Increased levels of choline metabolites are an early marker of docetaxel treatment response in BRCA1-mutated mouse mammary tumors: an assessment by ex vivo proton magnetic resonance spectroscopy

Application of Metabolic Biomarkers in Breast Cancer: A Literature Review

Breast cancer is the most common cancer and the second leading cause of cancer death in women worldwide. Novel biomarkers for early diagnosis, treatment, and prognosis in breast cancer are needed and extensively studied. Metabolites, which are small molecules produced during metabolic processes, provide links between genetics, environment, and phenotype, making them useful biomarkers for diagnosis, prognosis, and disease classification. With recent advancements in metabolomics techniques, metabolomics research has expanded, which has led to significant progress in biomarker research. In breast cancer, alterations in metabolic pathways result in distinct metabolomic profiles that can be harnessed for biomarker discovery. Studies using mass spectrometry and nuclear magnetic resonance spectroscopy have helped identify significant changes in metabolites, such as amino acids, lipids, and organic acids, in the tissues, blood, and urine of patients with breast cancer, highlighting their potential as biomarkers. Integrative analysis of these metabolite biomarkers with existing clinical parameters is expected to improve the accuracy of breast cancer diagnosis and to be helpful in predicting prognosis and treatment responses. However, to apply these findings in clinical practice, larger cohorts for validation and standardized analytical methods for QC are necessary. In this review, we provide information on the current state of metabolite biomarker research in breast cancer, highlighting key findings and their clinical implications.

Insights into molecular mechanisms of chemotherapy resistance in cancer

Cancer heterogeneity poses a significant hurdle to the successful treatment of the disease, and is being influenced by genetic inheritance, cellular and tissue biology, disease development, and response to therapy. While chemotherapeutic drugs have demonstrated effectiveness, their efficacy is impeded by challenges such as presence of resilient cancer stem cells, absence of specific biomarkers, and development of drug resistance. Often chemotherapy leads to a myriad of epigenetic, transcriptional and post-transcriptional alterations in gene expression as well as changes in protein expression, thereby leading to massive metabolic reprogramming. This review seeks to provide a detailed account of various transcriptional regulations, proteomic changes, and metabolic reprogramming in various cancer models in response to three primary chemotherapeutic interventions, docetaxel, carboplatin, and doxorubicin. Discussing the molecular targets of some of these regulatory events and highlighting their contribution in sensitivity to chemotherapy will provide insights into drug resistance mechanisms and uncover novel perspectives in cancer treatment.

Matairesinol Nanoparticles Restore Chemosensitivity and Suppress Colorectal Cancer Progression in Preclinical Models: Role of Lipid Metabolism Reprogramming

Oncogenic-driven lipogenic metabolism is a common hallmark of colorectal cancer (CRC) progression. Therefore, there is an urgent need to develop novel therapeutic strategies for metabolic reprogramming. Herein, the metabolic profiles in the plasma between CRC patients and paired healthy controls were compared using metabolomics assays. Matairesinol downregulation was evident in CRC patients, and matairesinol supplementation significantly represses CRC tumorigenesis in azoxymethane/dextran sulfate sodium (AOM/DSS) colitis-associated CRC mice. Matairesinol rewired lipid metabolism to improve the therapeutic efficacy in CRC by inducing mitochondrial damage and oxidative damage and blunting ATP production. Finally, matairesinol-loaded liposomes significantly promoted the enhanced antitumor activity of 5-Fu/leucovorin combined with oxaliplatin (FOLFOX) in CDX and PDX mouse models by restoring chemosensitivity to the FOLFOX regimen. Collectively our findings highlight matairesinol-mediated lipid metabolism reprogramming as a novel druggable strategy to restore CRC chemosensitivity, and this nanoenabled approach for matairesinol will improve the chemotherapeutic efficacy with good biosafety.

Investigation of the apoptosis-inducing effect of docetaxel by a comprehensive LC-MS based metabolomics and network pharmacology approaches

Docetaxel is one of the clinical first-line drugs and its combination with other chemotherapy agents for advanced or metastatic cancers has attracted widespread attention. Therefore, to promote the clinical application of docetaxel alone or in combination, a comprehensive investigation of the metabolic mechanism of docetaxel is of great importance. Here, we apply an integrative analysis of metabolomics and network pharmacology to elucidate the underlying mechanisms of docetaxel. After taking the intersection of the above two methods, 5 pathways including ABC transporters, Central carbon metabolism in cancer, Glycolysis and Gluconeogenesis, Cysteine and methionine metabolism, and Arginine biosynthesis have been screened out. In concern of the interaction network of these pathways and the anti-apoptosis effect of docetaxel itself, the Central carbon metabolism in cancer pathway was mainly focused. This study may help delineate global landscapes of cellular protein-metabolite interactions, to provide molecular insights about their mechanisms of action, to promote the clinical applications at well.

Phosphatidylcholine-Derived Lipid Mediators: The Crosstalk Between Cancer Cells and Immune Cells

To become resistant, cancer cells need to activate and maintain molecular defense mechanisms that depend on an energy trade-off between resistance and essential functions. Metabolic reprogramming has been shown to fuel cell growth and contribute to cancer drug resistance. Recently, changes in lipid metabolism have emerged as an important driver of resistance to anticancer agents. In this review, we highlight the role of choline metabolism with a focus on the phosphatidylcholine cycle in the regulation of resistance to therapy. We analyze the contribution of phosphatidylcholine and its metabolites to intracellular processes of cancer cells, both as the major cell membrane constituents and source of energy. We further extended our discussion about the role of phosphatidylcholine-derived lipid mediators in cellular communication between cancer and immune cells within the tumor microenvironment, as well as their pivotal role in the immune regulation of therapeutic failure. Changes in phosphatidylcholine metabolism are part of an adaptive program activated in response to stress conditions that contribute to cancer therapy resistance and open therapeutic opportunities for treating drug-resistant cancers.

Metabolic Reprogramming of Chemoresistant Cancer Cells and the Potential Significance of Metabolic Regulation in the Reversal of Cancer Chemoresistance

Metabolic reprogramming is one of the hallmarks of tumors. Alterations of cellular metabolism not only contribute to tumor development, but also mediate the resistance of tumor cells to antitumor drugs. The metabolic response of tumor cells to various chemotherapy drugs can be analyzed by metabolomics. Although cancer cells have experienced metabolic reprogramming, the metabolism of drug resistant cancer cells has been further modified. Metabolic adaptations of drug resistant cells to chemotherapeutics involve redox, lipid metabolism, bioenergetics, glycolysis, polyamine synthesis and so on. The proposed metabolic mechanisms of drug resistance include the increase of glucose and glutamine demand, active pathways of glutaminolysis and glycolysis, promotion of NADPH from the pentose phosphate pathway, adaptive mitochondrial reprogramming, activation of fatty acid oxidation, and up-regulation of ornithine decarboxylase for polyamine production. Several genes are associated with metabolic reprogramming and drug resistance. Intervening regulatory points described above or targeting key genes in several important metabolic pathways may restore cell sensitivity to chemotherapy. This paper reviews the metabolic changes of tumor cells during the development of chemoresistance and discusses the potential of reversing chemoresistance by metabolic regulation.

Metabolomic studies of breast cancer in murine models: A review

BACKGROUND

Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies.

SCOPE OF REVIEW

This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturally-occurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study.

MAJOR CONCLUSIONS

Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination.

GENERAL SIGNIFICANCE

Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.

Race, the microbiome and colorectal cancer

In the past decade, more cancer researchers have begun to understand the significance of cancer prevention, which has prompted a shift in the increasing body of scientific literature. An area of fascination and great potential is the human microbiome. Recent studies suggest that the gut microbiota has significant roles in an individual's ability to avoid cancer, with considerable focus on the gut microbiome and colorectal cancer. That in mind, racial disparities with regard to colorectal cancer treatment and prevention are generally understudied despite higher incidence and mortality rates among Non-Hispanic Blacks compared to other racial and ethnic groups in the United States. A comprehension of ethnic differences with relation to colorectal cancer, dietary habits and the microbiome is a meritorious area of investigation. This review highlights literature that identifies and bridges the gap in understanding the role of the human microbiome in racial disparities across colorectal cancer. Herein, we explore the differences in the gut microbiota, common short chain fatty acids produced in abundance by microbes, and their association with racial differences in cancer acquisition.

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers?

Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.

Docetaxel Down-Regulates PD-1 Expression via STAT3 in T Lymphocytes

BACKGROUND

Lung tumor is a major cause of cancer incidence and patient death. Chemotherapy is the primary therapy used to treat lung cancer. In addition to direct cytotoxic effect on tumor cells, chemotherapeutic drugs activate immune responses to exert antitumor function. Here, the effects of docetaxel on the inhibitory molecules, programmed cell death 1 (PD-1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), and T-cell immunoglobulin and mucin domain 3 (TIM-3) in T lymphocytes were explored in patients with lung adenocarcinoma.

PATIENTS AND METHODS

Peripheral blood mononuclear cells were isolated from lung adenocarcinoma patients receiving cisplatin-docetaxel chemotherapy. By flow cytometry and PCR, the expressions of CTLA-4, PD-1 and TIM-3 in T cell subsets were analyzed. Health subjects were used as control group.

RESULTS

During chemotherapy, suppressive markers were down-regulated in peripheral CD4+ and CD8+ T cells from patients with partial remission or stable disease. Additionally, interferon-γ production was also augmented during this period. In vitro assay showed that docetaxel reduced the expression of PD-1 on T-cell subsets without altering cell death. Further tests in Jurkat T cells demonstrated that docetaxel activated signal transduction and activator of transcription 3 (STAT3) signaling to suppress PD-1 expression, whereas STAT3 inhibition reversed the down-regulation of PD-1.

CONCLUSION

Our data support the hypothesis that chemotherapeutic drugs are not only purely cytotoxic but are also immune modulators.

Correlation between Ki-67 Expression and Hemodynamics of Contrast-Enhanced Ultrasound in Patients with Breast Infiltrative Ductal Carcinoma

Breast cancer causes great threats to public health worldwide. The aim of this study was to investigate the correlation between Ki-67 expression and the hemodynamics of contrast-enhanced ultrasound (CEUS) in patients with infiltrative ductal carcinoma (IDC). CEUS was performed on 109 masses in 85 IDC cases before resection. Based on the immunohistochemical staining on the antigen Ki-67, the masses were divided into negative group, weakly positive group, positive group, and strong-positive group. Significant statistical differences were noticed in time to peak, arrive intensity, and peak intensity in the positive groups compared with the negative group. Compared with the positive groups, the negative group showed significant statistical differences in arrive intensity and peak intensity. The antigen Ki-67 was positively correlated with arrived intensity, intensity changes, and rising curve's slope. In contrast, it was negatively correlated with arrived time, time to peak, and continuous time. The hemodynamic parameters of CEUS were correlated with the expression of antigen Ki-67. On this basis, Ki-67 is an effective supplement to the diagnosis of IDC.

A Metabolomic Approach to Predict Breast Cancer Behavior and Chemotherapy Response

Although the classification of breast carcinomas into molecular or immunohistochemical subtypes has contributed to a better categorization of women into different therapeutic regimens, breast cancer nevertheless still progresses or recurs in a remarkable number of patients. Identifying women who would benefit from chemotherapy could potentially increase treatment effectiveness, which has important implications for long-term survival. Metabolomic analyses of fluids and tissues from cancer patients improve our knowledge of the reprogramming of metabolic pathways involved in resistance to chemotherapy. This review evaluates how recent metabolomic approaches have contributed to understanding the relationship between breast cancer and the acquisition of resistance. We focus on the advantages and challenges of cancer treatment and the use of new strategies in clinical care, which helps us comprehend drug resistance and predict responses to treatment.

Applications of Metabolomics in Cancer Studies

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics

INTRODUCTION

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

OBJECTIVES

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case-control, prognostic and longitudinal study designs.

METHODS

A literature search of the current relevant primary research was performed.

RESULTS

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case-control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

CONCLUSION

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.

Efficacy of single voxel 1H MR spectroscopic imaging at 3T for the differentiation of benign and malign breast lesions

PURPOSE

The aim of our study was to evaluate the effect of 1H Magnetic Resonance Spectroscopy (MRS) in differentiating breast lesions.

MATERIALS AND METHODS

Single voxel 1H Magnetic Resonance Spectroscopy (1H-MRS) was performed with 3T magnet in 45 women. The choline cut off point was set semi-quantitavely. Sensitivity, specificity and accuracy of MRS were calculated.

RESULTS

Twenty-four of 25 (96%) malignant and 9 of 26 (35%) benign lesions had choline peak. With the use cutoff value of 19,5 MRS provided a 96% sensitivity, 65% specificity and 80% accuracy.

CONCLUSION

MRS has a high diagnostic accuracy in differentiating breast lesions.

Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS)

According to World Health Organization (WHO) estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics.

Impact of Freezing Delay Time on Tissue Samples for Metabolomic Studies

Introduction

Metabolic profiling of intact tumor tissue by high-resolution magic angle spinning (HR MAS) MR spectroscopy (MRS) provides important biological information possibly useful for clinical diagnosis and development of novel treatment strategies. However, generation of high-quality data requires that sample handling from surgical resection until analysis is performed using systematically validated procedures. In this study, we investigated the effect of postsurgical freezing delay time on global metabolic profiles and stability of individual metabolites in intact tumor tissue.

Materials and methods

Tumor tissue samples collected from two patient-derived breast cancer xenograft models (n = 3 for each model) were divided into pieces that were snap-frozen in liquid nitrogen at 0, 15, 30, 60, 90, and 120 min after surgical removal. In addition, one sample was analyzed immediately, representing the metabolic profile of fresh tissue exposed neither to liquid nitrogen nor to room temperature. We also evaluated the metabolic effect of prolonged spinning during the HR MAS experiments in biopsies from breast cancer patients (n = 14). All samples were analyzed by proton HR MAS MRS on a Bruker Avance DRX600 spectrometer, and changes in metabolic profiles were evaluated using multivariate analysis and linear mixed modeling.

Results

Multivariate analysis showed that the metabolic differences between the two breast cancer models were more prominent than variation caused by freezing delay time. No significant changes in levels of individual metabolites were observed in samples frozen within 30 min of resection. After this time point, levels of choline increased, whereas ascorbate, creatine, and glutathione (GS) levels decreased. Freezing had a significant effect on several metabolites but is an essential procedure for research and biobank purposes. Furthermore, four metabolites (glucose, glycine, glycerophosphocholine, and choline) were affected by prolonged HR MAS experiment time possibly caused by physical release of metabolites caused by spinning or due to structural degradation processes.

Conclusion

The MR metabolic profiles of tumor samples are reproducible and robust to variation in postsurgical freezing delay up to 30 min.