Interactions between MDSCs and the Autonomic Nervous System: Opportunities and Challenges in Cancer Neuroscience

Myeloid-derived suppressor cells (MDSC) are a population of heterogeneous immune cells that are involved in precancerous conditions and neoplasms. The autonomic nervous system (ANS), which is composed of the sympathetic nervous system and the parasympathetic nervous system, is an important component of the tumor microenvironment that responds to changes in the internal and external environment mainly through adrenergic and cholinergic signaling. An abnormal increase of autonomic nerve density has been associated with cancer progression. As we discuss in this review, growing evidence indicates that sympathetic and parasympathetic signals directly affect the expansion, mobilization, and redistribution of MDSCs. Dysregulated autonomic signaling recruits MDSCs to form an immunosuppressive microenvironment in chronically inflamed tissues, resulting in abnormal proliferation and differentiation of adult stem cells. The two components of the ANS may also be responsible for the seemingly contradictory behaviors of MDSCs. Elucidating the underlying mechanisms has the potential to provide more insights into the complex roles of MDSCs in tumor development and lay the foundation for the development of novel MDSC-targeted anticancer strategies.

Listeria monocytogenes: a promising vector for tumor immunotherapy

Cancer receives enduring international attention due to its extremely high morbidity and mortality. Immunotherapy, which is generally expected to overcome the limits of traditional treatments, serves as a promising direction for patients with recurrent or metastatic malignancies. Bacteria-based vectors such as Listeria monocytogenes take advantage of their unique characteristics, including preferential infection of host antigen presenting cells, intracellular growth within immune cells, and intercellular dissemination, to further improve the efficacy and minimize off-target effects of tailed immune treatments. Listeria monocytogenes can reshape the tumor microenvironment to bolster the anti-tumor effects both through the enhancement of T cells activity and a decrease in the frequency and population of immunosuppressive cells. Modified Listeria monocytogenes has been employed as a tool to elicit immune responses against different tumor cells. Currently, Listeria monocytogenes vaccine alone is insufficient to treat all patients effectively, which can be addressed if combined with other treatments, such as immune checkpoint inhibitors, reactivated adoptive cell therapy, and radiotherapy. This review summarizes the recent advances in the molecular mechanisms underlying the involvement of Listeria monocytogenes vaccine in anti-tumor immunity, and discusses the most concerned issues for future research.

Direct and indirect effects of pathogenic bacteria on the integrity of intestinal barrier

Bacterial translocation is a pathological process involving migration of pathogenic bacteria across the intestinal barrier to enter the systemic circulation and gain access to distant organs. This phenomenon has been linked to a diverse range of diseases including inflammatory bowel disease, pancreatitis, and cancer. The intestinal barrier is an innate structure that maintains intestinal homeostasis. Pathogenic infections and dysbiosis can disrupt the integrity of the intestinal barrier, increasing its permeability, and thereby facilitating pathogen translocation. As translocation represents an essential step in pathogenesis, a clear understanding of how barrier integrity is disrupted and how this disruption facilitates bacterial translocation could identify new routes to effective prophylaxis and therapy. In this comprehensive review, we provide an in-depth analysis of bacterial translocation and intestinal barrier function. We discuss currently understood mechanisms of bacterial-enterocyte interactions, with a focus on tight junctions and endocytosis. We also discuss the emerging concept of bidirectional communication between the intestinal microbiota and other body systems. The intestinal tract has established 'axes' with various organs. Among our regulatory systems, the nervous, immune, and endocrine systems have been shown to play pivotal roles in barrier regulation. A mechanistic understanding of intestinal barrier regulation is crucial for the development of personalized management strategies for patients with bacterial translocation-related disorders. Advancing our knowledge of barrier regulation will pave the way for future research in this field and novel clinical intervention strategies.

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs]

Objective: To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Methods: Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical examination centers in China were included in this retrospective study. Two radiologists, who were not aware of the study design, independently evaluated the coronary angiography images of each subject to make CHD diagnosis. A deep learning model using convolutional neural networks (CNN) was used to label the fundus images according to the presence or absence of CHD, and the model was proportionally divided into training and test sets for model training. The prediction performance of the model was evaluated in the test set using monocular and binocular fundus images respectively. Prediction efficacy of the algorithm for cardiovascular risk factors (e.g., age, systolic blood pressure, gender) and coronary events were evaluated by regression analysis using the area under the receiver operating characteristic curve (AUC) and R² correlation coefficient. Results: The study retrospectively collected 51 765 fundus images from 25 222 subjects, including 10 255 patients with CHD, and there were 14 419 male subjects in this cohort. Of these, 46 603 fundus images from 22 701 subjects were included in the training set and 5 162 fundus images from 2 521 subjects were included in the test set. In the test set, the deep learning model could accurately predict patients' age with an R² value of 0.931 (95%CI 0.929-0.933) for monocular photos and 0.938 (95%CI 0.936-0.940) for binocular photos. The AUC values for sex identification from single eye and binocular retinal fundus images were 0.983 (95%CI 0.982-0.984) and 0.988 (95%CI 0.987-0.989), respectively. The AUC value of the model was 0.876 (95%CI 0.874-0.877) with either monocular fundus photographs and AUC value was 0.885 (95%CI 0.884-0.888) with binocular fundus photographs to predict CHD, the sensitivity of the model was 0.894 and specificity was 0.755 with accuracy of 0.714 using binocular fundus photographs for the prediction of CHD. Conclusion: The deep learning model based on fundus photographs performs well in identifying coronary heart disease and assessing related risk factors such as age and sex.

Heart failure and cardiovascular outcomes in european patients with atrial fibrillation

Background

Heart failure (HF) has an intimate bidirectional association with atrial fibrillation (AF). Few data are available about the impact of HF phenotypes (HF with preserved ejection fraction, HFpEF; HF with mildly reduced ejection fraction, HFmrEF; HF with reduced ejection fraction, HFrEF) as predictors for adverse outcomes in AF patients.

Purpose

To investigate the association of HFpEF, HFmrEF and HFrEF with adverse outcomes in a large contemporary cohort of European AF patients and evaluate the effect of EF throughout its entire spectrum.

Methods

We analyzed patients enrolled in the ESC-EHRA EORP-AF General Long-Term Registry. HF patients were categorized according the three phenotypes and compared to those without HF (“non HF”). Main outcome was a composite outcome of all-cause death and major adverse cardiac events (MACE).

Results

Among the original 11,096 AF patients enrolled, 9857 (88.8%) were included in this analysis (median age 71 years, interquartile range [IQR 63–77], 40.1% females) with median EF 55% [IQR 45–61%] and CHA2DS2-VASc 3 [2–4]). In this cohort, 5935 (60.2%) were non HF patients, and 3240 (32.9%) had HF patients (with HF status and EF values data available). Accordingly, 1662 (51.2%) were categorized as HFpEF; 523 (14.1%) were HFmrEF; and 1235 (35.1%) were HFrEF.

After a median follow-up of 731 days [IQR 690–748], the composite outcome was significantly higher throughout HF categories (HFpEF 19.0%, HFmrEF 21.8% and HFrEF 29.6%, compared to non HF 10.7%; p<0.001). In a fully adjusted multivariate Cox regression, HF phenotypes were associated with a progressively higher risk for the composite outcome (HFpEF HR 1.45 [95% CI, 1.23–1.70]; HFmrEF HR 1.82 [95% CI, 1.45–2.3]; HFrEF HR 2.51 [95% CI, 2.14–2.95], when compared to non HF patients). Considering EF in its continuous spectrum, an adjusted regression curve analysis found that progressively lower EF was associated with a progressively higher risk for the composite outcome, both in HF and overall AF patients (Figure 1, left and right panel, respectively).

Conclusions

Over a two-years follow-up, in a large contemporary cohort of European AF patients, HF phenotypes were associated with a progressively higher risk for adverse outcomes. Lower EF values increased the risk of adverse outcomes both in HF patients and overall AF patients, irrespective of HF phenotype status.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): Since the start of EORP, the following companies have supported the programme: Abbott Vascular Int. (2011–2021), Amgen Cardiovascular (2009–2018), AstraZeneca (2014–2021), Bayer (2009–2018), Boehringer Ingelheim (2009–2019), Boston Scientific (2009–2012), The Bristol Myers Squibb and Pfizer Alliance (2011–2016), The Alliance Daiichi Sankyo Europe GmbH and Eli Lilly and Company (2011–2017), Edwards (2016–2019), Gedeon Richter Plc. (2014–2017), Menarini Int. Op. (2009–2012), MSD-Merck & Co. (2011–2014), Novartis Pharma AG (2014–2020), ResMed (2014–2016), Sanofi (2009–2011), SERVIER (2010–2021), and Vifor (2019–2022).

Intracerebroventricular injection of senktide-induced Fos expression in vasopressin-containing hypothalamic neurons in the rat

Intracerebroventricular injection of senktide, a selective agonist for neurokinin B receptor (NK3), induced Fos expression in many neurons of the rat hypothalamus. Fos-positive neurons were predominantly present in the supraoptic and paraventricular hypothalamic nuclei, and some of them were seen in the lateral preoptic area, lateral hypothalamic area, arcuate nucleus, perifornical region, posterior hypothalamic area, circular nucleus, and along relatively large blood vessels (lateral hypothalamic perivascular nucleus) in the anterior hypothalamus. A double labeling study was performed to examine if vasopressin-containing neurons in the hypothalamus could be activated by the treatment. Neurons with both Fos-like immunoreactivity (-LI) and vasopressin-LI were found in the paraventricular nucleus, supraoptic nucleus, circular nucleus and lateral hypothalamic perivascular nucleus. In the supraoptic nucleus, about 87% of vasopressin-containing neurons exhibited Fos-LI, which corresponded to about 64% of Fos-positive neurons in the nucleus. In the paraventricular nucleus, about 80% of vasopressin-like immunoreactive neurons exhibited Fos-LI, which constituted about 51% of the total population of Fos-positive neurons in the region. The results suggest that NK3 receptor may be involved in the modulation of release of vasopressin from the hypothalamus in the rat.