Application of metabolomics in drug resistant breast cancer research

Oxidative Stress in Breast Cancer: A Biochemical Map of Reactive Oxygen Species Production

This review systematizes information about the metabolic features of breast cancer directly related to oxidative stress. It has been shown those redox changes occur at all levels and affect many regulatory systems in the human body. The features of the biochemical processes occurring in breast cancer are described, ranging from nonspecific, at first glance, and strictly biochemical to hormone-induced reactions, genetic and epigenetic regulation, which allows for a broader and deeper understanding of the principles of oncogenesis, as well as maintaining the viability of cancer cells in the mammary gland. Specific pathways of the activation of oxidative stress have been studied as a response to the overproduction of stress hormones and estrogens, and specific ways to reduce its negative impact have been described. The diversity of participants that trigger redox reactions from different sides is considered more fully: glycolytic activity in breast cancer, and the nature of consumption of amino acids and metals. The role of metals in oxidative stress is discussed in detail. They can act as both co-factors and direct participants in oxidative stress, since they are either a trigger mechanism for lipid peroxidation or capable of activating signaling pathways that affect tumorigenesis. Special attention has been paid to the genetic and epigenetic regulation of breast tumors. A complex cascade of mechanisms of epigenetic regulation is explained, which made it possible to reconsider the existing opinion about the triggers and pathways for launching the oncological process, the survival of cancer cells and their ability to localize.

The emerging regulatory roles of non-coding RNAs associated with glucose metabolism in breast cancer

Altered energy metabolism is one of the hallmarks of tumorigenesis and essential for fulfilling the high demand for metabolic energy in a tumor through accelerating glycolysis and reprogramming the glycolysis metabolism through the Warburg effect. The dysregulated glucose metabolic pathways are coordinated not only by proteins coding genes but also by non-coding RNAs (ncRNAs) during the initiation and cancer progression. The ncRNAs are responsible for regulating numerous cellular processes under developmental and pathological conditions. Recent studies have shown that various ncRNAs such as microRNAs, circular RNAs, and long noncoding RNAs are extensively involved in rewriting glucose metabolism in human cancers. In this review, we demonstrated the role of ncRNAs in the progression of breast cancer with a focus on outlining the aberrant expression of glucose metabolic pathways. Moreover, we have discussed the existing and probable future applications of ncRNAs to regulate energy pathways along with their importance in the prognosis, diagnosis, and future therapeutics for human breast carcinoma.

The Interplay between Microbiota and Chemotherapy-Derived Metabolites in Breast Cancer

The most common cancer in women is breast cancer, which is also the second leading cause of death in this group. It is, however, important to note that some women will develop or will not develop breast cancer regardless of whether certain known risk factors are present. On the other hand, certain compounds are produced by bacteria in the gut, such as short-chain fatty acids, secondary bile acids, and other metabolites that may be linked to breast cancer development and mediate the chemotherapy response. Modeling the microbiota through dietary intervention and identifying metabolites directly associated with breast cancer and its complications may be useful to identify actionable targets and improve the effect of antiangiogenic therapies. Metabolomics is therefore a complementary approach to metagenomics for this purpose. As a result of the combination of both techniques, a better understanding of molecular biology and oncogenesis can be obtained. This article reviews recent literature about the influence of bacterial metabolites and chemotherapy metabolites in breast cancer patients, as well as the influence of diet.

Monolayer LDH Nanosheets with Ultrahigh ICG Loading for Phototherapy and Ca2+-Induced Mitochondrial Membrane Potential Damage to Co-Enhance Cancer Immunotherapy

Tumor recurrence and metastasis are the main causes of cancer mortality; traditional chemotherapeutic drugs have severe toxicity and side effects in cancer treatment. To overcome these issues, here, we present a pH-responsive, self-destructive intelligent nanoplatform for magnetic resonance/fluorescence dual-mode image-guided mitochondrial membrane potential damage (MMPD)/photodynamic (PDT)/photothermal (PTT)/immunotherapy for breast cancer treatment with external near infrared (NIR) light irradiation. To do so, we construct multifunctional monolayer-layered double hydroxide (LDH) nanosheets (MICaP), co-loading indocyanine green (ICG) with ultrahigh loading content realized via electrostatic interactions, and calcium phosphate (Ca3(PO4)2) coating via biomineralization. Such a combined therapy design is featured by the outstanding biocompatibility and provokes immunogenic cell death (ICD) of tumors toward cancer immunotherapy. The active transport of excess Ca2+ released from pH-sensitive Ca3(PO4)2 can induce MMPD of tumor cells to minimize oxygen consumption in the tumor microenvironment (TME). The presence of ICG not only generates singlet oxygen (1O2) to induce apoptosis by photodynamic therapy (PDT) but also initiates tumor cell necrosis by photothermal therapy (PTT) under near-infrared (NIR) light radiation. Eventually, the immune response generated by MMPD/PDT/PTT greatly promotes a cytotoxic T lymphocyte (CTL) response that can limit tumor growth and metastasis. Both in vitro and in vivo studies indeed illustrate outstanding antitumor efficiency and outcomes. We anticipate that such precisely designed nanoformulations can contribute in a useful and advantageous way that is conducive to explore novel nanomedicines with notable values in antitumor therapy.

When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.

Transcriptomics and Lipid Metabolomics Analysis of Subcutaneous, Visceral, and Abdominal Adipose Tissues of Beef Cattle

Fat deposition traits are influenced by genetics and environment, which affect meat quality, growth rate, and energy metabolism of domestic animals. However, at present, the molecular mechanism of fat deposition is not entirely understood in beef cattle. Therefore, the current study conducted transcriptomics and lipid metabolomics analysis of subcutaneous, visceral, and abdominal adipose tissue (SAT, VAT, and AAT) of Huaxi cattle to investigate the differences among these adipose tissues and systematically explore how candidate genes interact with metabolites to affect fat deposition. These results demonstrated that compared with SAT, the gene expression patterns and metabolite contents of VAT and AAT were more consistent. Particularly, SCD expression, monounsaturated fatty acid (MUFA) and triglyceride (TG) content were higher in SAT, whereas PCK1 expression and the contents of saturated fatty acid (SFA), diacylglycerol (DG), and lysoglycerophosphocholine (LPC) were higher in VAT. Notably, in contrast to PCK1, 10 candidates including SCD, ELOVL6, ACACA, and FABP7 were identified to affect fat deposition through positively regulating MUFA and TG, and negatively regulating SFA, DG, and LPC. These findings uncovered novel gene resources and offered a theoretical basis for future investigation of fat deposition in beef cattle.

Metabolomics by NMR Combined with Machine Learning to Predict Neoadjuvant Chemotherapy Response for Breast Cancer

Simple Summary

Neoadjuvant chemotherapy (NACT) is offered to breast cancer (BC) patients to downstage the disease. However, some patients may not respond to NACT, being resistant. We used the serum metabolic profile by Nuclear Magnetic Resonance (NMR) combined with disease characteristics to differentiate between sensitive and resistant BC patients. We obtained accuracy above 80% for the response prediction and showcased how NMR can substantially enhance the prediction of response to NACT.

Abstract

Neoadjuvant chemotherapy (NACT) is offered to patients with operable or inoperable breast cancer (BC) to downstage the disease. Clinical responses to NACT may vary depending on a few known clinical and biological features, but the diversity of responses to NACT is not fully understood. In this study, 80 women had their metabolite profiles of pre-treatment sera analyzed for potential NACT response biomarker candidates in combination with immunohistochemical parameters using Nuclear Magnetic Resonance (NMR). Sixty-four percent of the patients were resistant to chemotherapy. NMR, hormonal receptors (HR), human epidermal growth factor receptor 2 (HER2), and the nuclear protein Ki67 were combined through machine learning (ML) to predict the response to NACT. Metabolites such as leucine, formate, valine, and proline, along with hormone receptor status, were discriminants of response to NACT. The glyoxylate and dicarboxylate metabolism was found to be involved in the resistance to NACT. We obtained an accuracy in excess of 80% for the prediction of response to NACT combining metabolomic and tumor profile data. Our results suggest that NMR data can substantially enhance the prediction of response to NACT when used in combination with already known response prediction factors.

Emerging Roles of Ceramides in Breast Cancer Biology and Therapy

One of the classic hallmarks of cancer is the imbalance between elevated cell proliferation and reduced cell death. Ceramide, a bioactive sphingolipid that can regulate this balance, has long been implicated in cancer. While the effects of ceramide on cell death and therapeutic efficacy are well established, emerging evidence indicates that ceramide turnover to downstream sphingolipids, such as sphingomyelin, hexosylceramides, sphingosine-1-phosphate, and ceramide-1-phosphate, is equally important in driving pro-tumorigenic phenotypes, such as proliferation, survival, migration, stemness, and therapy resistance. The complex and dynamic sphingolipid network has been extensively studied in several cancers, including breast cancer, to find key sphingolipidomic alterations that can be exploited to develop new therapeutic strategies to improve patient outcomes. Here, we review how the current literature shapes our understanding of how ceramide synthesis and turnover are altered in breast cancer and how these changes offer potential strategies to improve breast cancer therapy.

Metabolomics and EMT Markers of Breast Cancer: A Crosstalk and Future Perspective

Cancer cells undergo transient EMT and MET phenomena or vice versa, along with the parallel interplay of various markers, often correlated as the determining factor in decoding metabolic profiling of breast cancers. Moreover, various cancer signaling pathways and metabolic changes occurring in breast cancer cells modulate the expression of such markers to varying extents. The existing research completed so far considers the expression of such markers as determinants regulating the invasiveness and survival of breast cancer cells. Therefore, this manuscript is crosstalk among the expression levels of such markers and their correlation in regulating the aggressiveness and invasiveness of breast cancer. We also attempted to cover the possible EMT-based metabolic targets to retard migration and invasion of breast cancer.

Metabolomics Signatures and Subsequent Maternal Health among Mothers with a Congenital Heart Defect-Affected Pregnancy

Congenital heart defects (CHDs) are the most prevalent and serious of all birth defects in the United States. However, little is known about the impact of CHD-affected pregnancies on subsequent maternal health. Thus, there is a need to characterize the metabolic alterations associated with CHD-affected pregnancies. Fifty-six plasma samples were identified from post-partum women who participated in the National Birth Defects Prevention Study between 1997 and 2011 and had (1) unaffected control offspring (n = 18), (2) offspring with tetralogy of Fallot (ToF, n = 22), or (3) hypoplastic left heart syndrome (HLHS, n = 16) in this pilot study. Absolute concentrations of 408 metabolites using the AbsoluteIDQ® p400 HR Kit (Biocrates) were evaluated among case and control mothers. Twenty-six samples were randomly selected from above as technical repeats. Analysis of covariance (ANCOVA) and logistic regression models were used to identify significant metabolites after controlling for the maternal age at delivery and body mass index. The receiver operating characteristic (ROC) curve and area-under-the-curve (AUC) are reported to evaluate the performance of significant metabolites. Overall, there were nine significant metabolites (p < 0.05) identified in HLHS case mothers and 30 significant metabolites in ToF case mothers. Statistically significant metabolites were further evaluated using ROC curve analyses with PC (34:1), two sphingolipids SM (31:1), SM (42:2), and PC-O (40:4) elevated in HLHS cases; while LPC (18:2), two triglycerides: TG (44:1), TG (46:2), and LPC (20:3) decreased in ToF; and cholesterol esters CE (22:6) were elevated among ToF case mothers. The metabolites identified in the study may have profound structural and functional implications involved in cellular signaling and suggest the need for postpartum dietary supplementation among women who gave birth to CHD offspring.

The Comprehensive "Omics" Approach from Metabolomics to Advanced Omics for Development of Immune Checkpoint Inhibitors: Potential Strategies for Next Generation of Cancer Immunotherapy

In the past decade, immunotherapies have been emerging as an effective way to treat cancer. Among several categories of immunotherapies, immune checkpoint inhibitors (ICIs) are the most well-known and widely used options for cancer treatment. Although several studies continue, this treatment option has yet to be developed into a precise application in the clinical setting. Recently, omics as a high-throughput technique for understanding the genome, transcriptome, proteome, and metabolome has revolutionized medical research and led to integrative interpretation to advance our understanding of biological systems. Advanced omics techniques, such as multi-omics, single-cell omics, and typical omics approaches, have been adopted to investigate various cancer immunotherapies. In this review, we highlight metabolomic studies regarding the development of ICIs involved in the discovery of targets or mechanisms of action and assessment of clinical outcomes, including drug response and resistance and propose biomarkers. Furthermore, we also discuss the genomics, proteomics, and advanced omics studies providing insights and comprehensive or novel approaches for ICI development. The overview of ICI studies suggests potential strategies for the development of other cancer immunotherapies using omics techniques in future studies.

Long noncoding RNAs in triple-negative breast cancer: A new frontier in the regulation of tumorigenesis

In recent years, triple-negative breast cancer (TNBC) has emerged as the most aggressive subtype of breast cancer and is usually associated with increased mortality worldwide. The severity of TNBC is primarily observed in younger women, with cases ranging from approximately 12%-24% of all breast cancer cases. The existing hormonal therapies offer limited clinical solutions in completely circumventing the TNBC, with chemoresistance and tumor recurrences being the common hurdles in the path of TNBC treatment. Accumulating evidence has correlated the dysregulation of long noncoding RNAs (lncRNAs) with increased cell proliferation, invasion, migration, tumor growth, chemoresistance, and decreased apoptosis in TNBC. Various clinical studies have revealed that aberrant expression of lncRNAs in TNBC tissues is associated with poor prognosis, lower overall survival, and disease-free survival. Due to these specific characteristics, lncRNAs have emerged as novel diagnostic and prognostic biomarkers for TNBC treatment. However, the underlying mechanism through which lncRNAs perform their actions remains unclear, and extensive research is being carried out to reveal it. Therefore, understanding of mechanisms regulating the modulation of lncRNAs will be a substantial breakthrough in effective treatment therapies for TNBC. This review highlights the association of several lncRNAs in TNBC progression and treatment, along with their possible functions and mechanisms.

The evolving landscape of untargeted metabolomics

AIMS

Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics.

DATA SYNTHESIS

Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available.

CONCLUSIONS

Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.

Curcumin reverses doxorubicin resistance in colon cancer cells at the metabolic level

Doxorubicin (Dox) is commonly used for the treatment of malignant tumors, including colon cancer. However, the development of P-glycoprotein (P-gp)-mediated multidrug resistance (MDR) in tumor chemotherapy has seriously reduced the therapeutic efficacy of Dox. Natural product curcumin (Cur) was demonstrated to have a variety of pharmacological effects, such as anti-tumor, anti-oxidation and anti-aging activities. Here, we examined the MDR reversal capability of Cur in drug sensitive-(SW620) and resistant-(SW620/Ad300) colon cancer cells, and elucidated the underlying molecular mechanisms at the metabolic level. It was found that Cur reversed P-gp-mediated resistance in SW620/Ad300 cells by enhancing the Dox-induced cytotoxicity and apoptosis. Further mechanistic studies indicated that Cur inhibited the ATP-dependent transport activity of P-gp, thereby increasing the intra-celluar accumulation of Dox in drug-resistant cells. Metabolomics analysis based on UPLC-MS/MS showed that the MDR phenomenon in SW620/Ad300 cells was closely correlated with the upregulation of spermine and spermidine synthesis and D-glutamine metabolism. Cur significantly inhibited the biosynthesis of spermine and spermidine by decreasing the expression of ornithine decarboxylase (ODC) and suppressed D-glutamine metabolism, which in turn decreased the anti-oxidative stress ability and P-gp transport activity of SW620/Ad300 cells, eventually reversed MDR. These findings indicated the MDR reversal activity and the related mechanism of action of Cur, suggesting that Cur could be a promising MDR reversal agent for cancer treatment.

Cancer Omics in Africa: Present and Prospects

During the last century, cancer biology has been arguably one of the most investigated research fields. To gain deeper insight into cancer mechanisms, scientists have been attempting to integrate multi omics data in cancer research. Cancer genomics, transcriptomics, metabolomics, proteomics, and metagenomics are the main multi omics strategies used currently in the diagnosis, prognosis, treatment, and biomarker discovery in cancer. In this review, we describe the use of different multi omics strategies in cancer research in the African continent and discuss the main challenges facing the implementation of these approaches in African countries such as the lack of training programs in bioinformatics in general and omics strategies in particular and suggest paths to address deficiencies. As a way forward, we advocate for the establishment of an "African Cancer Genomics Consortium" to promote intracontinental collaborative projects and enhance engagement in research activities that address indigenous aspects for cancer precision medicine.

The free amino acid profiles and metabolic biomarkers of predicting the chemotherapeutic response in advanced sarcoma patients

PURPOSE

Metabolomics is an emerging field in cancer research. Plasma free amino acid profiles (PFAAs) have shown different features in various cancers, but the characteristic in advanced sarcoma remains unclear. We aimed to uncover the specific PFAAs in advanced sarcoma and to find the relationship between the altering of PFAAs and response to chemotherapy.

PATIENTS AND METHODS

We analyzed the differences in PFAAs between 23 sarcoma patients and 30 healthy subjects basing on liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, we compared the dynamics of PFAAs after chemotherapy between improvement group and deterioration group.

RESULTS

We identified seven biological differential amino acids and four pathways which were perturbed in the sarcoma patients compared with healthy subjects. After one cycle chemotherapy, the levels of γ-aminobutyric acid (GABA) and carnosine (Car) decreased significantly in the improvement group but not in deterioration group. The levels of α-aminobutyric acid (Abu) increased significantly in the deterioration group but not in the improvement group.

CONCLUSION

Our study suggests the potential specific PFAAs in sarcoma patients. The unusual amino acids and metabolic pathways may provide ideas for clinical drugs targeting therapy. Three amino acids including Car, GABA and Abu may be metabolic biomarkers playing a role in dynamic monitoring of the therapeutic effect.

[Ten years of the Russian metabolomics: history of development and achievements]

Metabolomics is one of the omics sciences, the technologies of which are widely used today in many life sciences. Its application influenced the discovery of new biomarkers of diseases, the description of biochemical processes occurring in many organisms, laid the basis for a new generation of clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in the studies of Russian scientists, to demonstrate the main directions and achievements of the Russian science in this field. The review also highlights the history of metabolomics, existing problems and the place of Russian metabolomics in their solution.

Mechanistic Involvement of Long Non-Coding RNAs in Oncotherapeutics Resistance in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is one of the most lethal forms of breast cancer (BC), with a significant disease burden worldwide. Chemoresistance and lack of targeted therapeutics are major hindrances to effective treatments in the clinic and are crucial causes of a worse prognosis and high rate of relapse/recurrence in patients diagnosed with TNBC. In the last decade, long non-coding RNAs (lncRNAs) have been found to perform a pivotal role in most cellular functions. The aberrant functional expression of lncRNAs plays an ever-increasing role in the progression of diverse malignancies, including TNBC. Therefore, lncRNAs have been recently studied as predictors and modifiers of chemoresistance. Our review discusses the potential involvement of lncRNAs in drug-resistant mechanisms commonly found in TNBC and highlights various therapeutic strategies to target lncRNAs in this malignancy.

GC-MS based comparative metabolomic analysis of MCF-7 and MDA-MB-231 cancer cells treated with Tamoxifen and/or Paclitaxel

Breast cancer cells MCF-7 and MDA-MB-231 were treated with Tamoxifen (5 μM) or Paclitaxel (1 μM) or with a combination of the two drugs. Herein, we have employed gas chromatography coupled with mass spectroscopy to identify metabolic changes occurring as response to different drug treatments. We report the identification of sixty-one metabolites and overall the two studied cell lines showed a distinct metabolomic profile from each other. Further data analysis indicates that a total of 30 metabolites were significantly differentially abundant in MCF-7 drug-treated cells, most of the metabolic changes occurred when cells were treated with either Tamoxifen (15) or Paclitaxel (25). On the other side, a total of 31 metabolites were significantly differentially abundant in MDA-MB-31 cells with drug treatment. Similarly, to MCF-7 most of the metabolic changes occurred when cells were treated with either Tamoxifen (19) or Paclitaxel (20). In conclusion, this report demonstrates that Tamoxifen and/or Paclitaxel treatment have a pronounced effect on the main metabolic pathways in both breast cancer (BC) cell lines (MCF-7 and MDA-MB231), which could be used as a foundation for future investigations to understand the possible effect of these drugs on different metabolic pathways. SIGNIFICANCE: Metabolic profiling of cancer cells is a promising tool in tumor diagnosis, biomarker discovery and drug treatment protocols, since cancer cells exhibit altered metabolism when compared to normal cells. Although numerous studies have reported the use of various OMICs applications to investigate breast cancer cells, very few of these have performed thorough screening of metabolites in such cells. Our investigation highlights the first study to characterize MCF7 and MDA-MB-231 cancer cells treated with Tamoxifen and/or Paclitaxel and to identify the affected metabolic pathways. Such findings might play an important role in revealing the molecular bases of the underlying mechanism of action of these two frontline anti-breast cancer drugs.

Challenges and future of precision medicine strategies for breast cancer based on a database on drug reactions

Breast cancer (BC) is a malignancy with the highest incidence in women. Great progress has been made in research related to traditional precision medicine for BC. However, many reports have suggested that patients with BC have not benefited a lot from such progress. Thus, we analyze traditional precision medicine strategies for BC, sum up their limitations and challenges, and preliminarily propose future orientations of precision medicine strategies based on a database on drug reaction of patients with BC. According to related research, traditional precision medicine strategies for BC, which are based on molecular subtypes, perform pertinent treatments, new drug research and development according to molecular typing results. Nevertheless, these strategies still have some deficiencies. First, there are very few patients with each molecular subtype, the match ratio of drugs is low. Second, these strategies can not solve the problem of poor drug sensitivity resulting from heterogeneity. The main strategy we put forward in the present paper is based on patients’ varying drug reactions. Focusing on treating existing patients and maximizing the utilization of existing drugs, it is expected to not have deficiencies of traditional precision medicine for BC, including low match rate and poor therapeutic efficacy arising from tumor heterogeneity of BC.

Translational Metabolomics: Current Challenges and Future Opportunities

Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.

Metabolomics reveals the effect of valproic acid on MCF-7 and MDA-MB-231 cells

1. Breast cancer is one of the most common malignancies in women worldwide. Metabolomics has been shown to be a promising strategy to elucidate the underlying pathogenesis of cancer and identify new targets for cancer diagnosis and therapy. Valproic acid (VPA), a histone deacetylase inhibitor, is a potential new drug in tumor therapy. This work used metabolomics to examine the effect of VPA on metabolism in breast cancer cells.2. Based on UPLC-MS/MS, we identified 3137 differential metabolites in human breast cancer MCF-7 cells and 2472 differential metabolites in human breast cancer MDA-MB-231 cells after VPA treatment.3. We selected 63 differential metabolites from MCF-7 samples and 61 differential metabolites from MDA-MB-231 cells with the more conspicuous changing trend. Furfural was up-regulated after VPA treatment in both cell lines. In both samples, VPA exerted an effect on the beta-alanine metabolism pathway and the taurine and hypotaurine metabolism pathway.4. This study identified the effect of VPA on metabolites and metabolic pathways in breast cancer cells, and these findings may contribute to the identification of new targets for breast cancer treatment.

Synergistic effect of phototherapy and chemotherapy on bladder cancer cells

Drug resistance as an important barrier to cancer treatment, has a close relation with alteration of cancer metabolism. Therefore, in this study the synergistic effect of phototherapy and chemotherapy were investigated on the bladder cancer cells viability. The cytotoxicity effect of blue light irradiation was measured by the MTT assay. Glucose consumption, lactate and ammonium formation were analyzed in the blue LED-irradiated cancer cells culture. Also, the expression of some genes involved in apoptosis and epithelial-mesenchymal transition was assessed using real-time PCR in comparison with the control group. The analysis of the results indicated that blue light irradiation inhibited the cell viability in a dose-dependent manner. Blue light irradiation decreased the cell viability by 7% and 19% (p < .05) in 5637 cells at doses of 8.7 J/cm² and 17.5 J/cm² in comparison with the control group respectively. Glucose consumption, lactate and ammonium formation diminished in the blue LED-irradiated 5637 cells in both doses. The real time PCR results indicated that the expression of Bax increased in blue light-irradiated cells. In addition, the cell cycle analysis showed that blue light irradiation arrested the bladder cancer in the G1 phase. Also, the effect of combination therapy on cancer cells was investigated in presence of blue light irradiation and cisplatin. The obtained results of the MTT assay indicated that blue light irradiation enhance the cytotoxicity effect of cisplatin on bladder cancer cells.

A multi-state model of chemoresistance to characterize phenotypic dynamics in breast cancer

The development of resistance to chemotherapy is a major cause of treatment failure in breast cancer. While mathematical models describing the dynamics of resistant cancer cell subpopulations have been proposed, experimental validation has been difficult due to the complex nature of resistance that limits the ability of a single phenotypic marker to sufficiently identify the drug resistant subpopulations. We address this problem with a coupled experimental/modeling approach to reveal the composition of drug resistant subpopulations changing in time following drug exposure. We calibrate time-resolved drug sensitivity assays to three mathematical models to interrogate the models' ability to capture drug response dynamics. The Akaike information criterion was employed to evaluate the three models, and it identified a multi-state model incorporating the role of population heterogeneity and cellular plasticity as the optimal model. To validate the model's ability to identify subpopulation composition, we mixed different proportions of wild-type MCF-7 and MCF-7/ADR resistant cells and evaluated the corresponding model output. Our blinded two-state model was able to estimate the proportions of cell types with an R-squared value of 0.857. To the best of our knowledge, this is the first work to combine experimental time-resolved drug sensitivity data with a mathematical model of resistance development.

Integrated Network Pharmacology and Metabolomics Analysis of the Therapeutic Effects of Zi Dian Fang on Immune Thrombocytopenic Purpura

Current hormone-based treatments for immune thrombocytopenic purpura (ITP) are associated with potentially serious adverse reactions. Zi Dian Fang (ZDF) is a multi-target Traditional Chinese Medicine (TCM) used to treat both the symptoms and root causes of ITP, with fewer side effects than hormone-based treatments. This study analysis of the therapeutic effects of ZDF on ITP from three aspects: platelet proliferation, immunoregulation, and inflammation. After detection of 52 chemical constituents of ZDF by UPLC-Q-TOF/MS, The main targets and pathways affected by ZDF were screened by network pharmacology and verified by Western blot and ELISA. Meanwhile, metabolomics analysis were applied to a mouse model of ITP to identify and screen endogenous terminal metabolites differentially regulated by ZDF. Integrated network pharmacology and metabolomics analysis of the therapeutic effects of ZDF on ITP may be as follows: ZDF counteracts ITP symptoms mainly by inhibiting Ras/MAPKs (Ras/Mitogen-activated protein kinases) pathway, and the expression of upstream protein (Ras) and downstream protein (p-ERK, p-JNK, p-p38) were inhibited, which affects the content of effect index associated with proliferation (Thrombopoietin, TPO; Granulocyte-macrophage colony stimulating factor, GM-CSF), inflammation (Tumor necrosis factor-α, TNF-α; Interleukin-6, IL-6), immune (Interleukin-2, IL-2; Interferon-gamma, IFN-γ; Interleukin-4, IL-4), so that the body’s arginine, Δ¹²-prostaglandin j2 (Δ¹²-PGJ2), 9-cis-Retinoic Acid, sphingosine-1-phosphate (S1P), oleic acid amide and other 12 endogenous metabolites significantly changes. Considering the established safety profile, the present study suggests ZDF may be a useful alternative to hormone-based therapies for the treatment of ITP.

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.

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

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

Deciphering metabolic rewiring in breast cancer subtypes

Metabolic reprogramming, an emerging hallmark of cancer, is observed in breast cancer. Breast cancer cells rewire their cellular metabolism to meet the demands of survival, proliferation, and invasion. However, breast cancer is a heterogeneous disease, and metabolic rewiring is not uniform. Each subtype of breast cancer displays distinct metabolic alterations. Here, we focus on unique metabolic reprogramming associated with subtypes of breast cancer, as well as common features. Therapeutic opportunities based on subtype-specific metabolic alterations are also discussed. Through this discussion, we aim to provide insight into subtype-specific metabolic rewiring and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients.

Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges

The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now.

Impact of chemotherapy on metabolic reprogramming: Characterization of the metabolic profile of breast cancer MDA-MB-231 cells using 1H HR-MAS NMR spectroscopy

Doxorubicin, cisplatin, and tamoxifen are part of many chemotherapeutic regimens. However, studies investigating the effect of chemotherapy on the metabolism of breast cancer cells are still limited. We used ¹H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to study the metabolic profile of human breast cancer MDA-MB-231 cells either untreated (control) or treated with tamoxifen, cisplatin, and doxorubicin. ¹H HR-MAS NMR single pulse spectra evidenced signals from all mobile cell compounds, including fatty acids (membranes), water-soluble proteins, and metabolites. NMR spectra showed that phosphocholine (i.e., a biomarker of breast cancer malignant transformation) signals were stronger in control than in treated cells, but significantly decreased upon treatment with tamoxifen/cisplatin. NMR spectra acquired with Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence were interpreted only qualitatively because signal areas were attenuated according to their transverse relaxation times (T₂). The CPMG method was used to identify soluble metabolites such as organic acids, amino acids, choline and derivatives, taurine, guanidine acetate, tyrosine, and phenylalanine. The fatty acid variations observed by single pulse as well as the lactate, acetate, glycine, and phosphocholine variations observed through CPMG ¹H HR-MAS NMR have potential to characterize both responder and non-responder tumors in a molecular level. Additionally, we emphasized that comparable tumors (i.e., with the same origin, in this case breast cancer) may respond totally differently to chemotherapy. Our observations reinforce the theory that alterations in cellular metabolism may contribute to the development of a malignant phenotype and cell resistance.

Urine metabolomics as a predictor of patient tolerance and response to adjuvant chemotherapy in colorectal cancer

Colorectal cancer is the third leading cause of cancer-associated mortality in the western world. The ability to predict a patient's response to chemotherapy may be of great value for clinicians and patients when planning cancer treatment. The aim of the current study was to develop a urine metabolomics-based biomarker panel to predict adverse events and response to chemotherapy in patients with colorectal cancer. A retrospective chart review of patients diagnosed with stage III or IV colorectal cancer between 2008 and 2012 was performed. The exclusion criteria included chemotherapy for palliation and patients living outside of Alberta. Data was collected concerning the chemotherapy regimen, adverse events associated with chemotherapy, disease progression and recurrence and 5-year survival. Adverse events were subdivided as follows: Delays in treatment, dose reductions, hospitalizations and chemotherapy regime changes. Patients provided urine samples for analysis prior to any intervention. Nuclear magnetic resonance (NMR) spectra of urine samples were acquired. The 1H NMR spectrum of each urine sample was analyzed using Chenomx NMRSuite v7.0. Using machine learning, predictors were generated and evaluated using 10-fold cross-validation. Urine spectra were obtained for 62 patients. The best predictors resulted in area under the receiver operating characteristic curve values of: 0.542 for chemotherapy dose reduction, 0.612 for 5-year survival, 0.650 for cancer recurrence and 0.750 for treatment delay. Therefore, predictors were developed for response to and adverse events from chemotherapy for patients with colorectal cancer patients. The predictor for treatment delay has the most promise, and further studies will aid its refinement and improvement of its accuracy.

Treatment for the endocrine resistant breast cancer: Current options and future perspectives

Endocrine resistance remains a challenge and an unmet need for managing hormone receptor-positive breast cancer. The mechanisms of endocrine resistance are multifaceted and are likely to evolve over time following various single or combination therapies. The purpose of this review article is to provide general understanding of molecular basis of endocrine resistance of breast cancer and to offer comprehensive review on current treatment options and potential new treatment strategies for endocrine resistant breast cancers. Last but not the least, we discuss current challenges and future directions for management of endocrine resistant breast cancers.

Dopamine D2 receptor antagonist sulpiride enhances dexamethasone responses in the treatment of drug-resistant and metastatic breast cancer

Recent evidence shows that dopamine D2-like receptor (D2DR) antagonists, such as trifluoperazine and thioridazine, are effective for cancer therapy and inhibition of cancer stem-like cells (CSCs). In this study, we investigated the anti-cancer effects of combination therapy of dexamethasone (DEX) and sulpiride (SUL), an atypical antipsychotic, against drug-resistant and metastatic breast cancers and further explored the underlying mechanisms. Oral administration of SUL (25, 100 mg·kg^-1·d^-1) alone did not inhibit the tumor growth in human breast cancer MCF-7/Adr xenograft model, but dose-dependently decreased the proportion of CSCs in vitro and in vivo. In contrast, combination therapy of SUL (50 mg·kg^-1·d^-1) and DEX (8 mg·kg^-1·d^-1) markedly suppressed the tumor growth in MCF-7/Adr xenograft model with little systemic toxicity and lung metastasis in murine metastatic breast cancer 4T1 xenograft model. Among the metastasis-associated biomarkers analyzed, the combination therapy significantly decreased the levels of MMP-2, but increased E-cadherin levels in 4T1 xenograft tumors. Moreover, the combination therapy significantly inhibited the cell colony formation, migration and invasion of 4T1 and human breast cancer MDA-MB-231 cells in vitro. Addition of a specific D2DR agonist 7-OH-DPAT to the combination therapy reversed the enhanced anti-cancer effects in vivo and CSC population loss in tumor tissues. Our data demonstrate that SUL remarkably enhances the efficacy of DEX in the treatment of drug-resistant and metastatic breast cancer via the antagonism of D2DR, which might result from the eradication of CSCs.

Livestock metabolomics and the livestock metabolome: A systematic review

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

Mitochondrial "power" drives tamoxifen resistance: NQO1 and GCLC are new therapeutic targets in breast cancer

Here, we identified two new molecular targets, which are functionally sufficient to metabolically confer the tamoxifen-resistance phenotype in human breast cancer cells. Briefly, ~20 proteins were first selected as potential candidates, based on unbiased proteomics analysis, using tamoxifen-resistant cell lines. Then, the cDNAs of the most promising candidates were systematically transduced into MCF-7 cells. Remarkably, NQO1 and GCLC were both functionally sufficient to autonomously confer a tamoxifen-resistant metabolic phenotype, characterized by i) increased mitochondrial biogenesis, ii) increased ATP production and iii) reduced glutathione levels. Thus, we speculate that pharmacological inhibition of NQO1 and GCLC may be new therapeutic strategies for overcoming tamoxifen-resistance in breast cancer patients. In direct support of this notion, we demonstrate that treatment with a known NQO1 inhibitor (dicoumarol) is indeed sufficient to revert the tamoxifen-resistance phenotype. As such, these findings could have important translational significance for the prevention of tumor recurrence in ER(+) breast cancers, which is due to an endocrine resistance phenotype. Importantly, we also show here that NQO1 has significant prognostic value as a biomarker for the prediction of tumor recurrence. More specifically, higher levels of NQO1 mRNA strongly predict patient relapse in high-risk ER(+) breast cancer patients receiving endocrine therapy (mostly tamoxifen; H.R. > 2.15; p = 0.007).

Metabolomic profiling of breast tumors using ductal fluid

Identification of new biomarkers for breast cancer remains critical in order to enhance early detection of the disease and improve its prognosis. Towards this end, we performed an untargeted metabolomic analysis of breast ductal fluid using an ultra-performance liquid chromatography coupled with a quadrupole time-of-light (UPLC-QTOF) mass spectrometer. We investigated the metabolomic profiles of breast tumors using ductal fluid samples collected by ductal lavage (DL). We studied fluid from both the affected breasts and the unaffected contralateral breasts (as controls) from 43 women with confirmed unilateral breast cancer. Using this approach, we identified 1560 ions in the positive mode and 538 ions in the negative mode after preprocessing of the UPLC‑QTOF data. Paired t-tests applied on these data matrices identified 209 ions (positive and negative modes combined) with significant change in intensity level between affected and unaffected control breasts (adjusted p-values <0.05). Among these, 83 ions (39.7%) showed a fold change (FC) >1.2 and 66 ions (31.6%) were identified with putative compound names. The metabolites that we identified included endogenous metabolites such as amino acid derivatives (N-Acetyl-DL-tryptophan) or products of lipid metabolism such as N-linoleoyl taurine, trans-2-dodecenoylcarnitine, lysophosphatidylcholine LysoPC(18:2(9Z,12Z)), glycerophospholipids PG(18:0/0:0), and phosphatidylserine PS(20:4(5Z,8Z,11Z,14Z). Generalized LASSO regression further selected 21 metabolites when race, menopausal status, smoking, grade and TNM stage were adjusted for. A predictive conditional logistic regression model, using the LASSO selected 21 ions, provided diagnostic accuracy with the area under the curve of 0.956 (sensitivity/specificity of 0.907/0.884). This is the first study that shows the feasibility of conducting a comprehensive metabolomic profiling of breast tumors using breast ductal fluid to detect changes in the cellular microenvironment of the tumors and shows the potential for this approach to be used to improve detection of breast cancer.

Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis

This paper presents a review of the importance and role of precision medicine and molecular imaging technologies in cancer diagnosis with therapeutics and diagnostics purposes. Precision medicine is progressively becoming a hot topic in all disciplines related to biomedical investigation and has the capacity to become the paradigm for clinical practice. The future of medicine lies in early diagnosis and individually appropriate treatments, a concept that has been named precision medicine, i.e. delivering the right treatment to the right patient at the right time. Molecular imaging is quickly being recognized as a tool with the potential to ameliorate every aspect of cancer treatment. On the other hand, emerging high-throughput technologies such as omics techniques and systems approaches have generated a paradigm shift for biological systems in advanced life science research. In this review, we describe the precision medicine, difference between precision medicine and personalized medicine, precision medicine initiative, systems biology/medicine approaches (such as genomics, radiogenomics, transcriptomics, proteomics, and metabolomics), P4 medicine, relationship between systems biology/medicine approaches and precision medicine, and molecular imaging modalities and their utility in cancer treatment and diagnosis. Accordingly, the precision medicine and molecular imaging will enable us to accelerate and improve cancer management in future medicine.

Metabolomics: Bridging the Gap between Pharmaceutical Development and Population Health

Metabolomics has emerged as an essential tool for studying metabolic processes, stratification of patients, as well as illuminating the fundamental metabolic alterations in disease onset, progression, or response to therapeutic intervention. Metabolomics materialized within the pharmaceutical industry as a standalone assay in toxicology and disease pathology and eventually evolved towards aiding in drug discovery and pre-clinical studies via supporting pharmacokinetic and pharmacodynamic characterization of a drug or a candidate. Recent progress in the field is illustrated by coining of the new term—Pharmacometabolomics. Integration of data from metabolomics with large-scale omics along with clinical, molecular, environmental and behavioral analysis has demonstrated the enhanced utility of deconstructing the complexity of health, disease, and pharmaceutical intervention(s), which further highlight it as an essential component of systems medicine. This review presents the current state and trend of metabolomics applications in pharmaceutical development, and highlights the importance and potential of clinical metabolomics as an essential part of multi-omics protocols that are directed towards shaping precision medicine and population health.

Effects of Ketamine on Metabolomics of Serum and Urine in Cynomolgus Macaques (Macaca fascicularis)

In this study, a metabolomics approach based on nuclear magnetic resonance spectroscopy and pertinent multivariate data analyses was used to evaluate the effect of ketamine on metabolic markers in cynomolgus macaques. Principal component analysis and orthogonal projection to latent structure with discriminant analysis showed that ketamine (10 mg/kg) induced metabolic perturbations. Compared with the control group, ketamine-treated macaques had lower serum levels of α-glucose, myoinositol, lactate and succinate and lower urine levels of pyruvate and lactate. In contrast, the levels of leucine in serum and arginine in urine were significantly higher in the ketamine group. Our results also demonstrated that a single injection of ketamine influenced the major energy and amino acid metabolic pathways in cynomolgus macaques. Our study suggests that these influences should be considered in the design of experiments and the interpretation related blood and urine data from ketamine-sedated cynomolgus macaques.

Shenqi Fuzheng Injection Combined with Chemotherapy for Breast Cancer: A Meta-Analysis of Randomized Controlled Trials

Purpose. To evaluate the therapeutic effectiveness and safety of shenqi fuzheng injection (SFI) in the associated chemotherapy of breast cancer. Methods. 1247 subjects were included in this study for meta-analysis with RevMan 5.3. Results. The clinical curative effective rate (OR = 2.03, 95% Cl [1.44, 2.86], P < 0.0001), grades of KPS (OR = 4.11, 95% Cl [2.74, 6.16], P < 0.00001), CD3(+) cells (MD = 7.05, 95% Cl [0.45, 13.64], P = 0.04) and CD4(+) cells (MD = 8.60, 95% Cl [2.67, 14.54], P = 0.004) and CD4/CD8(+) cells (MD = 0.35, 95% Cl [0.14, 0.56], P = 0.001), WBC (OR = 0.30, 95% Cl [0.20, 0.46], P ≤ 0.0001), PLT (OR = 0.36, 95% Cl [0.20, 0.67], P = 0.001), gastrointestinal reaction (OR = 0.21, 95% Cl [0.14, 0.32], P < 0.00001), and ECG (OR = 0.26, 95% Cl [0.13, 0.51], P < 0.0001) in the experimental group were superior to the control group. While there were no differences between two groups in CD8(+) (MD = 0.21, 95% Cl [-2.81, 3.23], P = 0.89), NK(+) (MD = 1.06, 95% Cl [-9.40, 11.53], P = 0.84), RBC (OR = 0.49, 95% Cl [0.14, 1.74], P = 0.27), liver function (OR = 0.59, 95% Cl [0.28, 1.24], P = 0.16), renal function (OR = 0.56, 95% Cl [0.13, 2.45], P = 0.44), and bone marrow suppression (OR = 0.50, 95% Cl [0.25, 1.01], P = 0.05). Conclusion. SFI combined with chemotherapy, to some extent, can improve the effectiveness and the security in the treatment of breast cancer; the mechanism may be related to the elevated immunity.

Micheliolide overcomes KLF4-mediated cisplatin resistance in breast cancer cells by downregulating glutathione

Micheliolide (MCL) is a promising novel compound with broad-spectrum anticancer activity. However, little is known regarding its action and mechanism in breast cancer. To explore the potential therapeutic application of MCL as a chemosensitivity modulator, this study investigated the effects of MCL on cisplatin sensitivity in breast cancer and the underlying mechanisms. In the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide cytotoxicity assay and a xenograft tumor model, MCL enhanced the cisplatin sensitivity of the breast cancer cell line MCF-7 both in vitro and in vivo. Treatment of MCF-7 cells with low-dose cisplatin (10 µM) was sufficient to enrich the proportion of ALDH(+) cells and upregulate Krüppel-like factor 4 (KLF4) expression. The results obtained from knockdown and overexpression experiments demonstrate that KLF4 is both necessary and sufficient to induce a cisplatin resistance phenotype in breast cancer cells. Furthermore, the glutathione (GSH) content was elevated in MCF-7 cells after overexpression of KLF4. KLF4-mediated resistance to cisplatin was found to be abrogated by treatment with buthionine sulfoximine, an inhibitor of GSH synthesis. MCL induced GSH depletion and severe cell death in KLF4-overexpressing MCF-7 cells following exposure to cisplatin. Therefore, these results suggest that MCL-mediated direct depletion of GSH represents a major mechanism in reversing KLF4-induced cisplatin resistance in MCF-7 cells.

Metabolomic Approaches in Cancer Epidemiology

Metabolomics is the study of low molecular weight molecules or metabolites produced within cells and biological systems. It involves technologies such as mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) that can measure hundreds of thousands of unique chemical entities (UCEs). The metabolome provides one of the most accurate reflections of cellular activity at the functional level and can be leveraged to discern mechanistic information during normal and disease states. The advantages of metabolomics over other “omics” include its high sensitivity and ability to enable the analysis of relatively few metabolites compared with the number of genes and messenger RNAs (mRNAs). In clinical samples, metabolites are more stable than proteins or RNA. In fact, metabolomic profiling in basic, epidemiologic, clinical, and translational studies has revealed potential new biomarkers of disease and therapeutic outcome and has led to a novel mechanistic understanding of pathogenesis. These potential biomarkers include novel metabolites associated with cancer initiation, regression, and recurrence. Unlike genomics or even proteomics, however, the degree of metabolite complexity and heterogeneity within biological systems presents unique challenges that require specialized skills and resources to overcome. This article discusses epidemiologic studies of altered metabolite profiles in several cancers as well as challenges in the field and potential approaches to overcoming them.