MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population
Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine suscep...
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| creator | Bakshi, Divya Nagpal, Ashna Sharma, Varun Sharma, Indu Shah, Ruchi Sharma, Bhanu Bhat, Amrita Verma, Sonali Bhat, Gh Rasool Abrol, Deepak Sharma, Rahul Vaishnavi, Samantha Kumar, Rakesh |
| description | Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis.
SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study.
The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123-0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings.
It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability. |
| doi_str_mv | 10.1186/s12885-020-07361-8 |
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SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study.
The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123-0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings.
It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.</description><identifier>ISSN: 1471-2407</identifier><identifier>EISSN: 1471-2407</identifier><identifier>DOI: 10.1186/s12885-020-07361-8</identifier><identifier>PMID: 32894086</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adult ; Aged ; Alleles ; Analysis ; Asian Continental Ancestry Group - genetics ; Binding sites ; Breast cancer ; Breast Neoplasms - epidemiology ; Breast Neoplasms - genetics ; Breast Neoplasms - pathology ; Cancer research ; Carcinogenesis ; Cell cycle ; Colorectal cancer ; Deoxyribonucleic acid ; Disease susceptibility ; DNA ; DNA damage ; EDTA ; ERCC1 protein ; Female ; Gene mutation ; Genes ; Genetic aspects ; Genetic Association Studies ; Genetic diversity ; Genetic Predisposition to Disease ; Genetic Variation - genetics ; Genetics, Population ; Genotype ; Genotyping ; Heritability ; Humans ; India - epidemiology ; Jammu and Kashmir ; Lung cancer ; Middle Aged ; Neoplasm Proteins - genetics ; Polymorphism, Single Nucleotide - genetics ; Population ; Population studies ; Single nucleotide polymorphism ; Single nucleotide polymorphisms ; Womens health</subject><ispartof>BMC cancer, 2020-09, Vol.20 (1), p.861-8, Article 861</ispartof><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c628t-167f96510800935e2aea3568639c543751cab0b5c3083e1c62b9add4115f6bad3</citedby><cites>FETCH-LOGICAL-c628t-167f96510800935e2aea3568639c543751cab0b5c3083e1c62b9add4115f6bad3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487711/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487711/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,862,883,2098,27907,27908,53774,53776</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32894086$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bakshi, Divya</creatorcontrib><creatorcontrib>Nagpal, Ashna</creatorcontrib><creatorcontrib>Sharma, Varun</creatorcontrib><creatorcontrib>Sharma, Indu</creatorcontrib><creatorcontrib>Shah, Ruchi</creatorcontrib><creatorcontrib>Sharma, Bhanu</creatorcontrib><creatorcontrib>Bhat, Amrita</creatorcontrib><creatorcontrib>Verma, Sonali</creatorcontrib><creatorcontrib>Bhat, Gh Rasool</creatorcontrib><creatorcontrib>Abrol, Deepak</creatorcontrib><creatorcontrib>Sharma, Rahul</creatorcontrib><creatorcontrib>Vaishnavi, Samantha</creatorcontrib><creatorcontrib>Kumar, Rakesh</creatorcontrib><title>MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population</title><title>BMC cancer</title><addtitle>BMC Cancer</addtitle><description>Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis.
SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study.
The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123-0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings.
It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.</description><subject>Adult</subject><subject>Aged</subject><subject>Alleles</subject><subject>Analysis</subject><subject>Asian Continental Ancestry Group - genetics</subject><subject>Binding sites</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - epidemiology</subject><subject>Breast Neoplasms - genetics</subject><subject>Breast Neoplasms - pathology</subject><subject>Cancer research</subject><subject>Carcinogenesis</subject><subject>Cell cycle</subject><subject>Colorectal cancer</subject><subject>Deoxyribonucleic acid</subject><subject>Disease susceptibility</subject><subject>DNA</subject><subject>DNA damage</subject><subject>EDTA</subject><subject>ERCC1 protein</subject><subject>Female</subject><subject>Gene mutation</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic Association Studies</subject><subject>Genetic diversity</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Variation - genetics</subject><subject>Genetics, Population</subject><subject>Genotype</subject><subject>Genotyping</subject><subject>Heritability</subject><subject>Humans</subject><subject>India - epidemiology</subject><subject>Jammu and Kashmir</subject><subject>Lung cancer</subject><subject>Middle Aged</subject><subject>Neoplasm Proteins - genetics</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>Population</subject><subject>Population studies</subject><subject>Single nucleotide polymorphism</subject><subject>Single nucleotide polymorphisms</subject><subject>Womens health</subject><issn>1471-2407</issn><issn>1471-2407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNptkl2L1DAUhoso7rr6B7yQgrDgRdd8J70RhsWPgRVh1AuvwmmaTjO0yZi04vx7szvrOgXJRcLJ876cnLxF8RKjK4yVeJswUYpXiKAKSSpwpR4V55hJXBGG5OOT81nxLKUdQlgqpJ4WZ5SomiElzgvzGVJabTarH1UDybZlcn472NLPZrBhcq0t92E4jCHue5fGEjwMh-RS6XzZRAtpKg14Y2MZutKHOPXl2rcOfJbt5wEmF_zz4kkHQ7Iv7veL4vuH99-uP1U3Xz6ur1c3lRFETRUWsqsFx0ghVFNuCVigXChBa8MZlRwbaFDDDUWKWpxFTQ1tyzDmnWigpRfF-ujbBtjpfXQjxIMO4PRdIcSthji5_DDNUduCwrQxUjJmORgCiPLGQk24oE32enf02s_NaFtj_RRhWJgub7zr9Tb80pIpKTHOBq_vDWL4Ods06V2YY55e0oSx3DQRTP6jtpC7cr4L2cyMLhm9EpQjITEjmbr6D5VXa0dngredy_WF4M1CkJnJ_p62MKek1183S_byhO0tDFOfwjDf_lxaguQImhhSirZ7mAZG-jaQ-hhInQOp7wKpVRa9Op3jg-RvAukf_1_ZSg</recordid><startdate>20200907</startdate><enddate>20200907</enddate><creator>Bakshi, Divya</creator><creator>Nagpal, Ashna</creator><creator>Sharma, Varun</creator><creator>Sharma, Indu</creator><creator>Shah, Ruchi</creator><creator>Sharma, Bhanu</creator><creator>Bhat, Amrita</creator><creator>Verma, Sonali</creator><creator>Bhat, Gh Rasool</creator><creator>Abrol, Deepak</creator><creator>Sharma, Rahul</creator><creator>Vaishnavi, Samantha</creator><creator>Kumar, Rakesh</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><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>ISR</scope><scope>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20200907</creationdate><title>MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population</title><author>Bakshi, Divya ; Nagpal, Ashna ; Sharma, Varun ; Sharma, Indu ; Shah, Ruchi ; Sharma, Bhanu ; Bhat, Amrita ; Verma, Sonali ; Bhat, Gh Rasool ; Abrol, Deepak ; Sharma, Rahul ; Vaishnavi, Samantha ; Kumar, Rakesh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c628t-167f96510800935e2aea3568639c543751cab0b5c3083e1c62b9add4115f6bad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Alleles</topic><topic>Analysis</topic><topic>Asian Continental Ancestry Group - genetics</topic><topic>Binding sites</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - epidemiology</topic><topic>Breast Neoplasms - genetics</topic><topic>Breast Neoplasms - pathology</topic><topic>Cancer research</topic><topic>Carcinogenesis</topic><topic>Cell cycle</topic><topic>Colorectal cancer</topic><topic>Deoxyribonucleic acid</topic><topic>Disease susceptibility</topic><topic>DNA</topic><topic>DNA damage</topic><topic>EDTA</topic><topic>ERCC1 protein</topic><topic>Female</topic><topic>Gene mutation</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic Association Studies</topic><topic>Genetic diversity</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Variation - genetics</topic><topic>Genetics, Population</topic><topic>Genotype</topic><topic>Genotyping</topic><topic>Heritability</topic><topic>Humans</topic><topic>India - epidemiology</topic><topic>Jammu and Kashmir</topic><topic>Lung cancer</topic><topic>Middle Aged</topic><topic>Neoplasm Proteins - genetics</topic><topic>Polymorphism, Single Nucleotide - genetics</topic><topic>Population</topic><topic>Population studies</topic><topic>Single nucleotide polymorphism</topic><topic>Single nucleotide polymorphisms</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bakshi, Divya</creatorcontrib><creatorcontrib>Nagpal, Ashna</creatorcontrib><creatorcontrib>Sharma, Varun</creatorcontrib><creatorcontrib>Sharma, Indu</creatorcontrib><creatorcontrib>Shah, Ruchi</creatorcontrib><creatorcontrib>Sharma, Bhanu</creatorcontrib><creatorcontrib>Bhat, Amrita</creatorcontrib><creatorcontrib>Verma, Sonali</creatorcontrib><creatorcontrib>Bhat, Gh Rasool</creatorcontrib><creatorcontrib>Abrol, Deepak</creatorcontrib><creatorcontrib>Sharma, Rahul</creatorcontrib><creatorcontrib>Vaishnavi, Samantha</creatorcontrib><creatorcontrib>Kumar, Rakesh</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bakshi, Divya</au><au>Nagpal, Ashna</au><au>Sharma, Varun</au><au>Sharma, Indu</au><au>Shah, Ruchi</au><au>Sharma, Bhanu</au><au>Bhat, Amrita</au><au>Verma, Sonali</au><au>Bhat, Gh Rasool</au><au>Abrol, Deepak</au><au>Sharma, Rahul</au><au>Vaishnavi, Samantha</au><au>Kumar, Rakesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population</atitle><jtitle>BMC cancer</jtitle><addtitle>BMC Cancer</addtitle><date>2020-09-07</date><risdate>2020</risdate><volume>20</volume><issue>1</issue><spage>861</spage><epage>8</epage><pages>861-8</pages><artnum>861</artnum><issn>1471-2407</issn><eissn>1471-2407</eissn><abstract>Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis.
SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study.
The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123-0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings.
It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>32894086</pmid><doi>10.1186/s12885-020-07361-8</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; PubMed Central Open Access; Springer Nature OA Free Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; SpringerLink Journals - AutoHoldings |
| subjects | Adult Aged Alleles Analysis Asian Continental Ancestry Group - genetics Binding sites Breast cancer Breast Neoplasms - epidemiology Breast Neoplasms - genetics Breast Neoplasms - pathology Cancer research Carcinogenesis Cell cycle Colorectal cancer Deoxyribonucleic acid Disease susceptibility DNA DNA damage EDTA ERCC1 protein Female Gene mutation Genes Genetic aspects Genetic Association Studies Genetic diversity Genetic Predisposition to Disease Genetic Variation - genetics Genetics, Population Genotype Genotyping Heritability Humans India - epidemiology Jammu and Kashmir Lung cancer Middle Aged Neoplasm Proteins - genetics Polymorphism, Single Nucleotide - genetics Population Population studies Single nucleotide polymorphism Single nucleotide polymorphisms Womens health |
| title | MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population |
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