Mitochondrial Aconitase ACO2 Links Iron Homeostasis with Tumorigenicity in Non-Small Cell Lung Cancer

Fe-S cluster biosynthesis and maturation: Mass spectrometry-based methods advancing the field

Iron‑sulfur (FeS) clusters are inorganic protein cofactors that perform essential functions in many physiological processes. Spectroscopic techniques have historically been used to elucidate details of FeS cluster type, their assembly and transfer, and changes in redox and ligand binding properties. Structural probes of protein topology, complex formation, and conformational dynamics are also necessary to fully understand these FeS protein systems. Recent developments in mass spectrometry (MS) instrumentation and methods provide new tools to investigate FeS cluster and structural properties. With the unique advantage of sampling all species in a mixture, MS-based methods can be utilized as a powerful complementary approach to probe native dynamic heterogeneity, interrogate protein folding and unfolding equilibria, and provide extensive insight into protein binding partners within an entire proteome. Here, we highlight key advances in FeS protein studies made possible by MS methodology and contribute an outlook for its role in the field.

In silico model development and optimization of in vitro lung cell population growth

Tissue engineering predominantly relies on trial and error in vitro and ex vivo experiments to develop protocols and bioreactors to generate functional tissues. As an alternative, in silico methods have the potential to significantly reduce the timelines and costs of experimental programs for tissue engineering. In this paper, we propose a methodology to formulate, select, calibrate, and test mathematical models to predict cell population growth as a function of the biochemical environment and to design optimal experimental protocols for model inference of in silico model parameters. We systematically combine methods from the experimental design, mathematical statistics, and optimization literature to develop unique and explainable mathematical models for cell population dynamics. The proposed methodology is applied to the development of this first published model for a population of the airway-relevant bronchio-alveolar epithelial (BEAS-2B) cell line as a function of the concentration of metabolic-related biochemical substrates. The resulting model is a system of ordinary differential equations that predict the temporal dynamics of BEAS-2B cell populations as a function of the initial seeded cell population and the glucose, oxygen, and lactate concentrations in the growth media, using seven parameters rigorously inferred from optimally designed in vitro experiments.

Metabolic Profiles of Cancer Stem Cells and Normal Stem Cells and Their Therapeutic Significance

Cancer stem cells (CSCs) are a rare cancer cell population, responsible for the facilitation, progression, and resistance of tumors to therapeutic interventions. This subset of cancer cells with stemness and tumorigenic properties is organized in niches within the tumor microenvironment (TME) and presents altered regulation in a variety of metabolic pathways, including glycolysis, oxidative phosphorylation (OXPHOS), as well as lipid, amino acid, and iron metabolism. CSCs exhibit similarities as well as differences when comparedto normal stem cells, but also possess the ability of metabolic plasticity. In this review, we summarize the metabolic characteristics of normal, non-cancerous stem cells and CSCs. We also highlight the significance and implications of interventions targeting CSC metabolism to potentially achieve more robust clinical responses in the future.

The Pro-Oncogenic Sphingolipid-Metabolizing Enzyme β-Galactosylceramidase Modulates the Proteomic Landscape in BRAF(V600E)-Mutated Human Melanoma Cells

β-Galactosylceramidase (GALC) is a lysosomal enzyme involved in sphingolipid metabolism by removing β-galactosyl moieties from β-galactosylceramide and β-galactosylsphingosine. Previous observations have shown that GALC may exert pro-oncogenic functions in melanoma and Galc silencing, leading to decreased oncogenic activity in murine B16 melanoma cells. The tumor-driving BRAF(V600E) mutation is present in approximately 50% of human melanomas and represents a major therapeutic target. However, such mutation is missing in melanoma B16 cells. Thus, to assess the impact of GALC in human melanoma in a more relevant BRAF-mutated background, we investigated the effect of GALC overexpression on the proteomic landscape of A2058 and A375 human melanoma cells harboring the BRAF(V600E) mutation. The results obtained by liquid chromatography-tandem mass spectrometry (LC-MS/MS) demonstrate that significant differences exist in the protein landscape expressed under identical cell culture conditions by A2058 and A375 human melanoma cells, both harboring the same BRAF(V600E)-activating mutation. GALC overexpression resulted in a stronger impact on the proteomic profile of A375 cells when compared to A2058 cells (261 upregulated and 184 downregulated proteins versus 36 and 14 proteins for the two cell types, respectively). Among them, 25 proteins appeared to be upregulated in both A2058-upGALC and A375-upGALC cells, whereas two proteins were significantly downregulated in both GALC-overexpressing cell types. These proteins appear to be involved in melanoma biology, tumor invasion and metastatic dissemination, tumor immune escape, mitochondrial antioxidant activity, endoplasmic reticulum stress responses, autophagy, and/or apoptosis. Notably, analysis of the expression of the corresponding genes in human skin cutaneous melanoma samples (TCGA, Firehose Legacy) using the cBioPortal for Cancer Genomics platform demonstrated a positive correlation between GALC expression and the expression levels of 14 out of the 27 genes investigated, thus supporting the proteomic findings. Overall, these data indicate for the first time that the expression of the lysosomal sphingolipid-metabolizing enzyme GALC may exert a pro-oncogenic impact on the proteomic landscape in BRAF-mutated human melanoma.

Metabolism in Cancer Stem Cells: Targets for Clinical Treatment

Cancer stem cells (CSCs) have high tumorigenicity, high metastasis and high resistance to treatment. They are the key factors for the growth, metastasis and drug resistance of malignant tumors, and are also the important reason for the occurrence and recurrence of tumors. Metabolic reprogramming refers to the metabolic changes that occur when tumor cells provide sufficient energy and nutrients for themselves. Metabolic reprogramming plays an important role in regulating the growth and activity of cancer cells and cancer stem cells. In addition, the immune cells or stromal cells in the tumor microenvironment (TME) will change due to the metabolic reprogramming of cancer cells. Summarizing the characteristics and molecular mechanisms of metabolic reprogramming of cancer stem cells will provide new ideas for the comprehensive treatment of malignant tumors. In this review, we summarized the changes of the main metabolic pathways in cancer cells and cancer stem cells.