Identification and validation of N-acetylputrescine in combination with non-canonical clinical features as a Parkinson's disease biomarker panel.

Parkinson's disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3-25% of sporadic Parkinson's patients present with genetic abnormalities that could represent a risk factor, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson's disease, which highlights the critical need for biomarkers. In the present study, we prospectively collected and analyzed plasma samples from 194 Parkinson's disease patients and 197 age-matched non-diseased controls. N-acetyl putrescine (NAP) in combination with sense of smell (B-SIT), depression/anxiety (HADS), and acting out dreams (RBD1Q) clinical measurements demonstrated combined diagnostic utility. NAP was increased by 28% in Parkinsons disease patients and exhibited an AUC of 0.72 as well as an OR of 4.79. The clinical and NAP panel demonstrated an area under the curve, AUC = 0.9 and an OR of 20.4. The assessed diagnostic panel demonstrates combinatorial utility in diagnosing Parkinson's disease, allowing for an integrated interpretation of disease pathophysiology and highlighting the use of multi-tiered panels in neurological disease diagnosis.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality.

BACKGROUND: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions. OBJECTIVES: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables. METHODS: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping. RESULTS: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients. CONCLUSIONS: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

Multiplexed LC-MS/MS analysis of methylsuccinic acid, ethylmalonic acid, and glutaric acid in plasma and urine.

Low molecular-mass aliphatic carboxylic acids are critically important for intermediate metabolism and may serve as important biomarkers for metabolic homeostasis. Here in, we focused on multiplexed method development of aliphatic carboxylic analytes, including methylsuccinic acid (MSA), ethylmalonic acid (EMA), and glutaric acid (GA). Also assessed was their utility in a population's health as well as metabolic disease screening in both plasma and urine matrices. MSA, EMA, and GA are constitutional isomers of dicarboxylic acid with high polarity and poor ionization efficiency, resulting in such challenges as poor signal intensity and retention, particularly in reversed-phase liquid chromatography with electrospray mass spectrometry (RP-LC-ESI-MS/MS). Derivatization using n-butanol was performed in the sample preparation to enhance the signal intensity accompanied with a positive charge from ionization in complicated biomatrices as well as to improve the separation of these isomers with optimal retention. Fit-for-purpose method validation results demonstrated quantitative ranges for MSA/EMA/GA from 5/10/20 ng/mL to 400 ng/mL in plasma analysis, and 100/200/100 ng/mL to 5000/10000/5000 ng/mL in urine analysis. This validated method demonstrates future utility when exploring population health analysis and biomarker development in metabolic diseases.

Impact of hemolysis on multi-OMIC pancreatic biomarker discovery to derisk biomarker development in precision medicine studies.

Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants. Multi-omic profiling of candidate protein, lipid, and metabolite biomarkers is confounded by timing and fasting status of sample collection, participant demographics and treatment exposures of the study population. Contamination by hemoglobin, whether caused by hemolysis during sample preparation or underlying red cell fragility, contributes 0-10 g/L of extraneous protein to plasma, serum, and Buffy coat samples and may interfere with biomarker detection and validation. We analyzed 617 plasma, 701 serum, and 657 buffy coat samples from a 7-year longitudinal multi-omic biomarker discovery program evaluating 400+ participants with or at risk for pancreatic cancer, known as Project Survival. Hemolysis was undetectable in 93.1% of plasma and 95.0% of serum samples, whereas only 37.1% of buffy coat samples were free of contamination by hemoglobin. Regression analysis of multi-omic data demonstrated a statistically significant correlation between hemoglobin concentration and the resulting pattern of analyte detection and concentration. Although hemolysis had the greatest impact on identification and quantitation of the proteome, distinct differentials in metabolomics and lipidomics were also observed and correlated with severity. We conclude that quality control is vital to accurate detection of informative molecular differentials using OMIC technologies and that caution must be exercised to minimize the impact of hemolysis as a factor driving false discovery in large cancer biomarker studies.

Ubc1 turnover contributes to the spindle assembly checkpoint in Saccharomyces cerevisiae.

The spindle assembly checkpoint protects the integrity of the genome by ensuring that chromosomes are properly attached to the mitotic spindle before they are segregated during anaphase. Activation of the spindle checkpoint results in inhibition of the Anaphase-Promoting Complex (APC), an E3 ubiquitin ligase that triggers the metaphase-anaphase transition. Here, we show that levels of Ubc1, an E2 enzyme that functions in complex with the APC, modulate the response to spindle checkpoint activation in Saccharomyces cerevisiae. Overexpression of Ubc1 increased resistance to microtubule poisons, whereas Ubc1 shut-off sensitized cells. We also found that Ubc1 levels are regulated by the spindle checkpoint. Checkpoint activation or direct APC inhibition led to a decrease in Ubc1 levels, charging, and half-life. Additionally, stabilization of Ubc1 prevented its down-regulation by the spindle checkpoint and increased resistance to checkpoint-activating drugs. These results suggest that down-regulation of Ubc1 in response to spindle checkpoint signaling is necessary for a robust cell cycle arrest.

In-hospital use of ACE inhibitors/angiotensin receptor blockers associates with COVID-19 outcomes in African American patients.

BACKGROUNDThe angiotensin-converting enzyme (ACE) D allele is more prevalent among African Americans compared with other races and ethnicities and has previously been associated with severe coronavirus disease 2019 (COVID-19) pathogenesis through excessive ACE1 activity. ACE inhibitors/angiotensin receptor blockers (ACE-I/ARB) may counteract this mechanism, but their association with COVID-19 outcomes has not been specifically tested in the African American population.METHODSWe identified 6218 patients who were admitted into Mount Sinai hospitals with COVID-19 between February 24 and May 31, 2020, in New York City. We evaluated whether the outpatient and in-hospital use of ACE-I/ARB is associated with COVID-19 in-hospital mortality in an African American compared with non-African American population.RESULTSOf the 6218 patients with COVID-19, 1138 (18.3%) were ACE-I/ARB users. In a multivariate logistic regression model, ACE-I/ARB use was independently associated with a reduced risk of in-hospital mortality in the entire population (OR, 0.655; 95% CI, 0.505-0.850; P = 0.001), African American population (OR, 0.44; 95% CI, 0.249-0.779; P = 0.005), and non-African American population (OR, 0.748, 95% CI, 0.553-1.012, P = 0.06). In the African American population, in-hospital use of ACE-I/ARB was associated with improved mortality (OR, 0.378; 95% CI, 0.188-0.766; P = 0.006), whereas outpatient use was not (OR, 0.889; 95% CI, 0.375-2.158; P = 0.812). When analyzing each medication class separately, ARB in-hospital use was significantly associated with reduced in-hospital mortality in the African American population (OR, 0.196; 95% CI, 0.074-0.516; P = 0.001), whereas ACE-I use was not associated with impact on mortality in any population.CONCLUSIONIn-hospital use of ARB was associated with a significant reduction in in-hospital mortality among COVID-19-positive African American patients.FUNDINGNone.

Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

Prostate-specific antigen (PSA) screening for prostate cancer (PCa) is limited by the lack of specificity but is further complicated in the benign prostatic hyperplasia (BPH) population which also exhibit elevated PSA, representing a clear unmet need to distinguish BPH from PCa. Herein, we evaluated the utility of FLNA IP-MRM, age, and prostate volume to stratify men with BPH from those with PCa. Diagnostic performance of the biomarker panel was better than PSA alone in discriminating patients with negative biopsy from those with PCa, as well as those who have had multiple prior biopsies (AUC 0.75 and 0.87 compared to AUC of PSA alone 0.55 and 0.57 for patients who have had single compared to multiple negative biopsies, respectively). Of interest, in patients with PCa, the panel demonstrated improved performance than PSA alone in those with Gleason scores of 5-7 (AUC 0.76 vs. 0.56) and Gleason scores of 8-10 (AUC 0.74 vs. 0.47). With Gleason scores (8-10), the negative predictive value of the panel is 0.97, indicating potential to limit false negatives in aggressive cancers. Together, these data demonstrate the ability of the biomarker panel to perform better than PSA alone in men with BPH, thus preventing unnecessary biopsies.

The influence of low-carbohydrate diets on the metabolic response to androgen-deprivation therapy in prostate cancer.

BACKGROUND: Prostate cancer (PC) is the second most lethal cancer for men. For metastatic PC, standard first-line treatment is androgen deprivation therapy (ADT). While effective, ADT has many metabolic side effects. Previously, we found in serum metabolome analysis that ADT reduced androsterone sulfate, 3-hydroxybutyric acid, acyl-carnitines but increased serum glucose. Since ADT reduced ketogenesis, we speculate that low-carbohydrate diets (LCD) may reverse many ADT-induced metabolic abnormalities in animals and humans. METHODS: In a multicenter trial of patients with PC initiating ADT randomized to no diet change (control) or LCD, we previously showed that LCD intervention led to significant weight loss, reduced fat mass, improved insulin resistance, and lipid profiles. To determine whether and how LCD affects ADT-induced metabolic changes, we analyzed serum metabolites after 3-, and 6-months of ADT on LCD versus control. RESULTS: We found androsterone sulfate was most consistently reduced by ADT and was slightly further reduced in the LCD arm. Contrastingly, LCD intervention increased 3-hydroxybutyric acid and various acyl-carnitines, counteracting their reduction during ADT. LCD also reversed the ADT-reduced lactic acid, alanine, and S-adenosyl methionine (SAM), elevating glycolysis metabolites and alanine. While the degree of androsterone reduction by ADT was strongly correlated with glucose and indole-3-carboxaldehyde, LCD disrupted such correlations. CONCLUSIONS: Together, LCD intervention significantly reversed many ADT-induced metabolic changes while slightly enhancing androgen reduction. Future research is needed to confirm these findings and determine whether LCD can mitigate ADT-linked comorbidities and possibly delaying disease progression by further lowering androgens.

Elevated levels of mitochondrial CoQ10 induce ROS-mediated apoptosis in pancreatic cancer.

Reactive oxygen species (ROS) are implicated in triggering cell signalling events and pathways to promote and maintain tumorigenicity. Chemotherapy and radiation can induce ROS to elicit cell death allows for targeting ROS pathways for effective anti-cancer therapeutics. Coenzyme Q10 is a critical cofactor in the electron transport chain with complex biological functions that extend beyond mitochondrial respiration. This study demonstrates that delivery of oxidized Coenzyme Q10 (ubidecarenone) to increase mitochondrial Q-pool is associated with an increase in ROS generation, effectuating anti-cancer effects in a pancreatic cancer model. Consequent activation of cell death was observed in vitro in pancreatic cancer cells, and both human patient-derived organoids and tumour xenografts. The study is a first to demonstrate the effectiveness of oxidized ubidecarenone in targeting mitochondrial function resulting in an anti-cancer effect. Furthermore, these findings support the clinical development of proprietary formulation, BPM31510, for treatment of cancers with high ROS burden with potential sensitivity to ubidecarenone.

Ethnic Prevalence of Angiotensin-Converting Enzyme Deletion (D) Polymorphism and COVID-19 Risk: Rationale for Use of Angiotensin-Converting Enzyme Inhibitors/Angiotensin Receptor Blockers.

RATIONALE: Hypertension, obesity and diabetes are major risk factors associated with morbidities underlying COVID-19 infections. Regression analysis correlated presence of ACE insertion/deletion (I/D) polymorphism to COVID-19 incidence and mortality. Furthermore, COVID-19 prevalence correlated to allele frequency of angiotensin-converting enzyme (ACE) deletion (D) polymorphism within the European population. OBJECTIVE: Homozygous ACE deletion polymorphism is associated with increase in ACE and angiotensin II (Ang-II), sustained levels can result in inflammation, fibrosis and organ damage. The ACE DD polymorphism is also associated with hypertension, acute respiratory distress and diabetic nephropathy, all considered high risk for COVID-19 infection and outcomes. The study objective was to describe a biological framework associating ethnic prevalence of ACE deletion polymorphism to COVID-19 comorbidities providing rationale for therapeutic utility of ACE-I/ARBs to improve outcomes. METHOD AND RESULTS: The Allele Frequency Database (ALFRED) was queried for frequency of rs4646994 representing ACE I/D polymorphism. In a total of 349 worldwide population samples, frequency of ACE D allele was higher in European, Asian, and Africans cohorts. In the USA, the frequency of ACE D allele was higher in non-Hispanic Black compared with non-Hispanic White and Mexican Americans. CONCLUSION: COVID-19 binding mediated reduction/inactivation of ACE-II can increase ACE/Ang-II signalling pathway and related pathologies. The presence of ACE DD polymorphism with COVID-19 infection likely augments ACE/Ang-II activities, increasing severity of COVID-19 morbidities and impacts outcomes. Thus, ethnic prevalence of ACE DD polymorphism can explain in part the severity of COVID-19 morbidity providing rationale for the use of ACE-I/ARBs to improve outcomes.

A phase I safety study of topical calcitriol (BPM31543) for the prevention of chemotherapy-induced alopecia.

PURPOSE: Chemotherapy-induced alopecia (CIA) negatively affects psychosocial health and quality of life (QoL). Currently, there are no approved pharmacologic agents to prevent CIA. Here, we evaluated the safety, tolerability, and potential signal of efficacy of topical calcitriol (BPM31543) on CIA prevention. MATERIALS AND METHODS: This Phase 1 trial included 23 female patients with breast cancer, gynecologic cancer, or sarcomas receiving a taxane-based chemotherapy. Patients received a 3 + 3 dose-escalation regimen at 5, 10, 20, 40, 60, and 80 µg/mL, with 3-6 patients per group. Patients applied topical BPM31543 to the scalp twice a day for 2 weeks prior to chemotherapy and continued until chemotherapy treatment was completed. The maximum tolerated dose (MTD) during first 28 day application was determined. Adverse event (AE) monitoring, pharmacokinetics, blinded photographic assessments, and patient self-assessment were evaluated. RESULTS: Out of 23 patients treated with BPM31543, 8 patients experienced at least 1 treatment-related adverse event (AE). The majority of AEs were mild to moderate in severity. Only 1 patient experienced SAEs (vomiting, nausea, fever, and flank pain) considered treatment related. Alopecia < 50% from baseline was observed in 8 patients at Week 7, and, of which 2 patients had < 50% alopecia maintained at Week 15. There were no detectable effects of topical BPM31543 on serum levels of calcitriol. CONCLUSIONS: BPM31543 applied topically twice daily to the scalp is safe and well tolerated in patients receiving taxane-based chemotherapy. No DLT was observed at up to 80 µg/mL, and MTD was not reached. Based on the data from this trial, BPM31543 represents a promising therapy and warrants further investigation in Phase 2/3 trials.

Comparative analysis of differentially abundant proteins quantified by LC-MS/MS between flash frozen and laser microdissected OCT-embedded breast tumor samples.

BACKGROUND: Proteomic studies are typically conducted using flash-frozen (FF) samples utilizing tandem mass spectrometry (MS). However, FF specimens are comprised of multiple cell types, making it difficult to ascertain the proteomic profiles of specific cells. Conversely, OCT-embedded (Optimal Cutting Temperature compound) specimens can undergo laser microdissection (LMD) to capture and study specific cell types separately from the cell mixture. In the current study, we compared proteomic data obtained from FF and OCT samples to determine if samples that are stored and processed differently produce comparable results. METHODS: Proteins were extracted from FF and OCT-embedded invasive breast tumors from 5 female patients. FF specimens were lysed via homogenization (FF/HOM) while OCT-embedded specimens underwent LMD to collect only tumor cells (OCT/LMD-T) or both tumor and stromal cells (OCT/LMD-TS) followed by incubation at 37 °C. Proteins were extracted using the illustra triplePrep kit and then trypsin-digested, TMT-labeled, and processed by two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS). Proteins were identified and quantified with Proteome Discoverer v1.4 and comparative analyses performed to identify proteins that were significantly differentially expressed amongst the different processing methods. RESULTS: Among the 4,950 proteins consistently quantified across all samples, 216 and 171 proteins were significantly differentially expressed (adjusted p-value < 0.05; |log2 FC|> 1) between FF/HOM vs. OCT/LMD-T and FF/HOM vs. OCT/LMD-TS, respectively, with most proteins being more highly abundant in the FF/HOM samples. PCA and unsupervised hierarchical clustering analysis with these 216 and 171 proteins were able to distinguish FF/HOM from OCT/LMD-T and OCT/LMD-TS samples, respectively. Similar analyses using significantly differentially enriched GO terms also discriminated FF/HOM from OCT/LMD samples. No significantly differentially expressed proteins were detected between the OCT/LMD-T and OCT/LMD-TS samples but trended differences were detected. CONCLUSIONS: The proteomic profiles of the OCT/LMD-TS samples were more similar to those from OCT/LMD-T samples than FF/HOM samples, suggesting a strong influence from the sample processing methods. These results indicate that in LC-MS/MS proteomic studies, FF/HOM samples exhibit different protein expression profiles from OCT/LMD samples and thus, results from these two different methods cannot be directly compared.

Chronic stress and antidepressant treatment alter purine metabolism and beta oxidation within mouse brain and serum.

Major depressive disorder (MDD) is a complex condition with unclear pathophysiology. Molecular disruptions within limbic brain regions and the periphery contribute to depression symptomatology and a more complete understanding the diversity of molecular changes that occur in these tissues may guide the development of more efficacious antidepressant treatments. Here, we utilized a mouse chronic social stress model for the study of MDD and performed metabolomic, lipidomic, and proteomic profiling on serum plus several brain regions (ventral hippocampus, nucleus accumbens, and medial prefrontal cortex) of susceptible, resilient, and unstressed control mice. To identify how commonly used tricyclic antidepressants impact the molecular composition in these tissues, we treated stress-exposed mice with imipramine and repeated our multi-OMIC analyses. Proteomic analysis identified three serum proteins reduced in susceptible animals; lipidomic analysis detected differences in lipid species between resilient and susceptible animals in serum and brain; and metabolomic analysis revealed dysfunction of purine metabolism, beta oxidation, and antioxidants, which were differentially associated with stress susceptibility vs resilience by brain region. Antidepressant treatment ameliorated stress-induced behavioral abnormalities and affected key metabolites within outlined networks, most dramatically in the ventral hippocampus. This work presents a resource for chronic social stress-induced, tissue-specific changes in proteins, lipids, and metabolites and illuminates how molecular dysfunctions contribute to individual differences in stress sensitivity.

High levels of ubidecarenone (oxidized CoQ10) delivered using a drug-lipid conjugate nanodispersion (BPM31510) differentially affect redox status and growth in malignant glioma versus non-tumor cells.

Metabolic reprogramming in cancer cells, vs. non-cancer cells, elevates levels of reactive oxygen species (ROS) leading to higher oxidative stress. The elevated ROS levels suggest a vulnerability to excess prooxidant loads leading to selective cell death, a therapeutically exploitable difference. Co-enzyme Q10 (CoQ10) an endogenous mitochondrial resident molecule, plays an important role in mitochondrial redox homeostasis, membrane integrity, and energy production. BPM31510 is a lipid-drug conjugate nanodispersion specifically formulated for delivery of supraphysiological concentrations of ubidecarenone (oxidized CoQ10) to the cell and mitochondria, in both in vitro and in vivo model systems. In this study, we sought to investigate the therapeutic potential of ubidecarenone in the highly treatment-refractory glioblastoma. Rodent (C6) and human (U251) glioma cell lines, and non-tumor human astrocytes (HA) and rodent NIH3T3 fibroblast cell lines were utilized for experiments. Tumor cell lines exhibited a marked increase in sensitivity to ubidecarenone vs. non-tumor cell lines. Further, elevated mitochondrial superoxide production was noted in tumor cells vs. non-tumor cells hours before any changes in proliferation or the cell cycle could be detected. In vitro co-culture experiments show ubidecarenone differentially affecting tumor cells vs. non-tumor cells, resulting in an equilibrated culture. In vivo activity in a highly aggressive orthotopic C6 glioma model demonstrated a greater than 25% long-term survival rate. Based on these findings we conclude that high levels of ubidecarenone delivered using BPM31510 provide an effective therapeutic modality targeting cancer-specific modulation of redox mechanisms for anti-cancer effects.

Current Status of Metabolomic Biomarker Discovery: Impact of Study Design and Demographic Characteristics.

Widespread application of omic technologies is evolving our understanding of population health and holds promise in providing precise guidance for selection of therapeutic interventions based on patient biology. The opportunity to use hundreds of analytes for diagnostic assessment of human health compared to the current use of 10-20 analytes will provide greater accuracy in deconstructing the complexity of human biology in disease states. Conventional biochemical measurements like cholesterol, creatinine, and urea nitrogen are currently used to assess health status; however, metabolomics captures a comprehensive set of analytes characterizing the human phenotype and its complex metabolic processes in real-time. Unlike conventional clinical analytes, metabolomic profiles are dramatically influenced by demographic and environmental factors that affect the range of normal values and increase the risk of false biomarker discovery. This review addresses the challenges and opportunities created by the evolving field of clinical metabolomics and highlights features of study design and bioinformatics necessary to maximize the utility of metabolomics data across demographic groups.

Metabolomic effects of androgen deprivation therapy treatment for prostate cancer.

Androgen deprivation therapy (ADT) is the main treatment strategy for men with metastatic prostate cancer (PC). However, ADT is associated with various metabolic disturbances, including impaired glucose tolerance, insulin resistance and weight gain, increasing risk of diabetes and cardiovascular death. Much remains unknown about the metabolic pathways and disturbances altered by ADT and the mechanisms. We assessed the metabolomic effects of ADT in the serum of 20 men receiving ADT. Sera collected before (baseline), 3 and 6 months after initiation of ADT was used for the metabolomics and lipidomics analyses. The ADT-associated metabolic changes were identified by univariable and multivariable statistical analysis, ANOVA, and Pearson correlation. We found multiple key changes. First, ADT treatments reduced the steroid synthesis as reflected by the lower androgen sulfate and other steroid hormones. Greater androgen reduction was correlated with higher serum glucose levels, supporting the diabetogenic role of ADT. Second, ADT consistently decreased the 3-hydroxybutyric acid and ketogenesis. Third, many acyl-carnitines were reduced, indicating the effects on the fatty acid metabolism. Fourth, ADT was associated with a corresponding reduction in 3-formyl indole (a.k.a. indole-3-carboxaldehyde), a microbiota-derived metabolite from the dietary tryptophan. Indole-3-carboxaldehyde is an agonist for the aryl hydrocarbon receptor and regulates the mucosal reactivity and inflammation. Together, these ADT-associated metabolomic analyses identified reduction in steroid synthesis and ketogenesis as prominent features, suggesting therapeutic potential of restricted ketogenic diets, though this requires formal testing. ADT may also impact the microbial production of indoles related to the immune pathways. Future research is needed to determine the functional impact and underlying mechanisms to prevent ADT-linked comorbidities and diabetes risk.

Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer.

BACKGROUND: Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients 'sera using a multi-omics discovery platform. METHODS: Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan-Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort. RESULTS: Among 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins-Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite-1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98-14.40), P < 0.05], in differentiating patients with and without BCR event. In the validation set all four metabolites consistently reproduced an equivalent performance with high negative predictive value (NPV; > 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45-32.05, P < 0.05], with an increased NPV (0.96) and OR (12.4) for BCR. The panel of markers combined with the pathological parameters demonstrated a more accurate prediction of BCR than the pathological parameters alone in prostate cancer. CONCLUSIONS: In this study, a panel of serum analytes were identified that complemented pathologic patient features in predicting prostate cancer progression. This panel offers a new opportunity to complement current prognostic markers and to monitor the potential impact of primary treatment versus surveillance on patient oncological outcome.

Genomic alterations of Tenascin C in highly aggressive prostate cancer: a meta-analysis.

Tenascin C (TNC), an extra-cellular matrix (ECM) family gene, is expressed in several cancer tissues of breast, lung, colon, and gastrointestinal tract leading to proliferation, migration, invasion, angiogenesis and metastasis, but its role in tumorigenesis of prostate cancer is poorly understood. We took a meta-analysis approach to characterize the alterations of TNC gene in prostate cancer using publicly available databases (cBioportal Version 2.2.0, http://www.cBioportal.org/index.do). The analysis identified TNC alterations (gene amplification) significantly in the neuroendocrine prostate cancer dataset (Trento/Broad/Cornell, N = 114), which was further validated in other prostate cancer datasets, including The Cancer Genome Atlas (TCGA) prostate cancer (2015). In the TCGA prostate cancer dataset (N = 498), high TNC (alteration frequency, 36%) revealed a strong association with high diagnostic Gleason score. Genomic alterations of TNC was also significantly associated (P < 0.05) with expression level of genes from NOTCH, SOX and WNT family, implicating a link between TNC and poorly differentiated aggressive phenotype in NEPC. TCGA prostate adenocarcinoma cases with TNC alteration also demonstrated prominent decrease in disease-free survival (P = 0.0637). These findings indicate a possible association of TNC to the aggressive subtype of prostate cancer and warrant further functional studies to evident the involvement of TNC in prostate cancer progression.

Diablo ubiquitination analysis by sandwich immunoassay.

Ubiquitin plays an essential role in modulating protein function, and deregulation of the ubiquitin system leads to the development of a variety of human diseases. E3 Ubiquitin ligases that mediate ubiquitination and degradation of caspases prevent apoptosis, and as such belong to the family of inhibitors of apoptosis proteins (IAPs). Diablo is a substrate of IAPs but also a negative regulator of IAPs in apoptotic pathway as it blocks the interaction between IAPs and caspases. In efforts to identify IAP inhibitors, we developed sandwich immunoassays in conjunction with an electrochemical luminescence (ECL) platform for quantitation of total Diablo, ubiquitinated Diablo, and ubiquitinated Diablo with K48-specific linkage. The assay panel detects Diablo ubiquitination level changes in the presence of IAP inhibitor or proteasome inhibitor, demonstrating its potential as a cost-efficient high-throughput method for drug discovery involving IAP ubiquitination cascade. The ECL based sandwich assay panel performance was subsequently evaluated for precision, linearity, and limit of quantification.