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Biomedical subjects

Keith A Baggerly

Publications and source records attributed to Keith A Baggerly.

5 recordsLinked to original sources
PubMed2017

Surface PD-L1, E-cadherin, CD24, and VEGFR2 as markers of epithelial cancer stem cells associated with rapid tumorigenesis.

Cancer cells require both migratory and tumorigenic property to establish metastatic tumors outside the primary microenvironment. Identifying the characteristic features of migratory cancer stem cells with tumorigenic property is important to predict patient prognosis and combat metastasis. Here we established one epithelial and two mesenchymal cell lines from ascites of a bladder cancer patient (i.e. cells already migrated outside primary tumor). Analyses of these cell lines demonstrated that the epithelial cells with surface expression of PD-L1, E-cadherin, CD24, and VEGFR2 rapidly formed tumors outside the primary tumor microenvironment in nude mice, exhibited signatures of immune evasion, increased stemness, increased calcium signaling, transformation, and novel E-cadherin-RalBP1 interaction. The mesenchymal cells on the other hand, exhibited constitutive TGF-β signaling and were less tumorigenic. Hence, targeting epithelial cancer stem cells with rapid tumorigenesis signatures in future might help to combat metastasis.

B7-H1 Antigen↗
PubMed2003

Differential expression in SAGE: accounting for normal between-library variation.

MOTIVATION: In contrasting levels of gene expression between groups of SAGE libraries, the libraries within each group are often combined and the counts for the tag of interest summed, and inference is made on the basis of these larger 'pseudolibraries'. While this captures the sampling variability inherent in the procedure, it fails to allow for normal variation in levels of the gene between individuals within the same group, and can consequently overstate the significance of the results. The effect is not slight: between-library variation can be hundreds of times the within-library variation. RESULTS: We introduce a beta-binomial sampling model that correctly incorporates both sources of variation. We show how to fit the parameters of this model, and introduce a test statistic for differential expression similar to a two-sample t-test.

Algorithms↗
PubMed2003

A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples.

For our analysis of the data from the First Annual Proteomics Data Mining Conference, we attempted to discriminate between 24 disease spectra (group A) and 17 normal spectra (group B). First, we processed the raw spectra by (i) correcting for additive sinusoidal noise (periodic on the time scale) affecting most spectra, (ii) correcting for the overall baseline level, (iii) normalizing, (iv) recombining fractions, and (v) using variable-width windows for data reduction. Also, we identified a set of polymeric peaks (at multiples of 180.6 Da) that is present in several normal spectra (B1-B8). After data processing, we found the intensities at the following mass to charge (m/z) values to be useful discriminators: 3077, 12 886 and 74 263. Using these values, we were able to achieve an overall classification accuracy of 38/41 (92.6%). Perfect classification could be achieved by adding two additional peaks, at 2476 and 6955. We identified these values by applying a genetic algorithm to a filtered list of m/z values using Mahalanobis distance between the group means as a fitness function.

Blood Proteins↗
PubMed2002

Steps toward mapping the human vasculature by phage display.

The molecular diversity of receptors in human blood vessels remains largely unexplored. We developed a selection method in which peptides that home to specific vascular beds are identified after administration of a peptide library. Here we report the first in vivo screening of a peptide library in a patient. We surveyed 47,160 motifs that localized to different organs. This large-scale screening indicates that the tissue distribution of circulating peptides is nonrandom. High-throughput analysis of the motifs revealed similarities to ligands for differentially expressed cell-surface proteins, and a candidate ligand-receptor pair was validated. These data represent a step toward the construction of a molecular map of human vasculature and may have broad implications for the development of targeted therapies.

Blood Vessels↗
PubMed2002

Identifying and quantifying sources of variation in microarray data using high-density cDNA membrane arrays.

Microarray experiments involve many steps, including spotting cDNA, extracting RNA, labeling targets, hybridizing, scanning, and analyzing images. Each step introduces variability, confounding our ability to obtain accurate estimates of the biological differences between samples. We ran repeated experiments using high-density cDNA microarray membranes (Research Genetics Human GeneFilters Microarrays Version I) and 33P-labeled targets. Total RNA was extracted from a Burkitt lymphoma cell line (GA-10). We estimated the components of variation coming from: (1) image analysis, (2) exposure time to PhosphorImager screens, (3) differences in membranes, (4) reuse of membranes, and (5) differences in targets prepared from two independent RNA extractions. Variation was assessed qualitatively using a clustering algorithm and quantitatively using a version of ANOVA adapted to multivariate microarray data. The largest contribution to variation came from reusing membranes, which contributed 38% of the total variation. Differences in membranes and in exposure time each contributed about 10%. Differences in target preparations contributed less than 5%. The effect of image quantification was negligible. Much of the effect from reusing membranes was attributable to increasing levels of background radiation and can be reduced by using membranes at most four times. The effects of exposure time, which were partly attributable to variation in the scanning process, can be minimized by using the same exposure time for all experiments.

Algorithms↗