Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors
Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are chara...
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| Veröffentlicht in: | Breast cancer research and treatment 2008, Vol.107 (2), p.259-265 |
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| creator | Ellsworth, Rachel E. Hooke, Jeffrey A. Love, Brad Kane, Jennifer L. Patney, Heather L. Ellsworth, Darrell L. Shriver, Craig D. |
| description | Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1;
n
= 55), moderately-differentiated (grade 2;
n
= 71), and poorly-differentiated (grade 3;
n
= 59) stage I–IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (
P
|
| doi_str_mv | 10.1007/s10549-007-9547-2 |
| format | Article |
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n
= 55), moderately-differentiated (grade 2;
n
= 71), and poorly-differentiated (grade 3;
n
= 59) stage I–IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (
P
< 0.05). Grades 1 and 3 showed distinct genetic profiles - grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized ∼70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.</description><identifier>ISSN: 0167-6806</identifier><identifier>EISSN: 1573-7217</identifier><identifier>DOI: 10.1007/s10549-007-9547-2</identifier><identifier>PMID: 17351743</identifier><identifier>CODEN: BCTRD6</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Allelic Imbalance ; Biological and medical sciences ; Breast cancer ; Breast Neoplasms - metabolism ; Breast Neoplasms - pathology ; Cancer research ; Carcinoma - genetics ; Cell Differentiation ; Chromosome Mapping ; Female ; Genes ; Genomic Instability ; Gynecology. Andrology. Obstetrics ; Histology ; Humans ; Mammary gland diseases ; Medical sciences ; Medicine ; Medicine & Public Health ; Microsatellite Repeats ; Neoplasm Invasiveness ; Oncology ; Physical Chromosome Mapping ; Postmenopause ; Preclinical Study ; Premenopause ; Prognosis ; Treatment Outcome ; Tumors</subject><ispartof>Breast cancer research and treatment, 2008, Vol.107 (2), p.259-265</ispartof><rights>Springer Science+Business Media, LLC 2007</rights><rights>2008 INIST-CNRS</rights><rights>Springer Science+Business Media, LLC. 2007</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-a1f0248557ee76a62377799166ca65f034bba6c4d14b3fdf94469db41a22f7493</citedby><cites>FETCH-LOGICAL-c430t-a1f0248557ee76a62377799166ca65f034bba6c4d14b3fdf94469db41a22f7493</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10549-007-9547-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10549-007-9547-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,4010,27900,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20006739$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17351743$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ellsworth, Rachel E.</creatorcontrib><creatorcontrib>Hooke, Jeffrey A.</creatorcontrib><creatorcontrib>Love, Brad</creatorcontrib><creatorcontrib>Kane, Jennifer L.</creatorcontrib><creatorcontrib>Patney, Heather L.</creatorcontrib><creatorcontrib>Ellsworth, Darrell L.</creatorcontrib><creatorcontrib>Shriver, Craig D.</creatorcontrib><title>Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors</title><title>Breast cancer research and treatment</title><addtitle>Breast Cancer Res Treat</addtitle><addtitle>Breast Cancer Res Treat</addtitle><description>Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1;
n
= 55), moderately-differentiated (grade 2;
n
= 71), and poorly-differentiated (grade 3;
n
= 59) stage I–IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (
P
< 0.05). Grades 1 and 3 showed distinct genetic profiles - grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized ∼70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.</description><subject>Allelic Imbalance</subject><subject>Biological and medical sciences</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - metabolism</subject><subject>Breast Neoplasms - pathology</subject><subject>Cancer research</subject><subject>Carcinoma - genetics</subject><subject>Cell Differentiation</subject><subject>Chromosome Mapping</subject><subject>Female</subject><subject>Genes</subject><subject>Genomic Instability</subject><subject>Gynecology. Andrology. Obstetrics</subject><subject>Histology</subject><subject>Humans</subject><subject>Mammary gland diseases</subject><subject>Medical sciences</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Microsatellite Repeats</subject><subject>Neoplasm Invasiveness</subject><subject>Oncology</subject><subject>Physical Chromosome Mapping</subject><subject>Postmenopause</subject><subject>Preclinical Study</subject><subject>Premenopause</subject><subject>Prognosis</subject><subject>Treatment Outcome</subject><subject>Tumors</subject><issn>0167-6806</issn><issn>1573-7217</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkU2LFDEQhoMo7rj6A7xIEPTWmq9Opo8y-AULXvTcVHcnvVnSyZhKj-y_N80MLgjiKUXyvFWp9yXkJWfvOGPmPXLWqq6pZdO1yjTiEdnx1sjGCG4ekx3j2jR6z_QVeYZ4xxjrDOuekituZMuNkjuyHFLONkDxKdLkaLAnG5BCnOgRSrE54nY925gWP1IfscDggy_39Jcvt_TWY0khzX6EQOcMk4_zJvDxBOhPlg7ZAhZa1iVlfE6eOAhoX1zOa_Lj08fvhy_NzbfPXw8fbppRSVYa4I4JtW9bY63RoIU0xnQd13oE3Tom1TCAHtXE1SDd5DqldDcNioMQzqhOXpO3577HnH6uFku_eBxtCBBtWrE31QktufovKKrD7V6yCr7-C7xLa451icqIOl4LUSF-hsacELN1_TH7BfJ9z1m_JdafE-u3ckus3zSvLo3XYbHTg-ISUQXeXADAarLLEEePfzhRU9VGbjuLM4f1Kc42P_zw39N_AzENrkk</recordid><startdate>2008</startdate><enddate>2008</enddate><creator>Ellsworth, Rachel E.</creator><creator>Hooke, Jeffrey A.</creator><creator>Love, Brad</creator><creator>Kane, Jennifer L.</creator><creator>Patney, Heather L.</creator><creator>Ellsworth, Darrell L.</creator><creator>Shriver, Craig D.</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</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>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</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>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9-</scope><scope>K9.</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>2008</creationdate><title>Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors</title><author>Ellsworth, Rachel E. ; Hooke, Jeffrey A. ; Love, Brad ; Kane, Jennifer L. ; Patney, Heather L. ; Ellsworth, Darrell L. ; Shriver, Craig D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c430t-a1f0248557ee76a62377799166ca65f034bba6c4d14b3fdf94469db41a22f7493</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Allelic Imbalance</topic><topic>Biological and medical sciences</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - metabolism</topic><topic>Breast Neoplasms - pathology</topic><topic>Cancer research</topic><topic>Carcinoma - genetics</topic><topic>Cell Differentiation</topic><topic>Chromosome Mapping</topic><topic>Female</topic><topic>Genes</topic><topic>Genomic Instability</topic><topic>Gynecology. Andrology. Obstetrics</topic><topic>Histology</topic><topic>Humans</topic><topic>Mammary gland diseases</topic><topic>Medical sciences</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Microsatellite Repeats</topic><topic>Neoplasm Invasiveness</topic><topic>Oncology</topic><topic>Physical Chromosome Mapping</topic><topic>Postmenopause</topic><topic>Preclinical Study</topic><topic>Premenopause</topic><topic>Prognosis</topic><topic>Treatment Outcome</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ellsworth, Rachel E.</creatorcontrib><creatorcontrib>Hooke, Jeffrey A.</creatorcontrib><creatorcontrib>Love, Brad</creatorcontrib><creatorcontrib>Kane, Jennifer L.</creatorcontrib><creatorcontrib>Patney, Heather L.</creatorcontrib><creatorcontrib>Ellsworth, Darrell L.</creatorcontrib><creatorcontrib>Shriver, Craig D.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</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>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</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>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</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 Basic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Breast cancer research and treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ellsworth, Rachel E.</au><au>Hooke, Jeffrey A.</au><au>Love, Brad</au><au>Kane, Jennifer L.</au><au>Patney, Heather L.</au><au>Ellsworth, Darrell L.</au><au>Shriver, Craig D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors</atitle><jtitle>Breast cancer research and treatment</jtitle><stitle>Breast Cancer Res Treat</stitle><addtitle>Breast Cancer Res Treat</addtitle><date>2008</date><risdate>2008</risdate><volume>107</volume><issue>2</issue><spage>259</spage><epage>265</epage><pages>259-265</pages><issn>0167-6806</issn><eissn>1573-7217</eissn><coden>BCTRD6</coden><abstract>Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1;
n
= 55), moderately-differentiated (grade 2;
n
= 71), and poorly-differentiated (grade 3;
n
= 59) stage I–IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (
P
< 0.05). Grades 1 and 3 showed distinct genetic profiles - grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized ∼70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.</abstract><cop>Boston</cop><pub>Springer US</pub><pmid>17351743</pmid><doi>10.1007/s10549-007-9547-2</doi><tpages>7</tpages></addata></record> |
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| ispartof | Breast cancer research and treatment, 2008, Vol.107 (2), p.259-265 |
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| subjects | Allelic Imbalance Biological and medical sciences Breast cancer Breast Neoplasms - metabolism Breast Neoplasms - pathology Cancer research Carcinoma - genetics Cell Differentiation Chromosome Mapping Female Genes Genomic Instability Gynecology. Andrology. Obstetrics Histology Humans Mammary gland diseases Medical sciences Medicine Medicine & Public Health Microsatellite Repeats Neoplasm Invasiveness Oncology Physical Chromosome Mapping Postmenopause Preclinical Study Premenopause Prognosis Treatment Outcome Tumors |
| title | Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors |
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