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The Effect of Sugammadex on the Outcome After Colorectal Cancer Surgery

ABSTRACT: This study is retrospective study. The purpose of this study is checking the effect of sugammadex on the outcome after colorectal surgery. The outcome is compared among the 2 groups, sugammadex group and non-sugammadex group. The primary parameters of outcome are length of stay, readmission rate, postoperative complications, time interval for first successful oral intake.

DISEASE(S): Outcome, Fatal,Colorectal Neoplasms

PROVIDER: 2280194 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:The specific genes influencing the quantitative variation in macronutrient preference and food intake are virtually unknown. We refined a previously identified mouse chromosome 17 (MMU17) region harboring quantitative trait loci (QTL) with large effects on preferential macronutrient intake-carbohydrate (Mnic1), total kilcalories (Kcal2), and total food volume (Tfv1) using interval-specific congenic strains. These loci were isolated in the [C57BL/6J.CAST/EiJ-17.1-(D17Mit19-D17Mit50); B6.CAST-17.1] strain, developed by introgressing a ~40.1 Mb CAST MMU17 region into recipient B6 genome. In a diet selection paradigm (carbohydrate/protein vs. fat/protein), these B6.CAST-17.1 sub-congenic mice eat 30% more calories from the carbohydrate-rich diet, ~10% more total calories, and ~9% more total food volume per body weight. In the current study, this carbohydrate-preferring B6.CAST-17.1 subcongenic strain was crossed with the fat-preferring inbred B6 strain to generate a subcongenic-derived F2 mapping population; genotypes were determined using a high-density, custom SNP panel. The main outcome of this study is that genetic linkage analysis greatly reduced the 95% confidence interval (CI) for Mnic1 (encompassing Kcal2 and Tfv1) from 40.1 to 29.5 Mb and more precisely established the QTL boundaries. Specifically, the genetic architecture for Mnic1 (preferential carbohydrate intake) does not follow the same pattern as that for co-localized Kcal2/Tfv1 (total kcal and food volume, respectively), suggesting the presence of separate quantitative trait genes for these food intake traits. No genetic linkage for self-selected fat intake was detected, underscoring the carbohydrate-specific effects of this MMU17 locus. The Mnic1/Kcal2/Tfv1 QTL was further de-limited to a ~19.1 Mb interval, based on the absence of macronutrient diet selection phenotypes in subcongenic HQ17IIa mice that possess CAST MMU17 donor segment on a C57BL/6Jhg/hg background. A second key finding is the separation of two energy balance QTLs: Mnic1/Kcal2/Tfv1 for food intake and a newly discovered locus regulating short term body weight gain. The genes Decr2, Ppard and Agapt1 in the critical QTL interval were identified and prioritized using a combination of genome sequence analysis, and tag-based transcriptome sequencing to measure hypothalamic gene expression in non-recombinant F2 controls, possessing cast/cast and b6/b6 genotypes across the sub-congenic segment.

Project description:Background Published multi-gene classifiers suggested outcome prediction for patients with stage UICC II colon cancer based on different gene expression signatures. However, there is currently no translation of these classifiers for application in routine diagnostic. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable RNA and protein detection in routine diagnostic specimens. Results Immunohistochemistry was applied to 68 stage UICC II colon cancers to determine the protein expression of five selected previously published classifier genes (CDH17, LAT, CA2, EMR3, and TNFRSF11A). Correlation of protein expression data with clinical outcome within a 5-year post-surgery course failed to separate patients with a disease-free follow-up [Group DF] and relapse [Group R]). In addition, RNA from macrodissected tumor samples from 53 of these 68 patients was profiled on Affymetrix GeneChips (HG-U133 Plus 2.0). Prognostic signatures were generated by Nearest Shrunken Centroids with cross-validation. Although gene expression profiling allowed the identification of differentially expressed genes between the groups DF and R, a stable classification and prognosis signature was not discernable in our data. Furthermore, the application of previously published gene signatures consisting of 22 and 19 genes, respectively, to our gene expression data set using ‘global tests’ and leave-one-out cross-validation was unable to predict clinical outcome (prediction rate 75.5% and 64.2%; n.s.). T-stage was the only independent prognostic factor for relapse in multivariate analysis with established clinical and pathological parameters including microsatellite status. Conclusions Our protein and gene expression analyses currently do not support application of molecular classifiers for prediction of clinical outcome in routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.

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The Effect of Sugammadex on the Outcome After Colorectal Cancer Surgery

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