Large-scale transcriptome analyses reveal new genetic marker candidates of head, neck, and thyroid cancer

A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. in addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available.Univ São Paulo, Fac Med, Inst Psiquiatria, Neurosci Lab,Dept Psiquiatria, BR-05403010 São Paulo, BrazilUniv São Paulo, Fac Med, Dept Bioquim, BR-05403010 São Paulo, BrazilUniv São Paulo, Fac Med, Lab Bioinformat, Inst Quim, BR-05403010 São Paulo, BrazilUniv São Paulo, Fac Med, Disciplina Oncol, Dept Radiol, BR-05403010 São Paulo, BrazilUniversidade Federal de São Paulo, Mol Endocrinol Lab, Dept Med & Morfol, São Paulo, BrazilHosp Canc AC Camargo, Dept Cirurg Cabeca & Pescoco & Otorrinolaringolog, São Paulo, SP, BrazilUniv Estadual Campinas, Inst Biol, Dept Genet & Evolucao, Lab Biol Mol & Genom Hemoctr, Campinas, SP, BrazilUniv Estadual Campinas, Inst Biol, Dept Genet & Evolucao, Lab Genom & Expressao, Campinas, SP, BrazilUniv Estadual Paulista, Dept Biol, Inst Biociencias, Araraquara, SP, BrazilFac Med Sao Jose Rio Preto, Dept Biol Mol, Sao Jose de Rio Preto, SP, BrazilUniv Estadual Paulista, Escola Farm, Dept Ciencias Biol, Araraquara, SP, BrazilUniversidade Federal de São Paulo, Mol Endocrinol Lab, Dept Med & Morfol, São Paulo, BrazilWeb of Scienc

Identification of human chromosome 22 transcribed sequences with ORF expressed sequence tags

Transcribed sequences in the human genome can be identified with confidence only by alignment with sequences derived from cDNAs synthesized from naturally occurring mRNAs. We constructed a set of 250,000 cDNAs that represent partial expressed gene sequences and that are biased toward the central coding regions of the resulting transcripts. They are termed ORF expressed sequence tags (ORESTES). The 250,000 ORESTES were assembled into 81,429 contigs. Of these, 1,181 (1.45%) were found to match sequences in chromosome 22 with at least one ORESTES contig for 162 (65.6%) of the 247 known genes, for 67 (44.6%) of the 150 related genes, and for 45 of the 148 (30.4%) EST-predicted genes on this chromosome. Using a set of stringent criteria to validate our sequences, we identified a further 219 previously unannotated transcribed sequences on chromosome 22. Of these, 171 were in fact also defined by EST or full length cDNA sequences available in GenBank but not utilized in the initial annotation of the first human chromosome sequence. Thus despite representing less than 15% of all expressed human sequences in the public databases at the time of the present analysis, ORESTES sequences defined 48 transcribed sequences on chromosome 22 not defined by other sequences. All of the transcribed sequences defined by ORESTES coincided with DNA regions predicted as encoding exons by genscan. (http://genes.mit.edu/GENSCAN.html)

Large-scale transcriptome analyses reveal new genetic marker candidates of head, neck, and thyroid cancer

A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. In addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available