ABSTRACT Using a rapid bacterial lysis method, the Check MDR CT103 and CT103 XL microarrays demonstrated accuracies of 98.1% and 94.2%, respectively, for detection of known resistance genes in 108 multidrug-resistant Gram-negative bacilli. In 45 isolates, 49 previously unrecognized extended-spectrum β-lactamase or plasmid AmpC targets were detected and confirmed by conventional PCR.
Carbapenem- and Colistin-Resistant Enterobacter cloacae from Delta, Colorado, in 2015
ABSTRACT Resistance to carbapenems in Enterobacteriaceae is a clinical problem of growing significance. Difficulty in treating multidrug-resistant Gram-negative organisms with conventional antibiotics has led to a renewed and increasing use of polymyxin compounds, such as colistin. Here, we report the isolation of carbapenem- and colistin-resistant Enterobacter cloacae from a polymicrobial lower extremity wound in an ambulatory patient. Whole-genome sequencing demonstrated the presence of chromosomal bla IMI-1 and bla AmpC , as well as numerous efflux pump genes.
A targeted genetic association study of epithelial ovarian cancer susceptibility
ABSTRACT We report on nine draft genomes of Pseudomonas aeruginosa isolates, assembled using a hybrid paired-end and Nextera mate-pair library approach. Eight are of clinical origin, and one is the ATCC 27853 strain. We also report their multilocus sequence types.
Epithelial‐Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk
ABSTRACTEpithelial‐mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single‐nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome‐wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT‐related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive‐cancer patients and 23,447 controls. A P‐value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07–1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69–0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.
In Vitro
Activities of Ceftazidime-Avibactam, Aztreonam-Avibactam, and a Panel of Older and Contemporary Antimicrobial Agents against Carbapenemase-Producing Gram-Negative Bacilli
ABSTRACT Among 177 carbapenemase-producing Gram-negative bacilli (108 KPC, 32 NDM, 11 IMP, 8 OXA-48, 4 OXA-181, 2 OXA-232, 5 IMI, 4 VIM, and 3 SME producers), aztreonam-avibactam was active against all isolates except two NDM producers with elevated MICs of 8/4 and 16/4 mg/liter; ceftazidime-avibactam was active against all KPC-, IMI-, SME-, and most OXA-48 group-producing isolates (93%) but not metallo-β-lactamase producers. Among older and contemporary antimicrobials, the most active were colistin, tigecycline, and fosfomycin, with overall susceptibilities of 88%, 79%, and 78%, respectively.
Base Resolution Methylome Profiling: Considerations in Platform Selection, Data Preprocessing and Analysis
Abstract 4246: Comparison of pathology versus IHC-based ovarian carcinoma histology assignment using gene expression, DNA methylation, and clinical outcome data
Abstract Background: Epithelial ovarian cancer (EOC) is composed of five major histologic types: 1) high-grade serous carcinoma (HGSC), accounting for most cases (∼70%); and the rarer 2) clear cell, 3) endometrioid, 4) mucinous, and 5) low- grade serous carcinoma (LGSC). As EOC risk factors are histology specific, as are the site of precursor lesions, accurate subtyping is critical to understanding EOC prognostic factors and etiology. Our aim was to compare two currently employed histology assignment strategies using gene expression, DNA methylation, and clinical outcome data Methods: Histology assignment based on: a) pathologist, and b) an integrated pathologist and IHC prediction algorithm (pathIHC) (using ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1 staining patterns), was compared for tumors of all histologies at the Mayo Clinic, Rochester. The 500 most variable probes from Illumina Methylation450 BeadChips (N = 259) and Agilent 4×44K expression arrays (N = 245) were used to perform unsupervised hierarchical clustering. Fisher's Exact test was used to test the association of clusters with histology. Cox proportional hazards regression analysis was used to test the association of clusters and histology with time to progression (TTP) and time to death (TTD). Results: Eighty-two percent of tumors were concordant between histology assignment strategies. Clustering based on methylation data produced two distinct clusters. PathIHC produced more homogenous clusters (p-value = 2.8×10-16) than pathology alone (p = 1.3×10-9). Cluster M1, characterized by high levels of methylation across almost all probes, was enriched for the rarer EOC subtypes; cluster M2, characterized by moderate levels of methylation across 50%-75% of probes, was predominantly HGSC. These patterns were observed irrespective of histology assignment strategy; however, when using histology by pathologist, cluster M2 had more endometrioid and LGSC tumors interspersed with HGSC tumors. Clustering based on expression data also produced two clusters. PathIHC produced slightly more homogenous clusters (p = 9.0×10-11, pathology alone, p = 2.3×10-10). Cluster E1 was enriched for the rarer EOC subtypes; cluster E2 was primarily serous lineage tumours (HGSC and LGSC), particularly when using histology by pathIHC. Considering only clinical outcomes, histologies by pathology were more significantly different in terms of TTP (p = 1.1×10-6) and TTD (p = 1.7×10-3) than histologies by pathIHC (TTP, p = 5.4×10-6; TTD, p = 5.7×10-3). Conclusions: Histology by pathIHC produced more homogeneous clusters in both the methylation and expression data; thus, molecular data supports this strategy. Differences in clinical outcomes (TTP and TTD) between histology groups were more pronounced when using assignment by pathologist; thus, clinical data supports this strategy. Citation Format: M A. Earp, S J. Winham, S M. Armasu, B L. Fridley, M C. Larson, Z C. Fogarty, K R. Kalli, C Wang, G L. Keeney, J M. Cunningham, S Ramus, M Kobel, E L. Goode. Comparison of pathology versus IHC-based ovarian carcinoma histology assignment using gene expression, DNA methylation, and clinical outcome data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4246. doi:10.1158/1538-7445.AM2015-4246