Individual and combined soy isoflavones exert differential effects on metastatic cancer progression

To investigate the effects soy isoflavones in established cancers, the role of genistein, daidzein, and combined soy isoflavones was studied on progression of subcutaneous tumors in nude mice created from green fluorescent protein (GFP) tagged-MDA-MB-435 cells. Following tumor establishment, mice were gavaged with vehicle or genistein or daidzein at 10 mg/kg body weight (BW) or a combination of genistein (10 mg/kg BW), daidzein (9 mg/kg BW), and glycitein (1 mg/kg BW) three times per week. Tumor progression was quantified by whole body fluorescence image analysis followed by microscopic image analysis of excised organs for metastases. Results show that daidzein increased while genistein decreased mammary tumor growth by 38 and 33% respectively, compared to vehicle. Daidzein increased lung and heart metastases while genistein decreased bone and liver metastases. Combined soy isoflavones did not affect primary tumor growth but increased metastasis to all organs tested, which include lung, liver, heart, kidney, and bones. Phosphoinositide-3-kinase (PI3-K) pathway real time PCR array analysis and western blotting of excised tumors demonstrate that genistein significantly downregulated 10/84 genes, including the Rho GTPases RHOA, RAC1, and CDC42 and their effector PAK1. Daidzein significantly upregulated 9/84 genes that regulate proliferation and protein synthesis including EIF4G1, eIF4E, and survivin protein levels. Combined soy treatment significantly increased gene and protein levels of EIF4E and decreased TIRAP gene expression. Differential regulation of Rho GTPases, initiation factors, and survivin may account for the disparate responses of breast cancers to genistein and daidzein diets. This study indicates that consumption of soy foods may increase metastasis

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Secondary Bone Defect in Neuromuscular Diseases in Childhood: A Longitudinal “Muscle-Bone Unit” Analysis

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