Correlogic Systems Inc.

Germantown, MD, United States

Correlogic Systems Inc.

Germantown, MD, United States
Time filter
Source Type

Yip P.,Correlogic Systems Inc. | Chen T.-H.,Correlogic Systems Inc. | Seshaiah P.,Correlogic Systems Inc. | Stephen L.L.,Rules-Based Medicine, Inc. | And 6 more authors.
PLoS ONE | Year: 2011

FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC = 0.933) and CA-125 (AUC = 0.907) were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800). To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912). Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the detection of ovarian cancer. © 2011 Yip et al.

Chou J.Y.,U.S. National Institutes of Health | Jun H.S.,U.S. National Institutes of Health | Mansfield B.C.,U.S. National Institutes of Health | Mansfield B.C.,Correlogic Systems Inc
Current Opinion in Hematology | Year: 2010

Purpose of review: Glycogen storage disease type Ib, characterized by disturbed glucose homeostasis, neutropenia, and neutrophil dysfunction, is caused by a deficiency in a ubiquitously expressed glucose-6-phosphate transporter (G6PT). G6PT translocates glucose-6-phosphate (G6P) from the cytoplasm into the lumen of the endoplasmic reticulum, in which it is hydrolyzed to glucose either by a liver/kidney/intestine-restricted glucose-6-phosphatase- α (G6Pase-α) or by a ubiquitously expressed G6Pase-β. The role of the G6PT/G6Pase-α complex is well established and readily explains why G6PT disruptions disturb interprandial blood glucose homeostasis. However, the basis for neutropenia and neutrophil dysfunction in glycogen storage disease type Ib is poorly understood. Recent studies that are now starting to unveil the mechanisms are presented in this review. Recent findings: Characterization of G6Pase-β and generation of mice lacking either G6PT or G6Pase-β have shown that neutrophils express the G6PT/G6Pase-β complex capable of producing endogenous glucose. Loss of G6PT activity leads to enhanced endoplasmic reticulum stress, oxidative stress, and apoptosis that underlie neutropenia and neutrophil dysfunction in glycogen storage disease type Ib. Summary: Neutrophil function is intimately linked to the regulation of glucose and G6P metabolism by the G6PT/G6Pase-β complex. Understanding the molecular mechanisms that govern energy homeostasis in neutrophils has revealed a previously unrecognized pathway of intracellular G6P metabolism in neutrophils. © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Chou J.Y.,U.S. National Institutes of Health | Mansfield B.C.,U.S. National Institutes of Health | Mansfield B.C.,Correlogic Systems Inc.
Expert Opinion on Biological Therapy | Year: 2011

Introduction: Glycogen storage disease (GSD) type Ia and Ib are disorders of impaired glucose homeostasis affecting the liver and kidney. GSD-Ib also affects neutrophils. Current dietary therapies cannot prevent long-term complications. In animal studies, recombinant adeno-associated virus (rAAV) vector-mediated gene therapy can correct or minimize multiple aspects of the disorders, offering hope for human gene therapy. Areas covered: A summary of recent progress in rAAV-mediated gene therapy for GSD-I; strategies to improve rAAV-mediated gene delivery, transduction efficiency and immune avoidance; and vector refinements that improve expression. Expert opinion: rAAV-mediated gene delivery to the liver can restore glucose homeostasis in preclinical models of GSD-I, but some long-term complications of the liver and kidney remain. Gene therapy for GSD-Ib is less advanced than for GSD-Ia and only transient correction of myeloid dysfunction has been achieved. A question remains as to whether a single rAAV vector can meet the expression efficiency and tropism required to treat all aspects of GSD-I, or if a multi-pronged approach is needed. An understanding of the strengths and weaknesses of rAAV vectors in the context of strategies to achieve efficient transduction of the liver, kidney and hematopoietic stem cells is required for treating GSD-I. © 2011 Informa UK, Ltd.

PubMed | Correlogic Systems Inc
Type: Journal Article | Journal: Journal of clinical oncology : official journal of the American Society of Clinical Oncology | Year: 2016

9545 Background: Serum profiling may detect malignant disease. Low volume, high resolution mass spectrometry is capable of generating high complexity spectral profiles of the serum. Combined with powerful data-mining algorithms, coordinated changes in multiple serum species can be correlated with malignancy.691 serum samples were analyzed: 32 women with no breast disease; 659 women with breast abnormalities (clinical or radiologic) made up of 204 benign non-neoplastic conditions; 111 benign neoplastic conditions; 24 atypical ductal hyperplasia only; 234 invasive cancer; 86 in situ CA, (61 DCIS and 25 LCIS). All sera were collected prior to biopsy, and processed promptly by a standard protocol. Individual diagnosis was based on pathology of tissue biopsy. Sera were analyzed on an ABI QSTAR time-of-flight mass spectrometer equipped with an Advion Nanomate System. Spectra obtained were used to build models using the Correlogic Systems Inc. ProteomeQuest software which combines lead cluster mapping with a genetic algorithm to identify patterns predictive of disease status. We held an independent set of spectra files out from model development as a blinded validation set to emulate a clinical setting.A number of models were created which demonstrated sensitivities and specificities in the range of 80 - 90% on the blinded validation set. We identified three regions in the spectra that together contain at least 8 m/z features, which are very powerful in discriminating between invasive cancer and non-malignant conditions. Singly, the features are not very informative, but combined in a multi-dimensional model to reflect coordinated changes in the serum, the features are highly predictive of disease. One model, combining 10 features yielded 98.5% specificity (95% CI 95.2 - 99.6%) and 90.3% sensitivity (95% CI 82.4 - 95%) on a testing set of 196 non-malignant sera and 103 invasive sera, which dropped to 92% specificity (95% CI 74.5 - 93.6%) and 86% sensitivity (95% CI 76.4 - 97.8%) on a truly blinded validation set of 54 non-malignant and 41 invasive sera.Serum profiling using this technology and algorithm is reasonably accurate in classifying women with breast abnormalities prior to undergoing biopsy. Results support a larger study of these models. [Table: see text].

Correlogic Systems Inc. | Date: 2013-09-11

Methods are provided for predicting the presence, subtype and stage of ovarian cancer, as well as for assessing the therapeutic efficacy of a cancer treatment and determining whether a subject potentially is developing cancer. Associated test kits, computer and analytical systems as well as software and diagnostic models are also provided.

Loading Correlogic Systems Inc. collaborators
Loading Correlogic Systems Inc. collaborators