No-match ORESTES explored as tumor markers.

Sequencing technologies and new bioinformatics tools have led to the complete sequencing of various genomes. However, information regarding the human transcriptome and its annotation is yet to be completed. The Human Cancer Genome Project, using ORESTES (open reading frame EST sequences) methodology, contributed to this objective by generating data from about 1.2 million expressed sequence tags. Approximately 30% of these sequences did not align to ESTs in the public databases and were considered no-match ORESTES. On the basis that a set of these ESTs could represent new transcripts, we constructed a cDNA microarray. This platform was used to hybridize against 12 different normal or tumor tissues. We identified 3421 transcribed regions not associated with annotated transcripts, representing 83.3% of the platform. The total number of differentially expressed sequences was 1007. Also, 28% of analyzed sequences could represent noncoding RNAs. Our data reinforces the knowledge of the human genome being pervasively transcribed, and point out molecular marker candidates for different cancers. To reinforce our data, we confirmed, by real-time PCR, the differential expression of three out of eight potentially tumor markers in prostate tissues. Lists of 1007 differentially expressed sequences, and the 291 potentially noncoding tumor markers were provided.

Mining ORESTES no-match database: can we still contribute to cancer transcriptome?

The Human Cancer Genome Project generated about 1 million expressed sequence tags by the ORESTES method, principally with the aim of obtaining data from cancer. Of this total, 341,680 showed no similarity with sequences in the public transcript databases, referred to as "no-match". Some of them represent low abundance or difficult to detect human transcripts, but part of these sequences represent genomic contamination or immature mRNA. We performed a bioinformatics pipeline to determine the novelty of ORESTES "no-match" datasets from prostate or breast tissues. We started with 14,908 clusters mapped on the human genome. A total of 2226 clusters originating from more than two libraries or singletons with gaps upon genome alignment were selected. Ninety-four clusters with canonical splice sites representing the most stringent criteria to be considered a gene were subjected to manual inspection regarding genomic hits. Of the manually inspected clusters, 49.6% contained new sequences where 42.2% were probable low-expression alternative forms of the characterized genes and 7.4% unpredicted genes. RT-PCR followed by sequencing was performed to validate the largest spliced sequence from 8 clusters, resulting in the confirmation of five sequences as true human transcript fragments. Some of them were differentially expressed between tumor and normal tissue by an in silico analysis. We can conclude that after clean up of the no-match dataset, we still have about 939 new exons and 165 unpredicted genes that could complete the prostate or breast transcriptome.