Effects of hypoxic preconditioning on neuroblastoma tumour oxygenation and metabolic signature in a chick embryo model

Technical Implications of the Chicken Embryo Chorioallantoic Membrane Assay to Elucidate Neuroblastoma Biology

The chorioallantoic membrane (CAM) can be used as a valuable research tool to examine tumors. The CAM can be used to investigate processes such as migration, invasion, and angiogenesis and to assess novel antitumor drugs. The CAM can be used to establish tumors in a straightforward, rapid, and cost-effective manner via xenotransplantation of cells or tumor tissues with reproducible results; furthermore, the use of the CAM adheres to the three "R" principle, i.e., replace, reduce, and refine. To achieve successful tumor establishment and survival, several technical aspects should be taken into consideration. The complexity and heterogeneity of diseases including neuroblastoma and cancers in general and their impact on human health highlight the importance of preclinical models that help us describe tumor-specific biological processes. These models will not only help in understanding tumor biology, but also allow clinicians to explore therapeutic alternatives that will improve current treatment strategies. In this review, we summarize the technical characteristics as well as the main findings regarding the use of this model to study neuroblastoma for angiogenesis, metastasis, drug sensitivity, and drug resistance.

iDMET: network-based approach for integrating differential analysis of cancer metabolomics

BACKGROUND

Comprehensive metabolomic analyses have been conducted in various institutes and a large amount of metabolomic data are now publicly available. To help fully exploit such data and facilitate their interpretation, metabolomic data obtained from different facilities and different samples should be integrated and compared. However, large-scale integration of such data for biological discovery is challenging given that they are obtained from various types of sample at different facilities and by different measurement techniques, and the target metabolites and sensitivities to detect them also differ from study to study.

RESULTS

We developed iDMET, a network-based approach to integrate metabolomic data from different studies based on the differential metabolomic profiles between two groups, instead of the metabolite profiles themselves. As an application, we collected cancer metabolomic data from 27 previously published studies and integrated them using iDMET. A pair of metabolomic changes observed in the same disease from two studies were successfully connected in the network, and a new association between two drugs that may have similar effects on the metabolic reactions was discovered.

CONCLUSIONS

We believe that iDMET is an efficient tool for integrating heterogeneous metabolomic data and discovering novel relationships between biological phenomena.

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer

Simple Summary

Tumors exhibit metabolic changes that differentiate them from the normal tissues from which they derive. These metabolic changes favor tumor growth, are primarily induced by cancer cells, and produce metabolic and functional changes in the surrounding stromal cells. There is a close functional connection between the metabolic changes in tumor cells and those that appear in the surrounding stroma. A better understanding of intratumoral metabolic interactions may help identify new vulnerabilities that will facilitate new, more individualized treatment strategies against cancer. We review the metabolic changes described in tumor and stromal cells and their functional changes and then consider, in depth, the metabolic interactions between the cells of the two compartments. Although these changes are generic, we illustrate them mainly with reference to examples in breast cancer.

Abstract

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.

Grading of endometrial cancer using 1H HR-MAS NMR-based metabolomics

The tissue metabolomic characteristics associated with endometrial cancer (EC) at different grades were studied using high resolution (400 MHz) magic angle spinning (HR-MAS) proton spectroscopy. The metabolic profiles were obtained from 64 patients (14 with grade 1 (G1), 33 with grade 2 (G2) and 17 with grade 3 (G3) tumors) and compared with the profile acquired from 10 patients with the benign disorders. OPLS-DA revealed increased valine, isoleucine, leucine, hypotaurine, serine, lysine, ethanolamine, choline and decreased creatine, creatinine, glutathione, ascorbate, glutamate, phosphoethanolamine and scyllo-inositol in all EC grades in reference to the non-transformed tissue. The increased levels of taurine was additionally detected in the G1 and G2 tumors in comparison to the control tissue, while the elevated glycine, N-acetyl compound and lactate—in the G1 and G3 tumors. The metabolic features typical for the G1 tumors are the increased dimethyl sulfone, phosphocholine, and decreased glycerophosphocholine and glutamine levels, while the decreased myo-inositol level is characteristic for the G2 and G3 tumors. The elevated 3-hydroxybutyrate, alanine and betaine levels were observed in the G3 tumors. The differences between the grade G1 and G3 malignances were mainly related to the perturbations of phosphoethanolamine and phosphocholine biosynthesis, inositol, betaine, serine and glycine metabolism. The statistical significance of the OPLS-DA modeling was also verified by an univariate analysis. HR-MAS NMR based metabolomics provides an useful insight into the metabolic reprogramming in endometrial cancer.

Portable Oxygen-Sensing Device for the Improved Assessment of Compartment Syndrome and other Hypoxia-Related Conditions

Measurement of intramuscular oxygen could play a key role in the early diagnosis of acute compartment syndrome, a common condition occurring after severe trauma leading to ischemia and long-term consequences including rhabdomyolysis, limb loss, and death. However, to date, there is no existing oxygen sensor approved for such a purpose. To address the need to improve the assessment of compartment syndrome, a portable fiber-optic device for intramuscular oxygen measurements was developed. The device is based on phosphorescence quenching, where the tip of an optical fiber was coated with a poly(propyl methacrylate) (PPMA) matrix containing a brightly emitting Pt(II)-core porphyrin. The optoelectronic circuit is highly portable and is based on a microspectrometer and a microcontroller readout with a smartphone. Results from an in vivo tourniquet porcine model show that the sensor is sensitive across the physiological oxygen partial pressure range of 0-80 mmHg and exhibits an appropriate and reproducible response to changes in intramuscular oxygen. A commercial laboratory oxygen sensor based on a lifetime measurement did not respond as expected.