Lifestyle diseases and cardiovascular risk factors are interrelated to deficiencies of major substrates in ATP synthesis

Recent studies on diabetes and metabolic syndrome indicate a common disturbance of inorganic phosphate (Pi) metabolism. Pi is an important substrate in the formation of adenosine triphosphate (ATP), and many lifestyle diseases and cardiovascular risk factors similarly show deficiencies in either 1 or 2 major components of ATP synthesis. Age, male gender, hypertension, obesity, hypertriglyceridemia, metabolic syndrome, and diabetes mellitus are all associated with hypophosphatemia. In addition, tobacco smoking, hyperchylomicronemia, hypertension, and diabetes may involve defects in tissue oxygen delivery. Hypophosphatemia may lead to a critical decrease in intracellular Pi and to mitochondrial dysfunction, which might be counter-acted by the pharmacological use of fructose 1,6-diphosphate

Disturbance of inorganic phosphate metabolism in diabetes mellitus: clinical manifestations of phosphorus-depletion syndrome during recovery from diabetic ketoacidosis

The acute effects of intracellular phosphate depletion and hypophosphatemia on organs and tissues in and during recovery from diabetic ketoacidosis (DKA) have been reviewed. When insufficient phosphate and/or oxygen are available for high energy phosphate synthesis, cell homeostasis cannot be maintained and cell integrity may be impaired. The clinical consequences are recognized as occasional cause of morbidity and mortality. Although phosphate repletion has not been routinely recommended in the treatment of DKA, physicians should be aware of these clinical conditions and phosphate repletion in such situations should be considered

Disturbance of inorganic phosphate metabolism in diabetes mellitus: temporary therapeutic intervention trials

A paradoxical metabolic imbalance in inorganic phosphate occurs from the early onset of diabetes and may lead to a reduction of high energy phosphates and tissue hypoxia. These changes take place in the cells and tissues in which the entry of glucose is not controlled by insulin, and particularly in poorly regulated diabetes patients in whom long-term vascular complications are more likely to occur. Several therapeutic intervention trials have been carried out, including assessment of optimal glucose regulation, the effect of dietary inclusion of calcium diphosphate and pharmaceutical intake of etidronate disodium (EHDP), but none of these modalities wholly overcome the problem. The potential therapeutic application of fructose-1, 6-diphosphate, however, which also acts as human bioenergy, holds a great deal of promise as an efficacious and well-tolerated therapeutic regimen

De novo pathway-based biomarker identification

Gene expression profiles have been extensively discussed as an aid to guide the therapy by predicting disease outcome for the patients suffering from complex diseases, such as cancer. However, prediction models built upon single-gene (SG) features show poor stability and performance on independent datasets. Attempts to mitigate these drawbacks have led to the development of network-based approaches that integrate pathway information to produce meta-gene (MG) features. Also, MG approaches have only dealt with the two-class problem of good versus poor outcome prediction. Stratifying patients based on their molecular subtypes can provide a detailed view of the disease and lead to more personalized therapies. We propose and discuss a novel MG approach based on de novo pathways, which for the first time have been used as features in a multi-class setting to predict cancer subtypes. Comprehensive evaluation in a large cohort of breast cancer samples from The Cancer Genome Atlas (TCGA) revealed that MGs are considerably more stable than SG models, while also providing valuable insight into the cancer hallmarks that drive them. In addition, when tested on an independent benchmark non-TCGA dataset, MG features consistently outperformed SG models. We provide an easy-touse web service at http:// pathclass. compbio. sdu. dk where users can upload their own gene expression datasets from breast cancer studies and obtain the subtype predictions from all the classifiers

Global MicroRNA Expression Profiling of High-Risk ER+ Breast Cancers from Patients Receiving Adjuvant Tamoxifen Mono-Therapy: A DBCG Study

PURPOSE: Despite the benefits of estrogen receptor (ER)-targeted endocrine therapies in breast cancer, many tumors develop resistance. MicroRNAs (miRNAs) have been suggested as promising biomarkers and we here evaluated whether a miRNA profile could be identified, sub-grouping ER+ breast cancer patients treated with adjuvant Tamoxifen with regards to probability of recurrence. EXPERIMENTAL DESIGN: Global miRNA analysis was performed on 152 ER+ primary tumors from high-risk breast cancer patients with an initial discovery set of 52 patients, followed by two independent test sets (N = 60 and N = 40). All patients had received adjuvant Tamoxifen as mono-therapy (median clinical follow-up: 4.6 years) and half had developed distant recurrence (median time-to-recurrence: 3.5 years). MiRNA expression was examined by unsupervised hierarchical clustering and supervised analysis, including clinical parameters as co-variables. RESULTS: The discovery set identified 10 highly significant miRNAs that discriminated between the patient samples according to outcome. However, the subsequent two independent test sets did not confirm the predictive potential of these miRNAs. A significant correlation was identified between miR-7 and the tumor grade. Investigation of the microRNAs with the most variable expression between patients in different runs yielded a list of 31 microRNAs, eight of which are associated with stem cell characteristics. CONCLUSIONS: Based on the large sample size, our data strongly suggests that there is no single miRNA profile predictive of outcome following adjuvant Tamoxifen treatment in a broad cohort of ER+ breast cancer patients. We identified a sub-group of Tamoxifen-treated breast cancer patients with miRNA-expressing tumors associated with cancer stem cell characteristics

Functional heterogeneity within the CD44 high human breast cancer stem cell-like compartment reveals a gene signature predictive of distant metastasis

The CD44(hi) compartment in human breast cancer is enriched in tumor-initiating cells; however, the functional heterogeneity within this subpopulation remains poorly defined. We used a triple-negative breast cancer cell line with a known bilineage phenotype to isolate and clone CD44(hi) single cells that exhibited mesenchymal/basal B and luminal/basal A features, respectively. Herein, we demonstrate in this and other triple-negative breast cancer cell lines that, rather than CD44(hi)/CD24(−) mesenchymal-like basal B cells, the CD44(hi)/CD24(lo) epithelioid basal A cells retained classic cancer stem cell features, such as tumor-initiating capacity in vivo, mammosphere formation and resistance to standard chemotherapy. These results complement previous findings using oncogene-transformed normal mammary cells showing that only cell clones with a mesenchymal phenotype exhibit cancer stem cell features. Further, we performed comparative quantitative proteomic and gene array analyses of these cells and identified potential novel markers of breast cancer cells with tumor-initiating features, such as lipolysis-stimulated lipoprotein receptor (LSR), RAB25, S100A14 and mucin 1 (MUC1), as well as a novel 31-gene signature capable of predicting distant metastasis in cohorts of estrogen receptor–negative human breast cancers. These findings strongly favor functional heterogeneity in the breast cancer cell compartment and hold promise for further refinements of prognostic marker profiling. Our work confirms that, in addition to cancer stem cells with mesenchymal-like morphology, those tumor-initiating cells with epithelial-like morphology should also be the focus of drug development