Body mass index is not a predictor of biochemical recurrence after radical prostatectomy in Dutch men diagnosed with prostate cancer

Contains fulltext : 95677.pdf (publisher's version ) (Closed access)PURPOSE: To determine the effect of body mass index (BMI) on clinical and pathological characteristics at time of diagnosis and on risk of biochemical recurrence after radical prostatectomy among Dutch men diagnosed with prostate cancer. METHODS: In total, 1,116 prostate cancer patients with known BMI, diagnosed between 2003 and 2006, were identified from the population-based cancer registry held by the Comprehensive Cancer Centre East, The Netherlands. Of these, 504 patients underwent a radical prostatectomy. Patients were categorized as normal weight (BMI /= 30 kg/m(2)). Multivariable proportional hazards regression models, adjusted for age, prediagnostic PSA levels, and pathological characteristics were used to evaluate BMI as a prognostic factor for biochemical recurrence after radical prostatectomy. RESULTS: Overall, clinical and biopsy characteristics did not significantly differ among BMI groups. Pathological characteristics after radical prostatectomy did not significantly differ among BMI groups, except for tumor stage, which was highest in obese patients (P = 0.017). For patients treated with radical prostatectomy, 5-year risk (95% Confidence Intervals) of biochemical recurrence was 30% (23-37%) for normal weight, 32% (25-39%) for overweight, and 25% (9-41%) for obese patients (log rank P = 0.810). BMI was not an independent prognostic factor for biochemical recurrence in multivariable proportional hazards regression analyses (HR 0.99 per kg/m(2), 95% CI: 0.93-1.06). CONCLUSIONS: Compared with non-obese men, pathological tumor stage tended to be higher in obese men. Clinical relevance of this finding is unclear, because BMI was not an independent predictor of biochemical recurrence after radical prostatectomy

Identification of serum biomarkers for colon cancer by proteomic analysis

Colorectal cancer (CRC) is often diagnosed at a late stage with concomitant poor prognosis. Early detection greatly improves prognosis; however, the invasive, unpleasant and inconvenient nature of current diagnostic procedures limits their applicability. No serum-based test is currently of sufficient sensitivity or specificity for widespread use. In the best currently available blood test, carcinoembryonic antigen exhibits low sensitivity and specificity particularly in the setting of early disease. Hence, there is great need for new biomarkers for early detection of CRC. We have used surface-enhanced laser desorbtion/ionisation (SELDI) to investigate the serum proteome of 62 CRC patients and 31 noncancer subjects. We have identified proteins (complement C3a des-arg, α1-antitrypsin and transferrin) with diagnostic potential. Artificial neural networks trained using only the intensities of the SELDI peaks corresponding to identified proteins were able to classify the patients used in this study with 95% sensitivity and 91% specificity

Associations between an Obesity Related Genetic Variant (FTO rs9939609) and Prostate Cancer Risk

Observational studies suggest that obese men have a lower risk of incident prostate cancer, but an increased risk of advanced and fatal cancers. These observations could be due to confounding, detection bias, or a biological effect of obesity. Genetic studies are less susceptible to confounding than observational epidemiology and can suggest how associations between phenotypes (such as obesity) and diseases arise. To determine whether the associations between obesity and prostate cancer are causal, we conducted a genetic association study of the relationship between a single nucleotide polymorphism known to be associated with obesity (FTO rs9939609) and prostate cancer. Data are from a population-based sample of 1550 screen-detected prostate cancers, 1815 age- and general practice matched controls with unrestricted prostate specific antigen (PSA) values and 1175 low-PSA controls (PSA <0.5 ng/ml). The rs9939609 A allele, which was associated with higher BMI in the sample, was inversely associated with overall (odds ratio (OR) versus all controls  = 0.93; 95% confidence interval (CI): 0.85–1.02 p = 0.12 per allele) and low-grade (OR = 0.90; 0.81–0.99 p = 0.03 per allele) prostate cancer risk, but positively associated with high-grade cancer among cases (OR high- versus low-grade cancer  = 1.16; 0.99–1.37 p = 0.07 per allele). Although evidence for these effects was weak, they are consistent with observational data based on BMI phenotypes and suggest that the observed association between obesity and prostate cancer is not due to confounding. Further research should confirm these findings, extend them to other BMI-related genetic variants and determine whether they are due to detection bias or obesity-related hormonal changes

Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models

<p>Abstract</p> <p>Background</p> <p>Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood.</p> <p>Methods</p> <p>The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS).</p> <p>The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses.</p> <p>The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer.</p> <p>Results</p> <p>In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (<it>CHKA</it>, <it>CHKB</it>) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (<it>PLA2G4A</it>) and phospholipase B1 (<it>PLB1</it>) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer.</p> <p>Conclusions</p> <p>The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.</p

A Pathogenic Mechanism in Huntington's Disease Involves Small CAG-Repeated RNAs with Neurotoxic Activity

Huntington's disease (HD) is an autosomal dominantly inherited disorder caused by the expansion of CAG repeats in the Huntingtin (HTT) gene. The abnormally extended polyglutamine in the HTT protein encoded by the CAG repeats has toxic effects. Here, we provide evidence to support that the mutant HTT CAG repeats interfere with cell viability at the RNA level. In human neuronal cells, expanded HTT exon-1 mRNA with CAG repeat lengths above the threshold for complete penetrance (40 or greater) induced cell death and increased levels of small CAG-repeated RNAs (sCAGs), of ≈21 nucleotides in a Dicer-dependent manner. The severity of the toxic effect of HTT mRNA and sCAG generation correlated with CAG expansion length. Small RNAs obtained from cells expressing mutant HTT and from HD human brains significantly decreased neuronal viability, in an Ago2-dependent mechanism. In both cases, the use of anti-miRs specific for sCAGs efficiently blocked the toxic effect, supporting a key role of sCAGs in HTT-mediated toxicity. Luciferase-reporter assays showed that expanded HTT silences the expression of CTG-containing genes that are down-regulated in HD. These results suggest a possible link between HD and sCAG expression with an aberrant activation of the siRNA/miRNA gene silencing machinery, which may trigger a detrimental response. The identification of the specific cellular processes affected by sCAGs may provide insights into the pathogenic mechanisms underlying HD, offering opportunities to develop new therapeutic approaches

Differential Role of Human Choline Kinase α and β Enzymes in Lipid Metabolism: Implications in Cancer Onset and Treatment

11 pages, 6 figures, 1 table.Background The Kennedy pathway generates phosphocoline and phosphoethanolamine through its two branches. Choline Kinase (ChoK) is the first enzyme of the Kennedy branch of synthesis of 1phosphocholine, the major component of the plasma membrane. ChoK family of proteins is composed by ChoKα and ChoKβ isoforms, the first one with two different variants of splicing. Recently ChoKα has been implicated in the carcinogenic process, since it is over-expressed in a variety of human cancers. However, no evidence for a role of ChoKβ in carcinogenesis has been reported. Methodology/Principal Findings Here we compare the in vitro and in vivo properties of ChoKα1 and ChoKβ in lipid metabolism, and their potential role in carcinogenesis. Both ChoKα1 and ChoKβ showed choline and ethanolamine kinase activities when assayed in cell extracts, though with different affinity for their substrates. However, they behave differentially when overexpressed in whole cells. Whereas ChoKβ display an ethanolamine kinase role, ChoKα1 present a dual choline/ethanolamine kinase role, suggesting the involvement of each ChoK isoform in distinct biochemical pathways under in vivo conditions. In addition, while overexpression of ChoKα1 is oncogenic when overexpressed in HEK293T or MDCK cells, ChoKβ overexpression is not sufficient to induce in vitro cell transformation nor in vivo tumor growth. Furthermore, a significant upregulation of ChoKα1 mRNA levels in a panel of breast and lung cancer cell lines was found, but no changes in ChoKβ mRNA levels were observed. Finally, MN58b, a previously described potent inhibitor of ChoK with in vivo antitumoral activity, shows more than 20-fold higher efficiency towards ChoKα1 than ChoKβ. Conclusion/Significance This study represents the first evidence of the distinct metabolic role of ChoKα and ChoKβ isoforms, suggesting different physiological roles and implications in human carcinogenesis. These findings constitute a step forward in the design of an antitumoral strategy based on ChoK inhibition.This work has been supported by grants to JCL from Comunidad de Madrid (GR-SAL-0821-2004), Ministerio de Ciencia e Innovación (SAF2008-03750, RD06/0020/0016), Fundación Mutua Madrileña, and by a grant to ARM from Fundación Mutua Madrileña.Peer reviewe

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM

Protein expression in experimental malignant glioma varies over time and is altered by radiotherapy treatment

Radiotherapy is one of the mainstays of glioblastoma (GBM) treatment. This study aims to investigate and characterise differences in protein expression patterns in brain tumour tissue following radiotherapy, in order to gain a more detailed understanding of the biological effects. Rat BT4C glioma cells were implanted into the brain of two groups of 12 BDIX-rats. One group received radiotherapy (12 Gy single fraction). Protein expression in normal and tumour brain tissue, collected at four different time points after irradiation, were analysed using surface enhanced laser desorption/ionisation – time of flight – mass spectrometry (SELDI-TOF-MS). Mass spectrometric data were analysed by principal component analysis (PCA) and partial least squares (PLS). Using these multivariate projection methods we detected differences between tumours and normal tissue, radiation treatment-induced changes and temporal effects. 77 peaks whose intensity significantly changed after radiotherapy were discovered. The prompt changes in the protein expression following irradiation might help elucidate biological events induced by radiation. The combination of SELDI-TOF-MS with PCA and PLS seems to be well suited for studying these changes. In a further perspective these findings may prove to be useful in the development of new GBM treatment approaches