A Possible Perspective about the Compositional Models, Evolution, and Clinical Meaning of Human Enterotypes

Among the various parameters obtainable through the analysis of the human gut microbiota, the enterotype is one of the first classifications of the bacterial consortia, which tried to obtain, at the same time, as much information as possible to be applied in clinical medicine. Although some authors observed the existence not of clusters, but only of a real continuous gradient, enterotypes are commonly described according to various models. The first model predicted either clustering into enterotypes 1 and 2 based on two specific dominances, Bacteroides and Prevotella, respectively, with the Ruminococcus dominance blurred within the Bacteroides dominance, or it predicted a threedominant condition, in which the Ruminococcus driver constituted enterotype 3, separated from enterotype 1. A second model envisaged three possible ways to cluster gut microbiota, respectively centred on two, three, and four dominances. In the first case, enterotypes 1 and 2 coincided with the two original enterotypes, with the dominance of Bacteroides and Prevotella, respectively. In the second case, the existence of enterotype 3 was evident and whose dominance was not centred on Ruminococcus but extended more towards the entire Firmicutes phylum. In the third case, the presence of the phylum Firmicutes was split into two different enterotypes generating the clusters defined and named as Mixtures 1 and 2. Subsequently, the analysis of the water content (hydration) in the stool allowed the splitting of the Bacteroides enterotype into two sub-enterotype, respectively known as B1 and B2. All these models have allowed us to highlight some correlations between a specific enterotype, or cluster, and some characteristics, such as the greater predisposition of the respective hosts towards certain pathologies. These observations, coupled with the attempt to derive the different microbiota on an evolutionary basis, can help to shed new light on this topic and demonstrate the possible utility that the different ways of clustering the gut microbiota can have in a clinical application perspective and in preventive medicine.

Molecular Characterization of Peritoneal Involvement in Primary Colon and Ovary Neoplasm: The Possible Clinical Meaning of the P2X7 Receptor-Inflammasome Complex

<b><i>Introduction:</i></b> Colon cancer (CC) and epithelial ovarian cancer (EOC) are common and severe neoplasms frequently sharing a massive inflammatory involvement of peritoneum. A detailed molecular characterization of such carcinomatosis has not been performed, so far. <b><i>Methods:</i></b> Omental adipocytes were isolated from thirty-three adult women who underwent primary surgery for CC or EOC. Expression of several pro-inflammatory genes was determined by real-time PCR and immunofluorescence. Data were related to the clinical phenotype of the patients. <b><i>Results:</i></b> CD68, FGFR1, and IL-6 were significantly more expressed in adipocytes from CC patients and VEGF in adipocytes from EOC. TNFα, TGFβ, or MCP-1, as well as the pro-inflammatory platform P2X7R-NLRP3, did not differ between the 2 cancers. White blood cell count, mirroring systemic inflammation, was related to adipocyte P2X7R (<i>R</i> = 0.508, <i>p</i> = 0.003), NLRP3 (<i>R</i> = 0.405; <i>p</i> = 0.02), and MCP-1 (<i>R</i> = 0.448; <i>p</i> = 0.009). P2X7R and NLRP3 were the only inflammatory factors significantly more expressed in patients carrying both omental and peritoneal carcinosis, who were also characterized by a higher leukocytosis. None of the tested inflammatory markers was associated with tumor grading for both neoplasms; however, the presence of metastases was associated with a higher adipocyte expression of FGFR1 and TGFβ. <b><i>Conclusion:</i></b> We show here that rarely measured molecules seem to specifically characterize omental carcinomatosis of CC or EOC, while more common inflammatory agents like TNFα, TGFβ, or MCP-1 do not; the P2X7R-NLRP3 complex marks omental and peritoneal carcinosis and is related to circulating white blood cells and MCP-1, involved in monocyte-macrophage tissue infiltration; increased TGFβ and FGFR1 characterize the tumoral dissemination.

Has the time come to stop using the “standardised mean difference”?

Background Most meta-analyses use the ‘standardised mean difference’ (effect size) to summarise the outcomes of studies. However, the effect size has important limitations that need to be considered. Method After a brief explanation of the standardized mean difference, limitations are discussed and possible solutions in the context of meta-analyses are suggested. Results When using the effect size, three major limitations have to be considered. First, the effect size is still a statistical concept and small effect sizes may have considerable clinical meaning while large effect sizes may not. Second, specific assumptions of the effect size may not be correct. Third, and most importantly, it is very difficult to explain what the meaning of the effect size is to non-researchers. As possible solutions, the use of the ‘binomial effect size display’ and the number-needed-to-treat are discussed. Furthermore, I suggest the use of binary outcomes, which are often easier to understand. However, it is not clear what the best binary outcome is for continuous outcomes. Conclusion The effect size is still useful, as long as the limitations are understood and also binary outcomes are given.

Myositis/Myasthenia after Pembrolizumab in a Bladder Cancer Patient with an Autoimmunity-Associated HLA: Immune–Biological Evaluation and Case Report

Pembrolizumab (mAb to PD-1) has been recently approved for the therapy of pretreated urothelial cancer. Despite the efficacy, it is often accompanied by unpredictable and sometime severe immune-related (ir) adverse events (AEs). Here, we report the clinical and immune–biological characterization of a patient with a metastatic bladder cancer who developed myositis signs (M) and a myasthenia-like syndrome (MLS) during treatment with pembrolizumab. The patient presented an autoimmunity-associated HLA haplotype (HLA-A*02/HLA-B*08/HLA-C*07/HLA-DRB1*03) and experienced an increase in activated CD8 T-cells along the treatment. The symptomatology regressed after pembrolizumab discontinuation and a pyridostigmine and steroids-based therapy. This is the first report of concurrent M and MLS appearance in cancer patients receiving pembrolizumab. More efforts are needed to define early the risk and the clinical meaning of irAEs in this setting.

Physiological correlates of the Epworth sleepiness scale reveal different dimensions of daytime sleepiness

The Epworth Sleepiness Scale is commonly used to examine subjective daytime sleepiness in clinical populations; the physiologic correlates of this scale, however, are not well understood. Furthermore, how well this scale correlates with parallel objective and subjective concepts of daytime sleepiness is not well described. As such, we used machine learning algorithms to examine the association between Epworth Sleepiness Scale scores and 55 sleep and medical variables in the Sleep Heart Health Study (N=2105). Secondary analyses examined data stratified by age and gender and the relationship between the Epworth and other measures of daytime sleepiness. Analyses of the main dataset resulted in low explained variance (7.15-10.0%), with self-reported frequency of not getting enough sleep as most important predictor (10.3-13.9% of the model variance). Stratification by neither age nor gender significantly improved explained variance. Cross-correlational analysis revealed low correlation of other daytime sleepiness measures to Epworth scores. We find that Epworth scores are not well explained by habitual or polysomnographic sleep values, or other biomedical characteristics. These analyses indicate that there are different, potentially orthogonal dimensions of the concept of “daytime sleepiness” that may be driven by different aspects of sleep physiology. As the physiologic correlates of the Epworth Sleepiness Scale remain to be elucidated, interpretation of the clinical meaning of these scores should be done with caution.

Role of nutritional care and general guidance for patients with advanced or metastatic gastric cancer

Patients with advanced or metastatic gastric cancer often suffer from malnutrition, which can have an impact on quality of life, increase the toxicity of chemotherapy and reduce overall survival. Options available to the clinician to manage a patient’s nutritional status include screening and assessment of malnutrition at diagnosis, monitoring during the ‘cancer journey’, early detection of precachexia and the ongoing use of a multidisciplinary team (oncologists, other medical specialists and nutritionists). Because malnutrition is frequently overlooked and under treated in patients with advanced or metastatic gastric cancer, this narrative review focuses on the clinical meaning of nutritional status in gastric cancer and provides general guidance regarding nutritional care management for patients with advanced or metastatic gastric cancer.