Nandy, Debashis

260 Background: The purpose of this study was to evaluate cell free nucleic acid based biomarkers for prognosis in mCRPC stage. Methods: Uniformly collected blood from mCRPC patients was processed for plasma which was used for exosomal RNA extraction. RNA sequencing was applied to examine microRNA (miRNA) profiles initially in a discovery cohort of 23 mCRPC patients. The sequences from fastq files were mapped to human miRBase (release 19) for known miRNA read counts. A software package (miRDeep2) was used for novel miRNA prediction. Cox regression was used for association of candidate miRNAs with overall survival (OS), defined as time from development of mCRPC to death or last follow up after adjusting for Gleason Score (GS) and time on androgen deprivation (AD) for hormone sensitive disease. miRNAs significantly associated with OS (FDR<0.05) were then validated in an independent cohort of 100 mCRPC subjects using univariate Cox regression. Results: RNA sequencing generated >10 million mappable reads per specimen in the discovery cohort. Among these reads ~50% were known miRNAs which included 1237 unique RNA sequences. Due to low abundance of most RNA transcripts, only miRNAs (n=250) with >/= 32 reads (on average) were analyzed. Four mRNAs (miR-1290, -1246, -375 and a predicted miRNA on chr. 12) were associated with OS(FDR<0.05). These were evaluated as prognotic markers in the independent cohort (N=100) using real time RT-PCR. Median time on AD for this cohort prior to progression to mCRPC was 35.7 (range: 3.5-136) months; median GS was 7; median follow up after mCRPC development was 12.5 (1-41) months at which time 28 patients had died. Elevated expression for miR-1290 and -375 were associated with shorter OS after adjusting for GS and AD time with a Hazard Ratio (HR) for miR-375 of 1.19 (CI: 1.006-1.18); (p=0.04) and a HR for miR1290 of 1.58 (CI:1.01-2.4); (p=0.04). A stronger association with shorter OS was observed for elevated expression of both miRs-HR of 2.02 (CI: 1.1-3.6) (p=0.01). Conclusions: Blood-based nucleic acid assays are easily accessible for biomarker development in mCRPC. Results from this study suggest specific exosomal miRs are of prognostic value in mCRPC and should be validated in larger cohorts.

Our recent study defined the chemokine-induced human monocyte signaling under normoglycemic condition. To explore the hyperglycemia-induced monocyte signaling, we performed adhesion, migration, and transmigration assays on human monocytes obtained from THP-1 cell line in the presence of normal (5 mM) and high (10 and 20 mM) glucose concentrations without chemokines. We observed augmented ( P < 0.01) monocyte adhesion to human umbilical vein endothelial cell monolayer at 10 than 5 mM glucose with no further increase at 20-mM glucose concentration ( P < 0.07 vs 10 mM; P < 0.01 vs 5 mM). But incremental increases in monocyte migration ( P < 0.01), transmigration ( P < 0.01), and stress fiber response ( P < 0.01) were observed at 10- and 20-mM glucose concentrations in comparison to 5-mM glucose concentrations. We found gradational increase ( P < 0.01) in phosphorylation of Akt S473 and glycogen synthase kinase (GSK3β S9 ) in hyperglycemia (10 and 20 mM) when compared with 5 mM glucose. Furthermore, hyperglycemia (both 10 and 20 mM)-treated monocyte showed up-regulated phosphorylation of p101 and p110γ subunits of PI-3 kinase in comparison to 5 mM glucose. Hyperglycemia-induced monocyte migration was restored to basal levels in the presence of PI-3 kinase inhibitor, LY. These observations imply that modest hyperglycemia per se, as is commonly observed in diabetic individuals, is a potent stimulator of monocyte activity even without chemokines.

Objective Inadequate vascular remodeling is contributory to increased cardiovascular events in people with type 2 diabetes mellitus (DM) and impaired fasting glucose (IFG). Vascular endothelial growth factor (VEGF) and its regulatory molecule soluble Flt-1(sFlt-1) play important roles in atherogenesis. Research Design We measured fasting plasma concentrations of VEGF and sFlt-1 in 11 nondiabetic (ND) (aged 46.1 ± 2.1 years; body mass index [BMI], 26.1 ± 0.9 kg/m 2 ; glucose, 5.0 ± 0.1 mM), 15 IFG (aged 52.9 ± 1.8 years; BMI, 32.7 ± 1.3 kg/m 2 ; glucose, 6.4 ± 0.1 mM), and 8 DM (aged 55.8 ± 3.2 years; BMI, 30.0 ± 1.0 kg/m 2 ; glucose, 9.3 ± 0.5 mM) subjects. Results Plasma VEGF (42.1 ± 4.0 vs 24.2 ± 0.9 vs 29.4 ± 3.8 pg/mL, respectively) and sFlt-1 (119.4 ± 4.9 vs 58.9 ± 3.2 vs 56.7 ± 1.2 pg/mL, respectively) concentrations were higher ( P < 0.04) in DM than IFG and ND subjects. Whereas VEGF concentrations were significantly lower ( P < 0.05) in IFG than in ND subjects, sFlt-1 concentrations did not differ between the IFG and ND subjects. Conclusions Although plasma VEGF concentrations were higher (35%) in DM than in ND subjects, VEGF action on vascular remodeling was likely attenuated by higher sFlt-1 concentrations in DM. In contrast, IFG subjects did not have major perturbations in either VEGF or sFlt-1 levels. Further studies defining the roles of these mediators in DM and IFG are necessary to extend these observations.

BACKGROUNDProstate cancer (PCa) is a leading cause of cancer death of men worldwide. In hormone‐sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration‐resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients.METHODSA mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate‐specific antigen; PSA) as affected by ADT. Following fine‐tuning by a dataset of ADT‐treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in‐treatment.RESULTSThe mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT‐resistance mechanism, successfully retrieved individual time‐courses of PSA (R2 = 0.783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R2 = 0.98).CONCLUSIONSThe algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short‐lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision‐making. Prostate 76:48–57, 2016. © 2015 Wiley Periodicals, Inc.

This single-centre, 12-week, double-blind, placebo-controlled trial assessed how the human glucagon-like-peptide 1 analogue liraglutide impacted endothelial function in adult patients (n = 49) with type 2 diabetes and no overt cardiovascular disease. Patients were randomized to liraglutide, placebo or glimepiride. At baseline and Week 12, venous occlusion plethysmography was used to measure forearm blood flow (FBF) in response to acetylcholine (ACh) and sodium nitroprusside (SNP) before and after l-N G -monomethyl arginine (L-NMMA) infusion. At Week 12, ACh-mediated FBF increased with liraglutide and decreased with placebo; however, the between-treatment difference was not significant ( p = 0.055). Inhibition of ACh-mediated FBF after L-NMMA infusion increased with liraglutide and decreased with placebo; this between-treatment difference was also not significant ( p = 0.149). No change in FBF was observed with SNP. Liraglutide did not significantly impact endothelium-dependent vasodilation after 12 weeks; however, additional investigations looking at the effect of liraglutide on endothelial function in alternative vasculature and during the postprandial period are warranted.

We recently demonstrated a diurnal pattern to insulin action (i.e., insulin sensitivity [SI]) in healthy individuals with higher SI at breakfast than at dinner. To determine whether such a pattern exists in type 1 diabetes, we studied 19 subjects with C-peptide–negative diabetes (HbA1c 7.1 ± 0.6%) on insulin pump therapy with normal gastric emptying. Identical mixed meals were ingested during breakfast, lunch, and dinner at 0700, 1300, and 1900 h in randomized Latin square of order on 3 consecutive days when measured daily physical activity was equal. The triple tracer technique enabled measurement of glucose fluxes. Insulin was administered according to the customary insulin:carbohydrate ratio for each participant. Although postprandial glucose excursions did not differ among meals, insulin concentration was higher (P &lt; 0.01) and endogenous glucose production less suppressed (P &lt; 0.049) at breakfast than at lunch. There were no differences in meal glucose appearance or in glucose disappearance between meals. Although there was no statistical difference (P = 0.34) in SI between meals in type 1 diabetic subjects, the diurnal pattern of SI taken across the three meals in its entirety differed (P = 0.016) from that of healthy subjects. Although the pattern in healthy subjects showed decreasing SI between breakfast and lunch, the reverse SI pattern was observed in type 1 diabetic subjects. The results suggest that in contrast to healthy subjects, SI diurnal pattern in type 1 diabetes is specific to the individual and cannot be extrapolated to the type 1 diabetic population as a whole, implying that artificial pancreas algorithms may need to be personalized.

OBJECTIVE Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and patients with type 1 diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms. RESEARCH DESIGN AND METHODS We studied 12 healthy control subjects (five males, 37.7 ± 13.7 years of age) and 12 patients with type 1 diabetes (five males, 37.4 ± 14.2 years of age) for 88 h. Participants performed PA approximating a threefold increase over their basal metabolic rate. PA was captured using a PA-monitoring system, and interstitial fluid glucose concentrations were captured with continuous glucose monitors. In random order, one meal per day was followed by inactivity, and the other meals were followed by walking. Glucose and PA data for a total of 216 meals were analyzed from 30 min prior to meal ingestion to 270 min postmeal. RESULTS In healthy subjects, the incremental glucose area under the curve was 4.5 mmol/L/270 min for meals followed by walking, whereas it was 9.6 mmol/L/270 min (P = 0.022) for meals followed by inactivity. The corresponding glucose excursions for those with type 1 diabetes were 7.5 mmol/L/270 min and 18.4 mmol/L/270 min, respectively (P &lt; 0.001). CONCLUSIONS Walking significantly impacts postprandial glucose excursions in healthy populations and in those with type 1 diabetes. AEP algorithms incorporating PA may enhance tight glycemic control end points.