Deciphering breast cancer: from biology to the clinic
Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, c...
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Veröffentlicht in: | Cell 2023-04, Vol.186 (8), p.1708-1728 |
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description | Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, critical molecular drivers, clonal evolutionary trajectories, and prognostic signatures. Furthermore, multi-dimensional integration of high-resolution single-cell and spatial technologies has highlighted the importance of the entire breast cancer ecosystem and the presence of distinct cellular “neighborhoods.” Clinically, a plethora of new targeted therapies has emerged, now being rapidly incorporated into routine care. Resistance to therapy, however, remains a crucial challenge for the field.
Breast cancer is a complex and heterogeneous disease that is a leading cause of mortality in women. Understanding the disease subtypes, drivers, evolution, microenvironment, and resistance to therapy is providing new directions for the field and for patient care. |
doi_str_mv | 10.1016/j.cell.2023.01.040 |
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Breast cancer is a complex and heterogeneous disease that is a leading cause of mortality in women. Understanding the disease subtypes, drivers, evolution, microenvironment, and resistance to therapy is providing new directions for the field and for patient care.</description><subject>Breast Neoplasms - pathology</subject><subject>Breast Neoplasms - therapy</subject><subject>Drug Resistance, Neoplasm</subject><subject>Female</subject><subject>Gene Expression Profiling</subject><subject>Genomics</subject><subject>Humans</subject><subject>Transcriptome</subject><issn>0092-8674</issn><issn>1097-4172</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kD1PwzAURS0EglL4AwwoI0vCs2MnMWJB5VOqxAKzZTsvraukLnaK1H9PohZGpruce6V7CLmikFGgxe0qs9i2GQOWZ0Az4HBEJhRkmXJasmMyAZAsrYqSn5HzGFcAUAkhTslZXsicskJMiHhE6zZLDG69SExAHfvE6rXFcJc0wXeJcb71i13S-6RfYmJbt3b2gpw0uo14ecgp-Xx--pi9pvP3l7fZwzy1uSj6lBtaSURrkDGbg2mkBKltqSUKS6U2Whuodd2U3DAEVjCNTcNLbrUoK1HkU3Kz390E_7XF2KvOxfG0XqPfRsUqoLLiwPMBZXvUBh9jwEZtgut02CkKatSlVmpsqlGXAqoGXUPp-rC_NR3Wf5VfPwNwvwdwePntMKhoHQ56ahfQ9qr27r_9H1Fje10</recordid><startdate>20230413</startdate><enddate>20230413</enddate><creator>Nolan, Emma</creator><creator>Lindeman, Geoffrey J.</creator><creator>Visvader, Jane E.</creator><general>Elsevier Inc</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>7X8</scope><orcidid>https://orcid.org/0000-0001-9173-6977</orcidid></search><sort><creationdate>20230413</creationdate><title>Deciphering breast cancer: from biology to the clinic</title><author>Nolan, Emma ; Lindeman, Geoffrey J. ; Visvader, Jane E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-4b189eecbe22c30bf9909ac7a9e5c19abaab0dadf74b2e0262aeff474ca578563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Breast Neoplasms - pathology</topic><topic>Breast Neoplasms - therapy</topic><topic>Drug Resistance, Neoplasm</topic><topic>Female</topic><topic>Gene Expression Profiling</topic><topic>Genomics</topic><topic>Humans</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nolan, Emma</creatorcontrib><creatorcontrib>Lindeman, Geoffrey J.</creatorcontrib><creatorcontrib>Visvader, Jane E.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Cell</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nolan, Emma</au><au>Lindeman, Geoffrey J.</au><au>Visvader, Jane E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deciphering breast cancer: from biology to the clinic</atitle><jtitle>Cell</jtitle><addtitle>Cell</addtitle><date>2023-04-13</date><risdate>2023</risdate><volume>186</volume><issue>8</issue><spage>1708</spage><epage>1728</epage><pages>1708-1728</pages><issn>0092-8674</issn><eissn>1097-4172</eissn><abstract>Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, critical molecular drivers, clonal evolutionary trajectories, and prognostic signatures. Furthermore, multi-dimensional integration of high-resolution single-cell and spatial technologies has highlighted the importance of the entire breast cancer ecosystem and the presence of distinct cellular “neighborhoods.” Clinically, a plethora of new targeted therapies has emerged, now being rapidly incorporated into routine care. Resistance to therapy, however, remains a crucial challenge for the field.
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subjects | Breast Neoplasms - pathology Breast Neoplasms - therapy Drug Resistance, Neoplasm Female Gene Expression Profiling Genomics Humans Transcriptome |
title | Deciphering breast cancer: from biology to the clinic |
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