Global metabolite profiling analysis of lipotoxicity in HER2/neu-positive breast cancer cells

A prismatic view of the epigenetic-metabolic regulatory axis in breast cancer therapy resistance

Epigenetic regulation established during development to maintain patterns of transcriptional expression and silencing for metabolism and other fundamental cell processes can be reprogrammed in cancer, providing a molecular mechanism for persistent alterations in phenotype. Metabolic deregulation and reprogramming are thus an emerging hallmark of cancer with opportunities for molecular classification as a critical preliminary step for precision therapeutic intervention. Yet, acquisition of therapy resistance against most conventional treatment regimens coupled with tumor relapse, continue to pose unsolved problems for precision healthcare, as exemplified in breast cancer where existing data informs both cancer genotype and phenotype. Furthermore, epigenetic reprograming of the metabolic milieu of cancer cells is among the most crucial determinants of therapeutic resistance and cancer relapse. Importantly, subtype-specific epigenetic-metabolic interplay profoundly affects malignant transformation, resistance to chemotherapy, and response to targeted therapies. In this review, we therefore prismatically dissect interconnected epigenetic and metabolic regulatory pathways and then integrate them into an observable cancer metabolism-therapy-resistance axis that may inform clinical intervention. Optimally coupling genome-wide analysis with an understanding of metabolic elements, epigenetic reprogramming, and their integration by metabolic profiling may decode missing molecular mechanisms at the level of individual tumors. The proposed approach of linking metabolic biochemistry back to genotype, epigenetics, and phenotype for specific tumors and their microenvironment may thus enable successful mechanistic targeting of epigenetic modifiers and oncometabolites despite tumor metabolic heterogeneity.

Lipid profile in breast cancer: From signaling pathways to treatment strategies

Breast cancer is the most prevalent cancer in women. Metabolic abnormalities, particularly increased lipid synthesis and uptake, impact the onset and progression of the disease. However, the influence of lipid metabolism in breast cancer varies according to the disease stage and patient's hormone status. In postmenopausal patients, obesity is associated with a higher risk and poor prognosis of luminal tumors, while in premenopausal individuals, it is correlated to BRCA mutated tumors. In fact, the tumor's lipid profile may be used to distinguish between HER2+, luminal and BRCA-mutated tumors. Moreover, drug resistance was associated with increased fatty acid synthesis and alterations in membrane composition, impacting its fluidity and spatial subdomains such as lipid rafts. Here, we discuss the subtype-specific lipid metabolism alterations found in breast cancer and the potentiality of its modulation in a clinical setting.

Novel Anti-Cancer Products Targeting AMPK: Natural Herbal Medicine against Breast Cancer

Breast cancer is a common cancer in women worldwide. The existing clinical treatment strategies have been able to limit the progression of breast cancer and cancer metastasis, but abnormal metabolism, immunosuppression, and multidrug resistance involving multiple regulators remain the major challenges for the treatment of breast cancer. Adenosine 5'-monophosphate (AMP)-Activated Protein Kinase (AMPK) can regulate metabolic reprogramming and reverse the "Warburg effect" via multiple metabolic signaling pathways in breast cancer. Previous studies suggest that the activation of AMPK suppresses the growth and metastasis of breast cancer cells, as well as stimulating the responses of immune cells. However, some other reports claim that the development and poor prognosis of breast cancer are related to the overexpression and aberrant activation of AMPK. Thus, the role of AMPK in the progression of breast cancer is still controversial. In this review, we summarize the current understanding of AMPK, particularly the comprehensive bidirectional functions of AMPK in cancer progression; discuss the pharmacological activators of AMPK and some specific molecules, including the natural products (including berberine, curcumin, (-)-epigallocatechin-3-gallate, ginsenosides, and paclitaxel) that influence the efficacy of these activators in cancer therapy; and elaborate the role of AMPK as a potential therapeutic target for the treatment of breast cancer.

Prognostic and clinicopathological significance of fatty acid synthase in breast cancer: A systematic review and meta-analysis

Background

Aberrant expression of fatty acid synthase (FASN) was demonstrated in various tumors including breast cancer. A meta-analysis was conducted to investigate the role of FASN in breast cancer development and its potential prognostic significance.

Methods

The Web of Science, PubMed, Embase, and Cochrane Library databases were searched to identify studies that evaluated the relationship between FASN expression and overall survival (OS), relapse-free survival (RFS), and disease-free survival (DFS) of breast cancer patients. To analyze the clinicopathological and prognostic values of FASN expression in breast cancer, pooled hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were clustered based on random-effects models. To confirm whether the findings were stable and impartial, a sensitivity analysis was performed, and publication bias was estimated. Data were analyzed using Engauge Digitizer version 5.4 and Stata version 15.0.

Results

Five studies involving 855 participants were included. Patients with higher FASN expression did not have a shorter survival period compared to those with lower FASN expression (summary HR: OS, 0.73 [95% CI, 0.41-1.32; P=0.300]; DFS/RFS, 1.65 [95% CI, 0.61-4.43; P=0.323]). However, increased FASN expression was correlated with large tumor size (OR, 2.04; 95% CI, 1.04-4.00; P=0.038), higher human epidermal growth factor receptor 2 (HER2) positivity (OR, 1.53; 95% CI, 1.05-2.23; P=0.028). No significant associations were observed between FASN expression and histological grade (OR, 0.92; 95% CI, 0.41-2.04; P=0.832), Tumor Node Metastasis (TNM) stage (OR, 1.11; 95% CI, 0.49-2.53; P=0.795), nodal metastasis (OR, 1.42; 95% CI, 0.84-2.38; P=0.183), Ki-67 labelling index (OR, 0.64; 95% CI, 0.15-2.63; P=0.533), estrogen receptor (ER) status (OR, 0.90; 95% CI, 0.61-1.32; P=0.586), or progesterone receptor (PR) status (OR, 0.67; 95% CI, 0.29-1.56; P=0.354).

Conclusion

FASN is associated with HER2 expression and may contribute to tumor growth, but it has no significant impact on the overall prognosis of breast cancer.

(Wh)olistic (E)ndocannabinoidome-Microbiome-Axis Modulation through (N)utrition (WHEN) to Curb Obesity and Related Disorders

The discovery of the endocannabinoidome (eCBome) is evolving gradually with yet to be elucidated functional lipid mediators and receptors. The diet modulates these bioactive lipids and the gut microbiome, both working in an entwined alliance. Mounting evidence suggests that, in different ways and with a certain specialisation, lipid signalling mediators such as N-acylethanolamines (NAEs), 2-monoacylglycerols (2-MAGs), and N-acyl-amino acids (NAAs), along with endocannabinoids (eCBs), can modulate physiological mechanisms underpinning appetite, food intake, macronutrient metabolism, pain sensation, blood pressure, mood, cognition, and immunity. This knowledge has been primarily utilised in pharmacology and medicine to develop many drugs targeting the fine and specific molecular pathways orchestrating eCB and eCBome activity. Conversely, the contribution of dietary NAEs, 2-MAGs and eCBs to the biological functions of these molecules has been little studied. In this review, we discuss the importance of (Wh) olistic (E)ndocannabinoidome-Microbiome-Axis Modulation through (N) utrition (WHEN), in the management of obesity and related disorders.

Network analysis with biological data of cancer patients: A scoping review

BACKGROUND & OBJECTIVE

Network Analysis (NA) is a mathematical method that allows exploring relations between units and representing them as a graph. Although NA was initially related to social sciences, the past two decades was introduced in Bioinformatics. The recent growth of the networks' use in biological data analysis reveals the need to further investigate this area. In this work, we attempt to identify the use of NA with biological data, and specifically: (a) what types of data are used and whether they are integrated or not, (b) what is the purpose of this analysis, predictive or descriptive, and (c) the outcome of such analyses, specifically in cancer diseases.

METHODS & MATERIALS

The literature review was conducted on two databases, PubMed & IEEE, and was restricted to journal articles of the last decade (January 2010 - December 2019). At a first level, all articles were screened by title and abstract, and at a second level the screening was conducted by reading the full text article, following the predefined inclusion & exclusion criteria leading to 131 articles of interest. A table was created with the information of interest and was used for the classification of the articles. The articles were initially classified to analysis studies and studies that propose a new algorithm or methodology. Each one of these categories was further screened by the following clustering criteria: (a) data used, (b) study purpose, (c) study outcome. Specifically for the studies proposing a new algorithm, the novelty presented in each one was detected.

RESULTS

& Conclusions: In the past five years researchers are focusing on creating new algorithms and methodologies to enhance this field. The articles' classification revealed that only 25% of the analyses are integrating multi-omics data, although 50% of the new algorithms developed follow this integrative direction. Moreover, only 20% of the analyses and 10% of the newly developed methodologies have a predictive purpose. Regarding the result of the works reviewed, 75% of the studies focus on identifying, prognostic or not, gene signatures. Concluding, this review revealed the need for deploying predictive and multi-omics integrative algorithms and methodologies that can be used to enhance cancer diagnosis, prognosis and treatment.

N-Acyl Amino Acids: Metabolism, Molecular Targets, and Role in Biological Processes

The lipid signal is becoming increasingly crowded as increasingly fatty acid amide derivatives are being identified and considered relevant therapeutic targets. The identification of N-arachidonoyl-ethanolamine as endogenous ligand of cannabinoid type-1 and type-2 receptors as well as the development of different–omics technologies have the merit to have led to the discovery of a huge number of naturally occurring N-acyl-amines. Among those mediators, N-acyl amino acids, chemically related to the endocannabinoids and belonging to the complex lipid signaling system now known as endocannabinoidome, have been rapidly growing for their therapeutic potential. Here, we review the current knowledge of the mechanisms for the biosynthesis and inactivation of the N-acyl amino acids, as well as the various molecular targets for some of the N-acyl amino acids described so far.

Multimodal analysis of formalin-fixed and paraffin-embedded tissue by MALDI imaging and fluorescence in situ hybridization for combined genetic and metabolic analysis

Multimodal tissue analyses that combine two or more detection technologies provide synergistic value compared to single methods and are employed increasingly in the field of tissue-based diagnostics and research. Here, we report a technical pipeline that describes a combined approach of HER2/CEP17 fluorescence in situ hybridization (FISH) analysis with MALDI imaging on the very same section of formalin-fixed and paraffin-embedded (FFPE) tissue. FFPE biopsies and a tissue microarray of human gastroesophageal adenocarcinoma were analyzed by MALDI imaging. Subsequently, the very same section was hybridized by HER2/CEP17 FISH. We found that tissue morphology of both, the biopsies and the tissue microarray, was unaffected by MALDI imaging and the HER2 and CEP17 FISH signals were analyzable. In comparison with FISH analysis of samples without MALDI imaging, we observed no difference in terms of fluorescence signal intensity and gene copy number. Our combined approach revealed adenosine monophosphate, measured by MALDI imaging, as a prognostic marker. HER2 amplification, which was detected by FISH, is a stratifier between good and poor patient prognosis. By integrating both stratification parameters on the basis of our combined approach, we were able to strikingly improve the prognostic effect. Combining molecules detected by MALDI imaging with the gene copy number detected by HER2/CEP17 FISH, we found a synergistic effect, which enhances patient prognosis. This study shows that our combined approach allows the detection of genetic and metabolic properties from one very same FFPE tissue section, which are specific for HER2 and hence suitable for prognosis. Furthermore, this synergism might be useful for response prediction in tumors.

Metabolic Reprogramming in Breast Cancer and Its Therapeutic Implications

Current standard-of-care (SOC) therapy for breast cancer includes targeted therapies such as endocrine therapy for estrogen receptor-alpha (ERα) positive; anti-HER2 monoclonal antibodies for human epidermal growth factor receptor-2 (HER2)-enriched; and general chemotherapy for triple negative breast cancer (TNBC) subtypes. These therapies frequently fail due to acquired or inherent resistance. Altered metabolism has been recognized as one of the major mechanisms underlying therapeutic resistance. There are several cues that dictate metabolic reprogramming that also account for the tumors’ metabolic plasticity. For metabolic therapy to be efficacious there is a need to understand the metabolic underpinnings of the different subtypes of breast cancer as well as the role the SOC treatments play in targeting the metabolic phenotype. Understanding the mechanism will allow us to identify potential therapeutic vulnerabilities. There are some very interesting questions being tackled by researchers today as they pertain to altered metabolism in breast cancer. What are the metabolic differences between the different subtypes of breast cancer? Do cancer cells have a metabolic pathway preference based on the site and stage of metastasis? How do the cell-intrinsic and -extrinsic cues dictate the metabolic phenotype? How do the nucleus and mitochondria coordinately regulate metabolism? How does sensitivity or resistance to SOC affect metabolic reprogramming and vice-versa? This review addresses these issues along with the latest updates in the field of breast cancer metabolism.