Erythropoietin induction in Hep3B cells is not affected by inhibition of heme biosynthesis

AbstractErythropoietin (Epo) is one of the physiologically important genes whose transcription is up-regulated by hypoxia. Our laboratory previously proposed that the sensor of this event is a heme protein which turns over rapidly. We have investigated the effects of four inhibitors of heme synthesis (4,6-dioxoheptanoic acid (DHA), isoniazid (INH), N-methyl protoporphyrin IX (MPP), and deferoxamine mesylate (DSF)) on hypoxia-, cobalt-, and DSF-induced erythropoietin (Epo) mRNA expression, heme biosynthesis, and cell viability in Hep3B cells. DHA (0.1–1.0 mM) inhibited heme biosynthesis more than 85%, but did not suppress Epo mRNA expression. Epo mRNA expression was inhibited only at higher concentrations of DHA (2, 4 mM) which also inhibited cell viability. No suppression of Epo mRNA expression by INH was observed at doses known to inhibit heme biosynthesis. MPP did not suppress Epo mRNA expression although it showed an inhibitory effect on heme biosynthesis without any decreased cell viability. 130 μM DSF, a dose which inhibited heme biosynthesis without cell toxicity, suppressed hypoxia-induced Epo mRNA expression, but enhanced cobalt-induced Epo mRNA expression. These results show that although the oxygen sensor is probably a heme protein it does not turn over rapidly. Therefore, cobalt is unlikely to act by substituting for heme iron

Predicting gene promoter methylation in non-small-cell lung cancer by evaluating sputum and serum

The use of 5-methylcytosine demethylating agents in conjunction with inhibitors of histone deacetylation may offer a new therapeutic strategy for lung cancer. Monitoring the efficacy of gene demethylating treatment directly within the tumour may be difficult due to tumour location. This study determined the positive and negative predictive values of sputum and serum for detecting gene methylation in primary lung cancer. A panel of eight genes was evaluated by comparing methylation detected in the primary tumour biopsy to serum and sputum obtained from 72 patients with Stage III lung cancer. The prevalence for methylation of the eight genes in sputum (21–43%) approximated to that seen in tumours, but was 0.7–4.3-fold greater than detected in serum. Sputum was superior to serum in classifying the methylation status of genes in the tumour biopsy. The positive predictive value of the top four genes (p16, DAPK, PAX5 β, and GATA5) was 44–72% with a negative predictive value for these genes ⩾70%. The highest specificity was seen for the p16 gene, and this was associated with a odds ratio of six for methylation in the tumour when this gene was methylated in sputum. In contrast, for serum, the individual sensitivity for all genes was 6–27%. Evaluating the combined effect of methylation of at least one of the four most significant genes in sputum increased the positive predictive value to 86%. These studies demonstrate that sputum can be used effectively as a surrogate for tumour tissue to predict the methylation status of advanced lung cancer where biopsy is not feasible

Genetic Determinants of Variability in Glycated Hemoglobin (HbA1c) in Humans: Review of Recent Progress and Prospects for Use in Diabetes Care

Glycated hemoglobin A1c (HbA1c) indicates the percentage of total hemoglobin that is bound by glucose, produced from the nonenzymatic chemical modification by glucose of hemoglobin molecules carried in erythrocytes. HbA1c represents a surrogate marker of average blood glucose concentration over the previous 8 to 12 weeks, or the average lifespan of the erythrocyte, and thus represents a more stable indicator of glycemic status compared with fasting glucose. HbA1c levels are genetically determined, with heritability of 47% to 59%. Over the past few years, inroads into understanding genetic predisposition by glycemic and nonglycemic factors have been achieved through genome-wide analyses. Here I review current research aimed at discovering genetic determinants of HbA1c levels, discussing insights into biologic factors influencing variability in the general and diabetic population, and across different ethnicities. Furthermore, I discuss briefly the relevance of findings for diabetes monitoring and diagnosis