Altered insulin sensitivity and immune function in patients with colorectal cancer.

BACKGROUND & AIMS: Insulin resistance and chronic inflammation have been reported in patients with cancer. However, many of the underlying mechanisms and associations are yet to be unveiled. We examined both the level of insulin sensitivity and markers of inflammation in patients with colorectal cancer for comparison to controls. METHODS: Clinical exploratory study of patients with colorectal cancer (n = 20) and matched controls (n = 10). Insulin sensitivity was quantified using the hyperinsulinemic normoglycemic clamp and blood samples were taken for quantification of several key, both intra- and extracellular, inflammatory markers. We analysed the differences in these parameters between the two groups. RESULTS: Patients exhibited both insulin resistance (M-value, patients median (Mdn) 4.57 interquartile range (IQR) 3.49-5.75; controls Mdn 5.79 (IQR 5.20-6.81), p = 0.049), as well as increased plasma levels of the pro-inflammatory cytokines IL-1ß (patients Mdn 0.48 (IQR 0.33-0.58); controls Mdn 0.36 (IQR 0.29-0.42), p = 0.02) and IL-6 (patients Mdn 3.21 (IQR 2.31-4.93); controls Mdn 2.16 (IQR 1.50-2.65), p = 0.02). The latter is present despite an almost two to three fold decrease (p < 0.01) in caspase-1 activity, a facilitating enzyme of IL-1ß production, within circulating immune cells. CONCLUSION: Patients with colorectal cancer displayed insulin resistance and higher levels of plasma IL-1ß and IL-6, in comparison to matched healthy controls. The finding of a seemingly disconnect between inflammasome (caspase-1) activity and plasma levels of key pro-inflammatory cytokines in cancer patients may suggest that, in parallel to dysregulated immune cells, tumour-driven inflammatory pathways also are in effect.

Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation.

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, proinflammatory and anti-inflammatory cytokines interplay to orchestrate fine-tuned and dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation and development of the inflammatory response. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by mathematical models that enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent proinflammatory and anti-inflammatory cytokines with a focus on tumor necrosis factor and interleukin 10 (IL-10) in lipopolysaccharide-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform simulations to disentangle the role of IL-10 feedbacks during an acute inflammatory event. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10-tumor necrosis factor switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.

Predicting sepsis using a combination of clinical information and molecular immune markers sampled in the ambulance.

Sepsis is a time dependent condition. Screening tools based on clinical parameters have been shown to increase the identification of sepsis. The aim of current study was to evaluate the additional predictive value of immunological molecular markers to our previously developed prehospital screening tools. This is a prospective cohort study of 551 adult patients with suspected infection in the ambulance setting of Stockholm, Sweden between 2017 and 2018. Initially, 74 molecules and 15 genes related to inflammation were evaluated in a screening cohort of 46 patients with outcome sepsis and 50 patients with outcome infection no sepsis. Next, 12 selected molecules, as potentially synergistic predictors, were evaluated in combination with our previously developed screening tools based on clinical parameters in a prediction cohort (n = 455). Seven different algorithms with nested cross-validation were used in the machine learning of the prediction models. Model performances were compared using posterior distributions of average area under the receiver operating characteristic (ROC) curve (AUC) and difference in AUCs. Model variable importance was assessed by permutation of variable values, scoring loss of classification as metric and with model-specific weights when applicable. When comparing the screening tools with and without added molecular variables, and their interactions, the molecules per se did not increase the predictive values. Prediction models based on the molecular variables alone showed a performance in terms of AUCs between 0.65 and 0.70. Among the molecular variables, IL-1Ra, IL-17A, CCL19, CX3CL1 and TNF were significantly higher in septic patients compared to the infection non-sepsis group. Combing immunological molecular markers with clinical parameters did not increase the predictive values of the screening tools, most likely due to the high multicollinearity of temperature and some of the markers. A group of sepsis patients was consistently miss-classified in our prediction models, due to milder symptoms as well as lower expression levels of the investigated immune mediators. This indicates a need of stratifying septic patients with a priori knowledge of certain clinical and molecular parameters in order to improve prediction for early sepsis diagnosis.Trial registration: NCT03249597. Registered 15 August 2017.

Cytokine responses to LPS in reprogrammed monocytes are associated with the transcription factor PU.1.

Myeloid-derived suppressor cells (MDSCs) are functionally immunosuppressive cells that arise and expand during extensive inflammatory conditions by increased hematopoietic output or reprogramming of immune cells. In sepsis, an increase of circulating MDSCs is associated with adverse outcomes, but unique traits that can be used to identify increased activity of MDSCs are lacking. By using endotoxin tolerance as a model of sepsis-induced monocytic MDSCs (M-MDSC-like cells), this study aims to identify the mediator and transcriptional regulator profile associated with M-MDSC activity. After analyzing 180 inflammation-associated proteins, a profile of differentially expressed cytokines was found in M-MDSC-like cells versus normal monocytes stimulated with LPS. These cytokines were associated with 5 candidate transcription factors, where particularly PU.1 showed differential expression on both transcriptional and protein levels in M-MDSC-like cells. Furthermore, inhibition of PU.1 led to increased production of CXCL5 and CCL8 in M-MDSC-like cells indicating its role in regulating the ability of M-MDSC-like cells to recruit other immune cells. Taken together, the study identifies a unique profile in the pattern of immune mediators defining M-MDSC activity upon LPS stimulation, which offers a functional link to their contribution to immunosuppression.

Differential cytokine response in endotoxin induced M-MDSC-like cells and their associated regulators.

Dermal exposure to cobalt studied in vitro in keratinocytes - effects of cobalt exposure on inflammasome activated cytokines, and mRNA response.

BACKGROUND: Cobalt is a dermal sensitizer, and keratinocytes respond to cobalt exposure by releasing proinflammatory mediators, regulating the immune response. OBJECTIVE: To determine the effect of cobalt on the inflammasome associated cytokine- and gene expression in cultured human keratinocytes (HaCaT). Cultivation in low- or high calcium conditions model separate differentiation states of keratinocytes in the skin. METHOD: HaCaT cells in two different states of differentiation were exposed to cobalt chloride and caspase-1 activity as well as the production of IL-1ß, IL-18 and gene expression of IL1B, IL18, NLRP3, CASP1, and PYCARD was quantified. RESULTS: High cobalt chloride exposure mediated significant increase in caspase-1 activity, cytokine levels, and IL1B and NLRP3 expression with a corresponding regulatory decrease for CASP1 and PYCARD expression. No difference between high- and low calcium culturing conditions modelling differentiation states was detected. CONCLUSIONS: Our data suggest that HaCaT cells respond with inflammmasome associated activity upon cobalt exposure in a concentration-dependent manner. These mechanisms could be of importance for the understanding of the pathophysiology behind allergic sensitization to dermal cobalt exposure.

Dose- and time-dependent changes in viability and IL-6, CXCL8 and CCL2 production by HaCaT-cells exposed to cobalt. Effects of high and low calcium growth conditions.

BACKGROUND: Sensitization requires exposure to an allergen with subsequent production of a "danger "signal. In the skin, keratinocytes are the main producers of these signals. OBJECTIVE: To compare dose- and time-effects of cobalt on the viability of and cytokine release from HaCaT cells cultured at low or high calcium. METHOD: To model two separate states of differentiation of keratinocytes, HaCaT cells were cultured under low or high calcium conditions. HaCaT were exposed to different concentrations of cobalt chloride (10 µm to 5 mM) over time (30 minutes- 48 hours). Cell viability was measured with the Cell-Titer Blue Viability assay. Cytokine production was measured using a bead-based immunoassay and flow cytometry. Gene expression was quantified using qPCR. Data was analyzed by ANOVA and linear mixed model. RESULTS: Viability of the cells was dose- and time-dependent. A linear mixed statistical model showed that cobalt exposure induces increase in IL-6, CXCL8 and CCL2 production over time and whereas increase of IL-6 and a decrease of CCL2 was associated with increasing cobalt chloride concentrations. When comparing the cells incubated under high and low calcium conditions, the more differentiated cells in the high concentration were found to exert a stronger response in terms of IL-6 release. CONCLUSIONS: Our data suggest that cobalt chloride triggered an alarm system in HaCaT cells, and proinflammatory cytokines/chemokines were secreted in a dose- and time-dependent manner. When high and low calcium incubations were compared, the difference was seen only for IL-6. These findings indicate that the effect of cobalt chloride on cell toxicity occurs throughout the living epidermis.