum Stress and Its Role in Metabolic Reprogramming of Cancer

Background/Objectives: Endoplasmic reticulum (ER) stress occurs when ER homeostasis is disrupted, leading to the accumulation of misfolded or unfolded proteins. This condition activates the unfolded protein response (UPR), which aims to restore balance or trigger cell death if homeostasis cannot be achieved. In cancer, ER stress plays a key role due to the heightened metabolic demands of tumor cells. This review explores how metabolomics can provide insights into ER stress-related metabolic alterations and their implications for cancer therapy. Methods: A comprehensive literature review was conducted to analyze recent findings on ER stress, metabolomics, and cancer metabolism. Studies examining metabolic profiling of cancer cells under ER stress conditions were selected, with a focus on identifying potential biomarkers and therapeutic targets. Results: Metabolomic studies highlight significant shifts in lipid metabolism, protein synthesis, and oxidative stress management in response to ER stress. These metabolic alterations are crucial for tumor adaptation and survival. Additionally, targeting ER stress-related metabolic pathways has shown potential in preclinical models, suggesting new therapeutic strategies. Conclusions: Understanding the metabolic impact of ER stress in cancer provides valuable opportunities for drug development. Metabolomics-based approaches may help identify novel biomarkers and therapeutic targets, enhancing the effectiveness of antitumor therapies.

Lipidomics-driven drug discovery and delivery strategies in glioblastoma

With few viable treatment options, glioblastoma (GBM) is still one of the most aggressive and deadly types of brain cancer. Recent developments in lipidomics have demonstrated the potential of lipid metabolism as a therapeutic target in GBM. The thorough examination of lipids in biological systems, or lipidomics, is essential to comprehending the changed lipid profiles found in GBM, which are linked to the tumor's ability to grow, survive, and resist treatment. The use of lipidomics in drug delivery and discovery is examined in this study, focusing on how it may be used to find new biomarkers, create multi-target directed ligands, and improve drug delivery systems. We also cover the use of FDA-approved medications, clinical trials that use lipid-targeted medicines, and the integration of lipidomics with other omics technologies. This study emphasizes lipidomics as a possible tool in developing more effective treatment methods for GBM by exploring various lipid-centric techniques.

Gut microbiome and plasma lipidome analysis reveals a specific impact of Clostridioides difficile infection on intestinal bacterial communities and sterol metabolism

Clostridioides difficile infection (CDI) causes alterations in the intestinal microbiota, frequently associated with changes in the gut metabolism of bile acids and cholesterol. In addition to the impact on microbiome composition and given the metabolic changes occurring during CDI, our work focuses on the importance to know the effects at the local and systemic levels, both during the infection and its treatment, by paying particular attention to plasma lipid metabolism due to its relationship with CDI pathogenesis. Specific changes, characterized by a loss of microbial richness and diversity and related to a reduction in short-chain acid-producing bacteria and an increase in bile salt hydrolase-producing bacteria, were observed in the gut microbiota of CDI patients, especially in those suffering from recurrent CDI (RCDI). However, gut microbiota showed its ability to restore itself after treatment, resembling healthy individuals, in those patients treated by fecal microbiome transfer (FMT), in contrast with those treated with antibiotics, and displaying increased levels of Eubacterium coprostanoligenes, a cholesterol-reducing anaerobe. Interestingly, changes in plasma lipidome revealed a global depletion in circulating lipids in CDI, with the largest impact on cholesteryl esters. CDI patients also showed a specific and consistent decrease in the levels of lipid species containing linoleic acid-an essential fatty acid-which were only partially recovered after antibiotic treatment. Analysis of the plasma lipidome reflects CDI impact on the gut microbiota and its metabolism, evidencing changes in sterol and fatty acid metabolism that are possibly related to specific alterations observed in gut microbial communities of CDI patients.

IMPORTANCE

There is increasing evidence about the influence the changes in microbiota and its metabolism has on numerous diseases and infections such as Clostridioides difficile infection (CDI). The knowledge of these changes at local and systemic levels can help us manage this infection to avoid recurrences and apply the best therapies, such as fecal microbiota transfer (FMT). This study shows a better restoration of the gut in FMT-treated patients than in antibiotic-treated patients, resembling healthy controls and showing increased levels of cholesterol-reducing bacteria. Furthermore, it evidences the CDI impact on plasma lipidome. We observed in CDI patients a global depletion in circulating lipids, particularly cholesteryl esters, and a specific decrease in linoleic acid-containing lipids, an essential fatty acid. Our observations could impact CDI management because the lipid content was only partially recovered after treatment, suggesting that continued nutritional support, aiming to restore healthy lipid levels, could be essential for a full recovery.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study

BACKGROUND

Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge.

OBJECTIVES

To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management.

METHODS

In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM.

RESULTS

We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample.

CONCLUSIONS

These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer

BACKGROUND

This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients.

METHODS

A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre‑therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines.

RESULTS

Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels.

CONCLUSION

Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Unraveling lipid and inflammation interplay in cancer, aging and infection for novel theranostic approaches

The synergistic relationships between Cancer, Aging, and Infection, here referred to as the CAIn Triangle, are significant determinants in numerous health maladies and mortality rates. The CAIn-related pathologies exhibit close correlations with each other and share two common underlying factors: persistent inflammation and anomalous lipid concentration profiles in the membranes of affected cells. This study provides a comprehensive evaluation of the most pertinent interconnections within the CAIn Triangle, in addition to examining the relationship between chronic inflammation and specific lipidic compositions in cellular membranes. To tackle the CAIn-associated diseases, a suite of complementary strategies aimed at diagnosis, prevention, and treatment is proffered. Our holistic approach is expected to augment the understanding of the fundamental mechanisms underlying these diseases and highlight the potential of shared features to facilitate the development of novel theranostic strategies.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Lipid Biomarkers in Liquid Biopsies: Novel Opportunities for Cancer Diagnosis

Altered cellular metabolism is a well-established hallmark of cancer. Although most studies have focused on the metabolism of glucose and glutamine, the upregulation of lipid metabolism is also frequent in cells undergoing oncogenic transformation. In fact, cancer cells need to meet the enhanced demand of plasma membrane synthesis and energy production to support their proliferation. Moreover, lipids are precursors of signaling molecules, termed lipid mediators, which play a role in shaping the tumor microenvironment. Recent methodological advances in lipid analysis have prompted studies aimed at investigating the whole lipid content of a sample (lipidome) to unravel the complexity of lipid changes in cancer patient biofluids. This review focuses on the application of mass spectrometry-based lipidomics for the discovery of cancer biomarkers. Here, we have summarized the main lipid alteration in cancer patients' biofluids and uncovered their potential use for the early detection of the disease and treatment selection. We also discuss the advantages of using biofluid-derived extracellular vesicles as a platform for lipid biomarker discovery. These vesicles have a molecular signature that is a fingerprint of their originating cells. Hence, the analysis of their molecular cargo has emerged as a promising strategy for the identification of sensitive and specific biomarkers compared to the analysis of the unprocessed biofluid.

Breast adipose metabolites mediates the association of tetrabromobisphenol a with breast cancer: A case-control study in Chinese population

Studies exploring the association of tetrabromobisphenol A (TBBPA) with breast cancer and related mechanisms are limited. To investigate the relationship between TBBPA levels in breast adipose and breast cancer, we carried out case-control research. As well as further examine the mediating role of adipose metabolites between TBBPA and breast cancer using the metabolomics approach. In this study, the concentration of TBBPA was determined utilizing ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) after a solid phase extraction (SPE) pretreatment. High-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) was employed to analyze adipose metabolomics. Evaluation of metabolites linked to TBBPA exposure and breast cancer was performed utilizing mediation analysis. With an estimated OR (95%CI) of 1.153 (1.023, 1.299), TBBPA was firmly linked with breast cancer. We also used propensity score matching analysis and sensitivity analysis to reduce the effect of confounding factors on the results. Metabolomics of adipose suggested significant perturbation in the linoleic acid metabolism pathway. In addition, for PC (16:0/16:0) as phospholipids, a mediation effect on the associations of TBBPA exposure with breast cancer risks was observed (estimated mediation percentage: 56.58%). Understanding the relationship between TBBPA exposure and the risk of breast cancer may be facilitated by the findings, which point to potential mediation metabolites.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

Association of SNP rs5069 in APOA1 with Benign Breast Diseases in a Mexican Population

Breast cancer (BCa) is the most common type of cancer affecting women worldwide. Some histological subtypes of benign breast disease (BBD) are considered risk factors for developing BCa. Single nucleotide polymorphisms (SNPs) in the genes encoding apolipoproteins A-I (APOA1) and B (APOB) have been associated with BCa in Tunisian, Chinese, and Taiwanese populations. The objective of this pilot study is to evaluate the possible contribution of APOA1 and APOB polymorphisms to BCa and BBD in the Mexican population. We analyzed the association of 4 SNPs in genes encoding apolipoproteins: rs670 and rs5069 in the APOA1 gene, and rs693 and rs1042031 in the APOB gene, by performing PCR-RFLP with DNA extracted from the biopsy tissue of Mexican women with BCa or BBD and whole blood samples obtained from the general population (GP). Our results showed an association between the CT + TT genotypes of the SNP rs5069 and BBD (p = 0.03201). In the A-T haplotype, the frequency of the SNPs rs670 and rs5069 differed significantly between the BBD group and the GP and BCa groups (p = 0.004111; p = 0.01303). In conclusion, the SNP rs5069 is associated with BBD but not with BCa in the Mexican population.

Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma

Background: Lipid metabolism disorders play a key role in the pathogenesis of squamous cell carcinoma (SqCC). Herein we used lipidomics to study the tissue lipid profiles of 40 patients with SqCC. Methods: Lipidomics, based on ultrahigh-performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry, was applied to identify altered lipid metabolites between tumor and adjacent noninvolved tissues (ANIT), and partial least squares-discriminant analysis model facilitated the identification of differentially abundant lipids. The area under the receiver operator characteristic curve and variable importance in projection scores of the aforementioned model were calculated to select lipid profiles. Metabolic pathway analyses were completed using Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst. Results: Differences in lipid profiles were found between tumor and ANIT, early- and advanced-stage SqCC, and positive and negative lymph node metastases. The lipid profile panel was composed of five lipids-PC(44:4), diacylglycerol(36:5), sphingomyelin(d18:1/20:0), phosphatidylinositol(46:7), and HexCer-AP(t8:0/32:2 + O)-and could effectively differentiate between tumor and ANIT. Further, pathway analyses revealed alterations in several lipid metabolism pathways, including glycerophospholipid metabolism, glycosylphosphatidylinositol anchor biosynthesis, linoleic acid metabolism, glycerolipid metabolism, and sphingolipid metabolism. Conclusion: Our data revealed several changes in the tissue lipid profiles of patients with SqCC; moreover, we identified a lipid profile panel that could effectually distinguish tumor tissues from ANIT. We believe that our results provide new insights into the biological behavior of lung SqCC.

Lipidomic landscape in cancer: Actionable insights for membrane-based therapy and diagnoses

Cancer cells display altered cellular lipid metabolism, including disruption in endogenous lipid synthesis, storage, and exogenous uptake for membrane biogenesis and functions. Altered lipid metabolism and, consequently, lipid composition impacts cellular function by affecting membrane structure and properties, such as fluidity, rigidity, membrane dynamics, and lateral organization. Herein, we provide an overview of lipid membranes and how their properties affect cellular functions. We also detail how the rewiring of lipid metabolism impacts the lipidomic landscape of cancer cell membranes and influences the characteristics of cancer cells. Furthermore, we discuss how the altered cancer lipidome provides cues for developing lipid-inspired innovative therapeutic and diagnostic strategies while improving our limited understanding of the role of lipids in cancer initiation and progression. We also present the arcade of membrane characterization techniques to cement their relevance in cancer diagnosis and monitoring of treatment response.

Fatty Acid Unsaturation Degree of Plasma Exosomes in Colorectal Cancer Patients: A Promising Biomarker

Even though colorectal cancer (CRC) is one of the most preventable cancers, it is currently one of the deadliest. Worryingly, incidence in people <50 years has increased unexpectedly, and for unknown causes, despite the successful implementation of screening programs in the population aged >50 years. Thus, there is a need to improve early diagnosis detection strategies by identifying more precise biomarkers. In this scenario, the analysis of exosomes is given considerable attention. Previously, we demonstrated the exosome lipidome was able to classify CRC cell lines according to their malignancy. Herein, we investigated the use of the lipidome of plasma extracellular vesicles as a potential source of non-invasive biomarkers for CRC. A plasma exosome-enriched fraction was analyzed from patients undergoing colonoscopic procedure. Patients were divided into a healthy group and four pathological groups (patients with hyperplastic polyps; adenomatous polyps; invasive neoplasia (CRC patients); or hereditary non-polyposis CRC. The results showed a shift from 34:1- to 38:4-containing species in the pathological groups. We demonstrate that the ratio Σ34:1-containing species/Σ38:4-containing species has the potential to discriminate between healthy and pathological patients. Altogether, the results reinforce the utility of plasma exosome lipid fingerprint to provide new non-invasive biomarkers in a clinical context.

Apolipoprotein A1 is negatively associated with male papillary thyroid cancer patients: a cross-sectional study of single academic center in China

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer and the incidence of PTC has continued to increase over the past decades. Many studies have shown that obesity is an independent risk factor for PTC and obese PTC patients tend to have a relative larger tumor size and higher grade of tumor stage. Obesity is associated with disordered lipid metabolism and the relationship between serum lipids and PTC remains unclear. Therefore, this study aimed to investigate the association between serum lipid level and PTC.

METHODS

We retrospectively analyzed 1018 PTC patients diagnosed and treated in our hospital, all these cases were first diagnosed with PTC and had complete clinical information including ultrasound reports before surgery, serum lipid (CHOL, TG, HDL-c, LDL-c, Apo-A1, Apo-B, Apo-E) results, surgical records and pathological reports.

RESULTS

None of these lipid markers were associated with tumor size in the whole cohort and in the female group. In the male group, on crude analysis, Apo-A1 showed a marginally association with tumor size, [OR = 0.158 (0.021-1.777)], p = 0.072. After adjusting for age and multifocality, Apo-A1 showed a significant association with tumor size [OR = 0.126 (0.016-0.974)], p = 0.047. This association become more apparent in a young male subgroup, [OR = 0.051 (0.005-0.497)], p = 0.009. CHOL, TG, HDL-c, LDL-c, Apo-B, Apo-E did not show significant association with tumor size. As for LNM, neither in the male group nor in the female group were found to be associated with any serum lipid biomarkers.

CONCLUSION

As PTC incidences continues to increase, our findings demonstrated a negatively association between PTC and apoA-1 in male PTC patients, which may contribute to further investigation concerning diagnosing and preventing this most common type of thyroid cancer.

Lipid Metabolism and Lipidomics Applications in Cancer Research

Lipids are the critical components of cellular and plasma membrane, which constitute an impermeable barrier of cellular compartments, and play important roles on numerous cellular processes including cell growth, proliferation, differentiation, and signaling. Alterations in lipid metabolism have been implicated in the development and progression of cancers. However, unlike other biomolecules, the diversity in the structures and characteristics of lipid species results in the limited understanding of their metabolic alterations in cancers. Lipidomics is an emerging discipline that studies lipids in a large scale based on analytical chemistry principles and technological tools. Multidimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) uses direct infusion to avoid difficulties from alterations in concentration, chromatographic anomalies, and ion-pairing alterations to improve resolution and achieve rapid and accurate qualitative and quantitative analysis. In this chapter, lipids and lipid metabolism relevant to cancer research are introduced, followed by a brief description of MDMS-SL and other shotgun lipidomics techniques and some applications for cancer research.

Comparable Plasma Lipid Changes in Patients with High-Grade Cervical Intraepithelial Neoplasia and Patients with Cervical Cancer

Cervical cancer is the fourth most prevalent cancer among women worldwide and usually develops from cervical intraepithelial neoplasia (CIN). In the present study, we compared alterations in lipids associated with high-grade CIN and cervical cancer with those associated with a normal status and low-grade CIN by performing global lipid profiling on plasma (66 healthy controls and 55 patients with CIN1, 44 with CIN2/3, and 60 with cervical cancer) using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry. We identified 246 lipids and found 31 lipids with similar alterations in both high-grade CIN and cervical cancer. Among these 31 lipids, four lipid classes (phosphatidylcholine, phosphatidylethanolamine, diglyceride, and free fatty acids) were identified as the major lipid classes with significant differences in the patients with CIN2/3 and cervical cancer compared to the healthy controls and the patients with CIN1. Lipid metabolites belonging to the same classes were positively correlated with each other. High-grade CIN and cervical cancer induce comparable changes in lipid levels, which are closely related to the development of cervical tumors. These results suggest that lipid profiling is a useful method for monitoring progression to cervical cancer.

Metabolomic profile of cancer stem cell-derived exosomes from patients with malignant melanoma

Malignant melanoma (MM) is the most aggressive and life‐threatening form of skin cancer. It is characterized by an extraordinary metastasis capacity and chemotherapy resistance, mainly due to melanoma cancer stem cells (CSCs). To date, there are no suitable clinical diagnostic, prognostic or predictive biomarkers for this neoplasia. Therefore, there is an urgent need for new MM biomarkers that enable early diagnosis and effective disease monitoring. Exosomes represent a novel source of biomarkers since they can be easily isolated from different body fluids. In this work, a primary patient‐derived MM cell line enriched in CSCs was characterized by assessing the expression of specific markers and their stem‐like properties. Exosomes derived from CSCs and serums from patients with MM were characterized, and their metabolomic profile was analysed by high‐resolution mass spectrometry (HRMS) following an untargeted approach and applying univariate and multivariate statistical analyses. The aim of this study was to search potential biomarkers for the diagnosis of this disease. Our results showed significant metabolomic differences in exosomes derived from MM CSCs compared with those from differentiated tumour cells and also in serum‐derived exosomes from patients with MM compared to those from healthy controls. Interestingly, we identified similarities between structural lipids differentially expressed in CSC‐derived exosomes and those derived from patients with MM such as the glycerophosphocholine PC 16:0/0:0. To our knowledge, this is the first metabolomic‐based study aimed at characterizing exosomes derived from melanoma CSCs and patients' serum in order to identify potential biomarkers for MM diagnosis. We conclude that metabolomic characterization of CSC‐derived exosomes sets an open door to the discovery of clinically useful biomarkers in this neoplasia.

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.

Recent advances in the mass spectrometric analysis of glycosphingolipidome - A review

Aberrant expression of glycosphingolipids has been implicated in a myriad of diseases, but our understanding of the strucural diversity, spatial distribution, and biological function of this class of biomolecules remains limited. These challenges partly stem from a lack of sensitive tools that can detect, identify, and quantify glycosphingolipids at the molecular level. Mass spectrometry has emerged as a powerful tool poised to address most of these challenges. Here, we review the recent developments in analytical glycosphingolipidomics with an emphasis on sample preparation, mass spectrometry and tandem mass spectrometry-based structural characterization, label-free and labeling-based quantification. We also discuss the nomenclature of glycosphingolipids, and emerging technologies like ion mobility spectrometry in differentiation of glycosphingolipid isomers. The intrinsic advantages and shortcomings of each method are carefully critiqued in line with an individual's research goals. Finally, future perspectives on analytical sphingolipidomics are stated, including a need for novel and more sensive methods in isomer separation, low abundance species detection, and profiling the spatial distribution of glycosphingolipid molecular species in cells and tissues using imaging mass spectrometry.

Carnitine palmitoyltransferase 1C reverses cellular senescence of MRC-5 fibroblasts via regulating lipid accumulation and mitochondrial function

Cellular senescence, a state of growth arrest, is involved in various age-related diseases. We previously found that carnitine palmitoyltransferase 1C (CPT1C) is a key regulator of cancer cell proliferation and senescence, but it is unclear whether CPT1C plays a similar role in normal cells. Therefore, this study aimed to investigate the role of CPT1C in cellular proliferation and senescence of human embryonic lung MRC-5 fibroblasts and the involved mechanisms. The results showed that CPT1C could reverse the cellular senescence of MRC-5 fibroblasts, as evidenced by reduced senescence-associated β-galactosidase activity, downregulated messenger RNA (mRNA) expression of senescence-associated secretory phenotype factors, and enhanced bromodeoxyuridine incorporation. Lipidomics analysis further revealed that CPT1C gain-of-function reduced lipid accumulation and reversed abnormal metabolic reprogramming of lipids in late MRC-5 cells. Oil Red O staining and Nile red fluorescence also indicated significant reduction of lipid accumulation after CPT1C gain-of-function. Consequently, CPT1C gain-of-function significantly reversed mitochondrial dysfunction, as evaluated by increased adenosine triphosphate synthesis and mitochondrial transmembrane potential, decreased radical oxygen species, upregulated respiratory capacity and mRNA expression of genes related to mitochondrial function. In summary, CPT1C plays a vital role in MRC-5 cellular proliferation and can reverse MRC-5 cellular senescence through the regulation of lipid metabolism and mitochondrial function, which supports the role of CPT1C as a novel target for intervention into cellular proliferation and senescence and suggests CPT1C as a new strategy for antiaging.

Stereospecific synthesis of phosphatidylglycerol using a cyanoethyl phosphoramidite precursor

Phosphatidylglycerols (PG) are a family of naturally occurring phospholipids that are responsible for critical operations within cells. PG are characterized by an (R) configuration in the diacyl glycerol backbone and an (S) configuration in the phosphoglycerol head group. Herein, we report a synthetic route to provide control over the PG stereocenters as well as control of the acyl chain identity.

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).

Common and Differential Traits of the Membrane Lipidome of Colon Cancer Cell Lines and their Secreted Vesicles: Impact on Studies Using Cell Lines

Colorectal cancer (CRC) is the fourth leading cause of cancer death in the world. Despite the screening programs, its incidence in the population below the 50s is increasing. Therefore, new stratification protocols based on multiparametric approaches are highly needed. In this scenario, the lipidome is emerging as a powerful tool to classify tumors, including CRC, wherein it has proven to be highly sensitive to cell malignization. Hence, the possibility to describe the lipidome at the level of lipid species has renewed the interest to investigate the role of specific lipid species in pathologic mechanisms, being commercial cell lines, a model still heavily used for this purpose. Herein, we characterize the membrane lipidome of five commercial colon cell lines and their extracellular vesicles (EVs). The results demonstrate that both cell and EVs lipidome was able to segregate cells according to their malignancy. Furthermore, all CRC lines shared a specific and strikingly homogenous impact on ether lipid species. Finally, this study also cautions about the need of being aware of the singularities of each cell line at the level of lipid species. Altogether, this study firmly lays the groundwork of using the lipidome as a solid source of tumor biomarkers.

A conjunctive lipidomic approach reveals plasma ethanolamine plasmalogens and fatty acids as early diagnostic biomarkers for colorectal cancer patients

Background: Colorectal cancer (CRC) represents a third leading cause of cancer-related death worldwide. The reliable diagnostic biomarkers for detecting CRC at early stage is critical for decreasing the mortality.Method: A conjunctive lipidomic approach was employed to investigate the differences in plasma lipid profiles of CRC patients (n = 101) and healthy volunteers (n = 52). Based on UHPLC-Q-TOF MS and UHPLC-QQQ MS platforms, a total of 236 lipids were structurally detected. Multivariate data analysis was conducted for biomarkers discovery.Results: A total of 11 lipid species, including 1 Glycerophosphoethanolamine (PE), 3 ethanolamine plasmalogens (PlsEtn), 1 plasmanyl glycerophosphatidylethanolamine (PE-O), 3 fatty acids (FFA), 1 Fatty acid ester of hydroxyl fatty acid (FAHFA) and 2 Diacylglycerophosphates (PA) were identified to distinguish the CRC patients at early stage from healthy controls. In addition, these potential lipid biomarkers achieved an estimated AUC=0.981 in a validation set for univariate ROC analysis.Conclusion: By combining Q-TOF MS and QQQ MS analysis, the 11 lipids exhibited good performance in differentiating early-stage CRC and healthy control. This study also demonstrated that lipidomics is a powerful tool in discovering new potential biomarkers for cancer diagnosis.

Evaluation of LC-MS and LC×LC-MS in analysis of zebrafish embryo samples for comprehensive lipid profiling

In this study, both conventional one-dimensional liquid chromatography (1DLC) and comprehensive two-dimensional liquid chromatography (2DLC) coupled to a high-resolution time-of-flight mass spectrometer (HR-TOF MS) were used for full-scale lipid characterization of lipid extracts from zebrafish embryos. We investigated the influence on annotated lipids and different separation mechanisms (HILIC, C18, and PFP), and their different orders arranged in the first and the second dimensions. As a result, the number of lipid species annotated by conventional one-dimensional LC-MS was between 212 and 448. In contrast, the number of individual lipids species annotated by C18×HILIC, HILIC×C18, and HILIC×PFP were 1784, 1059, and 1123, respectively. Therefore, it was evident that the performance of comprehensive 2DLC, especially the C18×HILIC method, considerably exceeded 1DLC. Interestingly, a comparison of the HILIC×C18 and C18×HILIC approaches showed, under the optimized conditions, similar orthogonality, but the effective separation power of the C18×HILIC was much higher. A comparison of the HILIC×C18 and the HILIC×PFP methods demonstrated that the HILIC×PFP separation had superior orthogonality with a small increase on its effective peak capacity, indicating that the HILIC×PFP combination maybe a promising platform for untargeted lipidomics in complex samples. Finally, from the comprehensive lipid profiling respective, the C18×HILIC was selected for further studies.

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.

Pisum sativum Defensin 1 Eradicates Mouse Metastatic Lung Nodules from B16F10 Melanoma Cells

Psd1 is a pea plant defensin which can be actively expressed in Pichia pastoris and shows broad antifungal activity. This activity is dependent on fungal membrane glucosylceramide (GlcCer), which is also important for its internalization, nuclear localization, and endoreduplication. Certain cancer cells present a lipid metabolism imbalance resulting in the overexpression of GlcCer in their membrane. In this work, in vitroassays using B16F10 cells showed that labeled fluorescein isothiocyanate FITC-Psd1 internalized into live cultured cells and targeted the nucleus, which underwent fragmentation, exhibiting approximately 60% of cells in the sub-G0/G1 stage. This phenomenon was dependent on GlcCer, and the participation of cyclin-F was suggested. In a murine lung metastatic melanoma model, intravenous injection of Psd1 together with B16F10 cells drastically reduced the number of nodules at concentrations above 0.5 mg/kg. Additionally, the administration of 1 mg/kg Psd1 decreased the number of lung inflammatory cells to near zero without weight loss, unlike animals that received melanoma cells only. It is worth noting that 1 mg/kg Psd1 alone did not provoke inflammation in lung tissue or weight or vital signal losses over 21 days, inferring no whole animal cytotoxicity. These results suggest that Psd1 could be a promising prototype for human lung anti-metastatic melanoma therapy.

Using Phosphatidylinositol Phosphorylation as Markers for Hyperglycemic Related Breast Cancer

Studies have suggested that type 2 diabetes (T2D) is associated with a higher incidence of breast cancer and related mortality rates. T2D postmenopausal women have an ~20% increased chance of developing breast cancer, and women with T2D and breast cancer have a 50% increase in mortality compared to breast cancer patients without diabetes. This correlation has been attributed to the general activation of insulin receptor signaling, glucose metabolism, phosphatidylinositol (PI) kinases, and growth pathways. Furthermore, the presence of breast cancer specific PI kinase and/or phosphatase mutations enhance metastatic breast cancer phenotypes. We hypothesized that each of the breast cancer subtypes may have characteristic PI phosphorylation profiles that are changed in T2D conditions. Therefore, we sought to characterize the PI phosphorylation when equilibrated in normal glycemic versus hyperglycemic serum conditions. Our results suggest that hyperglycemia leads to: 1) A reduction in PI3P and PIP3, with increased PI4P that is later converted to PI(3,4)P2 at the cell surface in hormone receptor positive breast cancer; 2) a reduction in PI3P and PI4P with increased PIP3 surface expression in human epidermal growth factor receptor 2-positive (HER2+) breast cancer; and 3) an increase in di- and tri-phosphorylated PIs due to turnover of PI3P in triple negative breast cancer. This study begins to describe some of the crucial changes in PIs that play a role in T2D related breast cancer incidence and metastasis.

Serum Lipidomic Profiling in Breast Cancer to Identify Screening, Diagnostic, and Prognostic Biomarkers

Breast cancer is the major mortality cause of women worldwide. In the course of management of breast cancer, the identification of a biomarker is important in enhancing our knowledge on cancer pathology, predicting the response to treatment, and selecting the patients who are more favorable to receive certain treatments. These biomarkers have a prognostic value. In addition to traditional breast cancer prognosis factors such as the tumor size and grade, the axillary lymph node micrometastasis, and biomarkers such as HER2/neu, newly discovered biomarkers have been discovered. Some of these factors are genetic signature in tissue or in peripheral blood. Lipid profil, a simple and accessible biological examination, has been a novel path on the prediction of breast cancer risk of occurrence and recurrence in many studies. The main goal of our review is to evaluate lipid profile and breast cancer risk with an emphasis on the prognosis value of lipid profiles in breast cancer patient management.

Feature selection for OPLS discriminant analysis of cancer tissue lipidomics data

The mass spectrometry-based molecular profiling can be used for better differentiation between normal and cancer tissues and for the detection of neoplastic transformation, which is of great importance for diagnostics of a pathology, prognosis of its evolution trend, and development of a treatment strategy. The aim of the present study is the evaluation of tissue classification approaches based on various data sets derived from the molecular profile of the organic solvent extracts of a tissue. A set of possibilities are considered for the orthogonal projections to latent structures discriminant analysis: all mass spectrometric peaks over 300 counts threshold, subset of peaks selected by ranking with support vector machine algorithm, peaks selected by random forest algorithm, peaks with the statistically significant difference of the intensity determined by the Mann-Whitney U test, peaks identified as lipids, and both identified and significantly different peaks. The best predictive potential is obtained for OPLS-DA model built on nonpolar glycerolipids (Q² = 0.64, area under curve [AUC] = 0.95); the second one is OPLS-DA model with lipid peaks selected by random forest algorithm (Q² = 0.58, AUC = 0.87). Moreover, models based on particular molecular classes are more preferable from biological point of view, resulting in new explanatory mechanisms of pathophysiology and providing a pathway analysis. Another promising features for OPLS-DA modeling are phosphatidylethanolamines (Q² = 0.48, AUC = 0.86).

Membrane Dynamics in Health and Disease: Impact on Cellular Signalling

Biological membranes display a staggering complexity of lipids and proteins orchestrating cellular functions. Superior analytical tools coupled with numerous functional cellular screens have enabled us to query their role in cellular signalling, trafficking, guiding protein structure and function-all of which rely on the dynamic membrane lipid properties indispensable for proper cellular functions. Alteration of these has led to emergence of various pathological conditions, thus opening an area of lipid-centric therapeutic approaches. This perspective is a short summary of the dynamic properties of membranes essential for proper cellular functions, dictating both protein and lipid functions, and mis-regulated in diseases. Towards the end, we focus on some challenges lying ahead and potential means to tackle the same, mainly underscored by multi-disciplinary approaches.

Gangliosides profiling in serum of breast cancer patient: GM3 as a potential diagnostic biomarker

Gangliosides altered during the pathological conditions and particularly in cancers. Here, we aimed to profile the gangliosides in breast cancer serum and propose potential biomarkers. LC-FTMS method was first used to identify all the ganglioside species in serum, then LC-MS/MS-MRM method was employed to quantitate the levels of gangliosides in serum from healthy volunteers and patients with benign breast tumor or breast cancer. 49 ganglioside species were determined, including GM1, GM2, GM3, GD1, GD3 and GT1 species. Compared to healthy volunteers, the levels of GM1, GM2, GM3, GD1 and GD3 displayed a rising trend in breast cancer patients. In particular, as the major glycosphingolipid component, GM3 showed excellent diagnostic accuracy in cancer serum (AUC > 0.9). PCA profile of the GM3 species showed clear distinction between normal and cancer serum. What's more, ROC curve proved great diagnostic accuracy of GM3 between cancer and benign serum. In addition, GM3 was discovered as a diagnostic marker to differentiate luminal B subtype from other subtypes. Furthermore, a positive correlation between GM3 and Ki-67 status of patients was identified. In conclusion, our results introduced the alteration patterns of serum gangliosides in breast cancer and suggested serum GM3 as a potential diagnostic biomarker in breast cancer diagnosis and luminal B subtype distinction.

Chondroprotective Factors in Osteoarthritis: a Joint Affair

PURPOSE OF THE REVIEW

Osteoarthritis is widely regarded as a spectrum of conditions that affect all joint tissues, typified by a common entity: cartilage loss. Here, we review recent progress and challenges in chondroprotection and discuss new strategies to prevent cartilage loss in osteoarthritis.

RECENT FINDINGS

Advances in clinical, molecular, and cellular characterization are enabling improved stratification of osteoarthritis subtypes. Integration of next-generation sequencing and "omics" approaches with clinically relevant readouts shows promise in delineating both subtypes of disease and meaningful trial end points. Novel delivery strategies are enabling joint-specific delivery. Chondroprotection requires a whole joint approach, stratification of patient groups, and use of patient-relevant end points. Drug development should continue to explore new targets, while using modern technologies and recent knowledge to re-visit unsuccessful therapeutics from the past. The overarching goal for chondroprotection is to provide the right treatment(s) for the right patient at the right time.

Targeted lipidomics reveal derangement of ceramides in major depression and bipolar disorder

Changes of sphingolipid metabolism were suggested to contribute to the patho-etiology of major depression (MD) and bipolar disorder (BD). In a pilot study we assessed if lipid allostasis manifested in pathological plasma concentrations of bioactive lipids i.e. endocannabinoids, sphingolipids, ceramides, and lysophosphatidic acids.

METHODS

Targeted and untargeted lipidomic analyses were performed according to GLP guidelines in 67 patients with unipolar or bipolar disorders (20-67 years, 36 male, 31 female) and 405 healthy controls (18-79 years, 142 m, 263 f), who were matched according to gender, age and body mass index. Multivariate analyses were used to identify major components, which accounted for the variance between groups and were able to predict group membership.

RESULTS

Differences between MD and BP patients versus controls mainly originated from ceramides and their hexosyl-metabolites (C16Cer, C18Cer, C20Cer, C22Cer, C24Cer and C24:1Cer; C24:1GluCer, C24LacCer), which were strongly increased, particularly in male patients. Ceramide levels were neither associated with the current episode, nor with the therapeutic improvement of the Montgomery Åsberg Depression Rating Scale (MARDS). However, long-chain ceramides were linearly associated with age, stronger in patients than controls, and with high plasma levels of diacyl- and triacylglycerols. Patients receiving antidepressants had higher ceramide levels than patients not taking these drugs. There was no such association with lithium or antipsychotics except for olanzapine.

CONCLUSION

Our data suggest that high plasma ceramides in patients with major depression and bipolar disorder are indicative of a high metabolic burden, likely aggravated by certain medications.

Live single cell mass spectrometry reveals cancer-specific metabolic profiles of circulating tumor cells

Recently, there has been increased attention on the analysis of circulating tumor cells (CTCs), also known as liquid biopsy, owing to its potential benefits in cancer diagnosis and treatment. Circulating tumor cells are released from primary tumor lesions into the blood stream and eventually metastasize to distant body organs. However, a major hurdle with CTC analysis is their natural scarcity. Existing methods lack sensitivity, specificity, or reproducibility required in CTC characterization and detection. Here, we report untargeted molecular profiling of single CTCs obtained from gastric cancer and colorectal cancer patients, using live single cell mass spectrometry integrated with microfluidics-based cell enrichment techniques. Using this approach, we showed the difference in the metabolomic profile between CTCs originating from different cancer groups. Moreover, potential biomarkers were putatively annotated to be specific to each cancer type.

Liquid extraction surface analysis nanospray electrospray ionization based lipidomics for in situ analysis of tumor cells with multidrug resistance

RATIONALE

Multidrug resistance (MDR) occurs frequently and is a major challenge in tumor treatment. The lipid composition in the cell membrane and the redox balance are closely associated with the development of MDR. Liquid extraction surface analysis in combination with mass spectrometry (LESA-MS) has the characteristics of minimal sample preparation, rapid analysis, high sensitivity and high throughput, and has obtained wide applications.

METHODS

LESA-MS was employed to in situ determine the lipids and other specific metabolites of intact MCF-7/ADR cells (adriamycin-resistant breast cancer cells) and its parental MCF-7/S cells grown on a glass slide. In situ atomic force microscopy was used to observe the morphology of tumor cells before and after extraction. Multivariate statistical analysis was used to investigate the potential lipid biomarkers correlated with the MDR. Moreover, the cell membrane fluidity and potential were determined.

RESULTS

The changes in the level of the lipids were closely correlated with the multidrug resistance of MCF-7/S cells. Moreover, lower cell membrane fluidity and higher cell membrane potential were observed and thus demonstrated the changes in the cell membrane induced by multidrug resistance. Also, the ratios of GSH/GSSG, ATP/ADP and ATP/AMP were significantly higher in MCF-7/ADR cells relative to MCF-7/S cells.

CONCLUSIONS

Lower cell membrane fluidity and higher cell membrane potential caused by the changes in lipid compositions, enhanced anti-oxidative ability and energy generation were involved in the development of the MDR. The specific alterations identified in this study may provide more information for overcoming MDR.

Lipidomics: a promising cancer biomarker

The prevention, diagnosis and targeted therapies of cancer are important in cancer controlling and treatment. The present challenge about cancer biomarker still remains in identifying the special biomarkers for predicting cancer risk and assessing patient’s response during anticancer treatment. Lipidomics, in simple definition is the quantification of all lipids in a confined biological entity. Lipids play roles in membrane structure, energy storage, and signal transduction as well as in human cancers. Previous researches indicated that lipids may serve as a promising biomarker in the early diagnoses and individualized treatment of cancer.

HILIC/ESI-MS determination of gangliosides and other polar lipid classes in renal cell carcinoma and surrounding normal tissues

Negative-ion hydrophilic liquid chromatography-electrospray ionization mass spectrometry (HILIC/ESI-MS) method has been optimized for the quantitative analysis of ganglioside (GM3) and other polar lipid classes, such as sulfohexosylceramides (SulfoHexCer), sulfodihexosylceramides (SulfoHex2Cer), phosphatidylglycerols (PG), phosphatidylinositols (PI), lysophosphatidylinositols (LPI), and phosphatidylserines (PS). The method is fully validated for the quantitation of the studied lipids in kidney normal and tumor tissues of renal cell carcinoma (RCC) patients based on the lipid class separation and the coelution of lipid class internal standard with the species from the same lipid class. The raw data are semi-automatically processed using our software LipidQuant and statistically evaluated using multivariate data analysis (MDA) methods, which allows the complete differentiation of both groups with 100% specificity and sensitivity. In total, 21 GM3, 28 SulfoHexCer, 26 SulfoHex2Cer, 10 PG, 19 PI, 4 LPI, and 7 PS are determined in the aqueous phase of lipidomic extracts from kidney tumor tissue samples and surrounding normal tissue samples of 20 RCC patients. S-plots allow the identification of most upregulated (PI 40:5, PI 40:4, GM3 34:1, and GM3 42:2) and most downregulated (PI 32:0, PI 34:0, PS 36:4, and LPI 16:0) lipids, which are primarily responsible for the differentiation of tumor and normal groups. Another confirmation of most dysregulated lipids is performed by the calculation of fold changes together with T and p values to highlight their statistical significance. The comparison of HILIC/ESI-MS data and matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) data confirms that lipid dysregulation patterns are similar for both methods. Graphical abstract ᅟ.

A panel containing PD-1, IL-2Rα, IL-10, and CA15-3 as a biomarker to discriminate breast cancer from benign breast disease

INTRODUCTION

Programmed cell death protein 1 (PD-1), an immune checkpoint molecule, has recently been recognized as a predictive and prognostic biomarker in several malignant tumors, but its diagnostic value remains largely unknown. We aimed to investigate the differential diagnostic efficiency of PD-1 and other immune molecules and propose a panel of immune molecules combined with cancer antigen 15-3 (CA15-3) to distinguish breast cancer (BC) from benign breast disease (BBD).

PATIENTS AND METHODS

Ninety-one eligible BC patients and 31 BBD patients were enrolled. Pretreatment peripheral blood was collected and tested for mRNA expression of PD-1, cytotoxic T lymphocyte antigen 4, forkhead box P3, transforming growth factor beta, interleukin-10 (IL-10), IL-2 receptor alpha (IL-2Rα), and cluster of differentiation 28 by quantitative reverse transcription PCR.

RESULTS

The diagnostic areas under curve (AUCs) of PD-1, IL-2Rα, and IL-10 for BC-BBD discrimination were 0.764, 0.758, and 0.743, respectively. The diagnostic efficiencies of these three parameters in distinguishing early-stage or advanced BC from BBD were consistent with a role in BC-BBD discrimination. A panel of PD-1 + IL-10 + IL-2Rα + CA15-3 showed the highest AUC (0.862), with a sensitivity of 0.933 and a specificity of 0.724, for BC-BBD discrimination. In addition, for early-stage BC discrimination, this panel also had the highest AUC (0.811), with a sensitivity of 0.933 and a specificity of 0.614, while for advanced BC discrimination, a panel of PD-1 + IL-10 + CA15-3 exhibited the highest AUC (0.896), with a sensitivity of 0.933 and a specificity of 0.783.

CONCLUSION

These data indicate that the panel containing PD-1, IL-2Rα, IL-10, and CA15-3 can effectively discriminate BC from BBD with a high efficiency. After further confirmation, it could be used to complement conventional imaging modalities, especially in discriminating early-stage BC from BBD.

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

Multiplatform plasma metabolic and lipid fingerprinting of breast cancer: A pilot control-case study in Colombian Hispanic women

Breast cancer (BC) is a highly heterogeneous disease associated with metabolic reprogramming. The shifts in the metabolome caused by BC still lack data from Latin populations of Hispanic origin. In this pilot study, metabolomic and lipidomic approaches were performed to establish a plasma metabolic fingerprint of Colombian Hispanic women with BC. Data from 1H-NMR, GC-MS and LC-MS were combined and compared. Statistics showed discrimination between breast cancer and healthy subjects on all analytical platforms. The differentiating metabolites were involved in glycerolipid, glycerophospholipid, amino acid and fatty acid metabolism. This study demonstrates the usefulness of multiplatform approaches in metabolic/lipid fingerprinting studies to broaden the outlook of possible shifts in metabolism. Our findings propose relevant plasma metabolites that could contribute to a better understanding of underlying metabolic shifts driven by BC in women of Colombian Hispanic origin. Particularly, the understanding of the up-regulation of long chain fatty acyl carnitines and the down-regulation of cyclic phosphatidic acid (cPA). In addition, the mapped metabolic signatures in breast cancer were similar but not identical to those reported for non-Hispanic women, despite racial differences.

Taurine, glutamic acid and ethylmalonic acid as important metabolites for detecting human breast cancer based on the targeted metabolomics

BACKGROUND

This study investigated the use of serum amino acids and organic acids profiles as the novel metabolites for screening breast cancer (BC) patients.

METHODS

A total of 116 subjects as training set were divided into the following three groups: BC patients (n= 34), benign (BE) patients (n= 38) and controls (n= 44). The amino acids profiles from three groups were measured using liquid chromatography-mass spectrometry and organic acids profiles in three groups were studied by gas chromatography-mass spectrometry. The resultant study data set was subjected to multivariate statistical analysis to identify important metabolites related with BC and construct the criteria for discriminating BC patients from BE subjects or controls. A test data set derived from 60 patients (30 BC and 30 BE subjects) and 30 controls was used to validate the stability of the different metabolites.

RESULTS

The serum amino acids and organic acids profiles significantly differed between the BC patients, BE patients and the controls. Our results demonstrate that combinations of three candidate metabolites from taurine, glutamic acid and ethylmalonic acid were found to mirror tumour burden, with AUC values ranging from 0.751 to 0.834 when comparing BC patients to the controls. The areas under the curve from the taurine, glutamic acid and ethylmalonic acid in validated study were 0.901, 0.924 and 0.749, respectively.

CONCLUSIONS

This study shows that amino acids and organic acids profiles will be a potential screening tool for BC patients. The dysregulated metabolism of amino acids and organic acids in breast cancer might be useful for the diagnosis, therapy, prognosis and understanding the pathogenesis of breast cancer.