Phase 1 trial of nelfinavir added to standard cisplatin chemotherapy with concurrent pelvic radiation for locally advanced cervical cancer.

BACKGROUND: Nelfinavir (NFV), an HIV-1 protease inhibitor, has been shown to sensitize cancer cells to chemoradiation (CRT). The objectives of this phase 1 trial were to evaluate safety and identify the recommended phase 2 dose of NFV added to concurrent CRT for locally advanced cervical cancer. METHODS: Two dose levels of NFV were evaluated: 875 mg orally twice daily (dose level 1 [DL1]) and 1250 mg twice daily (DL2). NFV was initiated 7 days before CRT and continued through CRT completion. Toxicity, radiographic responses, and pathologic responses were evaluated. Serial tumor biopsies (baseline, after NFV monotherapy, on NFV + CRT, and posttreatment) were evaluated by immunohistochemistry, NanoString, and reverse-phase-protein-array analyses. RESULTS: NFV sensitized cervical cancer cells to radiation, increasing apoptosis and tumor suppression in vivo. Patients (n = 13) with International Federation of Gynecology and Obstetrics stage IIA through IVA squamous cell cervical carcinoma were enrolled, including 7 patients at DL1 and 6 patients at DL2. At DL1, expansion to 6 patients was required after a patient developed a dose-limiting toxicity, whereas no dose-limiting toxicities occurred at DL2. Therefore, DL2 was established as the recommended phase 2 dose. All patients at DL2 completed CRT, and 1 of 6 experienced grade 3 or 4 anemia, nausea, and diarrhea. One recurrence was noted at DL2, with disease outside the radiation field. Ten of 11 evaluable patients remained without evidence of disease at a median follow-up of 50 months. NFV significantly decreased phosphorylated Akt levels in tumors. Cell cycle and cancer pathways also were reduced by NFV and CRT. CONCLUSIONS: NFV with CRT is well tolerated. The response rate is promising compared with historic controls in this patient population and warrants further investigation.

DNA-Encoded Glutamine Synthetase Enzyme as Ammonia-Lowering Therapeutic for Hyperammonemia.

Hyperammonemia is a dangerous life-threatening metabolic complication characterized by markedly elevated ammonia levels that can lead to irreversible brain damage if not carefully monitored. Current pharmacological treatment strategies available for hyperammonemia patients are suboptimal and associated with major side effects. In this study, we focus on developing and evaluating the in vivo delivery of novel DNA-encoded glutamine synthetase (GS) enzymes for the treatment of hyperammonemia. Direct in vivo delivered DNA-encoded GS enzyme was evaluated in ammonium acetate-induced hyperammonemia and thioacetamide-induced acute liver injury (ALI) models in C57BL/6 mice. In ammonium acetate-induced hyperammonemia model, we achieved a 30.5% decrease in blood ammonia levels 15 min postadministration of ammonium acetate, with DNA-encoded GS-treated group. Significant increase in survival was observed in ALI model with the treated mice. A comparison of the secreted versus intracellular DNA-encoded GS enzyme demonstrated similar increases in survival in the ALI model, with 40% mortality in the secreted enzymes and 30% mortality in the intracellular enzymes, as compared with 90% mortality in the control group. Direct in vivo delivery of DNA-encoded GS demonstrated important ammonia-lowering potential. These results provide the initial steps toward development of delivered DNA as a potential new approach to ammonia-lowering therapeutics.

Synthetic DNA Delivery of an Engineered Arginase Enzyme Can Modulate Specific Immunity In Vivo.

Arginase is a complex and unique enzyme that plays diverse roles in health and disease. By metabolizing arginine, it can shape the outcome of innate and adaptive immune responses. The immunomodulatory capabilities of arginase could potentially be applied for local immunosuppression or induction of immune tolerance. With the use of an enhanced DNA delivery approach, we designed and studied a DNA-encoded secretable arginase enzyme as a tool for immune modulation and evaluated its immunomodulatory function in vivo. Strong immunosuppression of cluster of differentiation 4 (CD4) and CD8 T cells, as well as macrophages and dendritic cells, was observed in vitro in the presence of an arginase-rich supernatant. To further evaluate the efficacy of DNA-encoded arginase on in vivo immunosuppression against an antigen, a cancer antigen vaccine model was used in the presence or absence of DNA-encoded arginase. Significant in vivo immunosuppression was observed in the presence of DNA-encoded arginase. The efficacy of this DNA-encoded arginase delivery was examined in a local, imiquimod-induced, psoriasis-like, skin-inflammation model. Pretreatment of animals with the synthetic DNA-encoded arginase led to significant decreases in skin acanthosis, proinflammatory cytokines, and costimulatory molecules in extracted macrophages and dendritic cells. These results draw attention to the potential of direct in vivo-delivered arginase to function as an immunomodulatory agent for treatment of local inflammation or autoimmune diseases.

Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME.

In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over time and several researchers have incorporated SVM-RCE into their studies, resulting in a substantial number of scientific publications. This increased interest encouraged us to reconsider how feature selection, particularly in biological datasets, can benefit from considering the relationships of those genes in the selection process, this led to our development of SVM-RCE-R. The usefulness of SVM-RCE-R is further supported by development of maTE tool, which uses a similar approach to identify microRNA (miRNA) targets. We have now implemented the SVM-RCE-R algorithm in Knime in order to make it easier to apply and to make it more accessible to the biomedical community. The use of SVM-RCE-R in Knime is simple and intuitive, allowing researchers to immediately begin their data analysis without having to consult an information technology specialist. The input for the Knime tool is an EXCEL file (or text or CSV) with a simple structure and the output is also an EXCEL file. The Knime version also incorporates new features not available in the previous version. One of these features is a user-specific ranking function that enables the user to provide the weights of the accuracy, sensitivity, specificity, f-measure, area under curve and precision in the ranking function, allowing the user to select for greater sensitivity or greater specificity as needed. The results show that the ranking function has an impact on the performance of SVM-RCE-R. Some of the clusters that achieve high scores for a specified ranking can also have high scores in other metrics. This finding motivates future studies to suggest the optimal ranking function.

A Gene Expression Classifier from Whole Blood Distinguishes Benign from Malignant Lung Nodules Detected by Low-Dose CT.

Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests. In this study, we have developed a pulmonary nodule classifier (PNC) using RNA from whole blood collected in RNA-stabilizing PAXgene tubes that addresses this need. Samples were prospectively collected from high-risk and incidental subjects with a positive lung CT scan. A total of 821 samples from 5 clinical sites were analyzed. Malignant samples were predominantly stage 1 by pathologic diagnosis and 97% of the benign samples were confirmed by 4 years of follow-up. A panel of diagnostic biomarkers was selected from a subset of the samples assayed on Illumina microarrays that achieved a ROC-AUC of 0.847 on independent validation. The microarray data were then used to design a biomarker panel of 559 gene probes to be validated on the clinically tested NanoString nCounter platform. RNA from 583 patients was used to assess and refine the NanoString PNC (nPNC), which was then validated on 158 independent samples (ROC-AUC = 0.825). The nPNC outperformed three clinical algorithms in discriminating malignant from benign pulmonary nodules ranging from 6-20 mm using just 41 diagnostic biomarkers. Overall, this platform provides an accurate, noninvasive method for the diagnosis of pulmonary nodules in patients with non-small cell lung cancer. SIGNIFICANCE: These findings describe a minimally invasive and clinically practical pulmonary nodule classifier that has good diagnostic ability at distinguishing benign from malignant pulmonary nodules.

Circulating microRNA Signatures in Rodent Models of Pain.

MicroRNAs (miRNAs) remain stable in circulation and have been identified as potential biomarkers for a variety of conditions. We report miRNA changes in blood from multiple rodent models of pain, including spinal nerve ligation and spared nerve injury models of neuropathic pain; a complete Freund's adjuvant (CFA) model of inflammatory pain; and a chemotherapy-induced model of pain using the histone deacetylase inhibitor JNJ-26481585. The effect of celecoxib, a cyclooxygenase-2-selective nonsteroidal anti-inflammatory drug, was investigated in the CFA model as proof of principle for assessing the utility of circulating miRNAs as biomarkers in determining treatment response. Each study resulted in a unique miRNA expression profile. Despite differences in miRNAs identified from various models, computational target prediction and functional enrichment have identified biological pathways common among different models. The Wnt signaling pathway was affected in all models, suggesting a crucial role for this pathway in the pathogenesis of pain. Our studies demonstrate the utility of circulating miRNAs as pain biomarkers and suggest the potential for rigorous forward and reverse translational approaches. Evaluating alterations in miRNA fingerprints under different pain conditions and after administering therapeutic agents may be beneficial in evaluating clinical trial outcomes, predicting treatment response, and developing correlational outcomes between preclinical and human studies.

Analgesic Response to Intravenous Ketamine Is Linked to a Circulating microRNA Signature in Female Patients With Complex Regional Pain Syndrome.

Although ketamine is beneficial in treating complex regional pain syndrome (CRPS), a subset of patients respond poorly to therapy. We investigated treatment-induced microRNA (miRNA) changes and their predictive validity in determining treatment outcome by assessing miRNA changes in whole blood from patients with CRPS. Blood samples from female patients were collected before and after 5 days of intravenous ketamine administration. Seven patients were responders and 6 were poor responders. Differential miRNA expression was observed in whole blood before and after treatment. In addition, 33 miRNAs differed between responders and poor responders before therapy, suggesting the predictive utility of miRNAs as biomarkers. Investigation of the mechanistic significance of hsa-miR-548d-5p downregulation in poor responders showed that this miRNA can downregulate UDP-glucuronosyltransferase UGT1A1 mRNA. Poor responders had a higher conjugated/unconjugated bilirubin ratio, indicating increased UGT1A1 activity. We propose that lower pretreatment levels of miR-548d-5p may result in higher UDP-GT activity, leading to higher levels of inactive glucuronide conjugates, thereby minimizing the therapeutic efficacy of ketamine in poor responders. Differences in miRNA signatures can provide molecular insights distinguishing responders from poor responders. Extending this approach to other treatment and outcome assessments might permit stratification of patients for maximal therapeutic outcome. Perspective: This study suggests the usefulness of circulating miRNAs as potential biomarkers. Assessing miRNA signatures before and after treatment demonstrated miRNA alterations from therapy; differences in miRNA signature in responders and poor responders before therapy indicate prognostic value. Mechanistic studies on altered miRNAs can provide new insights into disease.

Functional significance of macrophage-derived exosomes in inflammation and pain.

Exosomes, secreted microvesicles transporting microRNAs (miRNAs), mRNAs, and proteins through bodily fluids, facilitate intercellular communication and elicit immune responses. Exosomal contents vary, depending on the source and the physiological conditions of cells, and can provide insights into how cells and systems cope with physiological perturbations. Previous analysis of circulating miRNAs in patients with complex regional pain syndrome (CRPS), a debilitating chronic pain disorder, revealed a subset of miRNAs in whole blood that are altered in the disease. To determine functional consequences of alterations in exosomal biomolecules in inflammation and pain, we investigated exosome-mediated information transfer in vitro, in a rodent model of inflammatory pain, and in exosomes from patients with CRPS. Mouse macrophage cells stimulated with lipopolysaccharides secrete exosomes containing elevated levels of cytokines and miRNAs that mediate inflammation. Transcriptome sequencing of exosomal RNA revealed global alterations in both innate and adaptive immune pathways. Exosomes from lipopolysaccharide-stimulated cells were sufficient to cause nuclear factor-κB activation in naive cells, indicating functionality in recipient cells. A single injection of exosomes attenuated thermal hyperalgesia in a murine model of inflammatory pain, suggesting an immunoprotective role for macrophage-derived exosomes. Macrophage-derived exosomes carry a protective signature that is altered when secreting cells are exposed to an inflammatory stimulus. We also show that circulating miRNAs altered in patients with complex regional pain syndrome are trafficked by exosomes. With their systemic signaling capabilities, exosomes can induce pleiotropic effects potentially mediating the multifactorial pathology underlying chronic pain, and should be explored for their therapeutic utility.

A novel method for the normalization of microRNA RT-PCR data.

BACKGROUND: MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate mRNA transcript levels and translation. Deregulation of microRNAs is indicated in a number of diseases and microRNAs are seen as a promising target for biomarker identification and drug development. miRNA expression is commonly measured by microarray or real-time polymerase chain reaction (RT-PCR). The findings of RT-PCR data are highly dependent on the normalization techniques used during preprocessing of the Cycle Threshold readings from RT-PCR. Some of the commonly used endogenous controls themselves have been discovered to be differentially expressed in various conditions such as cancer, making them inappropriate internal controls. METHODS: We demonstrate that RT-PCR data contains a systematic bias resulting in large variations in the Cycle Threshold (CT) values of the low-abundant miRNA samples. We propose a new data normalization method that considers all available microRNAs as endogenous controls. A weighted normalization approach is utilized to allow contribution from all microRNAs, weighted by their empirical stability. RESULTS: The systematic bias in RT-PCR data is illustrated on a microRNA dataset obtained from primary cutaneous melanocytic neoplasms. We show that through a single control parameter, this method is able to emulate other commonly used normalization methods and thus provides a more general approach. We explore the consistency of RT-PCR expression data with microarray expression by utilizing a dataset where both RT-PCR and microarray profiling data is available for the same miRNA samples. CONCLUSIONS: A weighted normalization method allows the contribution of all of the miRNAs, whether they are highly abundant or have low expression levels. Our findings further suggest that the normalization of a particular miRNA should rely on only miRNAs that have comparable expression levels.

Weighted set enrichment of gene expression data.

BACKGROUND: Sets of genes that are known to be associated with each other can be used to interpret microarray data. This gene set approach to microarray data analysis can illustrate patterns of gene expression which may be more informative than analyzing the expression of individual genes. Various statistical approaches exist for the analysis of gene sets. There are three main classes of these methods: over-representation analysis, functional class scoring, and pathway topology based methods. METHODS: We propose weighted hypergeometric and weighted chi-squared methods in order to assign a rank to the degree to which each gene participates in the enrichment. Each gene is assigned a weight determined by the absolute value of its log fold change, which is then raised to a certain power. The power value can be adjusted as needed. Datasets from the Gene Expression Omnibus are used to test the method. The significantly enriched pathways are validated through searching the literature in order to determine their relevance to the dataset. RESULTS: Although these methods detect fewer significantly enriched pathways, they can potentially produce more relevant results. Furthermore, we compare the results of different enrichment methods on a set of microarray studies all containing data from various rodent neuropathic pain models. DISCUSSION: Our method is able to produce more consistent results than other methods when evaluated on similar datasets. It can also potentially detect relevant pathways that are not identified by the standard methods. However, the lack of biological ground truth makes validating the method difficult.

Protein surface representation and analysis by dimension reduction.

BACKGROUND: Protein structures are better conserved than protein sequences, and consequently more functional information is available in structures than in sequences. However, proteins generally interact with other proteins and molecules via their surface regions and a backbone-only analysis of protein structures may miss many of the functional and evolutionary features. Surface information can help better elucidate proteins' functions and their interactions with other proteins. Computational analysis and comparison of protein surfaces is an important challenge to overcome to enable efficient and accurate functional characterization of proteins. METHODS: In this study we present a new method for representation and comparison of protein surface features. Our method is based on mapping the 3-D protein surfaces onto 2-D maps using various dimension reduction methods. We have proposed area and neighbor based metrics in order to evaluate the accuracy of this surface representation. In order to capture functionally relevant information, we encode geometric and biochemical features of the protein, such as hydrophobicity, electrostatic potential, and curvature, into separate color channels in the 2-D map. The resulting images can then be compared using efficient 2-D image registration methods to identify surface regions and features shared by proteins. RESULTS: We demonstrate the utility of our method and characterize its performance using both synthetic and real data. Among the dimension reduction methods investigated, SNE, LandmarkIsomap, Isomap, and Sammon's mapping provide the best performance in preserving the area and neighborhood properties of the original 3-D surface. The enriched 2-D representation is shown to be useful in characterizing the functional site of chymotrypsin and able to detect structural similarities in heat shock proteins. A texture mapping using the 2-D representation is also proposed as an interesting application to structure visualization.

MicroRNA modulation in complex regional pain syndrome.

BACKGROUND: Aberrant expression of small noncoding RNAs called microRNAs (miRNAs) is a common feature of several human diseases. The objective of the study was to identify miRNA modulation in patients with complex regional pain syndrome (CRPS) a chronic pain condition resulting from dysfunction in the central and/or peripheral nervous systems. Due to a multitude of inciting pathologies, symptoms and treatment conditions, the CRPS patient population is very heterogeneous. Our goal was to identify differentially expressed miRNAs in blood and explore their utility in patient stratification. METHODS: We profiled miRNAs in whole blood from 41 patients with CRPS and 20 controls using TaqMan low density array cards. Since neurogenic inflammation is known to play a significant role in CRPS we measured inflammatory markers including chemokines, cytokines, and their soluble receptors in blood from the same individuals. Correlation analyses were performed for miRNAs, inflammatory markers and other parameters including disease symptoms, medication, and comorbid conditions. RESULTS: Three different groups emerged from miRNA profiling. One group was comprised of 60% of CRPS patients and contained no control subjects. miRNA profiles from the remaining patients were interspersed among control samples in the other two groups. We identified differential expression of 18 miRNAs in CRPS patients. Analysis of inflammatory markers showed that vascular endothelial growth factor (VEGF), interleukin1 receptor antagonist (IL1Ra) and monocyte chemotactic protein-1 (MCP1) were significantly elevated in CRPS patients. VEGF and IL1Ra showed significant correlation with the patients reported pain levels. Analysis of the patients who were clustered according to their miRNA profile revealed correlations that were not significant in the total patient population. Correlation analysis of miRNAs detected in blood with additional parameters identified miRNAs associated with comorbidities such as headache, thyroid disorder and use of narcotics and antiepileptic drugs. CONCLUSIONS: miRNA profiles can be useful in patient stratification and have utility as potential biomarkers for pain. Differentially expressed miRNAs can provide molecular insights into gene regulation and could lead to new therapeutic intervention strategies for CRPS.