A Meta-analysis of Jejunostomy Versus Nasoenteral Tube for Enteral Nutrition Following Esophagectomy.

BACKGROUND: Postoperative nutritional therapy is of paramount importance for patients undergoing esophagectomy. The jejunostomy and nasoenteral tube are the popular routes for nutritional therapy. However, which one is the preferred route is unclear. This study aims to analyze the differences in safety and efficacy of the two routes for nutritional therapy. MATERIALS AND METHODS: PubMed, Web of Science, Cochrane Library, and EMBASE (till September 17, 2020) were searched. The primary outcome was postoperative pneumonia. Secondary outcomes were the length of hospital stays (LOS), bowel obstruction, catheter dislocation, anastomotic leakage, overall postoperative complications, and postoperative albumin. Weighted mean differences (WMD) and odds ratios (OR) were calculated for statistical analysis. RESULTS: Ten studies involving a total of 1,531 patients in the jejunostomy group and 1,375 patients in the nasoenteral tube group were included. Compared with patients in the nasoenteral tube group, those in the jejunostomy group had a lower incidence of postoperative pneumonia (OR = 0.68, P < 0.001), shorter LOS (WMD = -0.85, P < 0.001), and lower risk of catheter dislocation (OR = 0.15, P = 0.001). There were no significant differences in the incidence of anastomotic leakage (OR = 0.84, P = 0.43), overall postoperative complications (OR = 0.87, P = 0.59), and postoperative albumin (WMD = -0.40, P = 0.24). However, patients in the jejunostomy group had a higher risk of bowel obstruction (OR = 8.42, P = 0.002). CONCLUSIONS: Jejunostomy for enteral nutrition showed superior outcomes in terms of postoperative pneumonia, LOS, and catheter dislocation. Jejunostomy may be the preferred enteral nutritional route following esophagectomy.

Quantitative proteomics revealed energy metabolism pathway alterations in human epithelial ovarian carcinoma and their regulation by the antiparasite drug ivermectin: data interpretation in the context of 3P medicine.

OBJECTIVE: Energy metabolism abnormality is the hallmark in epithelial ovarian carcinoma (EOC). This study aimed to investigate energy metabolism pathway alterations and their regulation by the antiparasite drug ivermectin in EOC for the discovery of energy metabolism pathway-based molecular biomarker pattern and therapeutic targets in the context of predictive, preventive, and personalized medicine (PPPM) in EOC. METHODS: iTRAQ-based quantitative proteomics was used to identify mitochondrial differentially expressed proteins (mtDEPs) between human EOC and control mitochondrial samples isolated from 8 EOC and 11 control ovary tissues from gynecologic surgery of Chinese patients, respectively. Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of energy metabolic pathways in EOC cells treated with and without ivermectin. Cell proliferation, cell cycle, apoptosis, and important molecules in energy metabolism pathway were examined before and after ivermectin treatment of different EOC cells. RESULTS: In total, 1198 mtDEPs were identified, and various mtDEPs were related to energy metabolism changes in EOC, with an interesting result that EOC tissues had enhanced abilities in oxidative phosphorylation (OXPHOS), Kreb's cycle, and aerobic glycolysis, for ATP generation, with experiment-confirmed upregulations of UQCRH in OXPHOS; IDH2, CS, and OGDHL in Kreb's cycle; and PKM2 in glycolysis pathways. Importantly, PDHB that links glycolysis with Kreb's cycle was upregulated in EOC. SILAC-based quantitative proteomics found that the protein expression levels of energy metabolic pathways were regulated by ivermectin in EOC cells. Furthermore, ivermectin demonstrated its strong abilities to inhibit proliferation and cell cycle and promote apoptosis in EOC cells, through molecular networks to target PFKP in glycolysis; IDH2 and IDH3B in Kreb's cycle; ND2, ND5, CYTB, and UQCRH in OXPHOS; and MCT1 and MCT4 in lactate shuttle to inhibit EOC growth. CONCLUSIONS: Our findings revealed that the Warburg and reverse Warburg effects coexisted in human ovarian cancer tissues, provided the first multiomics-based molecular alteration spectrum of ovarian cancer energy metabolism pathways (aerobic glycolysis, Kreb's cycle, oxidative phosphorylation, and lactate shuttle), and demonstrated that the antiparasite drug ivermectin effectively regulated these changed molecules in energy metabolism pathways and had strong capability to inhibit cell proliferation and cell cycle progression and promote cell apoptosis in ovarian cancer cells. The observed molecular changes in energy metabolism pathways bring benefits for an in-depth understanding of the molecular mechanisms of energy metabolism heterogeneity and the discovery of effective biomarkers for individualized patient stratification and predictive/prognostic assessment and therapeutic targets/drugs for personalized therapy of ovarian cancer patients.

Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis.

Ovarian cancer is a common gynecologic cancer with high mortality but unclear molecular mechanism. Most ovarian cancers are diagnosed in the advanced stage, which seriously hampers therapy. Mitochondrial changes are a hallmark of human ovarian cancers, and mitochondria are the centers of energy metabolism, cell signaling, and oxidative stress. In-depth insights into the changes of the mitochondrial proteome in ovarian cancers compared to control ovarian tissue will benefit in-depth understanding of the molecular mechanisms of ovarian cancer, and the discovery of effective and reliable biomarkers and therapeutic targets. An effective mitochondrial preparation method coupled with an isobaric tag for relative and absolute quantification (iTRAQ) quantitative proteomics are presented here to analyze human ovarian cancer and control mitochondrial proteomes, including differential-speed centrifugation, density gradient centrifugation, quality assessment of mitochondrial samples, protein digestion with trypsin, iTRAQ labeling, strong cation exchange fractionation (SCX), liquid chromatography (LC), tandem mass spectrometry (MS/MS), database analysis, and quantitative analysis of mitochondrial proteins. Many proteins have been successfully identified to maximize the coverage of the human ovarian cancer mitochondrial proteome and to achieve the differentially expressed mitochondrial protein profile in human ovarian cancers.

The differentially mitochondrial proteomic dataset in human ovarian cancer relative to control tissues.

This data article presents a differentially mitochondrial proteomic dataset in human ovarian cancer tissues relative to control tissues. The mitochondrial samples were prepared from human ovarian cancer and control ovary tissues, and were digested with trypsin. The tryptic peptides from ovarian cancer and control mitochondrial samples were labeled by isobaric tags for relative and absolute quantification (iTRAQ) reagents, followed by strong-cation exchange (SCX) chromatography, liquid chromatography (LC)-tandem mass spectrometry (MS/MS), and bioinformatic analysis. This data article is related to a published article (Li et al., 2018) [1].

Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas.

Mitochondria play important roles in growth, signal transduction, division, tumorigenesis and energy metabolism in epithelial ovarian carcinomas (EOCs) without an effective biomarker. To investigate the proteomic profile of EOC mitochondrial proteins, a 6-plex isobaric tag for relative and absolute quantification (iTRAQ) proteomics was used to identify mitochondrial expressed proteins (mtEPs) in EOCs relative to controls, followed by an integrative analysis of the identified mtEPs and the Cancer Genome Atlas (TCGA) data from 419 patients. A total of 5115 quantified proteins were identified from purified mitochondrial samples, and 262 proteins were significantly related to overall survival in EOC patients. Furthermore, 63 proteins were identified as potential biomarkers for the development of an EOC, and our findings were consistent with previous reports on a certain extent. Pathway network analysis identified 70 signaling pathways. Interestingly, the results demonstrated that cancer cells exhibited an increased dependence on mitophagy, such as peroxisome, phagosome, lysosome, valine, leucine and isoleucine degradation and fatty acid degradation pathways, which might play an important role in EOC invasion and metastasis. Five proteins (GLDC, PCK2, IDH2, CPT2 and HMGCS2) located in the mitochondrion and enriched pathways were selected for further analysis in an EOC cell line and tissues, and the results confirmed reliability of iTRAQ proteomics. These findings provide a large-scale mitochondrial proteomic profiling with quantitative information, a certain number of potential protein biomarkers and a novel vision in the mitophagy bio-mechanism of a human ovarian carcinoma.

[Value of postoperative indocyanine green retention rate at 15 minutes combined with standard remnant liver volume in predicting liver dysfunction after hepatectomy].

OBJECTIVE: To investigate the value of indocyanine green retention rate at 15 minutes (ICG R15) on postoperative day 3 combined with standard remnant liver volume (SRLV) in predicting the occurrence of liver dysfunction after hepatectomyin hepatocellular carcinoma (HCC).
 Methods: The clinical data of 61 HCC patients undergone hepatectomy in Xiangya Hospital of Central South University from January 2015 to February 2016 were collected and analyzed. The patients were divided into 2 groups: a normal liver function group (n=40) and a liver dysfunction group (n=21). Univariate analysis was used to evaluate the risk factors for postoperative liver dysfunction. Logistic regression was used to assess the independent risk factors for postoperative liver dysfunction, and the regression equation between independent risk factors and postoperative liver dysfunction was established. The receiver operating characteristic (ROC) curve was used to examine the regression equation and compare the value difference in predicting postoperative liver dysfunction between single and combined independent risk factors.
 Results: Postoperative liver dysfunction occurred in 21 of the 61 patients, with an incidence rate at 34.4%. There was no significant difference in the time of operation, time of hepatic portal occlusion, volume of tumor and volume of resected liver between the 2 groups (all P>0.05), but there were significant differences in the ICG R15 on postoperative day 3, intraoperative blood loss and SRLV between the 2 groups (all P<0.05). The ICG R15 on postoperative day 3, intraoperative blood loss, SRLV were the risk factors for postoperative liver dysfunction. Logistic regression analysis showed ICG R15 on postoperative day 3 and SRLV were the independent risk factors for postoperative liver dysfunction, and the regression equation between independent risk factors and postoperative liver dysfunction was as follows: logit(P)=1.277+0.140×ICG R15 on postoperative day 3-5.125×SRLV. The area under the ROC curve of ICG R15 on postoperative day 3 combined with SRLV was more than that of single ICG R15 and single SRLV.
 Conclusion: ICG R15 on postoperative day 3 and SRLV are the independent risk factors for postoperative liver dysfunction. The regression equation, which is established by combination of ICG R15 with SRLV, can predict the occurrence of postoperative liver dysfunction. The accuracy of ICG R15 on postoperative day 3 combined with SRLV is better than that of single ICG R15 or single SRLV.