ddcP, pstB, and excess D-lactate impact synergism between vancomycin and chlorhexidine against Enterococcus faecium 1,231,410.

Vancomycin-resistant enterococci (VRE) are important nosocomial pathogens that cause life-threatening infections. To control hospital-associated infections, skin antisepsis and bathing utilizing chlorhexidine is recommended for VRE patients in acute care hospitals. Previously, we reported that exposure to inhibitory chlorhexidine levels induced the expression of vancomycin resistance genes in VanA-type Enterococcus faecium. However, vancomycin susceptibility actually increased for VanA-type E. faecium in the presence of chlorhexidine. Hence, a synergistic effect of the two antimicrobials was observed. In this study, we used multiple approaches to investigate the mechanism of synergism between chlorhexidine and vancomycin in the VanA-type VRE strain E. faecium 1,231,410. We generated clean deletions of 7 of 11 pbp, transpeptidase, and carboxypeptidase genes in this strain (ponA, pbpF, pbpZ, pbpA, ddcP, ldtfm, and vanY). Deletion of ddcP, encoding a membrane-bound carboxypeptidase, altered the synergism phenotype. Furthermore, using in vitro evolution, we isolated a spontaneous synergy escaper mutant and utilized whole genome sequencing to determine that a mutation in pstB, encoding an ATPase of phosphate-specific transporters, also altered synergism. Finally, addition of excess D-lactate, but not D-alanine, enhanced synergism to reduce vancomycin MIC levels. Overall, our work identified factors that alter chlorhexidine and vancomycin synergism in a model VanA-type VRE strain.

Bevacizumab increases risk for severe proteinuria in cancer patients.

Treatment with the chemotherapeutic agent bevacizumab, a humanized mAb that neutralizes vascular endothelial growth factor, can lead to proteinuria and renal damage. The risk factors and clinical outcomes of renal adverse events are not well understood. We performed a systematic review and meta-analysis of published randomized, controlled trials to assess the overall risk for severe proteinuria with bevacizumab. We analyzed data from 16 studies comprising 12,268 patients with a variety of tumors. The incidence of high-grade (grade 3 or 4) proteinuria with bevacizumab was 2.2% (95% confidence interval [CI] 1.2 to 4.3%). Compared with chemotherapy alone, bevacizumab combined with chemotherapy significantly increased the risk for high-grade proteinuria (relative risk 4.79; 95% CI 2.71 to 8.46) and nephrotic syndrome (relative risk 7.78; 95% CI 1.80 to 33.62); higher dosages of bevacizumab associated with increased risk for proteinuria. Regarding tumor type, renal cell carcinoma associated with the highest risk (cumulative incidence 10.2%). We did not detect a significant difference between platinum- and non-platinum-based concurrent chemotherapy with regard to risk for high-grade proteinuria (P = 0.39). In conclusion, the addition of bevacizumab to chemotherapy significantly increases the risk for high-grade proteinuria and nephrotic syndrome.

Class prediction models of thrombocytosis using genetic biomarkers.

Criteria for distinguishing among etiologies of thrombocytosis are limited in their capacity to delineate clonal (essential thrombocythemia [ET]) from nonclonal (reactive thrombocytosis [RT]) etiologies. We studied platelet transcript profiles of 126 subjects (48 controls, 38 RT, 40 ET [24 contained the JAK2V(617)F mutation]) to identify transcript subsets that segregated phenotypes. Cross-platform consistency was validated using quantitative real-time polymerase chain reaction (RT-PCR). Class prediction algorithms were developed to assign phenotypic class between the thrombocytosis cohorts, and by JAK2 genotype. Sex differences were rare in normal and ET cohorts (< 1% of genes) but were male-skewed for approximately 3% of RT genes. An 11-biomarker gene subset using the microarray data discriminated among the 3 cohorts with 86.3% accuracy, with 93.6% accuracy in 2-way class prediction (ET vs RT). Subsequent quantitative RT-PCR analysis established that these biomarkers were 87.1% accurate in prospective classification of a new cohort. A 4-biomarker gene subset predicted JAK2 wild-type ET in more than 85% patient samples using either microarray or RT-PCR profiling, with lower predictive capacity in JAK2V(617)F mutant ET patients. These results establish that distinct genetic biomarker subsets can predict thrombocytosis class using routine phlebotomy.