ABSTRACT
BACKGROUND: Uveal melanomas (UM) are rare malignancies in young patients. It is unknown if UM in young patients significantly differs from those in older patients concerning tumor size and localization, metastasis and genetics. The aim of this study was to evaluate the clinical course and tumor characteristics in young patients with UM. MATERIAL AND METHODS: All patients with UM below the age of 32 years who had been treated at our hospital were included in the study. Patient age and sex, duration of symptoms, visual impairment, tumor size and location, genetics, therapy, follow-up interventions and tumor-associated deaths were documented. RESULTS: A total of 57 patients (67 % male, mean age 24.7 years) were included in the study with an average symptomatic course of 5 months. Of the patients 8 (14 %) had an initial visual acuity of ≥ 0.9, 16 (28 %) 0.5-0.8, 22 (39 %) 0.05-0.4 and 9 (16 %) < 0.05 (no data for 2 patients, 4 %). After therapy visual acuity was < 0.05 in 54 % and 53 % of the tumors were choroidal UM (70 % juxtapapillary/circumpapillary), whereas 47 % were ciliochoroidal (54 % with iridociliary involvement). The average tumor size was 12.7 ± 3.6 mm with an average prominence of 6.2 ± 3.2 mm. Genetic evaluation (n = 16) revealed disomy 3 in 64 % and 54 % of the patients received radiotherapy with local application of ruthenium 106. In 46 % of cases follow-up interventions were neccessary including 70 % due to radiogenic retinopathy. CONCLUSION: In young patients UM did not show any preferred localization. The majority of genetically evaluated tumors revealed disomy 3 with no significant correlation to tumor location. Independent of tumor size, location and therapy, approximately half of the patients needed follow-up interventions, predominantly due to radiogenic retinopathy.
Subject(s)
Melanoma/mortality , Melanoma/radiotherapy , Neoplasm Recurrence, Local/mortality , Neoplasm Recurrence, Local/prevention & control , Uveal Neoplasms/mortality , Uveal Neoplasms/radiotherapy , Adolescent , Adult , Age Distribution , Causality , Ciliary Body/pathology , Comorbidity , Disease Progression , Female , Germany/epidemiology , Humans , Iris Neoplasms/mortality , Iris Neoplasms/radiotherapy , Male , Prognosis , Retrospective Studies , Sex Distribution , Survival Rate , Tumor Burden , Vision Disorders , Young AdultSubject(s)
Calcinosis/chemically induced , Choroid/pathology , Hypercalcemia/chemically induced , Scleral Diseases/chemically induced , Scleral Diseases/diagnosis , Vitamin D/adverse effects , Adult , Calcinosis/diagnosis , Calcinosis/therapy , Choroid/drug effects , Diagnosis, Differential , Humans , Hypercalcemia/diagnosis , Hypercalcemia/prevention & control , Male , Scleral Diseases/therapy , SunbathingABSTRACT
SUMMARY: Several programs are now available for analyzing the large datasets arising from cDNA microarray experiments. Most programs are expensive commercial packages or require expensive third party software. Some are freely available to academic researchers, but are limited to one operating system. MicroArray Genome Imaging and Clustering Tool (MAGIC Tool) is an open source program that works on all major platforms, and takes users 'from tiff to gif'. Several unique features of MAGIC Tool are particularly useful for research and teaching. AVAILABILITY: http://www.bio.davidson.edu/MAGIC
Subject(s)
Algorithms , Gene Expression Profiling/methods , Oligonucleotide Array Sequence Analysis/methods , Software , User-Computer Interface , Computer Graphics , Systems IntegrationABSTRACT
Analysis procedures are needed to extract useful information from the large amount of gene expression data that is becoming available. This work describes a set of analytical tools and their application to yeast cell cycle data. The components of our approach are (1) a similarity measure that reduces the number of false positives, (2) a new clustering algorithm designed specifically for grouping gene expression patterns, and (3) an interactive graphical cluster analysis tool that allows user feedback and validation. We use the clusters generated by our algorithm to summarize genome-wide expression and to initiate supervised clustering of genes into biologically meaningful groups.
Subject(s)
Gene Expression Profiling/methods , Algorithms , Cluster Analysis , Computational BiologyABSTRACT
We present a computational scheme to locally align a collection of RNA sequences using sequence and structure constraints. In addition, the method searches for the resulting alignments with the most significant common motifs, among all possible collections. The first part utilizes a simplified version of the Sankoff algorithm for simultaneous folding and alignment of RNA sequences, but maintains tractability by constructing multi-sequence alignments from pairwise comparisons. The algorithm finds the multiple alignments using a greedy approach and has similarities to both CLUSTAL and CONSENSUS, but the core algorithm assures that the pairwise alignments are optimized for both sequence and structure conservation. The choice of scoring system and the method of progressively constructing the final solution are important considerations that are discussed. Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones.
Subject(s)
Computer Simulation , RNA/genetics , Sequence Analysis , Algorithms , Animals , Databases, Factual , HumansABSTRACT
We present a computational scheme to search for the most common motif, composed of a combination of sequence and structure constraints, among a collection of RNA sequences. The method uses a simplified version of the Sankoff algorithm for simultaneous folding and alignment of RNA sequences, but maintains tractability by constructing multi-sequence alignments from pairwise comparisons. The overall method has similarities to both CLUSTAL and CONSENSUS, but the core algorithm assures that the pairwise alignments are optimized for both sequence and structure conservation. Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones.
Subject(s)
Algorithms , RNA/chemistry , RNA/genetics , Sequence Alignment/methods , Base Sequence , Databases, Factual , Molecular Structure , Nucleic Acid Conformation , SoftwareABSTRACT
MOTIVATION: We extend the standard 'Sequence Logo' method of Schneider and Stevens (Nucleic Acids Res., 18, 6097-6100, 1990) to incorporate prior frequencies on the bases, allow for gaps in the alignments, and indicate the mutual information of base-paired regions in RNA. RESULTS: Given an alignment of RNA sequences with the base pairings indicated, the program will calculate the information at each position, including the mutual information of the base pairs, and display the results in a 'Structure Logo'. Alignments without base pairing can also be displayed in a 'Sequence Logo', but still allowing gaps and incorporating prior frequencies if desired. AVAILABILITY: The code is available from, and an Internet server can be used to run the program at, http://www.cbs.dtu.dk/gorodkin/appl/slogo. html.
