Effect of metformin versus placebo on metabolic factors in the MA.32 randomized breast cancer trial

Abstract Metformin may exert anticancer effects through indirect (mediated by metabolic changes) or direct mechanisms. The goal was to examine metformin impact on metabolic factors in non-diabetic subjects and determine whether this impact varies by baseline BMI, insulin, and rs11212617 SNP in CCTG MA.32, a double-blind placebo-controlled randomized adjuvant breast cancer (BC) trial. 3649 subjects with T1-3, N0-3, M0 BC were randomized; pretreatment and 6-month on-treatment fasting plasma was centrally assayed for insulin, leptin, highly sensitive C-reactive protein (hsCRP). Glucose was measured locally and homeostasis model assessment (HOMA) calculated. Genomic DNA was analyzed for the rs11212617 SNP. Absolute and relative change of metabolic factors (metformin versus placebo) were compared using Wilcoxon rank and t-tests. Regression models were adjusted for baseline differences and assessed interactions with baseline BMI, insulin, and the SNP. Mean age was 52 years. The majority had T2/3, node positive, hormone receptor positive, HER2 negative BC treated with (neo)adjuvant chemotherapy and hormone therapy. Median baseline body mass index (BMI) was 27.4 kg/m2 (metformin) and 27.3 kg/m2 (placebo). Median weight change was −1.4 kg (metformin) vs +0.5 kg (placebo). Significant improvements were seen in all metabolic factors, with 6 month standardized ratios (metformin/placebo) of 0.85 (insulin), 0.83 (HOMA), 0.80 (leptin), and 0.84 (hsCRP), with no qualitative interactions with baseline BMI or insulin. Changes did not differ by rs11212617 allele. Metformin (vs placebo) led to significant improvements in weight and metabolic factors; these changes did not differ by rs11212617 allele status

A global analysis of protein expression profiles in Sinorhizobium meliloti: Discovery of new genes for nodule occupancy and stress adaptation

A proteomic examination of Sinorhizobium meliloti strain 1021 was undertaken using a combination of 2-D gel electrophoresis, peptide mass fingerprinting, and bioinformatics. Our goal was to identify (i) putative symbiosis- or nutrientstress-specific proteins, (ii) the biochemical pathways active under different conditions, (iii) potential new genes, and (iv) the extent of posttranslational modifications of S. meliloti proteins. In total, we identified the protein products of 810 genes (13.1% of the genome's coding capacity). The 810 genes generated 1,180 gene products, with chromosomal genes accounting for 78% of the gene products identified (18.8% of the chromosome's coding capacity). The activity of 53 metabolic pathways was inferred from bioinformatic analysis of proteins with assigned Enzyme Commission numbers. Of the remaining proteins that did not encode enzymes, ABC-type transporters composed 12.7% and regulatory proteins 3.4% of the total. Proteins with up to seven transmembrane domains were identified in membrane preparations. A total of 27 putative nodulespecific proteins and 35 nutrient-stress-specific proteins were identified and used as a basis to define genes and describe processes occurring in S. meliloti cells in nodules and under stress. Several nodule proteins from the plant host were present in the nodule bacteria preparations. We also identified seven potentially novel proteins not predicted from the DNA sequence. Post-translational modifications such as N-terminal processing could be inferred from the data. The posttranslational addition of UMP to the key regulator of nitrogen metabolism, PII, was demonstrated. This work demonstrates the utility of combining mass spectrometry with protein arraying or separation techniques to identify candidate genes involved in important biological processes and niche occupations that may be intransigent to other methods of gene expression profiling

The Composite Genome Of The Legume Symbiont Sinorhizobium Meliloti

The scarcity of usable nitrogen frequently limits plant growth. A tight metabolic association with rhizobial bacteria allows legumes to obtain nitrogen compounds by bacterial reduction of dinitrogen (N2) to ammonium (NH4+). We present here the annotated DNA sequence of the alpha-proteobacterium Sinorhizobium meliloti, the symbiont of alfalfa. The tripartite 6.7-megabase (Mb) genome comprises a 3.65-Mb chromosome, and 1.35-Mb pSymA and 1.68-Mb pSymB megaplasmids. Genome sequence analysis indicates that all three elements contribute, in varying degrees, to symbiosis and reveals how this genome may have emerged during evolution. The genome sequence will be useful in understanding the dynamics of interkingdom associations and of life in soil environments