Citations

BACKGROUNDApproximately 1.7 million individuals per year are affected with health care‐associated infections (HAIs) in the United States. The authors examined trends in the incidence of HAI after major cancer surgery (MCS) and risk factors for HAI to describe the effects of HAI on mortality after MCS.METHODSPatients undergoing 1 of 8 MCS procedures within the Nationwide Inpatient Sample between 1999 and 2009 were identified (n = 2,502,686). Generalized linear regression models were used to estimate the impact of the primary predictors (procedure type, age, sex, race, insurance status, Charlson comorbidity index, hospital volume, and hospital bed size) on the odds of HAI and in‐hospital mortality. Trends in incidence were evaluated with linear regression.RESULTSOverall, MCS‐associated HAI incidence increased 2.7% per year (P < .001), whereas mortality decreased 1.3% per year (P < .001). Male gender (odds ratio [OR], 1.12, 95% confidence interval [CI], 1.10‐1.14), advancing age (OR, 1.02; 95% CI, 1.02‐1.02), black race (OR, 1.26; 95% CI, 1.21‐1.31), ≥1 comorbidities (OR, from 1.08 [95% CI, 1.04‐1.13] to 1.31 [95% CI, 1.27‐1.35]), and nonprivate insurance (OR, from 1.18 [95% CI, 1.15‐1.22] to 1.67 [95% CI, 1.59‐1.76]) were associated with an increased odds of HAI on multivariable analysis. Conversely, increasing hospital volume was associated with lower odds of HAI (OR, 0.999; 95% CI, 0.99‐0.99). Patients with MCS‐associated HAI had increased odds of mortality (OR, 8.66; 95% CI, 8.51‐8.82).CONCLUSIONSBetween 1999 and 2009, the incidence of MCS‐associated HAI events increased; however, HAI‐associated mortality decreased. That said, significant disparities exist in the hospital and demographic attributes associated with MCS‐associated HAI, with attendant health policy implications. Moreover, HAI remains detrimentally linked to mortality during hospitalization. Cancer 2013;119:2317–2324. © 2013 American Cancer Society.

Precise measurement of low enrichment of stable isotope labeled amino‐acid tracers in tissue samples is a prerequisite in measuring tissue protein synthesis rates. The challenge of this analysis is augmented when small sample size is a critical factor. Muscle samples from human participants following an 8 h intravenous infusion of L‐[ring‐13C6]phenylalanine and a bolus dose of L‐[ring‐13C6]phenylalanine in a mouse were utilized. Liquid chromatography tandem mass spectrometry (LC/MS/MS), gas chromatography (GC) MS/MS and GC/MS were compared to the GC‐combustion‐isotope ratio MS (GC/C/IRMS), to measure mixed muscle protein enrichment of [ring‐13C6]phenylalanine enrichment. The sample isotope enrichment ranged from 0.0091 to 0.1312 molar percent excess. As compared with GC/C/IRMS, LC/MS/MS, GC/MS/MS and GC/MS showed coefficients of determination of R2 = 0.9962 and R2 = 0.9942, and 0.9217 respectively. However, the precision of measurements (coefficients of variation) for intra‐assay are 13.0%, 1.7%, 6.3% and 13.5% and for inter‐assay are 9.2%, 3.2%, 10.2% and 25% for GC/C/IRMS, LC/MS/MS, GC/MS/MS and GC/MS, respectively. The muscle sample sizes required to obtain these results were 8 µg, 0.8 µg, 3 µg and 3 µg for GC/C/IRMS, LC/MS/MS, GC/MS/MS and GC/MS, respectively. We conclude that LC/MS/MS is optimally suited for precise measurements of L‐[ring‐13C6]phenylalanine tracer enrichment in low abundance and in small quantity samples. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract Rare germline mutations in the breast and ovarian cancer predisposition genes BRCA1 and BRCA2 are present in roughly 5 percent of ovarian cancer patients. Both genes play key roles in DNA damage repair but appear to have distinct, although often complementary, functions. The risks of breast and ovarian cancer have been shown to differ between BRCA1 and BRCA2 carriers, and mutation-specific effects have also been suggested for both groups. Published reports comparing the survival of ovarian cancer patients with and without BRCA1/2 mutations generally show a survival advantage among mutation carriers. This is thought to be related to an improved response of carriers to platinum-based therapies. Since it is not known whether BRCA1 and BRCA2 carriers show similar survival patterns, we have performed a large, multicenter study to investigate the impact of germline BRCA1 and BRCA2 mutations on ovarian cancer survival. 3,531 invasive epithelial ovarian cancer cases (1,178 BRCA1, 367 BRCA2 and 1,986 BRCA-negative) with survival time data from twenty-four studies in the U.S.A, Europe, Israel and Asia were included. In our main analysis, we excluded patients who were known or who were likely to have not received platinum-based therapy. Compared to non-carriers, BRCA1 and BRCA2 carriers were more likely to present with advanced stage (BRCA1; p=2×10−4, BRCA2; p=4×10−6), high grade (BRCA1; p=4×10−9, BRCA2; p=1×10−4), serous disease (BRCA1; p=3×10−6, BRCA2; p=0.003). BRCA1 carriers were younger at diagnosis (p=2×10−9) and BRCA2 slightly older at diagnosis (p=0.002) than non-carriers. BRCA1 and BRCA2 carriers did not differ in terms of tumor stage, grade or histology but did show differences in the age at diagnosis (p=2×10−14). In an unadjusted analysis, neither BRCA1 nor BRCA2 carriers differed from non-carriers in overall survival (BRCA1: HR=1.02, p=0.77, BRCA2: HR=0.89, p=0.36). After adjusting for stage, grade, histology and age at diagnosis, BRCA1 carriers showed a modest, non-significant, survival advantage (HR=0.84, p=0.12) while BRCA2 carriers showed a marked improvement (HR=0.57, p=6×10−4) compared to non-carriers. This survival advantage was also seen when comparing BRCA2 carriers to BRCA1 carriers after adjustment for age at diagnosis (HR=0.69, p=5×10−4). Similar results were obtained when we restricted the analysis to high grade, advanced stage, serous cases. The survival differences we observed between BRCA1 and BRCA2 carriers could be related to differences in tumor biology or chemo-sensitivity. Additional analyses investigating the later will be presented in addition to mutation-specific effects within BRCA1 and BRCA2. In this study, we provide strong evidence for genetic heterogeneity of survival effects in ovarian cancer patients with BRCA mutations. This could be applied to both clinical prediction and to aid our understanding of the complex biology of BRCA mutations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2752. doi:10.1158/1538-7445.AM2011-2752

Abstract Background: Genome-wide association studies (GWAS) identified variants at 19p13.1 and ZNF365 (10q21.2) as risk factors for breast cancer among BRCA1 and BRCA2 mutation carriers, respectively. We explored associations with ovarian cancer and with breast cancer by tumor histopathology for these variants in mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Methods: Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined. Results: We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers [HR, 1.17; 95% confidence interval (CI), 1.07–1.27; P = 7.42 × 10−4] and between rs16917302 at ZNF365 (HR, 0.84; 95% CI, 0.73–0.97; P = 0.017) but not rs311499 at 20q13.3 (HR, 1.11; 95% CI, 0.94–1.31; P = 0.22) and breast cancer risk for BRCA2 mutation carriers. Analyses based on tumor histopathology showed that 19p13 variants were predominantly associated with estrogen receptor (ER)-negative breast cancer for both BRCA1 and BRCA2 mutation carriers, whereas rs16917302 at ZNF365 was mainly associated with ER-positive breast cancer for both BRCA1 and BRCA2 mutation carriers. We also found for the first time that rs67397200 at 19p13.1 was associated with an increased risk of ovarian cancer for BRCA1 (HR, 1.16; 95% CI, 1.05–1.29; P = 3.8 × 10−4) and BRCA2 mutation carriers (HR, 1.30; 95% CI, 1.10–1.52; P = 1.8 × 10−3). Conclusions: 19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers. Impact: These findings can lead to an improved understanding of tumor development and may prove useful for breast and ovarian cancer risk prediction for BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev; 21(4); 645–57. ©2012 AACR.

RATIONALE Sphingolipids are important components of cell membranes that serve as cell signaling molecules; ceramide plays a central role in sphingolipid metabolism. De novo ceramide biosynthesis depends on fatty acid availability, but whether muscle uses circulating free fatty acids or pre‐existing intracellular stores is unknown. Our goal was to develop a method to detect the incorporation of intravenously infused [U‐ 13 C]palmitate into intramyocellular ceramides. METHODS We used liquid chromatography/tandem mass spectrometry (LC/MS/MS) to measure the concentrations of different sphingolipid species and 13 C‐isotopic enrichment of 16:0‐ceramide. Chromatographic separation was performed using ultra‐performance liquid chromatography. The analysis was performed on a triple quadrupole mass spectrometer using a positive ion electrospray ionization source with selected reaction monitoring (SRM). RESULTS The sphingolipids ions, except enriched ceramide, were monitored as [M+2+H] + . The [ 13 C 16 ]16:0‐ceramide was monitored as [M+16+H] + . By monitoring two different transitions of the [ 13 C 16 ]16:0‐ceramide (554/536 and 554/264) we could indirectly measure enrichment of the palmitate that is not a part of the sphingoid base. Concentration and enrichment could be measured using 20 mg of muscle obtained from volunteers receiving a low dose [U‐ 13 C]palmitate infusion. CONCLUSIONS LC/MS/MS can be used to detect the incorporation of plasma palmitate into muscle ceramides in humans, in vivo . Copyright © 2012 John Wiley & Sons, Ltd.

Insulin regulates many cellular processes, but the full impact of insulin deficiency on cellular functions remains to be defined. Applying a mass spectrometry–based nontargeted metabolomics approach, we report here alterations of 330 plasma metabolites representing 33 metabolic pathways during an 8-h insulin deprivation in type 1 diabetic individuals. These pathways included those known to be affected by insulin such as glucose, amino acid and lipid metabolism, Krebs cycle, and immune responses and those hitherto unknown to be altered including prostaglandin, arachidonic acid, leukotrienes, neurotransmitters, nucleotides, and anti-inflammatory responses. A significant concordance of metabolome and skeletal muscle transcriptome–based pathways supports an assumption that plasma metabolites are chemical fingerprints of cellular events. Although insulin treatment normalized plasma glucose and many other metabolites, there were 71 metabolites and 24 pathways that differed between nondiabetes and insulin-treated type 1 diabetes. Confirmation of many known pathways altered by insulin using a single blood test offers confidence in the current approach. Future research needs to be focused on newly discovered pathways affected by insulin deficiency and systemic insulin treatment to determine whether they contribute to the high morbidity and mortality in T1D despite insulin treatment.