Person:

Bhasin, Manoj

The purpose of the study was to develop tumor specific, water dispersible superparamagnetic iron oxide nanoparticles (SPIONs) and evaluate their efficacy as a contrast agent in magnetic resonance imaging (MRI). We have developed SPIONs capped with citric acid/2-bromo-2-methylpropionic acid which are compact, water dispersible, biocompatible having narrow range of size dispersity (8–10 nm), and relatively high T2 relaxivity (R2 = 222L · mmol−1 · sec−l). The targeting efficacy of unconjugated and folic acid-conjugated SPIONs (FA-SPIONS) was evaluated in a folic acid receptor overexpressing and negative tumor cell lines. Folic acid receptor-positive cells incubated with FA-SPIONs showed much higher intracellular iron content without any cytotoxicity. Ultrastructurally, SPIONs were seen as clustered inside the various stages of endocytic pathways without damaging cellular organelles and possible mechanism for their entry is via receptor mediated endocytosis. In vitro MRI studies on tumor cells showed better T2-weighted images in FA-SPIONs. These findings indicate that FA-SPIONs possess high colloidal stability with excellent sensitivity of imaging and can be a useful MRI contrast agent for the detection of cancer.

Decidual NK (dNK) cells, a distinct type of NK cell, are thought to regulate uterine spiral artery remodeling, a process that allows for increased blood delivery to the fetal-placental unit. Impairment of uterine spiral artery remodeling is associated with decreased placental perfusion, increased uterine artery resistance, and obstetric complications such as preeclampsia and intrauterine growth restriction. Ex vivo manipulation of human peripheral blood NK (pNK) cells by a combination of hypoxia, TGFß-1 and 5-aza-2’-deoxycytidine yields cells with phenotypic and in vitro functional similarities to dNK cells, called idNK cells. Here, gene expression profiling shows that CD56Bright idNK cells derived ex vivo from human pNK cells, and to a lesser extent CD56Dim idNK cells, are enriched in the gene expression signature that distinguishes dNK cells from pNK cells. When injected into immunocompromised pregnant mice with elevated uterine artery resistance, idNK cells homed to the uterus and reduced the uterine artery resistance index, suggesting improved placental perfusion.

The early, accurate diagnosis and risk stratification of sepsis remains an important challenge in the critically ill. Since traditional biomarker strategies have not yielded a gold standard marker for sepsis, focus is shifting towards novel strategies that improve assessment capabilities. The combination of technological advancements and information generated through the human genome project positions systems biology at the forefront of biomarker discovery. While previously available, developments in the technologies focusing on DNA, gene expression, gene regulatory mechanisms, protein and metabolite discovery have made these tools more feasible to implement and less costly, and they have taken on an enhanced capacity such that they are ripe for utilization as tools to advance our knowledge and clinical research. Medicine is in a genome-level era that can leverage the assessment of thousands of molecular signals beyond simply measuring selected circulating proteins. Genomics is the study of the entire complement of genetic material of an individual. Epigenetics is the regulation of gene activity by reversible modifications of the DNA. Transcriptomics is the quantification of the relative levels of messenger RNA for a large number of genes in specific cells or tissues to measure differences in the expression levels of different genes, and the utilization of patterns of differential gene expression to characterize different biological states of a tissue. Proteomics is the large-scale study of proteins. Metabolomics is the study of the small molecule profiles that are the terminal downstream products of the genome and consists of the total complement of all low-molecular-weight molecules that cellular processes leave behind. Taken together, these individual fields of study may be linked during a systems biology approach. There remains a valuable opportunity to deploy these technologies further in human research. The techniques described in this paper not only have the potential to increase the spectrum of diagnostic and prognostic biomarkers in sepsis, but they may also enable the discovery of new disease pathways. This may in turn lead us to improved therapeutic targets. The objective of this paper is to provide an overview and basic framework for clinicians and clinical researchers to better understand the 'omics technologies' to enhance further use of these valuable tools.

Background: Human ascending thoracic aortic aneurysms (ATAAs) are life threatening and constitute a leading cause of mortality in the United States. Previously, we demonstrated that collagens α2(V) and α1(XI) mRNA and protein expression levels are significantly increased in ATAAs. Methods and Results: In this report, the authors extended these preliminary studies using high‐throughput proteomic analysis to identify additional biomarkers for use in whole blood real‐time RT‐PCR analysis to allow for the identification of ATAAs before dissection or rupture. Human ATAA samples were obtained from male and female patients aged 65±14 years. Both bicuspid and tricuspid aortic valve patients were included and compared with nonaneurysmal aortas (mean diameter 2.3 cm). Five biomarkers were identified as being suitable for detection and identification of ATAAs using qRT‐PCR analysis of whole blood. Analysis of 41 samples (19 small, 13 medium‐sized, and 9 large ATAAs) demonstrated the overexpression of 3 of these transcript biomarkers correctly identified 79.4% of patients with ATAA of ≥4.0 cm (P<0.001, sensitivity 0.79, CI=0.62 to 0.91; specificity 1.00, 95% CI=0.42 to 1.00). Conclusion: A preliminary transcript biomarker panel for the identification of ATAAs using whole blood qRT‐PCR analysis in men and women is presented.

Encapsulating peritoneal sclerosis (EPS) is a devastating complication of peritoneal dialysis (PD), characterized by marked inflammation and severe fibrosis of the peritoneum, and associated with high morbidity and mortality. EPS can occur years after termination of PD and, in severe cases, leads to intestinal obstruction and ileus requiring surgical intervention. Despite ongoing research, the pathogenesis of EPS remains unclear. We performed a global transcriptome analysis of peritoneal tissue specimens from EPS patients, PD patients without EPS, and uremic patients without history of PD or EPS (Uremic). Unsupervised and supervised bioinformatics analysis revealed distinct transcriptional patterns that discriminated these three clinical groups. The analysis identified a signature of 219 genes expressed differentially in EPS as compared to PD and Uremic groups. Canonical pathway analysis of differentially expressed genes showed enrichment in several pathways, including antigen presentation, dendritic cell maturation, B cell development, chemokine signaling and humoral and cellular immunity (P value<0.05). Further interactive network analysis depicted effects of EPS-associated genes on networks linked to inflammation, immunological response, and cell proliferation. Gene expression changes were confirmed by qRT-PCR for a subset of the differentially expressed genes. EPS patient tissues exhibited elevated expression of genes encoding sulfatase1, thrombospondin 1, fibronectin 1 and alpha smooth muscle actin, among many others, while in EPS and PD tissues mRNAs encoding leptin and retinol-binding protein 4 were markedly down-regulated, compared to Uremic group patients. Immunolocalization of Collagen 1 alpha 1 revealed that Col1a1 protein was predominantly expressed in the submesothelial compact zone of EPS patient peritoneal samples, whereas PD patient peritoneal samples exhibited homogenous Col1a1 staining throughout the tissue samples. The results are compatible with the hypothesis that encapsulating peritoneal sclerosis is a distinct pathological process from the simple peritoneal fibrosis that accompanies all PD treatment.

The relaxation response (RR) is the counterpart of the stress response. Millennia-old practices evoking the RR include meditation, yoga and repetitive prayer. Although RR elicitation is an effective therapeutic intervention that counteracts the adverse clinical effects of stress in disorders including hypertension, anxiety, insomnia and aging, the underlying molecular mechanisms that explain these clinical benefits remain undetermined. To assess rapid time-dependent (temporal) genomic changes during one session of RR practice among healthy practitioners with years of RR practice and also in novices before and after 8 weeks of RR training, we measured the transcriptome in peripheral blood prior to, immediately after, and 15 minutes after listening to an RR-eliciting or a health education CD. Both short-term and long-term practitioners evoked significant temporal gene expression changes with greater significance in the latter as compared to novices. RR practice enhanced expression of genes associated with energy metabolism, mitochondrial function, insulin secretion and telomere maintenance, and reduced expression of genes linked to inflammatory response and stress-related pathways. Interactive network analyses of RR-affected pathways identified mitochondrial ATP synthase and insulin (INS) as top upregulated critical molecules (focus hubs) and NF-κB pathway genes as top downregulated focus hubs. Our results for the first time indicate that RR elicitation, particularly after long-term practice, may evoke its downstream health benefits by improving mitochondrial energy production and utilization and thus promoting mitochondrial resiliency through upregulation of ATPase and insulin function. Mitochondrial resiliency might also be promoted by RR-induced downregulation of NF-κB-associated upstream and downstream targets that mitigates stress.

Background: The incidence and mortality of hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) is higher in African Americans (AA) than other racial/ethnic groups in the U.S., but the reasons for this disparity are unknown. There is an urgent need for the discovery of novel molecular signatures for HCV disease progression to understand the underlying biological basis for this cancer rate disparity to improve the clinical outcome. Methods: We performed differential proteomics with isobaric labeling tags for relative and absolute quantitation (iTRAQ) and MS/MS analysis to identify proteins differentially expressed in cirrhotic (CIR) and HCC as compared to normal tissues of Caucasian American (CA) patients. The raw data were analyzed using the ProteinPilot v3.0. Searches were performed against all known sequences populating the Swiss-Prot, Refseq, and TrEMBL databases. Quality control analyses were accomplished using pairwise correlation plots, boxplots, principal component analysis, and unsupervised hierarchical clustering. Supervised analysis was carried out to identify differentially expressed proteins. Candidates were validated in independent cohorts of CA and AA tissues by qRT-PCR or Western blotting. Results: A total of 238 unique proteins were identified. Of those, around 15% were differentially expressed between normal, CIR & HCC groups. Target validation demonstrates racially distinct alteration in the expression of certain proteins. For example, the mRNA expression levels of transferrin (TF) were 2 and18-fold higher in CIR and HCC in AA as compared to CA. Similarly; the expression of Apolipoprotein A1 (APOA1) was 7-fold higher in HCC of AA. This increase was mirrored in the protein expression levels. Interestingly, the level of hepatocyte nuclear factor4α (HNF4α) protein was down regulated in AA, whereas repression of transcription is seen more in CA compared to AA. These data suggest that racial disparities in HCC could be a consequence of differential dysregulation of HNF4α transcriptional activity. Conclusion: This study identifies novel molecular signatures in HCV-induced HCC using iTRAQ-based tissue proteomics. The proteins identified will further enhance a molecular explanation to the biochemical mechanism(s) that may play a role in HCC racial disparities.

Purpose Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification. Experimental Design Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells. Results: A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion. Conclusions: This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets.

The energetic burden of continuously concentrating solutes against gradients along the tubule may render the kidney especially vulnerable to ischemia. Indeed, acute kidney injury (AKI) affects 3% of all hospitalized patients.1,2 Here we show that the mitochondrial biogenesis regulator, PGC1α,3,4 is a pivotal determinant of renal recovery from injury by regulating NAD biosynthesis. Following renal ischemia, PGC1α−/− mice developed local deficiency of the NAD precursor niacinamide (Nam), marked fat accumulation, and failure to re-establish normal function. Remarkably, exogenous Nam improved local NAD levels, fat accumulation, and renal function in post-ischemic PGC1α−/− mice. Inducible tubular transgenic mice (iNephPGC1α) recapitulated the effects of Nam supplementation, including more local NAD and less fat accumulation with better renal function after ischemia. PGC1α coordinately upregulated the enzymes that synthesize NAD de novo from amino acids whereas PGC1α deficiency or AKI attenuated the de novo pathway. Nam enhanced NAD via the enzyme NAMPT and augmented production of the fat breakdown product beta-hydroxybutyrate (β-OHB), leading to increased prostaglandin PGE2, a secreted autocoid that maintains renal function.5 Nam treatment reversed established ischemic AKI and also prevented AKI in an unrelated toxic model. Inhibition of β-OHB signaling or prostaglandins similarly abolished PGC1α-dependent renoprotection. Given the importance of mitochondrial health in aging and the function of metabolically active organs, the results implicate Nam and NAD as key effectors for achieving PGC1α-dependent stress resistance.

Background: Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression. Methods: Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis. Results: Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities. Conclusions: It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0282-3) contains supplementary material, which is available to authorized users.