Microsatellite genotyping reveals a signature in breast cancer exomes
Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide ad...
Ausführliche Beschreibung
Autor*in: |
McIver, L. J. [verfasserIn] Fonville, N. C. [verfasserIn] Karunasena, E. [verfasserIn] Garner, H. R. [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2014 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Breast cancer research and treatment - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1981, 145(2014), 3 vom: 17. Mai, Seite 791-798 |
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Übergeordnetes Werk: |
volume:145 ; year:2014 ; number:3 ; day:17 ; month:05 ; pages:791-798 |
Links: |
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DOI / URN: |
10.1007/s10549-014-2908-8 |
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Katalog-ID: |
SPR011095288 |
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520 | |a Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. | ||
650 | 4 | |a Microsatellite variation |7 (dpeaa)DE-He213 | |
650 | 4 | |a Breast cancer risk assessment |7 (dpeaa)DE-He213 | |
650 | 4 | |a Cancer genomics |7 (dpeaa)DE-He213 | |
650 | 4 | |a The Cancer Genome Atlas |7 (dpeaa)DE-He213 | |
700 | 1 | |a Fonville, N. C. |e verfasserin |4 aut | |
700 | 1 | |a Karunasena, E. |e verfasserin |4 aut | |
700 | 1 | |a Garner, H. R. |e verfasserin |4 aut | |
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10.1007/s10549-014-2908-8 doi (DE-627)SPR011095288 (SPR)s10549-014-2908-8-e DE-627 ger DE-627 rakwb eng 610 ASE 44.92 bkl McIver, L. J. verfasserin aut Microsatellite genotyping reveals a signature in breast cancer exomes 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. Microsatellite variation (dpeaa)DE-He213 Breast cancer risk assessment (dpeaa)DE-He213 Cancer genomics (dpeaa)DE-He213 The Cancer Genome Atlas (dpeaa)DE-He213 Fonville, N. C. verfasserin aut Karunasena, E. verfasserin aut Garner, H. R. verfasserin aut Enthalten in Breast cancer research and treatment Dordrecht [u.a.] : Springer Science + Business Media B.V., 1981 145(2014), 3 vom: 17. Mai, Seite 791-798 (DE-627)320433722 (DE-600)2004077-5 1573-7217 nnns volume:145 year:2014 number:3 day:17 month:05 pages:791-798 https://dx.doi.org/10.1007/s10549-014-2908-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.92 ASE AR 145 2014 3 17 05 791-798 |
spelling |
10.1007/s10549-014-2908-8 doi (DE-627)SPR011095288 (SPR)s10549-014-2908-8-e DE-627 ger DE-627 rakwb eng 610 ASE 44.92 bkl McIver, L. J. verfasserin aut Microsatellite genotyping reveals a signature in breast cancer exomes 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. Microsatellite variation (dpeaa)DE-He213 Breast cancer risk assessment (dpeaa)DE-He213 Cancer genomics (dpeaa)DE-He213 The Cancer Genome Atlas (dpeaa)DE-He213 Fonville, N. C. verfasserin aut Karunasena, E. verfasserin aut Garner, H. R. verfasserin aut Enthalten in Breast cancer research and treatment Dordrecht [u.a.] : Springer Science + Business Media B.V., 1981 145(2014), 3 vom: 17. Mai, Seite 791-798 (DE-627)320433722 (DE-600)2004077-5 1573-7217 nnns volume:145 year:2014 number:3 day:17 month:05 pages:791-798 https://dx.doi.org/10.1007/s10549-014-2908-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.92 ASE AR 145 2014 3 17 05 791-798 |
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10.1007/s10549-014-2908-8 doi (DE-627)SPR011095288 (SPR)s10549-014-2908-8-e DE-627 ger DE-627 rakwb eng 610 ASE 44.92 bkl McIver, L. J. verfasserin aut Microsatellite genotyping reveals a signature in breast cancer exomes 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. Microsatellite variation (dpeaa)DE-He213 Breast cancer risk assessment (dpeaa)DE-He213 Cancer genomics (dpeaa)DE-He213 The Cancer Genome Atlas (dpeaa)DE-He213 Fonville, N. C. verfasserin aut Karunasena, E. verfasserin aut Garner, H. R. verfasserin aut Enthalten in Breast cancer research and treatment Dordrecht [u.a.] : Springer Science + Business Media B.V., 1981 145(2014), 3 vom: 17. Mai, Seite 791-798 (DE-627)320433722 (DE-600)2004077-5 1573-7217 nnns volume:145 year:2014 number:3 day:17 month:05 pages:791-798 https://dx.doi.org/10.1007/s10549-014-2908-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.92 ASE AR 145 2014 3 17 05 791-798 |
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McIver, L. J. |
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McIver, L. J. ddc 610 bkl 44.92 misc Microsatellite variation misc Breast cancer risk assessment misc Cancer genomics misc The Cancer Genome Atlas Microsatellite genotyping reveals a signature in breast cancer exomes |
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610 ASE 44.92 bkl Microsatellite genotyping reveals a signature in breast cancer exomes Microsatellite variation (dpeaa)DE-He213 Breast cancer risk assessment (dpeaa)DE-He213 Cancer genomics (dpeaa)DE-He213 The Cancer Genome Atlas (dpeaa)DE-He213 |
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Microsatellite genotyping reveals a signature in breast cancer exomes |
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microsatellite genotyping reveals a signature in breast cancer exomes |
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Microsatellite genotyping reveals a signature in breast cancer exomes |
abstract |
Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. |
abstractGer |
Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. |
abstract_unstemmed |
Abstract Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer. |
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3 |
title_short |
Microsatellite genotyping reveals a signature in breast cancer exomes |
url |
https://dx.doi.org/10.1007/s10549-014-2908-8 |
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author2 |
Fonville, N. C. Karunasena, E. Garner, H. R. |
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Fonville, N. C. Karunasena, E. Garner, H. R. |
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doi_str |
10.1007/s10549-014-2908-8 |
up_date |
2024-07-03T20:24:28.063Z |
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|
score |
7.40102 |