Effects of α-zearalenol on the metabolome of two breast cancer cell lines by 1H-NMR approach

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.

Endocrine-disrupting compounds and metabolomic reprogramming in breast cancer

Endocrine-disrupting chemicals pose a growing threat to human health through their increasing presence in the environment and their potential interactions with the mammalian endocrine systems. Due to their structural similarity to hormones like estrogen, these chemicals can interfere with endocrine signaling, leading to many deleterious effects. Exposure to estrogenic endocrine-disrupting compounds (EDC) is a suggested risk factor for the development of breast cancer, one of the most frequently diagnosed cancers in women. However, the mechanisms through which EDCs contribute to breast cancer development remain elusive. To rapidly proliferate, cancer cells undertake distinct metabolic programs to utilize existing nutrients in the tumor microenvironment and synthesize macromolecules de novo. EDCs are known to dysregulate cell signaling pathways related to cellular metabolism, which may be an important mechanism through which they exert their cancer-promoting effects. These altered pathways can be studied via metabolomic analysis, a new advancement in -omics technologies that can interrogate molecular pathways that favor cancer development and progression. This review will summarize recent discoveries regarding EDCs and the metabolic reprogramming that they may induce to facilitate the development 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.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Metabolomics as an emerging approach for deciphering the biological impact and toxicity of food contaminants: the case of mycotoxins

Exposure to mycotoxins through the dietary route occurs on a daily basis while their deleterious effects are exhibited in the form of ailments, such as inflammation, cancer, and hormonal imbalance. The negative impact of mycotoxins can be attributed to their interaction with various biomolecules and their interference in metabolic pathways. The activity of biomolecules, such as enzymes/receptors, which engage the intricate mechanism of endogenous metabolism, is more susceptible to disruption by metabolites of high toxicity, which gives rise to adverse health effects. Metabolomics is a useful analytical approach that can assist in unraveling such information. It can simultaneously and comprehensively analyze a large number of endogenous and exogenous molecules present in biofluids and can, thus, reveal biologically relevant perturbations following mycotoxin exposure. Information provided by genome, transcriptome and proteome analyses, which have been utilized for the elucidation of biological mechanisms so far, are further complemented by the addition of metabolomics in the available bioanalytics toolbox. Metabolomics can offer insight into complex biological processes and their respective response to several (co-)exposures. This review focuses on the most extensively studied mycotoxins reported in literature and their respective impact on the metabolome upon exposure.

Mechanistic insights into zearalenone-accelerated colorectal cancer in mice using integrative multi-omics approaches

Zearalenone (ZEA), a secondary metabolite of Fusarium fungi found in cereal-based foods, promotes the growth of colon, breast, and prostate cancer cells in vitro. However, the lack of animal studies hinders a deeper mechanistic understanding of the cancer-promoting effects of ZEA. This study aimed to determine the effect of ZEA on colon cancer progression and its underlying mechanisms. Through integrative analyses of transcriptomics, metabolomics, metagenomics, and host phenotypes, we investigated the impact of a 4-week ZEA intervention on colorectal cancer in xenograft mice. Our results showed a twofold increase in tumor weight with the 4-week ZEA intervention. ZEA exposure significantly increased the mRNA and protein levels of BEST4, DGKB, and Ki67 and the phosphorylation levels of ERK1/2 and AKT. Serum metabolomic analysis revealed that the levels of amino acids, including histidine, arginine, citrulline, and glycine, decreased significantly in the ZEA group. Furthermore, ZEA lowered the alpha diversity of the gut microbiota and reduced the abundance of nine genera, including Tuzzerella and Rikenella. Further association analysis indicated that Tuzzerella was negatively associated with the expression of BEST4 and DGKB genes, serum uric acid levels, and tumor weight. Additionally, circulatory hippuric acid levels positively correlated with tumor weight and the expression of oncogenic genes, including ROBO3, JAK3, and BEST4. Altogether, our results indicated that ZEA promotes colon cancer progression by enhancing the BEST4/AKT/ERK1/2 pathway, lowering circulatory amino acid concentrations, altering gut microbiota composition, and suppressing short chain fatty acids production.

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.

Integrated metabolomics and transcriptomics analysis reveals new biomarkers and mechanistic insights on atrazine exposures in MCF‑7 cells

Atrazine (ATZ) is a widely used herbicide worldwide and is a long-suspected endocrine-disrupting chemical. However, most endocrine-disrupting toxicity studies on ATZ have been based on animal models and those investigating inner mechanisms have only focused on a few genes. Therefore, the possible link between ATZ and endocrine-disrupting toxicity is still unclear. In this study, multi-omics and molecular biology techniques were used to elucidate the possible molecular mechanisms underlying the effect of ATZ exposure on MCF-7 proliferation at environmentally relevant concentrations. Our study is the first report on ATZ-induced one carbon pool by folate metabolic disorder in MCF-7 cells. A concentration of 1 μM ATZ yielded the highest cell viability and was selected for further mechanistic studies. A total of 34 significantly changed metabolites were identified based on metabolomic analysis, including vitamins, amino acids, fatty acids, and corresponding derivatives. Folate and pyridoxal have potential as biomarkers of ATZ exposure. One carbon pool by folate metabolic pathway was identified based on metabolic pathway analysis of the significantly altered pathways. Moreover, FTCD and MTHFD related to this pathway were further identified based on transcriptomic analysis and protein assays. Folate and different forms of 5,6,7,8-tetrahydrofolate, which participate in purine synthesis and associate with methyl groups (SOPC, arachidonic acid, and L-tryptophan) in one carbon pool by the folate metabolic pathway, potentially promote MCF-7 cell proliferation. These findings on the key metabolites and regulation of the related differentially expressed genes in folate metabolism will shed light on the mechanism of MCF-7 cell proliferation after ATZ exposure. Overall, this study provides new insights into the mechanistic understanding of toxicity caused by endocrine-disrupting chemicals.

NMR-Based Metabolomics in Cancer Research

Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.

Endocrine-Disrupting Chemicals' (EDCs) Effects on Tumour Microenvironment and Cancer Progression: Emerging Contribution of RACK1

Endocrine disruptors (EDCs) can display estrogenic and androgenic effects, and their exposure has been linked to increased cancer risk. EDCs have been shown to directly affect cancer cell regulation and progression, but their influence on tumour microenvironment is still not completely elucidated. In this context, the signalling hub protein RACK1 (Receptor for Activated C Kinase 1) could represent a nexus between cancer and the immune system due to its roles in cancer progression and innate immune activation. Since RACK1 is a relevant EDCs target that responds to steroid-active compounds, it could be considered a molecular bridge between the endocrine-regulated tumour microenvironment and the innate immune system. We provide an analysis of immunomodulatory and cancer-promoting effects of different EDCs in shaping tumour microenvironment, with a final focus on the scaffold protein RACK1 as a pivotal molecular player due to its dual role in immune and cancer contexts.

Hormone-Independent Mouse Mammary Adenocarcinomas with Different Metastatic Potential Exhibit Different Metabolic Signatures

The metabolic characteristics of metastatic and non-metastatic breast carcinomas remain poorly studied. In this work, untargeted Nuclear Magnetic Resonance (NMR) metabolomics was used to compare two medroxyprogesterone acetate (MPA)-induced mammary carcinomas lines with different metastatic abilities. Different metabolic signatures distinguished the non-metastatic (59-2-HI) and the metastatic (C7-2-HI) lines, with glucose, amino acid metabolism, nucleotide metabolism and lipid metabolism as the major affected pathways. Non-metastatic tumours appeared to be characterised by: (a) reduced glycolysis and tricarboxylic acid cycle (TCA) activities, possibly resulting in slower NADH biosynthesis and reduced mitochondrial transport chain activity and ATP synthesis; (b) glutamate accumulation possibly related to reduced glutathione activity and reduced mTORC1 activity; and (c) a clear shift to lower phosphoscholine/glycerophosphocholine ratios and sphingomyelin levels. Within each tumour line, metabolic profiles also differed significantly between tumours (i.e., mice). Metastatic tumours exhibited marked inter-tumour changes in polar compounds, some suggesting different glycolytic capacities. Such tumours also showed larger intra-tumour variations in metabolites involved in nucleotide and cholesterol/fatty acid metabolism, in tandem with less changes in TCA and phospholipid metabolism, compared to non-metastatic tumours. This study shows the valuable contribution of untargeted NMR metabolomics to characterise tumour metabolism, thus opening enticing opportunities to find metabolic markers related to metastatic ability in endocrine breast cancer.

Evaluation of Aflatoxin M1 Effects on the Metabolomic and Cytokinomic Profiling of a Hepatoblastoma Cell Line

Hepatoblastoma incidence has been associated with different environmental factors even if no data are reported about a correlation between aflatoxin exposure and hepatoblastoma initiation. Considering that hepatoblastoma develops in infants and children and aflatoxin M1 (AFM1), the aflatoxin B1 (AFB1) hydroxylated metabolite, can be present in mothers' milk and in marketed milk products, in this study we decided to test the effects of AFM1 on a hepatoblastoma cell line (HepG2). Firstly, we evaluated the effects of AFM1 on the cell viability, apoptosis, cell cycle, and metabolomic and cytokinomic profile of HepG2 cells after treatment. AFM1 induced: (1) a decrease of HepG2 cell viability, reaching IC50 at 9 µM; (2) the blocking of the cell cycle in the G0/G1 phase; (3) the decrease of formiate levels and incremented level of some amino acids and metabolites in HepG2 cells after treatment; and (4) the increase of the concentration of three pro-inflammatory cytokines, IL-6, IL-8, and TNF-α, and the decrease of the anti-inflammatory interleukin, IL-4. Our results show that AFM1 inhibited the growth of HepG2 cells, inducing both a modulation of the lipidic, glycolytic, and amino acid metabolism and an increase of the inflammatory status of these cells.