Metabolite Profiling Identifies Candidate Markers Reflecting the Clinical Adaptations Associated with Roux-en-Y Gastric Bypass Surgery

Background: Roux-en-Y gastric bypass (RYGB) surgery is associated with weight loss, improved insulin sensitivity and glucose homeostasis, and a reduction in co-morbidities such as diabetes and coronary heart disease. To generate further insight into the numerous metabolic adaptations associated with RYGB surgery, we profiled serum metabolites before and after gastric bypass surgery and integrated metabolite changes with clinical data. Methodology and Principal Findings: Serum metabolites were detected by gas and liquid chromatography-coupled mass spectrometry before, and 3 and 6 months after RYGB in morbidly obese female subjects (n = 14; BMI = 46.261.7). Subjects showed decreases in weight-related parameters and improvements in insulin sensitivity post surgery. The abundance of 48 % (83 of 172) of the measured metabolites changed significantly within the first 3 months post RYGB (p,0.05), including sphingosines, unsaturated fatty acids, and branched chain amino acids. Dividing subjects into obese (n = 9) and obese/ diabetic (n = 5) groups identified 8 metabolites that differed consistently at all time points and whose serum levels changed following RYGB: asparagine, lysophosphatidylcholine (C18:2), nervonic (C24:1) acid, p-Cresol sulfate, lactate, lycopene, glucose, and mannose. Changes in the aforementioned metabolites were integrated with clinical data for body mass index (BMI) and estimates for insulin resistance (HOMA-IR). Of these, nervonic acid was significantly and negatively correlated with HOMA-IR (p = 0.001, R = 20.55)

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

Increases in nervonic acid following RYGB.

<p>A significant increase in serum abundance of nervonic acid occurred following RYGB in both OB and OB/D subjects, as assessed using a mixed-effects ANOVA with group:time interaction (** <i>p</i><0.01 versus T0). Overall, nervonic acid levels were significantly different at each time point between OB and OB/D subgroups (p<0.01, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007905#pone-0007905-t002" target="_blank"><b>TABLE 2</b></a>). No group:time interaction was identified. Mean metabolite abundance±SEM is indicated in red.</p

Clinical data in subjects at all 3 time points (T0, T3, and T6) examined.

<p>All 14 subjects are included in the analysis of parameters related to body weight and lipids. Decreases after RYGB were observed for BMI, weight, fat mass, fat free mass, resting energy expenditure and triglycerides. Leptin was also decreased significantly. While HDL-cholesterol decreased from T0 to T3, HDL-Cholesterol levels recovered by T6 and are confirmed by the lack of change in Apo-A1 levels. Total caloric intake decreased after RYGB; however, the relative proportion of lipid, carbohydrate, and protein consumed remained stable. When considering the 12 subjects not treated with insulin, glucose and insulin levels decreased post RYGB. Estimates for HOMA-IR and HOMA%B decreased while HOMA%S increased after surgery. Data presented as mean±standard error. * represents p<0.1 and ** represents p<0.05, assessed by a Friedman test.</p

Estimates for HOMA-IR before and after RYGB.

<p>HOMA-IR was estimated for 12 subjects, 9 OB and 3 OB/D subjects. The OB/D subjects were treated with metformin and not with insulin. A significant reduction (T0 → T3, p = 0.014; T0 → T6, p = 0.001; T3 → T6, p = 0.123) in HOMA-IR occurred following RYGB, as assessed using a Friedman test. Prior to RYGB, significant variability in HOMA-IR estimations was observed between subjects (because OB and OB/D subjects are combined); however, post RYGB, all subjects demonstrated a major improvement in insulin sensitivity (illustrated by smaller error bars). Box plots indicate no outlying data (i.e. above or below the whiskers), and the band in the middle of the box indicates the median. ** <i>p</i><0.01.</p

Various profiles for metabolites that change significantly at some point following RYGB.

<p>A profile is characterized by 3 dots, which represent T0 (prior to RYGB), T3 and T6 (post surgery). An angled slope between two time points indicates a significant change (p<0.05) and a flat slope between two time points indicates non-significant changes. Based on data derived from the mixed-effects ANOVA using all 14 subjects together. (*1): Structure annotation is based on strong analytical evidence (combinations of chromatography, mass spectrometry, chemical reactions, deuterium-labeling, database and literature search, as well as comparisons to similar/homologue/isomeric reference compounds). (*2): Metabolite exhibits identical qualitative analytical characteristics (chromatography and mass spectrometry) compared to status (*1). Further structural and analytical investigations of this metabolite - also in comparison to structurally identified or status (*1) metabolites - are still pending.</p

Metabolite lists differentiating OB from OB/D subjects at each time point.

<p>Metabolites were identified using a mixed-effects ANOVA: 33 metabolites at T0, 32 metabolites at T3, and 28 metabolites at T6 (p<0.05), with indication of whether serum levels are higher in obese (OB) or obese/diabetic (OB/D) subjects. Those metabolites present in all three lists are indicated in bold font. The profiles for metabolites whose abundance changed post surgery are found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007905#pone-0007905-g001" target="_blank"><b>FIGURE 1</b></a>. (*1): Structure annotation is based on strong analytical evidence (combinations of chromatography, mass spectrometry, chemical reactions, deuterium-labeling, database and literature search, as well as comparisons to similar/homologue/isomeric reference compounds). (*2): Metabolite exhibits identical qualitative analytical characteristics (chromatography and mass spectrometry) compared to status (*1). Further structural and analytical investigations of this metabolite - also in comparison to structurally identified or status (*1) metabolites - are still pending.</p

Increases in 1,5-anhydrosorbitol and decreases in ascorbic acid following RYGB.

<p>The top two metabolites distinguishing OB and OB/D subjects were identified with the mixed-effects ANOVA allowing for group:time-interactions, where * indicates <i>p</i><0.05 (versus T0). White circles and black circles correspond to OB/D or OB subjects, respectively. Furthermore, symbols and numbers are consistently used for the same subject in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007905#pone-0007905-g004" target="_blank">Figures 4</a> & <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007905#pone-0007905-g005" target="_blank">5</a>. Mean metabolite abundance±SEM is indicated in red. A) A significant increase in 1,5-anhydrosorbitol (1,5-AG) occurred at T6 vs. T0 in OB/D subjects, while a non-significant increase was seen in OB subjects (group:time interaction was allowed for by the linear model). B) For ascorbic acid, the ANOVA model did not detect group-specific changes over time (no group:time interaction), but indicated significant decreases from T0 to T6 in both groups. Overall, 1,5-anhydrosorbitol and ascorbic acid were significantly different at each time point between OB and OB/D subgroups (p<0.01, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007905#pone-0007905-t002" target="_blank"><b>TABLE 2</b></a>).</p