Increasing experience in laparoscopic staging of early ovarian cancer

We assessed the effect of increasing experience of a single surgeon (learning curve) in the laparoscopic staging procedure for women with early ovarian cancer and compared the results with the literature. We retrospectively analysed a total of 25 women with apparent early-stage ovarian cancer who underwent a laparoscopic staging procedure by the same surgeon. Three time periods, based on date of surgery, were compared with respect to operating time, amount of lymph nodes harvested and surgical outcome. There was no significant difference in operation time, estimated blood loss and hospital stay between the three periods. There was, however, a significant increase in the median number of pelvic and para-aortal lymph nodes harvested (group1 = 6.5, group 2 = 8.0 and group 3 = 21.0; P < 0.005). For the total period, median operation time was 235 min and median estimated blood loss was 100 ml. The median length of hospital stay was 4.0 days. Two intraoperative and two postoperative complications occurred. The upstaging rate was 32%. The mean interval between initial surgery and laparoscopic staging was 51.2 days. Mean duration of follow-up was 43 months, range (1–116 months). Five (20%) patients had recurrences, and two (8%) patients died of the disease. In conclusion, there is a significant learning curve for the laparoscopic full staging procedure in ovarian cancer. In our study this is mainly reflected in the amount of lymph nodes harvested and not in the total operating time

Transcriptomic Coordination in the Human Metabolic Network Reveals Links between n-3 Fat Intake, Adipose Tissue Gene Expression and Metabolic Health

Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF2α. These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress

Eag and HERG potassium channels as novel therapeutic targets in cancer

Voltage gated potassium channels have been extensively studied in relation to cancer. In this review, we will focus on the role of two potassium channels, Ether à-go-go (Eag), Human ether à-go-go related gene (HERG), in cancer and their potential therapeutic utility in the treatment of cancer. Eag and HERG are expressed in cancers of various organs and have been implicated in cell cycle progression and proliferation of cancer cells. Inhibition of these channels has been shown to reduce proliferation both in vitro and vivo studies identifying potassium channel modulators as putative inhibitors of tumour progression. Eag channels in view of their restricted expression in normal tissue may emerge as novel tumour biomarkers

Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers

Role of dietary fatty acids in mammary gland development and breast cancer

Breast cancer is the most common cancer among women worldwide. Estimates suggest up to 35% of cases may be preventable through diet and lifestyle modification. Growing research on the role of fats in human health suggests that early exposure in life to specific fatty acids, when tissues are particularly sensitive to their environment, can have long-term health impacts. The present review examines the role of dietary fat in mammary gland development and breast cancer throughout the lifecycle. Overall, n-3 polyunsaturated fatty acids have promising cancer-preventive effects when introduced early in life, and warrant further research to elucidate the mechanisms of action