Comprehensive clinical and molecular analyses of neuroendocrine carcinomas of the breast
Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence, and prognosis remain controversial in the literature. The 2012 WHO classification of breast cancer categorizes neuroendocrine carcinomas into three morphologically distinct subtypes: well-differ...
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| Veröffentlicht in: | Modern pathology 2018, Vol.31 (1), p.68-82 |
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| creator | Lavigne, Marion Menet, Emmanuelle Tille, Jean-Christophe Lae, Marick Fuhrmann, Laetitia Bonneau, Claire Deniziaut, Gabrielle Melaabi, Samia Ng, Charlotte C K Marchiò, Caterina Rouzier, Roman Bièche, Ivan Vincent-Salomon, Anne |
| description | Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence, and prognosis remain controversial in the literature. The 2012 WHO classification of breast cancer categorizes neuroendocrine carcinomas into three morphologically distinct subtypes: well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation. We aimed to gain insight into the clinical, morphologic, phenotypic, and molecular features of 47 neuroendocrine breast carcinomas. Targeted next-generation sequencing by an AmpliSeq 22 cancer gene hotspot panel and the Prosigna assay were performed on 42/47 and 35/47 cases, respectively. Average age at diagnosis was 69 years. All tumors were estrogen receptor-positive and the large majority expressed progesterone receptor (89%), GATA3 (98%), FOXA1 (96%), and CK8/18 (98%). There was an almost equal distribution of luminal A (52%) and B (48%) carcinomas. Almost half of the cohort (49%) displayed a high risk of recurrence score with the Prosigna test. Patients with a neuroendocrine carcinoma had a shorter disease-free survival compared with those affected by carcinomas of no special type matched for age, size, grade, and estrogen receptor status. No significant differences were observed in terms of overall survival. Stratification of neuroendocrine carcinomas using the 2012 WHO criteria did not reveal statistically significant differences among the distinct categories (well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation), in terms of either progression-free or overall survival. Our targeted sequencing analysis found three cases (7%) harboring a
PIK3CA
mutation, and in three other cases (7%)
TP53
mutations were detected. This study showed that neuroendocrine breast carcinoma is a distinct subtype of luminal carcinoma with a low rate of
PIK3CA
mutations and with an aggressive clinical behavior. An accurate identification of neuroendocrine differentiation may be useful to better tailor patient adjuvant therapy within luminal carcinomas. |
| doi_str_mv | 10.1038/modpathol.2017.107 |
| format | Article |
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PIK3CA
mutation, and in three other cases (7%)
TP53
mutations were detected. This study showed that neuroendocrine breast carcinoma is a distinct subtype of luminal carcinoma with a low rate of
PIK3CA
mutations and with an aggressive clinical behavior. An accurate identification of neuroendocrine differentiation may be useful to better tailor patient adjuvant therapy within luminal carcinomas.</description><identifier>ISSN: 0893-3952</identifier><identifier>EISSN: 1530-0285</identifier><identifier>DOI: 10.1038/modpathol.2017.107</identifier><identifier>PMID: 28884749</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>13/51 ; 38/39 ; 45/23 ; 692/308/53/2421 ; 692/699/67/1347 ; Adult ; Aged ; Aged, 80 and over ; Breast cancer ; Breast carcinoma ; Breast Neoplasms - genetics ; Breast Neoplasms - mortality ; Breast Neoplasms - pathology ; Carcinoma, Neuroendocrine - genetics ; Carcinoma, Neuroendocrine - mortality ; Carcinoma, Neuroendocrine - pathology ; DNA Mutational Analysis ; Estrogens ; Female ; GATA-3 protein ; Humans ; Invasiveness ; Kaplan-Meier Estimate ; Laboratory Medicine ; Medical prognosis ; Medicine ; Medicine & Public Health ; Middle Aged ; Mutation ; Neuroendocrine tumors ; original-article ; p53 Protein ; Pathology ; Progesterone ; Prognosis ; Proportional Hazards Models ; Statistical analysis ; Survival ; Tumors</subject><ispartof>Modern pathology, 2018, Vol.31 (1), p.68-82</ispartof><rights>United States & Canadian Academy of Pathology USCAP, Inc 2018</rights><rights>Copyright Nature Publishing Group Jan 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c419t-ddee3eb95567b18e5e85a94ca34e432eea5416e85eba19063df067cc42250c743</citedby><cites>FETCH-LOGICAL-c419t-ddee3eb95567b18e5e85a94ca34e432eea5416e85eba19063df067cc42250c743</cites><orcidid>0000-0002-6100-0026</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28884749$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lavigne, Marion</creatorcontrib><creatorcontrib>Menet, Emmanuelle</creatorcontrib><creatorcontrib>Tille, Jean-Christophe</creatorcontrib><creatorcontrib>Lae, Marick</creatorcontrib><creatorcontrib>Fuhrmann, Laetitia</creatorcontrib><creatorcontrib>Bonneau, Claire</creatorcontrib><creatorcontrib>Deniziaut, Gabrielle</creatorcontrib><creatorcontrib>Melaabi, Samia</creatorcontrib><creatorcontrib>Ng, Charlotte C K</creatorcontrib><creatorcontrib>Marchiò, Caterina</creatorcontrib><creatorcontrib>Rouzier, Roman</creatorcontrib><creatorcontrib>Bièche, Ivan</creatorcontrib><creatorcontrib>Vincent-Salomon, Anne</creatorcontrib><title>Comprehensive clinical and molecular analyses of neuroendocrine carcinomas of the breast</title><title>Modern pathology</title><addtitle>Mod Pathol</addtitle><addtitle>Mod Pathol</addtitle><description>Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence, and prognosis remain controversial in the literature. The 2012 WHO classification of breast cancer categorizes neuroendocrine carcinomas into three morphologically distinct subtypes: well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation. We aimed to gain insight into the clinical, morphologic, phenotypic, and molecular features of 47 neuroendocrine breast carcinomas. Targeted next-generation sequencing by an AmpliSeq 22 cancer gene hotspot panel and the Prosigna assay were performed on 42/47 and 35/47 cases, respectively. Average age at diagnosis was 69 years. All tumors were estrogen receptor-positive and the large majority expressed progesterone receptor (89%), GATA3 (98%), FOXA1 (96%), and CK8/18 (98%). There was an almost equal distribution of luminal A (52%) and B (48%) carcinomas. Almost half of the cohort (49%) displayed a high risk of recurrence score with the Prosigna test. Patients with a neuroendocrine carcinoma had a shorter disease-free survival compared with those affected by carcinomas of no special type matched for age, size, grade, and estrogen receptor status. No significant differences were observed in terms of overall survival. Stratification of neuroendocrine carcinomas using the 2012 WHO criteria did not reveal statistically significant differences among the distinct categories (well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation), in terms of either progression-free or overall survival. Our targeted sequencing analysis found three cases (7%) harboring a
PIK3CA
mutation, and in three other cases (7%)
TP53
mutations were detected. This study showed that neuroendocrine breast carcinoma is a distinct subtype of luminal carcinoma with a low rate of
PIK3CA
mutations and with an aggressive clinical behavior. An accurate identification of neuroendocrine differentiation may be useful to better tailor patient adjuvant therapy within luminal carcinomas.</description><subject>13/51</subject><subject>38/39</subject><subject>45/23</subject><subject>692/308/53/2421</subject><subject>692/699/67/1347</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Breast cancer</subject><subject>Breast carcinoma</subject><subject>Breast Neoplasms - genetics</subject><subject>Breast Neoplasms - mortality</subject><subject>Breast Neoplasms - pathology</subject><subject>Carcinoma, Neuroendocrine - genetics</subject><subject>Carcinoma, Neuroendocrine - mortality</subject><subject>Carcinoma, Neuroendocrine - pathology</subject><subject>DNA Mutational Analysis</subject><subject>Estrogens</subject><subject>Female</subject><subject>GATA-3 protein</subject><subject>Humans</subject><subject>Invasiveness</subject><subject>Kaplan-Meier Estimate</subject><subject>Laboratory Medicine</subject><subject>Medical prognosis</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Mutation</subject><subject>Neuroendocrine tumors</subject><subject>original-article</subject><subject>p53 Protein</subject><subject>Pathology</subject><subject>Progesterone</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Statistical analysis</subject><subject>Survival</subject><subject>Tumors</subject><issn>0893-3952</issn><issn>1530-0285</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kEtLxDAUhYMozvj4Ay6k4MZNNc8mWcrgCwQ3Cu5Kmt5xOqTJmLTC_HszjooIri733O-ckIPQCcEXBDN12Yd2ZYZFcBcUE5k1uYOmRDBcYqrELppipVnJtKATdJDSEmPChaL7aEKVUlxyPUUvs9CvIizAp-4dCus631njCuPbog8O7OhMzJtx6wSpCPPCwxgD-DbY2PnsMNF2PvTm8zgsoGgimDQcob25cQmOv-Yher65fprdlQ-Pt_ezq4fScqKHsm0BGDRaiEo2RIEAJYzm1jAOnFEAIzipsgiNIRpXrJ3jSlrLKRXYSs4O0fk2dxXD2whpqPsuWXDOeAhjqolmUlBJOc7o2R90GcaYv7ahlKiwplRnim4pG0NKEeb1Kna9ieua4HrTe_3Te73pPWsym06_osemh_bH8l10BtgWSPnkXyH-evv_2A-oiZMR</recordid><startdate>2018</startdate><enddate>2018</enddate><creator>Lavigne, Marion</creator><creator>Menet, Emmanuelle</creator><creator>Tille, Jean-Christophe</creator><creator>Lae, Marick</creator><creator>Fuhrmann, Laetitia</creator><creator>Bonneau, Claire</creator><creator>Deniziaut, Gabrielle</creator><creator>Melaabi, Samia</creator><creator>Ng, Charlotte C K</creator><creator>Marchiò, Caterina</creator><creator>Rouzier, Roman</creator><creator>Bièche, Ivan</creator><creator>Vincent-Salomon, Anne</creator><general>Nature Publishing Group US</general><general>Elsevier Limited</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>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-6100-0026</orcidid></search><sort><creationdate>2018</creationdate><title>Comprehensive clinical and molecular analyses of neuroendocrine carcinomas of the breast</title><author>Lavigne, Marion ; Menet, Emmanuelle ; Tille, Jean-Christophe ; Lae, Marick ; Fuhrmann, Laetitia ; Bonneau, Claire ; Deniziaut, Gabrielle ; Melaabi, Samia ; Ng, Charlotte C K ; Marchiò, Caterina ; Rouzier, Roman ; Bièche, Ivan ; Vincent-Salomon, Anne</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-ddee3eb95567b18e5e85a94ca34e432eea5416e85eba19063df067cc42250c743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>13/51</topic><topic>38/39</topic><topic>45/23</topic><topic>692/308/53/2421</topic><topic>692/699/67/1347</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Breast cancer</topic><topic>Breast carcinoma</topic><topic>Breast Neoplasms - genetics</topic><topic>Breast Neoplasms - mortality</topic><topic>Breast Neoplasms - pathology</topic><topic>Carcinoma, Neuroendocrine - genetics</topic><topic>Carcinoma, Neuroendocrine - mortality</topic><topic>Carcinoma, Neuroendocrine - pathology</topic><topic>DNA Mutational Analysis</topic><topic>Estrogens</topic><topic>Female</topic><topic>GATA-3 protein</topic><topic>Humans</topic><topic>Invasiveness</topic><topic>Kaplan-Meier Estimate</topic><topic>Laboratory Medicine</topic><topic>Medical prognosis</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Mutation</topic><topic>Neuroendocrine tumors</topic><topic>original-article</topic><topic>p53 Protein</topic><topic>Pathology</topic><topic>Progesterone</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Statistical analysis</topic><topic>Survival</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lavigne, Marion</creatorcontrib><creatorcontrib>Menet, Emmanuelle</creatorcontrib><creatorcontrib>Tille, Jean-Christophe</creatorcontrib><creatorcontrib>Lae, Marick</creatorcontrib><creatorcontrib>Fuhrmann, Laetitia</creatorcontrib><creatorcontrib>Bonneau, Claire</creatorcontrib><creatorcontrib>Deniziaut, Gabrielle</creatorcontrib><creatorcontrib>Melaabi, Samia</creatorcontrib><creatorcontrib>Ng, Charlotte C K</creatorcontrib><creatorcontrib>Marchiò, Caterina</creatorcontrib><creatorcontrib>Rouzier, Roman</creatorcontrib><creatorcontrib>Bièche, Ivan</creatorcontrib><creatorcontrib>Vincent-Salomon, Anne</creatorcontrib><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>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</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>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</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>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Modern pathology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lavigne, Marion</au><au>Menet, Emmanuelle</au><au>Tille, Jean-Christophe</au><au>Lae, Marick</au><au>Fuhrmann, Laetitia</au><au>Bonneau, Claire</au><au>Deniziaut, Gabrielle</au><au>Melaabi, Samia</au><au>Ng, Charlotte C K</au><au>Marchiò, Caterina</au><au>Rouzier, Roman</au><au>Bièche, Ivan</au><au>Vincent-Salomon, Anne</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive clinical and molecular analyses of neuroendocrine carcinomas of the breast</atitle><jtitle>Modern pathology</jtitle><stitle>Mod Pathol</stitle><addtitle>Mod Pathol</addtitle><date>2018</date><risdate>2018</risdate><volume>31</volume><issue>1</issue><spage>68</spage><epage>82</epage><pages>68-82</pages><issn>0893-3952</issn><eissn>1530-0285</eissn><abstract>Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence, and prognosis remain controversial in the literature. The 2012 WHO classification of breast cancer categorizes neuroendocrine carcinomas into three morphologically distinct subtypes: well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation. We aimed to gain insight into the clinical, morphologic, phenotypic, and molecular features of 47 neuroendocrine breast carcinomas. Targeted next-generation sequencing by an AmpliSeq 22 cancer gene hotspot panel and the Prosigna assay were performed on 42/47 and 35/47 cases, respectively. Average age at diagnosis was 69 years. All tumors were estrogen receptor-positive and the large majority expressed progesterone receptor (89%), GATA3 (98%), FOXA1 (96%), and CK8/18 (98%). There was an almost equal distribution of luminal A (52%) and B (48%) carcinomas. Almost half of the cohort (49%) displayed a high risk of recurrence score with the Prosigna test. Patients with a neuroendocrine carcinoma had a shorter disease-free survival compared with those affected by carcinomas of no special type matched for age, size, grade, and estrogen receptor status. No significant differences were observed in terms of overall survival. Stratification of neuroendocrine carcinomas using the 2012 WHO criteria did not reveal statistically significant differences among the distinct categories (well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation), in terms of either progression-free or overall survival. Our targeted sequencing analysis found three cases (7%) harboring a
PIK3CA
mutation, and in three other cases (7%)
TP53
mutations were detected. This study showed that neuroendocrine breast carcinoma is a distinct subtype of luminal carcinoma with a low rate of
PIK3CA
mutations and with an aggressive clinical behavior. An accurate identification of neuroendocrine differentiation may be useful to better tailor patient adjuvant therapy within luminal carcinomas.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>28884749</pmid><doi>10.1038/modpathol.2017.107</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-6100-0026</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 13/51 38/39 45/23 692/308/53/2421 692/699/67/1347 Adult Aged Aged, 80 and over Breast cancer Breast carcinoma Breast Neoplasms - genetics Breast Neoplasms - mortality Breast Neoplasms - pathology Carcinoma, Neuroendocrine - genetics Carcinoma, Neuroendocrine - mortality Carcinoma, Neuroendocrine - pathology DNA Mutational Analysis Estrogens Female GATA-3 protein Humans Invasiveness Kaplan-Meier Estimate Laboratory Medicine Medical prognosis Medicine Medicine & Public Health Middle Aged Mutation Neuroendocrine tumors original-article p53 Protein Pathology Progesterone Prognosis Proportional Hazards Models Statistical analysis Survival Tumors |
| title | Comprehensive clinical and molecular analyses of neuroendocrine carcinomas of the breast |
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