Cell line-directed breast cancer research based on glucose metabolism status

Metabolic reprogramming is a potential hallmark of tumor cells to support continuous proliferation. Metabolic heterogeneity in breast cancer patients has been highlighted as the driving cause of tumor progression and resistance to anticancer drugs. Studying and identifying distinct metabolic alterations in breast cancer subtypes could offer new perspectives for faster diagnosis and treatment. Given cancer cell dependency on glycolysis, the primary energy source, this enzymatic pathway will play a critical role in targeting therapies. Knowledge about the specific metabolic dependencies of tumors for growth and proliferation can be promising for novel targeted and cell-based therapies. Here, the metabolic status with emphasis on glycolysis of breast cancer cell lines according to their classification was reviewed.

NMR Metabolomics for Stem Cell type discrimination

Cell metabolism is a key determinant factor for the pluripotency and fate commitment of Stem Cells (SCs) during development, ageing, pathological onset and progression. We derived and cultured selected subpopulations of rodent fetal, postnatal, adult Neural SCs (NSCs) and postnatal glial progenitors, Olfactory Ensheathing Cells (OECs), respectively from the subventricular zone (SVZ) and the olfactory bulb (OB). Cell lysates were analyzed by proton Nuclear Magnetic Resonance (¹H-NMR) spectroscopy leading to metabolites identification and quantitation. Subsequent multivariate analysis of NMR data by Principal Component Analysis (PCA), and Partial Least Square Discriminant Analysis (PLS-DA) allowed data reduction and cluster analysis. This strategy ensures the definition of specific features in the metabolic content of phenotypically similar SCs sharing a common developmental origin. The metabolic fingerprints for selective metabolites or for the whole spectra demonstrated enhanced peculiarities among cell types. The key result of our work is a neat divergence between OECs and the remaining NSC cells. We also show that statistically significant differences for selective metabolites characterizes NSCs of different ages. Finally, the retrived metabolome in cell cultures correlates to the physiological SC features, thus allowing an integrated bioengineering approach for biologic fingerprints able to dissect the (neural) SC molecular specificities.

Breast cancer redox heterogeneity detectable with chemical exchange saturation transfer (CEST) MRI

PURPOSE

Tissue redox state is an important mediator of various biological processes in health and diseases such as cancer. Previously, we discovered that the mitochondrial redox state of ex vivo tissues detected by redox scanning (an optical imaging method) revealed interesting tumor redox state heterogeneity that could differentiate tumor aggressiveness. Because the noninvasive chemical exchange saturation transfer (CEST) MRI can probe the proton transfer and generate contrasts from endogenous metabolites, we aim to investigate if the in vivo CEST contrast is sensitive to proton transfer of the redox reactions so as to reveal the tissue redox states in breast cancer animal models.

PROCEDURES

CEST MRI has been employed to characterize tumor metabolic heterogeneity and correlated with the redox states measured by the redox scanning in two human breast cancer mouse xenograft models, MDA-MB-231 and MCF-7. The possible biological mechanism on the correlation between the two imaging modalities was further investigated by phantom studies where the reductants and the oxidants of the representative redox reactions were measured.

RESULTS

The CEST contrast is found linearly correlated with NADH concentration and the NADH redox ratio with high statistical significance, where NADH is the reduced form of nicotinamide adenine dinucleotide. The phantom studies showed that the reductants of the redox reactions have more CEST contrast than the corresponding oxidants, indicating that higher CEST effect corresponds to the more reduced redox state.

CONCLUSIONS

This preliminary study suggests that CEST MRI, once calibrated, might provide a novel noninvasive imaging surrogate for the tissue redox state and a possible diagnostic biomarker for breast cancer in the clinic.

Metabolic characterization of triple negative breast cancer

Background

The aims of this study were to characterize the metabolite profiles of triple negative breast cancer (TNBC) and to investigate the metabolite profiles associated with human epidermal growth factor receptor-2/neu (HER-2) overexpression using ex vivo high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). Metabolic alterations caused by the different estrogen receptor (ER), progesterone receptor (PgR) and HER-2 receptor statuses were also examined. To investigate the metabolic differences between two distinct receptor groups, TNBC tumors were compared to tumors with ER^pos/PgR^pos/HER-2^pos status which for the sake of simplicity is called triple positive breast cancer (TPBC).

Methods

The study included 75 breast cancer patients without known distant metastases. HR MAS MRS was performed for identification and quantification of the metabolite content in the tumors. Multivariate partial least squares discriminant analysis (PLS-DA) modeling and relative metabolite quantification were used to analyze the MR data.

Results

Choline levels were found to be higher in TNBC compared to TPBC tumors, possibly related to cell proliferation and oncogenic signaling. In addition, TNBC tumors contain a lower level of Glutamine and a higher level of Glutamate compared to TPBC tumors, which indicate an increase in glutaminolysis metabolism. The development of glutamine dependent cell growth or “Glutamine addiction” has been suggested as a new therapeutic target in cancer. Our results show that the metabolite profiles associated with HER-2 overexpression may affect the metabolic characterization of TNBC. High Glycine levels were found in HER-2^pos tumors, which support Glycine as potential marker for tumor aggressiveness.

Conclusions

Metabolic alterations caused by the individual and combined receptors involved in breast cancer progression can provide a better understanding of the biochemical changes underlying the different breast cancer subtypes. Studies are needed to validate the potential of metabolic markers as targets for personalized treatment of breast cancer subtypes.

Metabolic Effects of Known and Novel HDAC and SIRT Inhibitors in Glioblastomas Independently or Combined with Temozolomide

Inhibition of protein deacetylation enzymes, alone or in combination with standard chemotherapies, is an exciting addition to cancer therapy. We have investigated the effect of deacetylase inhibition on the metabolism of glioblastoma cells. ¹H NMR metabolomics analysis was used to determine the major metabolic changes following treatment of two distinct glioblastoma cell lines, U373 and LN229, with five different histone deacetylase (HDAC) inhibitors, as well as one inhibitor of NAD+-dependent protein deacetylases (SIRT). The addition of the standard glioblastoma chemotherapy agent, temozolomide, to the HDAC and SIRT treatments led to a reduction in cell survival, suggesting a possibility for combined treatment. This study shows that distinct glioblastoma cell lines, with different metabolic profiles and gene expression, experience dissimilar changes following treatment with protein deacetylase inhibitors. The observed effects of inhibitors on mitochondrial metabolism, glycolysis and fatty acid synthesis suggest possible roles of protein deacetylases in metabolism regulation. Metabolic markers of the effectiveness of anti-protein deacetylase treatments have been explored. In addition to known deacetylation inhibitors, three novel inhibitors have been introduced and tested. Finally, ¹H NMR analysis of cellular metabolism is shown to be a fast, inexpensive method for testing drug effects.

Metabolic changes in psoriatic skin under topical corticosteroid treatment

Background

MR spectroscopy of intact biopsies can provide a metabolic snapshot of the investigated tissue. The aim of the present study was to explore the metabolic pattern of uninvolved skin, psoriatic skin and corticosteroid treated psoriatic skin.

Methods

The three types of skin biopsy samples were excised from patients with psoriasis (N = 10). Lesions were evaluated clinically, and tissue biopsies were excised and analyzed by one-dimensional ¹H MR spectroscopy. Relative levels were calculated for nine tissue metabolites. Subsequently, relative amounts of epidermis, dermis and subcutaneous tissue were scored by histopathological evaluation of HES stained sections.

Results

Seven out of 10 patients experienced at least 40% reduction in clinical score after corticosteroid treatment. Tissue biopsies from psoriatic skin contained lower levels of the metabolites myo-inositol and glucose, and higher levels of choline and taurine compared to uninvolved skin. In corticosteroid treated psoriatic skin, tissue levels of glucose, myo-inositol, GPC and glycine were increased, whereas choline was reduced, in patients with good therapeutic effect. These tissue levels are becoming more similar to metabolite levels in uninvolved skin.

Conclusion

This MR method demonstrates that metabolism in psoriatic skin becomes similar to that of uninvolved skin after effective corticosteroid treatment. MR profiling of skin lesions reflect metabolic alterations related to pathogenesis and treatment effects.

1H NMR metabolomics analysis of glioblastoma subtypes: correlation between metabolomics and gene expression characteristics

Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. (1)H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas.