The big picture: exploring the metabolic cross-talk in cancer

Viscum album mother tinctures: Harvest conditions and host trees influence the plant metabolome and the glycolytic pathway of breast cancer cells

Viscum album is a semi-parasitic plant used for over one hundred years in complementary cancer therapy. The main commercial drugs used in cancer patients' treatment are derived from the aqueous V. album extracts, whose cytotoxic potential is mostly attributed to the aqueous soluble antitumoral metabolites. On the counterpart, ethanol solvents must be used to obtain V. album mother tinctures. This methodology permits better solubilization of phenolic compounds, among others, which present antitumoral bioactivity. Recently, the metabolomics approach revealed the influence of the host tree on the V. album subspecies differentiation. To increase the scientific information about the chemical differences related to the host trees and to clarify the seasonal influences, in this study, the metabolome of 50 V. album mother tinctures from three subspecies (abietis, album, austriacum) and five host trees (Malus domestica, Quercus sp., Ulmus carpinifolia, Pinus sylvestris, Abies alba) was evaluated using summer and winter plant harvests. The in vitro cytotoxic activities were investigated in breast cancer cells (MDA-MB-231) and immortalized normal human keratinocytes (HaCaT). The summer V. album mother tinctures presented higher cytotoxic activity than winter ones. Among the summer samples, those prepared with V. album subsp. album were more cytotoxic than V. album subsp. abietis and subsp. V. album subsp. austriacum. The V. album harvested from Quercus petraea and Abies alba inhibited the key-glycolytic enzymes: hexokinase (HK), phosphofructokinase (PFK), pyruvate kinase (PK). This activity was related to a reduction in glucose uptake and lactate production, which were host-tree-time-dose-dependent. The untargeted metabolomic approach was able to discriminate the mother tinctures according to respective botanical classes and harvest season. A total of 188 metabolites were annotated under positive and negative modes. Fourteen compounds were responsible for the samples differentiation, and, to the best of our knowledge, eight were described in the Viscum album species for the first time. Our study shows the interruption of the Warburg effect as a novel antitumoral mechanism triggered by V. album mother tinctures, which is related to their metabolite profile. These results bring scientific evidence that encourages the use of V. album mother tinctures as a natural product for cancer therapy.

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment

The tumor's physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.

Metabolic Reprogramming of Colorectal Cancer Cells and the Microenvironment: Implication for Therapy

Colorectal carcinoma (CRC) is one of the most frequently diagnosed carcinomas and one of the leading causes of cancer-related death worldwide. Metabolic reprogramming, a hallmark of cancer, is closely related to the initiation and progression of carcinomas, including CRC. Accumulating evidence shows that activation of oncogenic pathways and loss of tumor suppressor genes regulate the metabolic reprogramming that is mainly involved in glycolysis, glutaminolysis, one-carbon metabolism and lipid metabolism. The abnormal metabolic program provides tumor cells with abundant energy, nutrients and redox requirements to support their malignant growth and metastasis, which is accompanied by impaired metabolic flexibility in the tumor microenvironment (TME) and dysbiosis of the gut microbiota. The metabolic crosstalk between the tumor cells, the components of the TME and the intestinal microbiota further facilitates CRC cell proliferation, invasion and metastasis and leads to therapy resistance. Hence, to target the dysregulated tumor metabolism, the TME and the gut microbiota, novel preventive and therapeutic applications are required. In this review, the dysregulation of metabolic programs, molecular pathways, the TME and the intestinal microbiota in CRC is addressed. Possible therapeutic strategies, including metabolic inhibition and immune therapy in CRC, as well as modulation of the aberrant intestinal microbiota, are discussed.

Differences in lipidomics may be potential biomarkers for early diagnosis of pancreatic cancer

Purpose

To analyze the plasma lipid spectrum between healthy control and patients with pancreatic cancer and to select differentially expressed tumor markers for early diagnosis.

Methods

In total, 20 patents were divided into case group and healthy control group according to surgical pathology. Of almost 1206 plasma lipid molecules harvested from 20 patients were measured by HILIC using the normal phase LC/MS. Heat map presented the relative levels of metabolites and lipids in the healthy control group and patients with pancreatic cancer. The PCA model was constructed to find out the difference in lipid metabolites. The principal components were drawn in a score plot and any clustering tendency could be observed. PLS-DA were performed to distinguish the healthy control group and pancreatic cancer according to the identified lipid profiling datasets. The volcano plot was used to visualize all variables with VIP>1 and presented the important variables with P<0.01 and |FC|>2.

Results

The upregulated lipid metabolites in patients with pancreatic cancer contained 9 lipids; however, the downregulated lipid metabolites contained 79 lipids.

Conclusion

There were lipid metabolomic differences in patients with pancreatic cancer, which could serve as potential tumor markers for pancreatic cancer.

Statistical mechanics of interacting metabolic networks

We cast the metabolism of interacting cells within a statistical mechanics framework considering both the actual phenotypic capacities of each cell and its interaction with its neighbors. Reaction fluxes will be the components of high-dimensional spin vectors, whose values will be constrained by the stochiometry and the energy requirements of the metabolism. Within this picture, finding the phenotypic states of the population turns out to be equivalent to searching for the equilibrium states of a disordered spin model. We provide a general solution of this problem for arbitrary metabolic networks and interactions. We apply this solution to a simplified model of metabolism and to a complex metabolic network, the central core of Escherichia coli, and demonstrate that the combination of selective pressure and interactions defines a complex phenotypic space. We also present numerical results for cells fixed in a grid. These results reproduce the qualitative picture discussed for the mean-field model. Cells may specialize in producing or consuming metabolites complementing each other, and this is described by an equilibrium phase space with multiple minima, like in a spin-glass model.

A Humanized Bone Niche Model Reveals Bone Tissue Preservation Upon Targeting Mitochondrial Complex I in Pseudo-Orthotopic Osteosarcoma

A cogent issue in cancer research is how to account for the effects of tumor microenvironment (TME) on the response to therapy, warranting the need to adopt adequate in vitro and in vivo models. This is particularly relevant in the development of strategies targeting cancer metabolism, as they will inevitably have systemic effects. For example, inhibition of mitochondrial complex I (CI), despite showing promising results as an anticancer approach, triggers TME-mediated survival mechanisms in subcutaneous osteosarcoma xenografts, a response that may vary according to whether the tumors are induced via subcutaneous injection or by intrabone orthotopic transplantation. Thus, with the aim to characterize the TME of CI-deficient tumors in a model that more faithfully represents osteosarcoma development, we set up a humanized bone niche ectopic graft. A prominent involvement of TME was revealed in CI-deficient tumors, characterized by the abundance of cancer associated fibroblasts, tumor associated macrophages and preservation of osteocytes and osteoblasts in the mineralized bone matrix. The pseudo-orthotopic approach allowed investigation of osteosarcoma progression in a bone-like microenvironment setting, without being invasive as the intrabone cell transplantation. Additionally, establishing osteosarcomas in a humanized bone niche model identified a peculiar association between targeting CI and bone tissue preservation.