The Heterogeneity of Breast Cancer Metabolism

Serum metabolomic profiling for predicting therapeutic response and toxicity in breast cancer neoadjuvant chemotherapy: a retrospective longitudinal study

BACKGROUND

Neoadjuvant chemotherapy (NACT) is the standard-of-care treatment for patients with locally advanced breast cancer (LABC), providing crucial benefits in tumor downstaging. Clinical parameters, such as molecular subtypes, influence the therapeutic impact of NACT. Moreover, severe adverse events delay the treatment process and reduce the effectiveness of therapy. Although metabolic changes during cancer treatment are crucial determinant factors in therapeutic responses and toxicities, related clinical research remains limited.

METHODS

One hundred paired blood samples were collected from 50 patients with LABC before and after a complete NACT treatment cycle. Untargeted metabolomics was used by liquid chromatography-mass spectrometry (LC-MS) to investigate the relationship between dynamically changing metabolites in serum and the responses and toxicities of NACT.

RESULTS

Firstly, we observed significant alterations in serum metabolite levels pre- and post-NACT, with a predominant enrichment in the sphingolipid and amino acid metabolism pathways. Second, pre-treatment serum metabolites successfully predicted the therapeutic response and hematotoxicities during NACT. In particular, molecular subtype variations in favorable treatment responses are linked to acyl carnitine levels. Finally, we discovered that the therapeutic effects of NACT could be attributed to essential amino acid metabolism.

CONCLUSION

This study elucidated the dynamic changes in metabolism during NACT treatment, providing a possibility for developing responsive metabolic signatures for personalized NACT treatment.

The Value of Whole-Volume Radiomics Machine Learning Model Based on Multiparametric MRI in Predicting Triple-Negative Breast Cancer

OBJECTIVE

This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) maps.

METHODS

This retrospective study included 326 patients with pathologically proven breast cancer (TNBC: 129, non-TNBC: 197). The lesions were segmented using the ITK-SNAP software, and whole-volume radiomics features were extracted using a radiomics platform. Radiomics features were obtained from DCE-MRI and ADC maps. The least absolute shrinkage and selection operator regression method was employed for feature selection. Three prediction models were constructed using a support vector machine classifier: Model A (based on the selected features of the ADC maps), Model B (based on the selected features of DCE-MRI), and Model C (based on the selected features of both combined). Receiver operating characteristic curves were used to evaluate the diagnostic performance of the conventional MR image model and the 3 radiomics models in predicting TNBC.

RESULTS

In the training dataset, the AUCs for the conventional MR image model and the 3 radiomics models were 0.749, 0.801, 0.847, and 0.896. The AUCs for the conventional MR image model and 3 radiomics models in the validation dataset were 0.693, 0.742, 0.793, and 0.876, respectively.

CONCLUSIONS

Radiomics based on the combination of whole volume DCE-MRI and ADC maps is a promising tool for distinguishing between TNBC and non-TNBC.

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

Influence of glutamine metabolism on diabetes Development:A scientometric review

Objective

"Metabolism affects function" is the consensus of researchers at present. It has potential clinical application value to study the effects of regulating glutamine (Gln) metabolism on diabetes physiology or pathology. Our research aimed to summarize the latest research progress, frontier hot topics and future development trends in this field from the perspective of scientometrics.

Methods

Relevant literatures and reviews were obtained from the Web of Science (WoS) between January 1, 2001 and May 31, 2022. An online analysis platform of bibliometrics, CiteSpace, and VOS viewer software were used to generate visual knowledge network graphs, including publication countries, institutions and authors partnership analysis, co-occurrence analysis, co-citation analysis, as well as citations and keywords burst detection to acquire research trends and hotspots.

Results

Our results showed that a total of 945 publications in the WoS database met the analysis requirements, with articles being the main type. The overall characteristics showed an increasing trend in the number of publications and citations. The United States was leading the way in this research and was a hub for aggregating collaborations across countries. Vanderbilt University delivered high-quality impact with the most published articles. DeBerardinis, RJ in this field was the most representative author and his main research contents were Gln metabolism and mitochondrial glutaminolysis. Significantly, there was a relative lack of collaboration between institutions and authors. In addition, "type 2 diabetes", "glutamine", "metabolism", "gene expression" and "metabolomics" were the keywords categories with high frequency in co-citation references and co-occurrence cluster keywords. Analysis of popular keywords burst detection showed that "branched chain", "oxidative phosphorylation", "kinase", "insulin sensitivity", "tca cycle", "magnetic resonance spectroscopy" and "flux analysis" were new research directions and emerging methods to explore the link between Gln metabolism and diabetes. Overall, exploring Gln metabolism showed a gradual upward trend in the field of diabetes.

Conclusion

This comprehensive scientometric study identified the general outlook for the field and provided valuable guidance for ongoing research. Strategies to regulate Gln metabolism hold promise as a novel target to treat diabetes, as well as integration and intersection of multidisciplinary provides cooperation strategies and technical guarantees for the development of this field.

Metabolic Phenotype Intricacies on Altered Glucose Metabolism of Breast Cancer Cells upon Glut-1 Inhibition and Mimic Hypoxia In Vitro

Breast cancer is the frequently diagnosed cancer and the leading cancer death among women. The growing tumour of the breast is composed of both normoxic and hypoxic cells, and the heterogeneity of tumour affects the targeted treatment strategies against breast cancer. The functional and therapeutic status of the Warburg effect is mostly recognized, and the genes involved in glycolysis have become a target for anticancer therapeutic strategies. Glut-1 is essential for basal glucose uptake among the glucose transporters and could act as a potential target for anticancer therapy. In the present study, we explored the alteration in the metabolic phenotype of SKBR-3 cells, representing HER-2 overexpressed breast cancer cell line, with Glut-1 inhibition by a synthetic small molecule inhibitor WZB117 in the presence or absence of cobalt chloride (CoCl2) induced biochemical hypoxia in vitro. We found that WZB117 and CoCl2 in combination could inhibit metabolic phenotype characteristics such as glucose uptake, cell migration, lactate and ATP production in SKBR-3 cells. Also, Glut-1 inhibition induced apoptosis and cell cycle arrest at the G0-G1 phase even under CoCl2-induced mimic hypoxia. Our findings suggest that Glut-1 inhibition by WZB117 could overcome the protective effect of CoCl2 mimic hypoxia by regulating glycolysis and altering the metabolic phenotype of breast cancer cells. The considering excellent efficacy and minimal toxicity suggest that WZB117 may be a promising anticancer drug to the current therapies.

Acetone extracts of Berberis vulgaris and Cornus mas L. induce apoptosis in MCF-7 breast cancer cells

Background/aim

This study aimed to determine the proliferation and apoptotic effects of extracts from Cornus mas L. and Berberis vulgaris fruits on human breast cancer cells (MCF-7).

Materials and methods

The Cornus mas L. and Berberis vulgaris fruits, which constitute the herbal material of the study, were turned into 80% acetone extract after washing. The total phenolic content in Berberis vulgaris fruit extracts was determined calorimetrically using Folin-Ciocalteu reagent. The spectrophotometric method was used to determine the total flavonoid amount of the extracts. In order to measure the antioxidant capacity of Cornus mas L. and Berberis vulgaris fruits and extracts, DPPH Radical Scavenging Power test and Cu (II) ion reducing antioxidant capacity method were applied. Cell viability rates were determined by the XTT method. Flow cytometric measurement was performed to examine the apoptotic role of the extracts in the cell by using the Annexin-V/7-AAD commercial kit.

Results

According to the data, Berberis vulgaris fruit extract appeared more effective on MCF-7 breast cancer cells in both 24 and 48 hours of exposure. Analyses made to examine the phenolic component and antioxidant capacity properties of the fruits used in the study and the results we encountered when we exposed the cell were found to be compatible with each other. Annexin-V/7-AAD method showed that the apoptotic effects of the extracts in 48 hour exposures were more effective.

Conclusion

It has been determined that Cornus mas L. and Berberis vulgaris fruits, which are rich in phenolic components with high flavonoid content and high antioxidant capacities, support the apoptosis of cancer cells.

A transfer learning‐based system for grading breast invasive ductal carcinoma

Breast carcinoma is a sort of malignancy that begins in the breast. Breast malignancy cells generally structure a tumour that can routinely be seen on an x‐ray or felt like a lump. Despite advances in screening, treatment, and observation that have improved patient endurance rates, breast carcinoma is the most regularly analyzed malignant growth and the subsequent driving reason for malignancy mortality among ladies. Invasive ductal carcinoma is the most boundless breast malignant growth with about 80% of all analyzed cases. It has been found from numerous types of research that artificial intelligence has tremendous capabilities, which is why it is used in various sectors, especially in the healthcare domain. In the initial phase of the medical field, mammography is used for diagnosis, and finding cancer in the case of a dense breast is challenging. The evolution of deep learning and applying the same in the findings are helpful for earlier tracking and medication. The authors have tried to utilize the deep learning concepts for grading breast invasive ductal carcinoma using Transfer Learning in the present work. The authors have used five transfer learning approaches here, namely VGG16, VGG19, InceptionReNetV2, DenseNet121, and DenseNet201 with 50 epochs in the Google Colab platform which has a single 12GB NVIDIA Tesla K80 graphical processing unit (GPU) support that can be used up to 12 h continuously. The dataset used for this work can be openly accessed from http://databiox.com. The experimental results that the authors have received regarding the algorithm's accuracy are as follows: VGG16 with 92.5%, VGG19 with 89.77%, InceptionReNetV2 with 84.46%, DenseNet121 with 92.64%, DenseNet201 with 85.22%. From the experimental results, it is clear that the DenseNet121 gives the maximum accuracy in terms of cancer grading, whereas the InceptionReNetV2 has minimal accuracy.

Metabolic Regulation of Fibroblast Activation and Proliferation during Organ Fibrosis

Background

Activated fibroblasts are present in the injury response, tumorigenesis, fibrosis, and inflammation in a variety of tissues and myriad disease types.

Summary

During normal tissue repair, quiescent fibroblasts transform into a proliferative and contractile phenotype termed myofibroblasts and are then lost as repair resolves to form a scar. When excessive levels are reached, activated fibroblasts proliferate and produce large amounts of extracellular matrix, which accumulates in the interstitial space of different organs. This accumulation leads to fibrotic dysfunction and multiple-organ dysfunction syndrome. To date, there are limited effective treatments for these conditions. Cellular metabolism is the cornerstone of all biological activities. Emerging evidence shows that metabolic alterations in fibroblasts are important for the activation process and illness progression. These discoveries, along with current clinical advances showing decreased lung fibrosis after targeting specific metabolic pathways, thus offer new possibilities for therapeutic interventions. The purpose of this review was to summarize the most recent knowledge of the major metabolic changes that occur during fibroblast transition from quiescent to activated states and the evidence linking alterations in fibroblast metabolism to the pathobiology of several common fibrotic diseases and tumor-related diseases.

Key Messages

Metabolic disorders are associated with the progression of chronic kidney diseases. Interfering with fibroblast metabolism may be a promising therapeutic strategy for renal fibrosis and other fibrosis-related diseases.

Biglycan Promotes Cancer Stem Cell Properties, NFκB Signaling and Metastatic Potential in Breast Cancer Cells

Simple Summary

Breast cancer stem cells (BCSCs) are a small sub-population of cells within tumors with high metastatic potential. We identified biglycan (BGN) as a prospective molecular target in BCSCs that regulates the aggressive phenotypes of these cells. These findings establish a foundation for the development of therapeutics against BGN to eliminate BCSCs and prevent metastatic breast cancer.

Abstract

It is a major challenge to treat metastasis due to the presence of heterogenous BCSCs. Therefore, it is important to identify new molecular targets and their underlying molecular mechanisms in various BCSCs to improve treatment of breast cancer metastasis. Here, we performed RNA sequencing on two distinct co-existing BCSC populations, ALDH⁺ and CD29^hi CD61⁺ from PyMT mammary tumor cells and detected upregulation of biglycan (BGN) in these BCSCs. Genetic depletion of BGN reduced BCSC proportions and tumorsphere formation. Furthermore, BCSC associated aggressive traits such as migration and invasion were significantly reduced by depletion of BGN. Glycolytic and mitochondrial metabolic assays also revealed that BCSCs exhibited decreased metabolism upon loss of BGN. BCSCs showed decreased activation of the NFκB transcription factor, p65, and phospho-IκB levels upon BGN ablation, indicating regulation of NFκB pathway by BGN. To further support our data, we also characterized CD24⁻/CD44⁺ BCSCs from human luminal MCF-7 breast cancer cells. These CD24⁻/CD44⁺ BCSCs similarly exhibited reduced tumorigenic phenotypes, metabolism and attenuation of NFκB pathway after knockdown of BGN. Finally, loss of BGN in ALDH⁺ and CD29^hi CD61⁺ BCSCs showed decreased metastatic potential, suggesting BGN serves as an important therapeutic target in BCSCs for treating metastasis of breast cancer.

Bioactive cationic peptides as potential agents for breast cancer treatment

Breast cancer continues to affect millions of women worldwide, and the number of new cases dramatically increases every year. The physiological causes behind the disease are still not fully understood. One in every 100 cases can occur in men, and although the frequency is lower than among women, men tend to have a worse prognosis of the disease. Various therapeutic alternatives to combat the disease are available. These depend on the type and progress of the disease, and include chemotherapy, radiotherapy, surgery, and cancer immunotherapy. However, there are several well-reported side effects of these treatments that have a significant impact on life quality, and patients either relapse or are refractory to treatment. This makes it necessary to develop new therapeutic strategies. One promising initiative are bioactive peptides, which have emerged in recent years as a family of compounds with an enormous number of clinical applications due to their broad spectrum of activity. They are widely distributed in several organisms as part of their immune system. The antitumoral activity of these peptides lies in a nonspecific mechanism of action associated with their interaction with cancer cell membranes, inducing, through several routes, bilayer destabilization and cell death. This review provides an overview of the literature on the evaluation of cationic peptides as potential agents against breast cancer under different study phases. First, physicochemical characteristics such as the primary structure and charge are presented. Secondly, information about dosage, the experimental model used, and the mechanism of action proposed for the peptides are discussed.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.

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

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

Glutamine Metabolism in Cancer

Metabolism is a fundamental process for all cellular functions. For decades, there has been growing evidence of a relationship between metabolism and malignant cell proliferation. Unlike normal differentiated cells, cancer cells have reprogrammed metabolism in order to fulfill their energy requirements. These cells display crucial modifications in many metabolic pathways, such as glycolysis and glutaminolysis, which include the tricarboxylic acid (TCA) cycle, the electron transport chain (ETC), and the pentose phosphate pathway (PPP) [1]. Since the discovery of the Warburg effect, it has been shown that the metabolism of cancer cells plays a critical role in cancer survival and growth. More recent research suggests that the involvement of glutamine in cancer metabolism is more significant than previously thought. Glutamine, a nonessential amino acid with both amine and amide functional groups, is the most abundant amino acid circulating in the bloodstream [2]. This chapter discusses the characteristic features of glutamine metabolism in cancers and the therapeutic options to target glutamine metabolism for cancer treatment.

The Intratumoral Heterogeneity of Cancer Metabolism

Cancer is one of the deadliest diseases in the world, causing over half a million deaths a year in the USA alone. Despite recent advances made in the field of cancer biology and the therapies that have been developed [1, 2], it is clear that more advances are necessary for us to classify cancer as curable. The logical question that arises is simple: Why, despite all the technologies and medical innovations of our time, has a complete cure eluded us? This chapter sheds light on one of cancer's most impactful attributes: its heterogeneity and, more specifically, the intratumoral heterogeneity of cancer metabolism. Simply put, what makes cancer one of the deadliest diseases is its ability to change and adapt. Cancer cells' rapid evolution, coupled with their irrepressible ability to divide, gives most of them the advantage over our immune systems. In this chapter, we delve into the complexities of this adaptability and the vital role that metabolism plays in the rise and progression of this heterogeneity.

Diabetes and Cancer: The Epidemiological and Metabolic Associations

Diabetes mellitus, commonly known as diabetes, and cancer are two of the most common diseases plaguing the world today. According to the Centers for Disease Control and Prevention (CDC), there are currently more than 20 million people with diabetes in the United States [1]. According to the International Agency for Research on Cancer (IARC), there were around 18 million people diagnosed with cancer, with approximately ten million deaths globally in 2018 [2]. Given the prevalence and deadliness of diabetes and cancer, these two diseases have long been the focus of many researchers with the goal of improving treatment outcomes. While diabetes and cancer may seem to be two very different diseases at first glance, they share several similarities, especially regarding their metabolic characteristics. This chapter discusses the similarities and relationships between the metabolism of diabetes, especially type 2 diabetes (T2D), and cancer, including their abnormal glucose and amino acid metabolism, the contribution of hyperglycemia to oncogenic mutation, and the contribution of hyperinsulinemia to cancer progression. Investigating the metabolic interplay between diabetes and cancer in an effort to exploit this connection for cancer treatment has the potential to significantly improve clinical efficacy.

Targeting Metabolic Cross Talk Between Cancer Cells and Cancer-Associated Fibroblasts

Although cancer has classically been regarded as a genetic disease of uncontrolled cell growth, the importance of the tumor microenvironment (TME) [1, 2] is continuously emphasized by the accumulating evidence that cancer growth is not simply dependent on the cancer cells themselves [3, 4] but also dependent on angiogenesis [5-8], inflammation [9, 10], and the supporting roles of cancer-associated fibroblasts (CAFs) [11-13]. After the discovery that CAFs are able to remodel the tumor matrix within the TME and provide the nutrients and chemicals to promote cancer cell growth [14], many studies have aimed to uncover the cross talk between cancer cells and CAFs. Moreover, a new paradigm in cancer metabolism shows how cancer cells act like "metabolic parasites" to take up the high-energy metabolites, such as lactate, ketone bodies, free fatty acids, and glutamine from supporting cells, including CAFs and cancer-associated adipocytes (CAAs) [15, 16]. This chapter provides an overview of the metabolic coupling between CAFs and cancer cells to further define the therapeutic options to disrupt the CAF-cancer cell interactions.

Metabolic Intersection of Cancer and Cardiovascular Diseases: Opportunities for Cancer Therapy

According to data from the World Health Organization, cardiovascular diseases and cancer are the two leading causes of mortality in the world [1]. Despite the immense effort to study these diseases and the constant innovation in treatment modalities, the number of deaths associated with cardiovascular diseases and cancer is predicted to increase in the coming decades [1]. From 2008 to 2030, due to population growth and population aging in many parts of the world, the number of deaths caused by cancer globally is projected to increase by 45%, corresponding to an annual increase of around four million people [1]. For cardiovascular diseases, this number is six million people [1]. In the United States, treatments for these two diseases are among the most costly and result in a disproportionate impact on low- and middleincome people. As the fight against these fatal diseases continues, it is crucial that we continue our investigation and broaden our understanding of cancer and cardiovascular diseases to innovate our prognostic and treatment approaches. Even though cardiovascular diseases and cancer are usually studied independently [2-12], there are some striking overlaps between their metabolic behaviors and therapeutic targets, suggesting the potential application of cardiovascular disease treatments for cancer therapy. More specifically, both cancer and many cardiovascular diseases have an upregulated glutaminolysis pathway, resulting in low glutamine and high glutamate circulating levels. Similar treatment modalities, such as glutaminase (GLS) inhibition and glutamine supplementation, have been identified to target glutamine metabolism in both cancer and some cardiovascular diseases. Studies have also found similarities in lipid metabolism, specifically fatty acid oxidation (FAO) and synthesis. Pharmacological inhibition of FAO and fatty acid synthesis have proven effective against many cancer types as well as specific cardiovascular conditions. Many of these treatments have been tested in clinical trials, and some have been medically prescribed to patients to treat certain diseases, such as angina pectoris [13, 14]. Other metabolic pathways, such as tryptophan catabolism and pyruvate metabolism, were also dysregulated in both diseases, making them promising treatment targets. Understanding the overlapping traits exhibited by both cancer metabolism and cardiovascular disease metabolism can give us a more holistic view of how important metabolic dysregulation is in the progression of diseases. Using established links between these illnesses, researchers can take advantage of the discoveries from one field and potentially apply them to the other. In this chapter, we highlight some promising therapeutic discoveries that can support our fight against cancer, based on common metabolic traits displayed in both cancer and cardiovascular diseases.

Glucose Metabolism in Cancer: The Warburg Effect and Beyond

Otto Warburg observed a peculiar phenomenon in 1924, unknowingly laying the foundation for the field of cancer metabolism. While his contemporaries hypothesized that tumor cells derived the energy required for uncontrolled replication from proteolysis and lipolysis, Warburg instead found them to rapidly consume glucose, converting it to lactate even in the presence of oxygen. The significance of this finding, later termed the Warburg effect, went unnoticed by the broader scientific community at that time. The field of cancer metabolism lay dormant for almost a century awaiting advances in molecular biology and genetics, which would later open the doors to new cancer therapies [2, 3].