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Biomedical subjects

Kevin R Coombes

Publications and source records attributed to Kevin R Coombes.

6 recordsLinked to original sources
PubMed2024

Extracellular Vesicle- MDM2 -DNA as a Potential Liquid Biopsy Biomarker for Disease Identification in Retroperitoneal Liposarcoma.

OBJECTIVE: We aimed to assess the levels of MDM2 -DNA within extracellular vesicles (EVs) isolated from the serum of retroperitoneal liposarcoma (RLS) patients versus healthy donors, as well as within the same patients at the time of surgery versus postoperative surveillance visits. To determine whether EV- MDM2 may serve as a possible first-ever biomarker of liposarcoma recurrence. BACKGROUND: A hallmark of well-differentiated and dedifferentiated (WD/DD) retroperitoneal liposarcoma is elevated MDM2 due to genome amplification, with recurrence rates of >50% even after complete resection. Imaging technologies frequently cannot resolve recurrent WD/DD-RLS versus postoperative scarring. Early detection of recurrent lesions, for which biomarkers are lacking, would guide surveillance and treatment decisions. METHODS: WD/DD-RLS serum samples were collected both at the time of surgery and during follow-up visits from 42 patients, along with sera from healthy donors (n=14). EVs were isolated, DNA purified, and MDM2 -DNA levels determined through q-PCR analysis. Nonparametric tests were employed to compare EV- MDM2 DNA levels from patients versus the control group, as well as the time of surgery versus postsurgery conditions. RESULTS: EV -MDM2 levels were significantly higher in WD/DD-RLS than controls ( P =0.00085). Moreover, EV- MDM2 levels were remarkably decreased in WD/DD-RLS patients after resection ( P =0.00036), reaching values comparable to control group ( P =0.124). During postoperative surveillance, significant increases of EV- MDM2 were observed in some patients, correlating with computed tomography scan evidence of recurrent or persistent postresection disease. CONCLUSIONS: Serum EV- MDM2 may serve as a potential biomarker of early recurrent or postoperatively persistent WD/DD-RLS, a disease currently lacking such determinants.

Humans↗
PubMed2003

High expression of activation-induced cytidine deaminase (AID) and splice variants is a distinctive feature of poor-prognosis chronic lymphocytic leukemia.

In chronic lymphocytic leukemia (CLL), analysis of immunoglobulin heavy chain variable regions for somatic hypermutation identifies 2 prognostic subsets, mutated and unmutated. Investigators have postulated that unmutated and mutated CLL arises from malignant transformation of pre- and post-germinal center (GC) B cells, respectively. Alternatively, unmutated cases may arise from B cells stimulated by T-cell-independent antigens or from GC B cells with inactive somatic hypermutation. Activation-induced cytidine deaminase (AID), a protein essential for somatic hypermutation, is expressed by GC B cells in which this process occurs. We investigated AID mRNA expression in 20 CLL cases. In 8 cases we detected high expression of wild-type AID mRNA and 2 splice variants; in 12 cases and 5 normal peripheral blood B-cell samples we detected no expression using standard conditions. Of 8 CLL cases that highly expressed AID, 7 were unmutated, suggesting that this subset may arise from GC-experienced B cells with inactive somatic hypermutation, and may predict prognosis.

Alternative Splicing↗
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

Obtaining reliable information from minute amounts of RNA using cDNA microarrays.

BACKGROUND: High density cDNA microarray technology provides a powerful tool to survey the activity of thousands of genes in normal and diseased cells, which helps us both to understand the molecular basis of the disease and to identify potential targets for therapeutic intervention. The promise of this technology has been hampered by the large amount of biological material required for the experiments (more than 50 microg of total RNA per array). We have modified an amplification procedure that requires only 1 microg of total RNA. Analyses of the results showed that most genes that were detected as expressed or differentially expressed using the regular protocol were also detected using the amplification protocol. In addition, many genes that were undetected or weakly detected using the regular protocol were clearly detected using the amplification protocol. We have carried out a series of confirmation studies by northern blotting, western blotting, and immunohistochemistry assays. RESULTS: Our results showed that most of the new information revealed by the amplification protocol represents real gene activity in the cells. CONCLUSION: We have confirmed a powerful and consistent cDNA microarray procedure that can be used to study minute amounts of biological tissue.

Journal Article↗
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↗