Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences

Replenishment of TCA cycle intermediates and long-noncoding RNAs regulation in breast cancer

The tricarboxylic acid (TCA) cycle is an essential interface that coordinates cellular metabolism and is as a primary route determining the fate of a variety of fuel sources, including glucose, fatty acid and glutamate. The crosstalk of nutrients replenished TCA cycle regulates breast cancer (BC) progression by changing substrate levels-induced epigenetic alterations, especially the methylation, acetylation, succinylation and lactylation. Long non-coding RNAs (lncRNA) have dual roles in inhibiting or promoting energy reprogramming, and so altering the metabolic flux of fuel sources to the TCA cycle, which may regulate epigenetic modifications at the cellular level of BC. This narrative review discussed the central role of the TCA cycle in interconnecting numerous fuels and the induced epigenetic modifications, and the underlying regulatory mechanisms of lncRNAs in BC.

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

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

A journey from omics to clinicomics in solid cancers: Success stories and challenges

The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading cause of death worldwide, responsible for one in six deaths and hence imposes a significant burden on global healthcare systems. High-throughput omics technologies combined with advanced imaging tools, have revolutionized our ability to interrogate the molecular landscape of tumors and has provided unprecedented understanding of the disease. Yet, there is a gap between basic research discoveries and their translation into clinically meaningful therapies for improving patient care. To bridge this gap, there is a need to analyse the vast amounts of high dimensional datasets from multi-omics platforms. The integration of multi-omics data with clinical information like patient history, histological examination and imaging has led to the novel concept of clinicomics and may expedite the bench-to-bedside transition in cancer. The journey from omics to clinicomics has gained momentum with development of radiomics which involves extracting quantitative features from medical imaging data with the help of deep learning and artificial intelligence (AI) tools. These features capture detailed information about the tumor's shape, texture, intensity, and spatial distribution. Together, the related fields of multiomics, translational bioinformatics, radiomics and clinicomics may provide evidence-based recommendations tailored to the individual cancer patient's molecular profile and clinical characteristics. In this chapter, we summarize multiomics studies in solid cancers with a specific focus on breast cancer. We also review machine learning and AI based algorithms and their use in cancer diagnosis, subtyping, prognosis and predicting treatment resistance and relapse.

The potential of aryl hydrocarbon receptor as receptors for metabolic changes in tumors

Cancer cells can alter their metabolism to meet energy and molecular requirements due to unfavorable environments with oxygen and nutritional deficiencies. Therefore, metabolic reprogramming is common in a tumor microenvironment (TME). Aryl hydrocarbon receptor (AhR) is a ligand-activated nuclear transcription factor, which can be activated by many exogenous and endogenous ligands. Multiple AhR ligands can be produced by both TME and tumor cells. By attaching to various ligands, AhR regulates cancer metabolic reprogramming by dysregulating various metabolic pathways, including glycolysis, lipid metabolism, and nucleotide metabolism. These regulated pathways greatly contribute to cancer cell growth, metastasis, and evading cancer therapies; however, the underlying mechanisms remain unclear. Herein, we review the relationship between TME and metabolism and describe the important role of AhR in cancer regulation. We also focus on recent findings to discuss the idea that AhR acts as a receptor for metabolic changes in tumors, which may provide new perspectives on the direction of AhR research in tumor metabolic reprogramming and future therapeutic interventions.

LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer

BACKGROUND

Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach.

METHODS

In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels.

RESULTS

There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965.

CONCLUSION

This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Metabolomics and triple-negative breast cancer: A systematic review

Triple-negative breast cancer stands out as the most aggressive subtype of breast malignancy and is characterized by an unfavourable prognosis. Objective: This systematic review summarizes the insights gleaned from metabolomic analyses of individuals afflicted with this cancer variant. The overarching goal was to delineate the molecular alterations associated with triple-negative breast cancer, pinpointing potential therapeutic targets and novel biomarkers. Methods: We systematically searched for evidence using the PubMed database and followed the PRISMA and STARLITE guidelines. The search parameters were delimited to articles published within the last 13 years. Results: From an initial pool of 148 scrutinized articles, 17 studies involving 1686 participants were deemed eligible for inclusion. The current body of research shows a paucity of studies, and the available evidence presents conflicting outcomes. Notwithstanding, Pathway Enrichment Analysis identified the urea and glucose-alanine cycles as the most affected metabolic pathways, followed by arginine, proline, and aspartate metabolism. Conclusion: Future investigations need to focus on elucidating which of those metabolites and/or pathways might be reliable candidates for novel therapeutic interventions or reliable biomarkers for diagnosis and prognosis of this subtype of breast cancer.

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

Identification of metabolic pathways contributing to ER+ breast cancer disparities using a machine-learning pipeline

African American (AA) women in the United States have a 40% higher breast cancer mortality rate than Non-Hispanic White (NHW) women. The survival disparity is particularly striking among (estrogen receptor positive) ER+ breast cancer cases. The purpose of this study is to examine whether there are racial differences in metabolic pathways typically activated in patients with ER+ breast cancer. We collected pretreatment plasma from AA and NHW ER+ breast cancer cases (AA n = 48, NHW n = 54) and cancer-free controls (AA n = 100, NHW n = 48) to conduct an untargeted metabolomics analysis using gas chromatography mass spectrometry (GC-MS) to identify metabolites that may be altered in the different racial groups. Unpaired t-test combined with multiple feature selection and prediction models were employed to identify race-specific altered metabolic signatures. This was followed by the identification of altered metabolic pathways with a focus in AA patients with breast cancer. The clinical relevance of the identified pathways was further examined in PanCancer Atlas breast cancer data set from The Cancer Genome Atlas Program (TCGA). We identified differential metabolic signatures between NHW and AA patients. In AA patients, we observed decreased circulating levels of amino acids compared to healthy controls, while fatty acids were significantly higher in NHW patients. By mapping these metabolites to potential epigenetic regulatory mechanisms, this study identified significant associations with regulators of metabolism such as methionine adenosyltransferase 1A (MAT1A), DNA Methyltransferases and Histone methyltransferases for AA individuals, and Fatty acid Synthase (FASN) and Monoacylglycerol lipase (MGL) for NHW individuals. Specific gene Negative Elongation Factor Complex E (NELFE) with histone methyltransferase activity, was associated with poor survival exclusively for AA individuals. We employed a comprehensive and novel approach that integrates multiple machine learning and statistical methods, coupled with human functional pathway analyses. The metabolic profile of plasma samples identified may help elucidate underlying molecular drivers of disproportionately aggressive ER+ tumor biology in AA women. It may ultimately lead to the identification of novel therapeutic targets. To our knowledge, this is a novel finding that describes a link between metabolic alterations and epigenetic regulation in AA breast cancer and underscores the need for detailed investigations into the biological underpinnings of breast cancer health disparities.

The impact of lipid metabolism on breast cancer: a review about its role in tumorigenesis and immune escape

BACKGROUND

Breast cancer (BC) is the second most frequent type of cancer in the world and most common among women, configuring a major challenge to global health. BC is a complex and heterogeneous disease that can be subdivided into distinct tumor types based on the expression of molecular markers predicting patient outcomes and response to therapy. A growing number of studies have tried to expand the known markers by investigating the association of altered lipid metabolism with BC immune escape, progression, and metastasis. In this review, we describe the metabolic peculiarities of each BC subtype, understanding how this influences its aggressiveness and identifying whether these intrinsic vulnerabilities of each subtype can play a role in therapeutic management and may affect immune system cells in the tumor microenvironment.

CONCLUSION

The evidence suggests so far that when changes occur in lipid pathways, it can affect the availability of structural lipids for membrane synthesis, lipid synthesis, and degradation that contribute to energy homeostasis and cell signaling functions. These findings will guide the next steps on the path to understanding the mechanisms underlying how lipids alterations are related to disparities in chemotherapeutic response and immune escape in BC. Video Abstract.

G6PD activation in TNBC cells induces macrophage recruitment and M2 polarization to promote tumor progression

Glucose-6-phosphate dehydrogenase (G6PD) is involved in triple-negative breast cancer (TNBC) progression. Metabolic crosstalk between cancer cells and tumor-associated macrophages mediates tumor progression in TNBC. Molecular biological methods were applied to clarify the mechanism of the crosstalk between TNBC cells and M2 macrophages. In the present study, we verified that G6PD overexpression drives M2 macrophage polarization by directly combining with phospho-STAT1 and upregulating CCL2 and TGF-β1 secretion in TNBC cells. In turn, M2-like TAMs activated TNBC cells through IL-10 secretion, providing feedback to upregulate G6PD and promote TNBC cell migration and proliferation in vitro. Furthermore, we found that 6-AN (a specific inhibitor of G6PD) not only suppressed the cancer-driven polarization of macrophages toward the M2 phenotype but also inhibited the inherent M2 polarization of macrophages. Targeting the G6PD-regulated pentose phosphate pathway restrained TNBC progression and M2-type polarization of macrophages in vitro and in vivo.

High-resolution magic angle spinning NMR for intact biological specimen analysis: Initial discovery, recent developments, and future directions

High-resolution magic angle spinning (HRMAS) NMR, an approach for intact biological material analysis discovered more than 25 years ago, has been advanced by many technical developments and applied to many biomedical uses. This article provides a history of its discovery, first by explaining the key scientific advances that paved the way for HRMAS NMR's invention, and then by turning to recent developments that have profited from applying and advancing the technique during the last 5 years. Developments aimed at directly impacting healthcare include HRMAS NMR metabolomics applications within studies of human disease states such as cancers, brain diseases, metabolic diseases, transplantation medicine, and adiposity. Here, the discussion describes recent HRMAS NMR metabolomics studies of breast cancer and prostate cancer, as well as of matching tissues with biofluids, multimodality studies, and mechanistic investigations, all conducted to better understand disease metabolic characteristics for diagnosis, opportune windows for treatment, and prognostication. In addition, HRMAS NMR metabolomics studies of plants, foods, and cell structures, along with longitudinal cell studies, are reviewed and discussed. Finally, inspired by the technique's history of discoveries and recent successes, future biomedical arenas that stand to benefit from HRMAS NMR-initiated scientific investigations are presented.

NMR-Based Metabolomics to Evaluate Individual Response to Treatments

The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using ¹H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the ¹H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.

African American Women with Cardiometabolic Complications of Pregnancy Have Decreased Serum Abundance of Specialized Pro-Resolving Lipid Mediators and Endocannabinoids

African American (AA) women experience higher rates of maternal morbidity and mortality compared to US women of other racial/ ethnic groups. Cardiometabolic complications of pregnancy (including gestational diabetes, gestational hypertension, and preeclampsia) are leading contributors to maternal morbidity and mortality. Marked changes in circulating lipids are known to accompany cardiometabolic complications of pregnancy. Serum concentrations of docosahexaenoic acid (DHA) have been shown to be inversely correlated with risk for preeclampsia. DHA is a biosynthetic precursor of a class of specialized pro-resolving mediators (SPMs), resolvins, that have anti-inflammatory properties and are also associated with hypertensive disorders of pregnancy. We employed targeted lipidomics to characterize the distribution of DHA-containing phospholipids and SPMs in maternal serum collected in early and late pregnancy (8-14 weeks and 24-30 weeks gestation, respectively) to identify key lipids that are dysregulated during pregnancy in AA women who develop cardiometabolic complications. We identified a lipid signature in early pregnancy serum samples of AA women that is predictive of cardiometabolic complications of pregnancy with 74% accuracy. These are Resolvin D1, Resolvin E1, 2-AG, PGE2-glyerol ester, and 36:6 PC. These findings suggest that there are blood-based markers detectable in early pregnancy that can potentially identify persons at risk and tailor clinical interventions.

Cellular reprogramming, chemoresistance, and dietary interventions in breast cancer

Breast cancer (BC) diagnosis has been associated with significant risk factors, including family history, late menopause, obesity, poor eating habits, and alcoholism. Despite the advances in the last decades regarding cancer treatment, some obstacles still hinder the effectiveness of therapy. For example, chemotherapy resistance is common in locally advanced or metastatic cancer, reducing treatment options and contributing to mortality. In this review, we provide an overview of BC metabolic changes, including the impact of restrictive diets associated with chemoresistance, the therapeutic potential of the diet on tumor progression, pathways related to metabolic health in oncology, and perspectives on the future in the area of oncological nutrition.

Characterization of the Metabolome of Breast Tissues from Non-Hispanic Black and Non-Hispanic White Women Reveals Correlations between Microbial Dysbiosis and Enhanced Lipid Metabolism Pathways in Triple-Negative Breast Tumors

Simple Summary

We previously showed that breast tumor tissues from women display an imbalance in abundance and composition of microbiota compared to normal healthy breast tissues. It is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The aim of our study was to conduct global metabolic profiling on normal and breast tumor tissues to identify differences in metabolite profiles and to determine whether breast microbial dysbiosis may be associated with enrichment of microbial metabolites in triple-negative breast cancer (TNBC) which disproportionately affects women of African ancestry. We observed significant correlations between elevated lipid metabolism pathways and microbial dysbiosis in TNBC tissues from both non-Hispanic black and white women. This is the first study to report an association between breast microbial dysbiosis and alterations in host metabolic pathways in breast tumors, including TNBC, of non-Hispanic black and non-Hispanic white women.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer that is non-responsive to hormonal therapies and disproportionately impact women of African ancestry. We previously showed that TN breast tumors have a distinct microbial signature that differs from less aggressive breast tumor subtypes and normal breast tissues. However, it is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The goal of this global metabolomic profiling study was to investigate alterations in microbial metabolism pathways in normal and breast tumor tissues, including TNBC, of non-Hispanic black (NHB) and non-Hispanic white (NHW) women. In this study, we profiled the microbiome (16S rRNA) from breast tumor tissues and analyzed 984 metabolites from a total of 51 NHB and NHW women. Breast tumor tissues were collected from 15 patients with TNBC, 12 patients with less aggressive luminal A-type (Luminal) breast cancer, and 24 healthy controls for comparison using UHPLC-tandem mass spectrometry. Principal component analysis and hierarchical clustering of the global metabolomic profiling data revealed separation between metabolic signatures of normal and breast tumor tissues. Random forest analysis revealed a unique biochemical signature associated with elevated lipid metabolites and lower levels of microbial-derived metabolites important in controlling inflammation and immune responses in breast tumor tissues. Significant relationships between the breast microbiome and the metabolome, particularly lipid metabolism, were observed in TNBC tissues. Further investigations to determine whether alterations in sphingolipid, phospholipid, ceramide, amino acid, and energy metabolism pathways modulate Fusobacterium and Tenericutes abundance and composition to alter host metabolism in TNBC are necessary to help us understand the risk and underlying mechanisms and to identify potential microbial-based targets.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Metabolomics of Breast Cancer: A Review

Breast cancer is the most commonly diagnosed cancer in women worldwide. Major advances have been made towards breast cancer prevention and treatment. Unfortunately, the incidence of breast cancer is still increasing globally. Metabolomics is the field of science which studies all the metabolites in a cell, tissue, system, or organism. Metabolomics can provide information on dynamic changes occurring during cancer development and progression. The metabolites identified using cutting-edge metabolomics techniques will result in the identification of biomarkers for the early detection, diagnosis, and treatment of cancers. This review briefly introduces the metabolic changes in cancer with particular focus on breast cancer.

Metabolomic Impact of Lidocaine on a Triple Negative Breast Cancer Cell Line

Background: Metabolomics and onco-anesthesia are two emerging research fields in oncology. Metabolomics (metabolites analysis) is a new diagnostic and prognostic tool that can also be used for predicting the therapeutic or toxic responses to anticancer treatments. Onco-anesthesia studies assess the impact of anesthesia on disease-free and overall survival after cancer surgery. It has been shown that local anesthetics (LA), particularly lidocaine (LIDO), exert antitumor properties both in vitro and in vivo and may alter the biologic fingerprints of cancer cells. As LA are known to impair mitochondrial bioenergetics and byproducts, the aim of the present study was to assess the impact of LIDO on metabolomic profile of a breast cancer cell line.

Methods: Breast cancer MDA-MB-231 cells were exposed for 4 h to 0.5 mM LIDO or vehicle (n = 4). The metabolomic fingerprint was characterized by high resolution magic angle spinning NMR spectroscopy (HRMAS). The multivariate technique using the Algorithm to Determine Expected Metabolite Level Alteration (ADEMA) (Cicek et al., PLoS Comput. Biol., 2013, 9, e1002859), based on mutual information to identify expected metabolite level changes with respect to a specific condition, was used to determine the metabolites variations caused by LIDO.

Results: LIDO modulates cell metabolites levels. Several pathways, including glutaminolysis, choline, phosphocholine and total choline syntheses were significantly downregulated in the LIDO group.

Discussion: This is the first study assessing the impact of LIDO on metabolomic fingerprint of breast cancer cells. Among pathways downregulated by LIDO, many metabolites are reported to be associated with adverse prognosis when present at a high titer in breast cancer patients. These results fit with the antitumor properties of LIDO and suggest its impact on metabolomics profile of cancer cells. These effects of LIDO are of clinical significance because it is widely used for local anesthesia with cutaneous infiltration during percutaneous tumor biopsy. Future in vitro and preclinical studies are necessary to assess whether metabolomics analysis requires modification of local anesthetic techniques during tumor biopsy.

Metabolomics-Microbiome Crosstalk in the Breast Cancer Microenvironment

Breast cancer, the most frequent cancer diagnosed among females, is associated with a high mortality rate worldwide. Alterations in the microbiota have been linked with breast cancer development, suggesting the possibility of discovering disease biomarkers. Metabolomics has emerged as an advanced promising analytical approach for profiling metabolic features associated with breast cancer subtypes, disease progression, and response to treatment. The microenvironment compromises non-cancerous cells such as fibroblasts and influences cancer progression with apparent phenotypes. This review discusses the role of metabolomics in studying metabolic dysregulation in breast cancer caused by the effect of the tumor microenvironment on multiple cells such as immune cells, fibroblasts, adipocytes, etc. Breast tumor cells have a unique metabolic profile through the elevation of glycolysis and the tricarboxylic acid cycle metabolism. This metabolic profile is highly sensitive to microbiota activity in the breast tissue microenvironment. Metabolomics shows great potential as a tool for monitoring metabolic dysregulation in tissue and associating the findings with microbiome expression.

Impact of the Pd2Spm (Spermine) Complex on the Metabolism of Triple-Negative Breast Cancer Tumors of a Xenograft Mouse Model

The interest in palladium(II) compounds as potential new anticancer drugs has increased in recent years, due to their high toxicity and acquired resistance to platinum(II)-derived agents, namely cisplatin. In fact, palladium complexes with biogenic polyamines (e.g., spermine, Pd₂Spm) have been known to display favorable antineoplastic properties against distinct human breast cancer cell lines. This study describes the in vivo response of triple-negative breast cancer (TNBC) tumors to the Pd₂Spm complex or to cisplatin (reference drug), compared to tumors in vehicle-treated mice. Both polar and lipophilic extracts of tumors, excised from a MDA-MB-231 cell-derived xenograft mouse model, were characterized through nuclear magnetic resonance (NMR) metabolomics. Interestingly, the results show that polar and lipophilic metabolomes clearly exhibit distinct responses for each drug, with polar metabolites showing a stronger impact of the Pd(II)-complex compared to cisplatin, whereas neither drug was observed to significantly affect tumor lipophilic metabolism. Compared to cisplatin, exposure to Pd₂Spm triggered a higher number of, and more marked, variations in some amino acids, nucleotides and derivatives, membrane precursors (choline and phosphoethanolamine), dimethylamine, fumarate and guanidine acetate, a signature that may be relatable to the cytotoxicity and/or mechanism of action of the palladium complex. Putative explanatory biochemical hypotheses are advanced on the role of the new Pd₂Spm complex in TNBC metabolism.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

Expression of Autophagy and Mitophagy Markers in Breast Cancer Tissues

Mitochondria play important roles in regulating cell bioenergetics status and reactive oxygen species (ROS) generation. ROS-induced mitochondrial damage is among the main intracellular signal inducers of autophagy. Autophagy is a cellular catabolic process that regulates protein and organelle turnover, while a selective form of autophagy, mitophagy, specifically targets dysfunctional mitochondrial degradation. This study aims to measure the levels of autophagy, mitophagy, oxidative stress, and apoptosis in invasive breast carcinoma tissues using immunohistochemistry (IHC). Tissue microarrays of 76 patients with breast cancer were stained with six IHC markers (MnSOD, Beclin-1, LC3, BNIP3, Parkin, and cleaved caspase 3). The expression intensity was determined for each tumor tissue and the adjacent tumor-matched control tissues. Intermediate and strong staining scores of MnSOD, Beclin-1, LC-3, BNIP-3, and Parkin were significantly higher in tumor tissues compared to the adjacent matched control. The scoring intensity was further classified into tissues with negative staining and positive staining, which showed that positive scores of Beclin-1 and Parkin were significantly high in tumor tissues compared to other markers. Positive association was also noted between BNIP-3 and Beclin-1 as well as LC-3 and cleaved caspase-3 immunostaining. To our knowledge, this is one of the first studies that measure both mitophagy and autophagy in the same breast cancer tissues and the adjacent matched control. The findings from this study will be of great potential in identifying new cancer biomarkers and inspire significant interest in applying anti-autophagy therapies as a possible treatment for breast cancer.

Metabolomics in cancer research and emerging applications in clinical oncology

Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.

Organotypic 3D decellularized matrix tumor spheroids for high-throughput drug screening

Decellularized extracellular matrix (dECM) is emerging as a valuable tool for generating 3D in vitro tumor models that better recapitulate tumor-stroma interactions. However, the development of dECM-3D heterotypic microtumors exhibiting a controlled morphology is yet to be materialized. Precisely controlling microtumors morphologic features is key to avoid an inaccurate evaluation of therapeutics performance during preclinical screening. To address this, herein we employed ultra-low adhesion surfaces for bioengineering organotypic 3D metastatic breast cancer-fibroblast models enriched with dECM microfibrillar fragments, as a bottom-up strategy to include major matrix components and their associated biomolecular cues during the early stages of 3D microtissue spheroids assembly, simulating pre-existing ECM presence in the in vivo setting. This biomimetic approach enabled the self-assembly of dECM-3D tumor-stroma spheroids with tunable size and reproducible morphology. Along time, dECM enriched and stroma-rich microtumors exhibited necrotic core formation, secretion of key biomarkers and higher cancer-cell specific resistance to different chemotherapeutics in comparison to standard spheroids. Exometabolomics profiling of dECM-Spheroid in vitro models further identified important breast cancer metabolic features including glucose/pyruvate consumption and lactate excretion, which suggest an intense glycolytic activity, recapitulating major hallmarks of the native microenvironment. Such organotypic dECM-enriched microtumors overcome the morphologic variability generally associated with cell-laden dECM models, while providing a scalable testing platform that can be foreseeable leveraged for high-throughput screening of candidate therapeutics.

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry

Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of European ancestry (EA). In this study, we sought to identify molecular differences that could provide insight into the biology of ancestry-associated disparities in clinical outcomes. We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. We observed an enrichment of BasalMyo tumors in AA patients (38 vs 16.5% in EA, p = 1.30E - 10), associated with a significant worse overall (hazard ratio (HR) = 2.39, p = 0.02) and disease-specific survival (HR = 2.57, p = 0.03). Gene set enrichment analysis of BasalMyo AA and EA samples revealed differences in the abundance of T-regulatory and T-helper type 2 cells, and enrichment of cancer-related pathways with prognostic implications (AA: PI3K-Akt-mTOR and ErbB signaling; EA: EGF, estrogen-dependent and DNA repair signaling). Strikingly, AMPK signaling was associated with opposing prognostic connotation (AA: 10-year HR = 2.79, EA: 10-year HR = 0.34). Analysis of ArA patients suggests enrichment of BasalMyo tumors with a trend for differential enrichment of T-regulatory cells and AMPK signaling. Together, our findings suggest that the disparity in the clinical outcome of AA breast cancer patients is likely related to differences in cancer-related and microenvironmental features.

Determination of FABP4, RBP4 and the MMP-9/NGAL complex in the serum of women with breast cancer

Breast cancer is the most common type of cancer in females and is the leading cause of cancer-associated death among women, worldwide. The present study aimed to measure the serum levels of fatty acid-binding protein 4 (FABP4), retinol binding protein 4 (RBP4) and the MMP-9/neutrophil gelatinase-associated lipocalin (NGAL) complex in women diagnosed with breast cancer. Serum levels of the examined proteins were determined in the peripheral blood of patients via ELISA. Furthermore, whether the concentration of each protein was associated with breast cancer growth, molecular subtype, BMI, postmenopausal status, diabetes and the social background of patients was assessed. Women with invasive breast cancer demonstrated significantly higher levels of FABP4 (P=0.008). Additionally, considerably elevated FABP4 levels were demonstrated specifically in Luminal breast cancer cases (P<0.01). No significant association was recorded between RBP4 and breast cancer development. In addition, significantly lower levels of the MMP-9/NGAL complex were recorded in triple negative/HER-2 cases (P<0.05). BMI values appeared to influence the aforementioned associations, while significantly high serum levels of FABP4 and the MMP-9/NGAL complex were found in postmenopausal patients with breast cancer and a BMI ≥25 kg/m² (P<0.05). In addition, high levels of FABP4 were significantly associated with breast cancer patients with diabetes (P=0.05). However, no association was identified between RBP4, the MMP-9/NGAL complex and diabetes. In conclusion, FABP4 can be regarded as a biomarker of breast cancer growth, while both FABP4 and the MMP-9/NGAL complex may provide considerable information regarding the development of specific breast cancer subtypes. FABP4 and the MMP-9/NGAL complex may also be able to predict the development of breast cancer in postmenopausal patients with obesity.

Differential epigenetic and transcriptional profile in MCF-7 breast cancer cells exposed to cadmium

Cadmium (Cd) has been confirmed to be associated with breast carcinogenesis, but the mechanism was not clarified yet. Given that epigenetic modification was speculated as underlying mechanism, we examined the differential epigenome caused by Cd in breast cancer cells. Profiles of DNA methylation, microRNA (miRNA), long non-coding RNA (lncRNA), and message RNA (mRNA) were derived from Cd-treated and untreated MCF-7 breast cancer cells by microarray. We identified 997 target genes epigenetically regulated by Cd through cross-verification with the differential epigenome and transcriptome, and 400 of them were further validated in a breast cancer cohort. Biological function analyses suggested that several pathways were involved in Cd-induced breast carcinogenesis, such as Wnt signaling, metabolism, and human papilloma virus (HPV) infection. TXNRD1 and CCT3 were further identified as the critical genes based on the degree of expression change, hazard ratio difference, and connectivity. The present study revealed that Cd epigenetically regulated several pathways involving in breast carcinogenesis, particularly the Wnt signaling and metabolic pathways, among which TXNRD1 and CCT3 might play critical roles. It was also suggested that Cd and HPV infection might jointly participate in breast tumorigenesis.

Metabolic Signatures of Tumor Responses to Doxorubicin Elucidated by Metabolic Profiling in Ovo

BACKGROUND

Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models (in ovo) with metabolomics phenotyping could offer a robust platform for drug testing. Here, we assess the potential of this approach in the treatment of an in ovo triple negative breast cancer with doxorubicin.

METHODS

MB-MDA-231 cells were grafted in ovo. The resulting tumors were then treated with doxorubicin or dimethyl sulfoxide (DMSO) for six days. Tumors were collected and analyzed using a global untargeted metabolomics and comprehensive lipidomics.

RESULTS

We observed a significant suppression of tumor growth in the doxorubicin treated group. The metabolic profiles of doxorubicin and DMSO-treated tumors were clearly separated in a principle component analysis. Inhibition of glycolysis, nucleotide synthesis, and glycerophospholipid metabolism appear to be triggered by doxorubicin treatment, which could explain the observed suppressed tumor growth. In addition, metabolic cancer survival mechanisms could be supported by an acceleration of antioxidative pathways.

CONCLUSIONS

Metabolomics in combination with in ovo tumor models provide a robust platform for drug testing to reveal tumor specific treatment targets such as the antioxidative tumor capacity.

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).

Evaluation of MDA-MB-468 Cell Culture Media Analysis in Predicting Triple-Negative Breast Cancer Patient Sera Metabolic Profiles

Triple-negative breast cancer (TNBC) is characterized by limited survival, poor prognosis, and high recurrence. Understanding the metabolic adaptations of TNBC could help reveal improved treatment regiments. Here we performed a comprehensive ¹H NMR metabolic characterization of the MDA-MB-468 cell line, a commonly used model of TNBC, followed by an analysis of serum samples obtained from TNBC patients and healthy controls. MDA-MB-468 cells were cultured, and changes in the metabolic composition of the medium were monitored for 72 h. Based on time courses, metabolites were categorized as being consumed, being produced, or showing a mixed behavior. When comparing TNBC and control samples (HC), and by using multivariate and univariate analyses, we identified nine metabolites with differing profiles). The serum of TNBC patients was characterized by higher levels of glucose, glutamine, citrate, and acetoacetate and by lower levels of lactate, alanine, tyrosine, glutamate, and acetone. A comparative analysis between MDA-MB-468 cell culture media and TNBC patients' serum identified a potential systemic response to the carcinogenesis-associated processes, highlighting that MDA-MB-468 cells footprint does not reflect metabolic changes observed in studied TNBC serum fingerprint.

G protein-coupled kisspeptin receptor induces metabolic reprograming and tumorigenesis in estrogen receptor-negative breast cancer

Triple-negative breast cancer (TNBC) is a highly metastatic and deadly disease. TNBC tumors lack estrogen receptor (ERα), progesterone receptor (PR), and HER2 (ErbB2) and exhibit increased glutamine metabolism, a requirement for tumor growth. The G protein-coupled kisspeptin receptor (KISS1R) is highly expressed in patient TNBC tumors and promotes malignant transformation of breast epithelial cells. This study found that TNBC patients displayed elevated plasma kisspeptin levels compared with healthy subjects. It also provides the first evidence that in addition to promoting tumor growth and metastasis in vivo, KISS1R-induced glutamine dependence of tumors. In addition, tracer-based metabolomics analyses revealed that KISS1R promoted glutaminolysis and nucleotide biosynthesis by increasing c-Myc and glutaminase levels, key regulators of glutamine metabolism. Overall, this study establishes KISS1R as a novel regulator of TNBC metabolism and metastasis, suggesting that targeting KISS1R could have therapeutic potential in the treatment of TNBC.

Emergence in protein derived nanomedicine as anticancer therapeutics: More than a tour de force

Cancer has thwarted as a major health problem affecting the global population. With an alarming increase in the patient population suffering from diverse varieties of cancers, the global demographic data predicts sharp escalation in the number of cancer patients. This can be expected to reach 420 million cases by 2025. Among the diverse types of cancers, the most frequently diagnosed cancers are the breast, colorectal, prostate and lung cancer. From years, conventional treatment approaches like surgery, chemotherapy and radiation therapy have been practiced. In the past few years, increasing research on molecular level diagnosis and treatment of cancers have significantly changed the realm of cancer treatment. Lately, uses of advanced chemotherapy and immunotherapy like treatments have gained significant progress in the cancer therapy, but these approaches have several limitations on their safety and toxicity. This has generated lot of momentum for the evolution of new drug delivery approaches for the effective delivery of anticancer therapeutics, which may improve the pharmacokinetic and pharmacodynamic effect of the drugs along with significant reduction in the side effects. In this regard, the protein-based nano-medicines have gained wider attention in the management of cancer. Proteins are organic macromolecules essential, for life and have quite well explored in developing the nano-carriers. Furthermore, it provides passive or active tumour cell targeted delivery, by using protein based nanovesicles or virus like structures, antibody drug conjugates, viral particles, etc. Moreover, by utilizing various formulation strategies, both the animal and plant derived proteins can be converted to produce self-assembled virus like nano-metric structures with high efficiency in targeting the metastatic cancer cells. Therefore, the present review extensively discusses the applications of protein-based nano-medicine with special emphasis on intracellular delivery/drug targeting ability for anticancer drugs.

Clinical applications of breast cancer metabolomics using high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS): systematic scoping review

INTRODUCTION

Breast cancer is a heterogeneous disease with different prognoses and responses to systemic treatment depending on its molecular characteristics, which makes it imperative to develop new biomarkers for an individualized diagnosis and personalized oncological treatment. Ex vivo high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS) is the most common technique for metabolic quantification in human surgical and biopsy tissue specimens.

OBJECTIVE

To perform a review of the current available literature on the clinical applications of HRMAS 1H MRS metabolic analysis in tissue samples of breast cancer patients.

METHODS

This systematic scoping review included original research papers published in the English language in peer-reviewed journals. Study selection was performed independently by two reviewers and preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed.

RESULTS

The literature search returned 159 studies and 26 papers were included as part of this systematic review. There was considerable variation regarding tissue type, aims, and statistical analysis methods across the different studies. To facilitate the interpretation of the results, the included studies were grouped according to their aims or main outcomes into: feasibility and tumor diagnosis (n = 6); tumor heterogeneity (n = 2); correlation with proteomics/transcriptomics (n = 3); correlation with prognostic factors (n = 11); and response evaluation to NAC (n = 4).

CONCLUSION

There is a lot of potential in including metabolic information of breast cancer tissue obtained with HRMAS 1H MRS. To date, studies show that metabolic concentrations quantified by this technique can be related to the diagnosis, prognosis, and treatment response in breast cancer patients.

Characterization of triple-negative breast cancer preclinical models provides functional evidence of metastatic progression

Triple-negative breast cancer (TNBC), an aggressive, metastatic and recurrent breast cancer (BC) subtype, currently suffers from a lack of adequately described spontaneously metastatic preclinical models that faithfully reproduce the clinical scenario. We describe two preclinical spontaneously metastatic TNBC orthotopic murine models for the development of advanced therapeutics: an immunodeficient human MDA-MB-231-Luc model and an immunocompetent mouse 4T1 model. Furthermore, we provide a broad range of multifactorial analysis for both models that could provide relevant information for the development of new therapies and diagnostic tools. Our comparisons uncovered differential growth rates, stromal arrangements and metabolic profiles in primary tumors, and the presence of cancer-associated adipocyte infiltration in the MDA-MB-231-Luc model. Histopathological studies highlighted the more rapid metastatic spread to the lungs in the 4T1 model following a lymphatic route, while we observed both homogeneous (MDA-MB-231-Luc) and heterogeneous (4T1) metastatic spread to axillary lymph nodes. We encountered unique metabolomic signatures in each model, including crucial amino acids and cell membrane components. Hematological analysis demonstrated severe leukemoid and lymphoid reactions in the 4T1 model with the partial reestablishment of immune responses in the immunocompromised MDA-MB-231-Luc model. Additionally, we discovered β-immunoglobulinemia and increased basal levels of G-CSF correlating with a metastatic switch, with G-CSF also promoting extramedullary hematopoiesis (both models) and causing hepatosplenomegaly (4T1 model). Overall, we believe that the characterization of these preclinical models will foster the development of advanced therapeutic strategies for TNBC treatment, especially for the treatment of patients presenting both, primary tumors and metastatic spread.

Metabolic crosstalk in the breast cancer microenvironment

During tumorigenesis, breast tumour cells undergo metabolic reprogramming, which generally includes enhanced glycolysis, tricarboxylic acid cycle activity, glutaminolysis and fatty acid biosynthesis. However, the extension and functional importance of these metabolic alterations may diverge not only according to breast cancer subtypes, but also depending on the interaction of cancer cells with the complex surrounding microenvironment. This microenvironment comprises a variety of non-cancerous cells, such as immune cells (e.g. macrophages, lymphocytes, natural killer cells), fibroblasts, adipocytes and endothelial cells, together with extracellular matrix components and soluble factors, which influence cancer progression and are predictive of clinical outcome. The continuous interaction between cancer and stromal cells results in metabolic competition and symbiosis, with oncogenic-driven metabolic reprogramming of cancer cells shaping the metabolism of neighbouring cells and vice versa. This review addresses current knowledge on this metabolic crosstalk within the breast tumour microenvironment (TME). Improved understanding of how metabolism in the TME modulates cancer development and evasion of tumour-suppressive mechanisms may provide clues for novel anticancer therapeutics directed to metabolic targets.

Recent advances in metabolomics of triple negative breast cancer

Triple-negative Breast Cancer (TNBC) is considered as the most aggressive subtype of breast cancer. Metabolic profiling has a great significance in cancer research due to profound changes in the metabolism of cancer cells. It has been used to investigate the entire set of metabolites and changes associated with it in disease conditions. These changes in the expression levels of metabolites bring functional changes associated with the pharmacological or nutritional intervention. The present minireview presents a brief note on changes associated with TNBC aggressiveness in terms of metabolomics.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

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

MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis

We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.

Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. A Review

Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted.

Plasma Peptidome Pattern of Breast Cancer Using Magnetic Beads-Based Plasma Fractionation and MALDI-TOF MS: A Case Control Study in Egypt

Objective: The present study aimed to determine peptidome patterns in breast cancer (BC). Methods: We analyzed the plasma proteomic profiling of 80 BC patients and 50 healthy controls, using hydrophobic interaction chromatography magnetic beads (MB-HIC8) separation followed by Matrix assisted laser desorption ionization/ time of flight mass spectrometry (MALDI-TOF MS). Results: ClinProTools software identified 92 peaks that differed among the analyzed groups, 33 peaks were significantly different (P < 0.05). Of those, 22 peaks were up-regulated while 11 peaks were down-regulated in BC patients compared with the healthy controls. Three peptide ion signatures (m/z 1,570.31, 1,897.4 and 2,568.17) were provided by the Quick Classifier model to discriminate BC patients from healthy control subjects with 96.4% accuracy. External validation was performed by an independent group and this achieved a sensitivity of 100% and a specificity of 76.9%. Conclusion: MALDI-TOF MS has good analytical performance in distinguishing BC patients from healthy controls.

Whole Genome Transcriptome Analysis of the Association between Obesity and Triple-Negative Breast Cancer in Caucasian Women

Background: Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer, with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this exploratory study was to investigate the association between obesity and TNBC in premenopausal and postmenopausal Caucasian women using transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight, and obese pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight, and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways associating obesity with TNBC. The discovered pathways included the unfolded protein response, endoplasmic reticulum stress, B cell receptor, and autophagy signaling pathways in obese premenopausal women; and the integrin, axonal guidance, ERK/MAPK (extracellular-signal-regulated kinase/mitogen activated protein kinase) and glutathione biosynthesis signaling pathways in obese postmenopausal women. Conclusions: The results suggest that both overweight and obese status are associated with TNBC, highlighting the need for conformation of these results in independent studies.

Metabolic fingerprinting in breast cancer stages through 1H NMR spectroscopy-based metabolomic analysis of plasma

Breast cancer (BC) is one of the most common malignancies among women worldwide, which is indeed associated with metabolic reprogramming. However, BC is a very complex and heterogeneous disease, which can relate with the changes in metabolic profiles during BC progression. Hence, investigating the metabolic alterations during BC stage progression may reveal the deregulated pathways and useful metabolic signatures of BC. To demonstrate the metabolic insights, we opted ¹H NMR spectroscopy based metabolomics of blood plasma of early and late stage BC (N = 72) with age and gender matched healthy subjects (N = 50). Further, the metabolic profiles were analyzed to delineate the potential signatures of BC by performing multivariate and nonparametric statistical analysis in early and late stages of BC in comparison with healthy subjects. Sixteen metabolites levels were differentially changed (p < 0.05) in the early and late stages of BC from healthy subjects. Among them, the levels of hydroxybutyrate, lysine, glutamate, glucose, N-acetyl glycoprotein, Lactate were highly distinguished in BC stages and showed a good biomarker potential using receiver-operating curves based diagnostic models. Furthermore, the significant modulation and good diagnostic performances of glutamate, N-acetyl glycoprotein and Lactate in LBC as compared to EBC give their significance in the BC progression. In general, our observations demonstrate that these panels of metabolites may act as vital component of the metabolism of early to late stage BC progression. Our results also open new avenue towards early and late stage BC diagnosis and intervention implying metabolomics approaches.

Metabolomics in breast cancer: A decade in review

Breast cancer (BC) is a heterogeneous disease which has been characterised and stratified by many platforms such as clinicopathological risk factors, genomic assays, computer generated models, and various "-omic" technologies. Genomic, proteomic and transcriptomic analysis in breast cancer research is well established, and metabolomics, which can be considered a downstream manifestation of the former disciplines, is of growing interest. The past decade has seen significant progress made within the field of clinical metabolomic BC research, with several groups demonstrating results with significant promise in the setting of BC screening and biological characterisation, as well as future potential for prognostic metabolomic biomarkers.