Publications by authors named "William Bigbee"

The Estonian study of Chernobyl cleanup workers was one of the first investigations to evaluate the possible health consequences of working in the Chernobyl area (the 30 km exclusion zone and/or adjacent territories) after the 1986 reactor accident. The cohort consists of 4831 men who were dispatched in 1986-1991 for tasks involving decontamination, construction of buildings, transport, radiation measurement, guard duty or other activities. By 31 December 2012, the follow-up of the cohort yielded 102 158 person-years of observation.

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Background: CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results: Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins.

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Background: Esophageal adenocarcinoma (EAC) is associated with a dismal prognosis. The identification of cancer biomarkers can advance the possibility for early detection and better monitoring of tumor progression and/or response to therapy. The authors present results from the development of a serum-based, 4-protein (biglycan, myeloperoxidase, annexin-A6, and protein S100-A9) biomarker panel for EAC.

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High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy.

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The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to 'omics'-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength.

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Objective: The biology of high grade serous ovarian carcinoma (HGSOC) is poorly understood. Little has been reported on intratumoral homogeneity or heterogeneity of primary HGSOC tumors and their metastases. We evaluated the global protein expression profiles of paired primary and metastatic HGSOC from formalin-fixed, paraffin-embedded (FFPE) tissue samples.

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Purpose: To determine the global metabolomic profile as measured in circulating plasma from surviving and non-surviving patients with community-acquired pneumonia (CAP) and sepsis.

Methods: Random, outcome-stratified case-control sample from a prospective study of 1,895 patients hospitalized with CAP and sepsis. Cases (n = 15) were adults who died before 90 days, and controls (n = 15) were adults who survived, matched on demographics, infection type, and procalcitonin.

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Regional quantitative analysis of airway morphological abnormalities is of great interest in lung disease investigation. Considering that pulmonary lobes are relatively independent functional unit, we develop and test a novel and efficient computerized scheme in this study to automatically and robustly classify the airways into different categories in terms of pulmonary lobe. Given an airway tree, which could be obtained using any available airway segmentation scheme, the developed approach consists of four basic steps: (1) airway skeletonization or centerline extraction, (2) individual airway branch identification, (3) initial rule-based airway classification/labeling, and (4) self-correction of labeling errors.

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Rationale And Objectives: The airway tree is a primary conductive structure, and airways' morphologic characteristics, or variations thereof, may have an impact on airflow, thereby affecting pulmonary function. The objective of this study was to investigate the correlation between airway tree architecture, as depicted on computed tomography, and pulmonary function.

Materials And Methods: A total of 548 chest computed tomographic examinations acquired on different patients at full inspiration were included in this study.

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We describe an automated computerized scheme to identify pulmonary fissures depicted in chest computed tomography (CT) examinations from a novel perspective. Whereas CT images can be regarded as a cloud of points, the underlying idea is to search for surface-like structures in the three-dimensional (3D) Euclidean space by using an efficient plane fitting algorithm. The proposed plane fitting operation is performed in a number of small spherical lung sub-volumes to detect small planar patches.

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Introduction: Clinical decision making in the setting of computed tomography (CT) screening could benefit from accessible biomarkers that help predict the level of lung cancer risk in high-risk individuals with indeterminate pulmonary nodules.

Methods: To identify candidate serum biomarkers, we measured 70 cancer-related proteins by Luminex xMAP (Luminex Corporation) multiplexed immunoassays in a training set of sera from 56 patients with biopsy-proven primary non-small-cell lung cancer and 56 age-, sex-, and smoking-matched CT-screened controls.

Results: We identified a panel of 10 serum biomarkers-prolactin, transthyretin, thrombospondin-1, E-selectin, C-C motif chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor, receptor tyrosine-protein kinase, erbb-2, cytokeratin fragment 21.

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Background: Computed tomography (CT) scanning has emerged as an effective means of early detection for lung cancer. Despite marked improvement over earlier methodologies, the low level of specificity demonstrated by CT scanning has limited its clinical implementation as a screening tool. A minimally-invasive biomarker-based test that could further characterize CT-positive patients based on risk of malignancy would greatly enhance its clinical efficacy.

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Aberrant interactions between the host and the intestinal bacteria are thought to contribute to the pathogenesis of many digestive diseases. However, studying the complex ecosystem at the human mucosal-luminal interface (MLI) is challenging and requires an integrative systems biology approach. Therefore, we developed a novel method integrating lavage sampling of the human mucosal surface, high-throughput proteomics, and a unique suite of bioinformatic and statistical analyses.

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Expressed prostatic secretion (EPS) is a proximal fluid directly derived from the prostate and, in the case of prostate cancer (PCa), is hypothesized to contain a repertoire of cancer-relevant proteins. Quantitative analysis of the EPS proteome may enable identification of proteins with utility for PCa diagnosis and prognosis. The present investigation demonstrates selective quantitation of proteins in EPS samples from PCa patients using a stable isotope labeled proteome standard (SILAP) generated through the selective harvest of the "secretome" from the PC3 prostate cancer cell line grown in stable isotope labeled cell culture medium.

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We present a novel framework for integrative biomarker discovery from related but separate data sets created in biomarker profiling studies. The framework takes prior knowledge in the form of interpretable, modular rules, and uses them during the learning of rules on a new data set. The framework consists of two methods of transfer of knowledge from source to target data: transfer of whole rules and transfer of rule structures.

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Introduction: Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer and the relatively favorable survival associated with early-stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit.

Methods: We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry in a set of pooled non-small cell lung cancer case sera and matched controls.

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Background: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery.

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Targeted glycoproteomics represents an attractive approach for conducting peripheral blood based cancer biomarker discovery due to the well-known altered pattern of protein glycosylation in cancer and the reduced complexity of the resultant glycoproteome. Here we report its application to a set of pooled nonsmall cell lung cancer (NSCLC) case sera (9 adenocarcinoma and 6 squamous cell carcinoma pools from 54 patients) and matched controls pools, including 8 clinical control pools with computed tomography detected nodules but being nonmalignant as determined by biopsy from 54 patients, and 8 matched healthy control pools from 106 cancer-free subjects. The goal of the study is to discover biomarkers that may enable improved early detection and diagnosis of lung cancer.

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Purpose: Aberrant promoter hypermethylation of tumor suppressor genes is a promising marker for lung cancer detection. We investigated the likelihood of detecting aberrant DNA methylation of tumor suppressor genes in plasma samples of patients with abnormalities of the lung detected upon computed tomography (CT) scan.

Experimental Design: In a small evaluation cohort, four gene promoters (DCC, Kif1a, NISCH, and Rarb) were found to be methylated with increased frequency in samples from cancer patients specifically.

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The effects of maternal cigarette smoking during pregnancy on structural chromosome aberrations were evaluated in peripheral lymphocytes from 239 mothers and their 241 newborns to determine whether smoking during pregnancy, genetic susceptibility, and race are associated with chromosome aberrations including translocations. Demographic information and cigarette smoking data were obtained via questionnaire. There were 119 Caucasian Americans, 118 African Americans, and 2 Asian Americans.

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The identification and eventual application of tumor markers in cancer screening, early detection, diagnosis, and prognosis is a continuing focus of significant translational cancer research. While many new candidate markers have been discovered and at least partly characterized, very few have found widespread clinical application limited presently to the use of CA-125 in ovarian cancer, CEA, primarily in colon cancer, and PSA in prostate cancer screening and patient monitoring. The rapidly emerging field of cancer genomics and proteomics, and their clinical translation as "molecular diagnosis" and "molecular medicine" are already beginning to transform the field, and the accelerating growth of information and technology in this research area will undoubtedly transform the field of tumor markers and their application in the near future leading to improved molecular tools for cancer diagnosis, prognosis, and treatment and ultimately, to the emergence of novel and more effective cancer therapies, including improved approaches for immunotherapy and cancer prevention strategies.

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A previous county mortality study of populations living near two nuclear materials processing and fabrication facilities in Westmoreland and Armstrong counties in Pennsylvania (1950-1995) was extended through 2004. Noncancer mortality (1996-2004) and cancer incidence (1990-2004) were also evaluated. Among the Westmoreland and Armstrong populations, 10,547 cancer deaths occurred during the period 1996 through 2004 and the relative risk (RR) based on comparisons with six demographically similar counties in western Pennsylvania was 0.

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Previous studies of cancer incidence among persons living in municipalities within one mile of two nuclear materials processing and fabrication plants in Pennsylvania were extended for the years 1998-2004. It had been shown that mailing addresses for residents of rural areas often did not reflect the actual municipality of residence and, if not corrected, would bias study results. The previous studies had corrected for this bias.

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Introduction: The importance of alpha-2-glycoprotein 1, zinc (AZGP1) in lung adenocarcinoma (AD) remains largely unknown. Analysis of serum autoantibodies to tumor antigens combined with gene expression profiling of primary tumors may provide insight into the mechanisms underlying lung carcinogenesis and identify new AD biomarkers.

Methods: T7 phage cDNA libraries were used to identify AZGP1 autoantibodies in the serum of 473 patients (192 ADs, 192 matched controls, and 89 additional ADs for confirmation of findings).

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Objective: The aim of this study was to evaluate the feasibility of using novel autoantibody and cancer-related protein arrays to identify potential biomarkers for the early detection of esophageal adenocarcinoma in serum.

Methods: Sera from 18 patients with esophageal adenocarcinoma and 14 with gastroesophageal reflux disease were added to microarrays designed to detect circulating autoantibodies to 51 tumor-associated antigens. Sera from the same patients were also added to a 53-plex assay for various cancer-related proteins.

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