Publications by authors named "Roger S Day"

Purpose: Despite an explosion of translational research to exploit biomarkers in diagnosis, prediction and prognosis, the impact of biomarkers on clinical practice has been limited. The elusiveness of clinical utility may partly originate when validation studies are planned, from a failure to articulate precisely how the biomarker, if successful, will improve clinical decision-making for patients. Clarifying what performance would suffice if the test is to improve medical care makes it possible to design meaningful validation studies.

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Data quality is a recognized problem for high-throughput genomics platforms, as evinced by the proliferation of methods attempting to filter out lower quality data points. Different filtering methods lead to discordant results, raising the question, which methods are best? Astonishingly, little computational support is offered to analysts to decide which filtering methods are optimal for the research question at hand. To evaluate them, we begin with a pair of expression data sets, transcriptomic and proteomic, on the same samples.

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The cancer stem cell hypothesis is that in human solid cancers, only a small proportion of the cells, the cancer stem cells (CSCs), are self-renewing; the vast majority of the cancer cells are unable to sustain tumor growth indefinitely on their own. In recent years, discoveries have led to the concentration, if not isolation, of putative CSCs. The evidence has mounted that CSCs do exist and are important.

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Background: In bioinformatics, we pre-process raw data into a format ready for answering medical and biological questions. A key step in processing is labeling the measured features with the identities of the molecules purportedly assayed: "molecular identification" (MI). Biological meaning comes from identifying these molecular measurements correctly with actual molecular species.

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Estrogen regulates over a thousand genes, with an equal number of them being induced or repressed. The distinct mechanisms underlying these dual transcriptional effects remain largely unknown. We derived comprehensive views of the transcription machineries assembled at estrogen-responsive genes through integrating multiple types of genomic data.

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DNA repair and cell cycle control play an important role in the repair of DNA damage caused by cigarette smoking. Given this role, functionally relevant single nucleotide polymorphisms (SNPs) in genes in these pathways may well affect the risk of smoking-related lung cancer. We examined the relationship between 240 SNPs in DNA repair and cell cycle control pathway genes and lung cancer risk in a case-control study of white current and ex-cigarette smokers (722 cases and 929 controls).

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Background: Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms.

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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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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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Background: In Phase II clinical trials in cancer, preventing the treatment of patients on a study when current data demonstrate that the treatment is insufficiently active or too toxic has obvious benefits, both in protecting patients and in reducing sponsor costs. Considerable efforts have gone into experimental designs for Phase II clinical trials with flexible sample size, usually implemented by early stopping rules. The intended benefits will not ensue, however, if the design is not followed.

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A clinical trial should never accrue a patient when the data collected to date indicate that this accrual could be unethical. An interim monitoring plan is a crude tool written into protocols to provide this assurance. At the University of Pittsburgh Cancer Institute, we have designed a software architecture to automate interim monitoring, acting appropriately when information required to determine whether a stopping criterion is fulfilled is missing.

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Concerns about bioterrorism and influenza have focused attention on identifying novel data sources to enhance public health surveillance. The authors evaluated free Pittsburgh Post-Gazette Internet death notices for Allegheny County, Pennsylvania, as a potentially timely source of mortality data. Data abstracted from Internet death notices for 1998-2001 were compared with mortality records from the Pennsylvania Department of Health.

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Background: Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available.

Principal Findings: We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations.

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Overview: Simulation, both physical and computer-based, has a rich history in support of medical education. Essentially all these efforts have been aimed at instilling concrete measurable skills, akin to vocational training. They present learners with choices, facilitating a degree of learning by doing.

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Objective: A training workshop for cancer clinical trials was developed utilizing a computer simulation encompassing cancer biology, metabolism, adverse effects, and clinical trial design.

Method: Fourth-year medical students in a neoplasia elective course participated. The workshop was structured to maximize group discussions and interactions.

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Purpose: Preclinical data indicate that progestational agents (progesterone, medroxyprogesterone acetate and megestrol acetate) interact with p-glycoprotein (P-gp) and reverse P-gp-associated resistance to vinca alkaloids and other natural products. Based on these data, we performed a phase I study of high-dose oral megestrol acetate and vinblastine to evaluate the safety of this regimen.

Patients And Methods: Enrolled in the study were 61 patients with advanced solid tumors, refractory to standard therapy.

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