Abstract
Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.
Highlights
Melanoma is an aggressive tumor marked by high metastatic potential and drug resistance [1,2]
With the aim of identifying genes with melanoma restricted expression we developed a simple in silico pipeline that was implemented as a new online tool, EST2TSE (Table S1)
Our tool is simpler than tools of similar function, such as Gene Library Summarizer (GLS) [10] from the Cancer Genome Anatomy Project-CGAP, UniGene Digital Differential Display – DDD [11] and the Tissue-specific Gene Expression and Regulation-TiGER database [12], it allows a more straightforward search for specific terms, for example, some tumor types or subtypes, since we can use as keyword any of the terms associated to the cell or tissue type in the GenBank reports (Table S1)
Summary
Melanoma is an aggressive tumor marked by high metastatic potential and drug resistance [1,2]. Great interest exists in the identification of genes of melanoma-specific expression that may lead to new markers to monitor the disease status or to new therapeutic targets. Tissue-restricted expression is a desirable property for candidate genes as therapeutic targets in cancer, since their function could be inhibited without damaging normal tissues, their promoters could be used to enhance expression of cell death-inducing proteins in tumor cells, and tumor-specific proteins could serve as targets for immunotherapy or site-specific delivery of antitumor agents. Besides the annotation of human genes, expressed sequence tags (ESTs) have been used for the identification of tissue-specific genes [4,5], including genes differentially expressed in normal and tumor tissues [6], and those encoding cancer/testis tumor antigens, characterized by their predominant expression in germ cells, trophoblast cells, and tumor tissues [7]. EST data and its associated UniGene information were used to create a database of genes preferentially expressed in 30 tissues [8,9]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call