Medium Chain Fatty Acids Are Selective Peroxisome Proliferator Activated Receptor (PPAR) γ Activators and Pan-PPAR Partial Agonists

Thiazolidinediones (TZDs) act through peroxisome proliferator activated receptor (PPAR) γ to increase insulin sensitivity in type 2 diabetes (T2DM), but deleterious effects of these ligands mean that selective modulators with improved clinical profiles are needed. We obtained a crystal structure of PPARγ ligand binding domain (LBD) and found that the ligand binding pocket (LBP) is occupied by bacterial medium chain fatty acids (MCFAs). We verified that MCFAs (C8–C10) bind the PPARγ LBD in vitro and showed that they are low-potency partial agonists that display assay-specific actions relative to TZDs; they act as very weak partial agonists in transfections with PPARγ LBD, stronger partial agonists with full length PPARγ and exhibit full blockade of PPARγ phosphorylation by cyclin-dependent kinase 5 (cdk5), linked to reversal of adipose tissue insulin resistance. MCFAs that bind PPARγ also antagonize TZD-dependent adipogenesis in vitro. X-ray structure B-factor analysis and molecular dynamics (MD) simulations suggest that MCFAs weakly stabilize C-terminal activation helix (H) 12 relative to TZDs and this effect is highly dependent on chain length. By contrast, MCFAs preferentially stabilize the H2-H3/β-sheet region and the helix (H) 11-H12 loop relative to TZDs and we propose that MCFA assay-specific actions are linked to their unique binding mode and suggest that it may be possible to identify selective PPARγ modulators with useful clinical profiles among natural products

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

MCFAs that bind PPARγ block TZD-dependent 3T3-L1 cell differentiation.

<p>3T3 fibroblasts were induced to differentiate with Insulin, Dexamethasone and Isobutylmethylxanthine −/+ 100 nM rosi (<b>A, C, E</b> versus <b>B, D, F</b>), 1 mM HA C6 (<b>C, D</b>) or 1 mM DA C10 (<b>E, F</b>). Adipogenesis was tested by Red Oil O staining and results showed that DA C10, but not HA C6, is weakly adipogenic and blocks rosi effects.</p

MD Simulations reveal a role for water in PPARγ-MCFA Interactions.

<p>(<b>A</b>) LBP showing superposed configurations of NA (white) observed in the simulations overlaid on native NA positions observed in the X-ray structure (red) and the corresponding average occupied volumes (color surfaces; NA1 is purple, NA2 is green and NA3 is orange. The average volume occupied by water molecules is shown in blue. Positions of NA carboxylate groups are marked with a C. (<b>B</b>) Waters surrounding NA at the three binding sites. The amount of water during independent simulations is shown in grey and average hydration numbers are shown in color; on average 1, 7, and 8 water molecules coordinate NA in sites I, II, and III respectively. (<b>C</b>) Distributions of RMSD of NA bound to PPARγ in the three binding sites computed from the simulations.</p

Predicted Interactions of NA3 and β-sheets.

<p>The figure shows a snapshot of the MD simulation, revealing contacts between NA3 and Ser342 that are not apparent in the crystal structure but are seen regularly throughout the course of the simulation.</p

MD Simulations Predict Poor H12 packing in the presence of LA (C12).

<p>MD snapshot showing a hydrogen bond between Tyr473 and the ligand (cyan), which is persistent throughout the course of the simulations with NA (C9) and DA (C10), and an instantaneous conformation obtained from LA (C12) runs showing rupture of this bond and the concomitant displacement of H12 away from the body of the LBD (magenta).</p

PPARγ binds three MCFAs.

<p>(<b>A</b>) Structure of the PPARγ LBD chain A subunit showing positions of MCFA electron densities in the LBP; NA1 (site I), NA2 (site II) and NA3 (site III). (<b>B</b>) LBP (in red) with its three arms filled with MCFA (<b>C</b>) Overlaid views of the PPARγ LBP in the presence of NA (PPARγ green, ligand yellow) and Rosiglitazone (PPARγ blue, ligand transparent pink) revealing ligand binding modes. <b>C</b>) Radiolabeled ligand displacement assay. Bacterially expressed PPARγ LBD was incubated with radiolabeled rosiglitazone +/_ cold competitors as indicated.</p

Interaction energies of NAs with PPARγ system components.

<p>Interaction energies of NAs with PPARγ system components.</p

Rosiglitazone and MCFAs stabilize PPARγ LBD in distinct ways.

<p>Variations in crystallographic B-factors represented as width of the backbone trace in PPARγ-NA (left) and PPARγ+rosi (right).</p