Metabolic Flexibility Is a Determinant of Breast Cancer Heterogeneity and Progression

Metastatic breast cancer cells are metabolically reprogrammed to maintain redox homeostasis during metastasis

Metabolic rewiring is essential for tumor growth and progression to metastatic disease, yet little is known regarding how cancer cells modify their acquired metabolic programs in response to different metastatic microenvironments. We have previously shown that liver-metastatic breast cancer cells adopt an intrinsic metabolic program characterized by increased HIF-1α activity and dependence on glycolysis. Here, we confirm by in vivo stable isotope tracing analysis (SITA) that liver-metastatic breast cancer cells retain a glycolytic profile when grown as mammary tumors or liver metastases. However, hepatic metastases exhibit unique metabolic adaptations including elevated expression of genes involved in glutathione (GSH) biosynthesis and reactive oxygen species (ROS) detoxification when compared to mammary tumors. Accordingly, breast-cancer-liver-metastases exhibited enhanced de novo GSH synthesis. Confirming their increased capacity to mitigate ROS-mediated damage, liver metastases display reduced levels of 8-Oxo-2'-deoxyguanosine. Depletion of the catalytic subunit of the rate-limiting enzyme in glutathione biosynthesis, glutamate-cysteine ligase (GCLC), strongly reduced the capacity of breast cancer cells to form liver metastases, supporting the importance of these distinct metabolic adaptations. Loss of GCLC also affected the early steps of the metastatic cascade, leading to decreased numbers of circulating tumor cells (CTCs) and impaired metastasis to the liver and the lungs. Altogether, our results indicate that GSH metabolism could be targeted to prevent the dissemination of breast cancer cells.

Saikosaponin-d mediates FOXG1 to reverse docetaxel resistance in prostate cancer through oxidative phosphorylation

BACKGROUND

Prostate cancer (PCa), a prevalent malignancy worldwide, is frequently identified in advanced stages due to the absence of distinctive early symptoms, thereby culminating in the development of chemotherapy-induced drug resistance. Exploring novel resistance mechanisms and identifying new therapeutic agents can facilitate the advancement of more efficacious strategies for PCa treatment.

METHODS

Bioinformatics analysis was employed to investigate the expression of FOXG1 in PCa tissues. Subsequently, qRT-PCR was utilized to validate FOXG1 mRNA expression levels in corresponding PCa cell lines. FOXG1 knockdown was performed, and cell proliferation was assessed using CCK-8 assays, while cell migration and invasion capabilities were evaluated through wound healing and Transwell assays. Western blot and Seahorse analyzer were used to measure oxidative phosphorylation (OXPHOS) levels. Additionally, to explore potential approaches to alleviate PCa drug resistance, this study assessed the impact of biologically active saikosaponin-d (SSd) on PCa malignant progression and resistance by regulating FOXG1 expression.

RESULTS

FOXG1 exhibited high expression in PCa tissues and cell lines. Knockdown of FOXG1 inhibited the proliferation, migration, and invasion of PCa cells, while FOXG1 overexpression had the opposite effect and promoted OXPHOS levels. The addition of an OXPHOS inhibitor prevented this outcome. Finally, SSd was shown to suppress FOXG1 expression and reverse docetaxel resistance in PCa cells through the OXPHOS pathway.

CONCLUSION

This work demonstrated that SSd mediated FOXG1 to reverse malignant progression and docetaxel resistance in PCa through OXPHOS.

I A, Banerjee S. Deciphering the Chemotherapeutic Role of the Aryl Hydrocarbon Receptor Antagonist Resveratrol against the High-Penetrance Genes of Triple-Negative Breast Cancer

In addition to several other malignancies, the ligand-activated aryl hydrocarbon receptor (AhR) signaling pathway has been found to enhance the risk of triple-negative breast cancer (TNBC). Many natural compounds of pharmaceutical importance are identified as antagonistic exogenous ligands of AhR. The expressional lack of hormone receptors coupled with adverse prognosis leads to the absence of molecular-targeted therapy in TNBC. Hence, discovering low-cost therapeutic alternatives involving the identification of effective biomarkers is an urgent necessity. This study investigates the binding mechanism of resveratrol, a dietary exogenous AhR ligand against the high-penetrance genes in TNBC, viz., PALB2, TP53, PTEN, STK11, BRCA1, and BRCA2. Post-pharmacokinetic evaluation, molecular docking revealed the binding energy scores of resveratrol against the six TNBC high-penetrance receptors. The results obtained from docking were confirmed by molecular dynamics simulation including principal component analysis, calculation of total interaction energy, and free-energy landscape computation. PALB2 emerged as a promising therapeutic receptor of resveratrol. Furthermore, the PALB2-resveratrol binding dynamics were evaluated against olaparib, an FDA-approved standardized TNBC inhibitor. Our study reveals comparatively better chemistry of PALB2-resveratrol than PALB2-olaparib. Considering the current surge in the discovery of precision medicine in biomarker-based cancer therapeutics, this study proposes PALB2-resveratrol as a unique drug-receptor combination thus awaiting validation through in vitro studies.

p66ShcA promotes malignant breast cancer phenotypes by alleviating energetic and oxidative stress

Significant efforts have focused on identifying targetable genetic drivers that support the growth of solid tumors and/or increase metastatic ability. During tumor development and progression to metastatic disease, physiological and pharmacological selective pressures influence parallel adaptive strategies within cancer cell sub-populations. Such adaptations allow cancer cells to withstand these stressful microenvironments. This Darwinian model of stress adaptation often prevents durable clinical responses and influences the emergence of aggressive cancers with increased metastatic fitness. However, the mechanisms contributing to such adaptive stress responses are poorly understood. We now demonstrate that the p66ShcA redox protein, itself a ROS inducer, is essential for survival in response to physiological stressors, including anchorage independence and nutrient deprivation, in the context of poor outcome breast cancers. Mechanistically, we show that p66ShcA promotes both glucose and glutamine metabolic reprogramming in breast cancer cells, to increase their capacity to engage catabolic metabolism and support glutathione synthesis. In doing so, chronic p66ShcA exposure contributes to adaptive stress responses, providing breast cancer cells with sufficient ATP and redox balance needed to withstand such transient stressed states. Our studies demonstrate that p66ShcA functionally contributes to the maintenance of aggressive phenotypes and the emergence of metastatic disease by forcing breast tumors to adapt to chronic and moderately elevated levels of oxidative stress.

Take metabolic heterogeneity into consideration when applying dietary interventions to cancer therapy: A review

In recent years, dietary interventions have attracted much attention in cancer therapy. Mechanistic studies suggest that dietary interventions can inhibit the progression of cancer through deprivation of essential metabolites, lowering the levels of protumor hormones, activation of anticancer immunity and synergistic effects with conventional anticancer therapies. The feasibility, safety and promising tumor outcomes have also been established in humans. However, the results from both preclinical and clinical studies are inconsistent or even conflicting, the reasons for which have not been extensively considered. In this review, we discuss the various heterogeneity, including dietary protocols, tissue of origin and cancer locations, spatial and temporal metabolic heterogeneity, and divergent combination treatment, that may affect the responses of different cancers to dietary interventions. Understanding this heterogeneity and taking them into consideration when applying dietary interventions to cancer therapy will allow us to deliver the right diet to the right patient at the right time to maximize compliance, safety and efficacy of conventional anticancer therapy and to improve the outcomes of patients with cancer.

Breast cancers as ecosystems: a metabolic perspective

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of cancer death. Despite enormous progress in its management, both from the therapeutic and early diagnosis viewpoints, still around 700,000 patients succumb to the disease each year, worldwide. Late recurrency is the major problem in BC, with many patients developing distant metastases several years after the successful eradication of the primary tumor. This is linked to the phenomenon of metastatic dormancy, a still mysterious trait of the natural history of BC, and of several other types of cancer, by which metastatic cells remain dormant for long periods of time before becoming reactivated to initiate the clinical metastatic disease. In recent years, it has become clear that cancers are best understood if studied as ecosystems in which the impact of non-cancer-cell-autonomous events-dependent on complex interaction between the cancer and its environment, both local and systemic-plays a paramount role, probably as significant as the cell-autonomous alterations occurring in the cancer cell. In adopting this perspective, a metabolic vision of the cancer ecosystem is bound to improve our understanding of the natural history of cancer, across space and time. In BC, many metabolic pathways are coopted into the cancer ecosystem, to serve the anabolic and energy demands of the cancer. Their study is shedding new light on the most critical aspect of BC management, of metastatic dissemination, and that of the related phenomenon of dormancy and fostering the application of the knowledge to the development of metabolic therapies.

The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes

Breast cancer, the most common type of cancer affecting women, encompasses a collection of histologic (mainly ductal and lobular) and molecular subtypes exhibiting diverse clinical presentation, disease trajectories, treatment options, and outcomes. Immunotherapy has revolutionized treatment for some solid tumors but has shown limited promise for breast cancers. In this review, we summarize recent advances in our understanding of the complex interactions between tumor and immune cells in subtypes of breast cancer at the cellular and microenvironmental levels. We aim to provide a perspective on opportunities for future immunotherapy agents tailored to specific features of each subtype of breast cancer.

SIGNIFICANCE

Although there are currently over 200 ongoing clinical trials testing immunotherapeutics, such as immune-checkpoint blockade agents, these are largely restricted to the triple-negative and HER2+ subtypes and primarily focus on T cells. With the rapid expansion of new in vitro, in vivo, and clinical data, it is critical to identify and highlight the challenges and opportunities unique for each breast cancer subtype to drive the next generation of treatments that harness the immune system.

BETi enhance ATGL expression and its lipase activity to exert their antitumoral effects in triple-negative breast cancer (TNBC) cells

BACKGROUND

Triple-Negative Breast Cancer (TNBC) is a subtype of breast cancer that differs from other types of breast cancers in the faster spread and worse outcome. TNBC presented limited treatment options. BET (Bromodomain and extra-terminal domain) proteins are epigenetic readers that control the expression of different oncogenic proteins, and their inhibition (BETi) is considered a promising anti-cancer strategy. Recent evidence demonstrated the involvement of BET proteins in regulation of metabolic processes.

METHODS

MDA-MB231 cells treated with JQ1 followed by RNA-sequencing analysis showed altered expression of lipid metabolic genes; among these, we focused on ATGL, a lipase required for efficient mobilization of triglyceride. Different in vitro approaches were performed to validate the RNA-sequencing data (qRT-PCR, immunofluorescence and flow cytometry). NMR (Nuclear Magnetic Resonance) was used to analyze the lipid reprogramming upon treatment. ATGL expression was determined by immunoblot and qRT-PCR, and the impact of ATGL function or protein knockdown, alone and in combination with BETi, was assessed by analyzing cell proliferation, mitochondrial function, and metabolic activity in TNBC and non-TNBC cells culture models.

RESULTS

TNBC cells treated with two BETi markedly increased ATGL expression and lipolytic function and decreased intracellular lipid content in a dose and time-dependent manner. The intracellular composition of fatty acids (FAs) after BETi treatment reflected a significant reduction in neutral lipids. The short-chain FA propionate entered directly into the mitochondria mimicking ATGL activity. ATGL KD (knockdown) modulated the levels of SOD1 and CPT1a decreasing ROS and helped to downregulate the expression of mitochondrial ß-oxidation genes in favor of the upregulation of glycolytic markers. The enhanced glycolysis is reflected by the increased of the mitochondrial activity (MTT assay). Finally, we found that after BETi treatment, the FoxO1 protein is upregulated and binds to the PNPLA2 promoter leading to the induction of ATGL. However, FoxO1 only partially prompted the induction of ATGL expression by BETi.

CONCLUSIONS

The anti-proliferative effect achieved by BETi is helped by ATGL mediating lipolysis. This study showed that BETi altered the mitochondrial dynamics taking advantage of ATGL function to induce cell cycle arrest and cell death. Schematic representation of BETi mechanism of action on ATGL in TNBC cells. BETi induce the expression of FoxO1 and ATGL, lowering the expression of G0G2, leading to a switch in metabolic status. The induced expression of ATGL leads to increased lipolysis and a decrease in lipid droplet content and bioavailability of neutral lipid. At the same time, the mitochondria are enriched with fatty acids. This cellular status inhibits cell proliferation and increases ROS production and mitochondrial stress. Interfering for ATGL expression, the oxidative phenotypic status mildly reverted to a glycolytic status where neutral lipids are stored into lipid droplets with a consequent reduction of oxidative stress in the mitochondrial.

Profiling the Epigenetic Landscape of the Tumor Microenvironment Using Chromatin Immunoprecipitation Sequencing

Cancer cells within a tumor exhibit phenotypic plasticity that allows adaptation and survival in hostile tumor microenvironments. Reprogramming of epigenetic landscapes can support tumor progression within a specific microenvironment by influencing chromatin accessibility and modulating cell identity. The profiling of epigenetic landscapes within various tumor cell populations has significantly improved our understanding of tumor progression and plasticity. This protocol describes an integrated approach using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) optimized to profile genome-wide post-translational modifications of histone tails in tumors. Essential tools amenable to ChIP-seq to isolate tumor cell populations of interest from the tumor microenvironment are also presented to provide a comprehensive approach to perform heterogeneous epigenetic landscape profiling of the tumor microenvironment.

Immunometabolism characteristics and a potential prognostic risk model associated with TP53 mutations in breast cancer

TP53, a gene with high-frequency mutations, plays an important role in breast cancer (BC) development through metabolic regulation, but the relationship between TP53 mutation and metabolism in BC remains to be explored. Our study included 1,066 BC samples from The Cancer Genome Atlas (TCGA) database, 415 BC cases from the Gene Expression Omnibus (GEO) database, and two immunotherapy cohorts. We identified 92 metabolic genes associated with TP53 mutations by differential expression analysis between TP53 mutant and wild-type groups. Univariate Cox analysis was performed to evaluate the prognostic effects of 24 TP53 mutation-related metabolic genes. By unsupervised clustering and other bioinformatics methods, the survival differences and immunometabolism characteristics of the distinct clusters were illustrated. In a training set from TCGA cohort, we employed the least absolute shrinkage and selection operator (LASSO) regression method to construct a metabolic gene prognostic model associated with TP53 mutations, and the GEO cohort served as an external validation set. Based on bioinformatics, the connections between risk score and survival prognosis, tumor microenvironment (TME), immunotherapy response, metabolic activity, clinical characteristics, and gene characteristics were further analyzed. It is imperative to note that our model is a powerful and robust prognosis factor in comparison to other traditional clinical features and also has high accuracy and clinical usefulness validated by receiver operating characteristic (ROC) and decision curve analysis (DCA). Our findings deepen our understanding of the immune and metabolic characteristics underlying the TP53 mutant metabolic gene profile in BC, laying a foundation for the exploration of potential therapies targeting metabolic pathways. In addition, our model has promising predictive value in the prognosis of BC.

Data integration and mechanistic modelling for breast cancer biology: Current state and future directions

Breast cancer is one of the most common cancers threatening women worldwide. A limited number of available treatment options, frequent recurrence, and drug resistance exacerbate the prognosis of breast cancer patients. Thus, there is an urgent need for methods to investigate novel treatment options, while taking into account the vast molecular heterogeneity of breast cancer. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics and metabolomics data, enable approaching breast cancer biology at multiple levels of omics interaction networks. Systems biology approaches, including computational inference of ‘big data’ and mechanistic modelling of specific pathways, are emerging to identify potential novel combinations of breast cancer subtype signatures and more diverse targeted therapies.

RIP140 inhibits glycolysis-dependent proliferation of breast cancer cells by regulating GLUT3 expression through transcriptional crosstalk between hypoxia induced factor and p53

Glycolysis is essential to support cancer cell proliferation, even in the presence of oxygen. The transcriptional co-regulator RIP140 represses the activity of transcription factors that drive cell proliferation and metabolism and plays a role in mammary tumorigenesis. Here we use cell proliferation and metabolic assays to demonstrate that RIP140-deficiency causes a glycolysis-dependent increase in breast tumor growth. We further demonstrate that RIP140 reduces the transcription of the glucose transporter GLUT3 gene, by inhibiting the transcriptional activity of hypoxia inducible factor HIF-2α in cooperation with p53. Interestingly, RIP140 expression was significantly associated with good prognosis only for breast cancer patients with tumors expressing low GLUT3, low HIF-2α and high p53, thus confirming the mechanism of RIP140 anti-tumor activity provided by our experimental data. Overall, our work establishes RIP140 as a critical modulator of the p53/HIF cross-talk to inhibit breast cancer cell glycolysis and proliferation.