Quantitating tissue specificity of human genes to facilitate biomarker discovery
We describe a method to identify candidate cancer biomarkers by analyzing numeric approximations of tissue specificity of human genes. These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human...
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| Veröffentlicht in: | Bioinformatics 2007-06, Vol.23 (11), p.1348-1355 |
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| creator | Vasmatzis, George Klee, Eric W. Kube, Dagmar M. Therneau, Terry M. Kosari, Farhad |
| description | We describe a method to identify candidate cancer biomarkers by analyzing numeric approximations of tissue specificity of human genes. These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human genome sequence using a binary indexing algorithm. Tissue-specificity values facilitated high-throughput analysis of the human genes and enabled the identification of genes highly specific to different tissues. Tissue expression distributions for several genes were compared to estimates obtained from other public gene expression datasets and experimentally validated using quantitative RT-PCR on RNA isolated from several human tissues. Our results demonstrate that most human genes (∼98%) are expressed in many tissues (low specificity), and only a small number of genes possess very specific tissue expression profiles. These genes comprise a rich dataset from which novel therapeutic targets and novel diagnostic serum biomarkers may be selected.
Contact: vasm@mayo.edu
Supplementary information: Supplementary data are available at Bioinformatics online. |
| doi_str_mv | 10.1093/bioinformatics/btm102 |
| format | Article |
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Contact: vasm@mayo.edu
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Contact: vasm@mayo.edu
Supplementary information: Supplementary data are available at Bioinformatics online.</description><subject>Biological and medical sciences</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Chromosome Mapping - methods</subject><subject>Expressed Sequence Tags</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Genetic Predisposition to Disease - genetics</subject><subject>Genome, Human - genetics</subject><subject>Humans</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</subject><subject>Neoplasm Proteins - genetics</subject><subject>Neoplasms - diagnosis</subject><subject>Neoplasms - genetics</subject><subject>Organ Specificity</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Sequence Analysis, DNA - methods</subject><issn>1367-4803</issn><issn>1367-4811</issn><issn>1460-2059</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkUtvFDEQhC0EIiHwE0AWEtyWuMevniOKwkOKBEhwHnk97eAwM15sD9L-exztiggu4dQ-fFVd7WLsOYg3IHp5vo0pLiHl2dXoy_m2ziC6B-wUpLEbhQAP_7yFPGFPSrkRQmihzWN2AlaiEtCfss9fVrfUWJvLcs1rLGUlXnbkY4g-1j1PgX9fZ7fwa1qo8Jp4cD5OtwriLcTs8g_KfIzFp1-U90_Zo-CmQs-O84x9e3f59eLD5urT-48Xb682XoOqG4edDT2isNZYdErjCL00ocM-dC0aqZFUcCgVytGQ1dKBQSAdEDV6kmfs9cF3l9PPlUod5haBpsktlNYyWGGUktreC0qpVG9B3gt2AmVvlGngy3_Am7TmpV07QI_GYLutQfoA-ZxKyRSGXY7ts_YDiOG2weHvBodDg0334mi-bmca71THyhrw6gi44t0Uslt8LHccopKA0Dhx4NK6-8_dvwHGV7n_</recordid><startdate>20070601</startdate><enddate>20070601</enddate><creator>Vasmatzis, George</creator><creator>Klee, Eric W.</creator><creator>Kube, Dagmar M.</creator><creator>Therneau, Terry M.</creator><creator>Kosari, Farhad</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TM</scope><scope>7TO</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20070601</creationdate><title>Quantitating tissue specificity of human genes to facilitate biomarker discovery</title><author>Vasmatzis, George ; Klee, Eric W. ; Kube, Dagmar M. ; Therneau, Terry M. ; Kosari, Farhad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c514t-a827f988077678a458d1936f289f2401e4de4fa83483d6e753a1681e5f8858ce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Biological and medical sciences</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Chromosome Mapping - methods</topic><topic>Expressed Sequence Tags</topic><topic>Fundamental and applied biological sciences. 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These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human genome sequence using a binary indexing algorithm. Tissue-specificity values facilitated high-throughput analysis of the human genes and enabled the identification of genes highly specific to different tissues. Tissue expression distributions for several genes were compared to estimates obtained from other public gene expression datasets and experimentally validated using quantitative RT-PCR on RNA isolated from several human tissues. Our results demonstrate that most human genes (∼98%) are expressed in many tissues (low specificity), and only a small number of genes possess very specific tissue expression profiles. These genes comprise a rich dataset from which novel therapeutic targets and novel diagnostic serum biomarkers may be selected.
Contact: vasm@mayo.edu
Supplementary information: Supplementary data are available at Bioinformatics online.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>17384019</pmid><doi>10.1093/bioinformatics/btm102</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Biological and medical sciences Biomarkers, Tumor - genetics Chromosome Mapping - methods Expressed Sequence Tags Fundamental and applied biological sciences. Psychology General aspects Genetic Predisposition to Disease - genetics Genome, Human - genetics Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Neoplasm Proteins - genetics Neoplasms - diagnosis Neoplasms - genetics Organ Specificity Reproducibility of Results Sensitivity and Specificity Sequence Analysis, DNA - methods |
| title | Quantitating tissue specificity of human genes to facilitate biomarker discovery |
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