Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer
Purpose Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classific...
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| Veröffentlicht in: | Breast cancer research and treatment Jg. 199; H. 1; S. 1 - 12 |
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| Sprache: | Englisch |
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New York
Springer US
01.05.2023
Springer Springer Nature B.V |
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| ISSN: | 0167-6806, 1573-7217, 1573-7217 |
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| Abstract | Purpose
Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.
Methods
In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.
Results
IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.
Conclusion
We suggest that the Ki67 be changed to a cutoff of 20–25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. |
|---|---|
| AbstractList | Purpose
Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.
Methods
In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.
Results
IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.
Conclusion
We suggest that the Ki67 be changed to a cutoff of 20–25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment. In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay. IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes. We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. PurposeBreast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.MethodsIn a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.ResultsIHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.ConclusionWe suggest that the Ki67 be changed to a cutoff of 20–25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. Purpose Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment. Methods In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay. Results IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes. Conclusion We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.PURPOSEBreast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.METHODSIn a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.RESULTSIHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable.CONCLUSIONWe suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment. In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay. IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes. We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable. |
| Audience | Academic |
| Author | Dix-Peek, Thérèse van den Berg, Eunice J. Ruff, Paul Cubasch, Herbert Dickens, Caroline Neugut, Alfred I. Joffe, Maureen Jacobson, Judith S. Duarte, Raquel A. B. Phakathi, Boitumelo P. Augustine, Tanya N. |
| Author_xml | – sequence: 1 givenname: Thérèse orcidid: 0000-0002-7593-0857 surname: Dix-Peek fullname: Dix-Peek, Thérèse email: therese.dix-peek@wits.ac.za organization: Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand – sequence: 2 givenname: Boitumelo P. surname: Phakathi fullname: Phakathi, Boitumelo P. organization: Department of Surgery, School of Clinical Medicine, Faculty of Health Sciences, University of Kwa-Zulu Natal, Department of Surgery, Faculty of Health Sciences, University of the Witwatersrand – sequence: 3 givenname: Eunice J. surname: van den Berg fullname: van den Berg, Eunice J. organization: Department of Histopathology, National Health Laboratory Service, Chris Hani Baragwanath Hospital, Department of Anatomical Pathology, University of the Witwatersrand – sequence: 4 givenname: Caroline surname: Dickens fullname: Dickens, Caroline organization: Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand – sequence: 5 givenname: Tanya N. surname: Augustine fullname: Augustine, Tanya N. organization: School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand – sequence: 6 givenname: Herbert surname: Cubasch fullname: Cubasch, Herbert organization: Batho Pele Breast Unit, Chris Hani Baragwanath Academic Hospital, SA MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand – sequence: 7 givenname: Alfred I. surname: Neugut fullname: Neugut, Alfred I. organization: Herbert Irving Comprehensive Cancer Centre, Vagelos College of Physicians and Surgeons, Columbia University, Department of Epidemiology, Mailman School of Public Health, Columbia University – sequence: 8 givenname: Judith S. surname: Jacobson fullname: Jacobson, Judith S. organization: Herbert Irving Comprehensive Cancer Centre, Vagelos College of Physicians and Surgeons, Columbia University, Department of Epidemiology, Mailman School of Public Health, Columbia University – sequence: 9 givenname: Maureen surname: Joffe fullname: Joffe, Maureen organization: SA MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand, Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand – sequence: 10 givenname: Paul surname: Ruff fullname: Ruff, Paul organization: Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand, SA MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand – sequence: 11 givenname: Raquel A. B. orcidid: 0000-0003-2750-2062 surname: Duarte fullname: Duarte, Raquel A. B. organization: Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36867282$$D View this record in MEDLINE/PubMed |
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| DOI | 10.1007/s10549-023-06886-3 |
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| Keywords | Immunohistochemistry PAM50 Subtypes Breast cancer Sub-Saharan Africa |
| Language | English |
| License | 2023. The Author(s). Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
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| ORCID | 0000-0002-7593-0857 0000-0003-2750-2062 |
| OpenAccessLink | https://link.springer.com/10.1007/s10549-023-06886-3 |
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| PublicationDate | 2023-05-01 |
| PublicationDateYYYYMMDD | 2023-05-01 |
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| PublicationDecade | 2020 |
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| PublicationTitle | Breast cancer research and treatment |
| PublicationTitleAbbrev | Breast Cancer Res Treat |
| PublicationTitleAlternate | Breast Cancer Res Treat |
| PublicationYear | 2023 |
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No Title. https://Gco.iarc.fr/Today CheangMCUChiaSKVoducDGaoDLeungSSniderJKi67 index, HER2 status, and prognosis of patients with luminal B breast cancerJ Natl Cancer Inst20091017367501:CAS:528:DC%2BD1MXmtlyit74%3D10.1093/jnci/djp082194360382684553 PingJGuoXYeFLongJLipworthLCaiQDifferences in gene-expression profiles in breast cancer between African and European-ancestry womenCarcinogenesis20214188789310.1093/CARCIN/BGAA035 AllredDCIssues and updates: evaluating estrogen receptor-α, progesterone receptor, and HER2 in breast cancerMod Pathol201023S52S591:CAS:528:DC%2BC3cXlsFWjsbo%3D10.1038/modpathol.2010.5520436503 VanderpuyeVGroverSHammadNPrabhakarPSimondsHOlopadeFAn update on the management of breast cancer in AfricaInfect Agent Cancer20171211210.1186/s13027-017-0124-y VialeGThe current state of breast cancer classificationAnn Oncol201223x207x21010.1093/annonc/mds32622987963 AwadelkarimKDElhajAAcetoGMariani-CostantiniRAbdallaEEHereditary breast cancer in sub-saharan AfricaCurr Womens Health Rev20128445410.2174/157340412799079219 HuoDHuHRhieSKGamazonERCherniackADLiuJComparison of breast cancer molecular features and survival by African and European ancestry in the cancer genome atlasJAMA Oncol201731654166210.1001/jamaoncol.2017.0595284722345671371 SungHDeSantisCEFedewaSAKantelhardtEJJemalABreast cancer subtypes among Eastern-African–born black women and other black women in the United StatesCancer2019125340134111:CAS:528:DC%2BC1MXhslyhu7%2FJ10.1002/cncr.3229331190337 AdenijiAADawoduOOHabeebuMYOyekanAOBashirMAMartinMGDistribution of breast cancer subtypes among Nigerian women and correlation to the risk factors and clinicopathological characteristicsWorld J Oncol2020111651721:CAS:528:DC%2BB3cXisV2qtLfM10.14740/wjon1303328499577430856 PhakathiBCubaschHNietzSDickensCDix-PeekTJoffeMClinico-pathological characteristics among South African women with breast cancer receiving anti-retroviral therapy for HIVBreast20194312312910.1016/j.breast.2018.12.00530550925 NwaguGCBhattaraiSSwahnMAhmedSAnejaRPrevalence and mortality of triple-negative breast cancer in West Africa: biologic and sociocultural factorsJCO Glob Oncol202110.1200/go.21.00082342647598457872 ParadaHSunXFlemingJMWilliams-DeVaneCLRKirkELOlssonLTRace-associated biological differences among luminal A and basal-like breast cancers in the Carolina breast cancer studyBreast Cancer Res201719191:CAS:528:DC%2BC1cXitFWnu77E10.1186/s13058-017-0914-6 SayedSMolooZWasikeRBirdPOigaraRGovenderDIs breast cancer from Sub Saharan Africa truly receptor poor? Prevalence of ER/PR/HER2 in breast cancer from KenyaBreast20142359159610.1016/j.breast.2014.06.00625012047 HarrisLNIsmailaNMcShaneLMAndreFCollyarDEGonzalez-AnguloAMUse of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of clinical Oncology clinical practice guidelineJ Clin Oncol201634113411501:CAS:528:DC%2BC2sXnvF2rsQ%3D%3D10.1200/JCO.2015.65.2289268583394933134 FitzgibbonsPLDillonDAAlsabehRBermanMAHayesDFHicksDGTemplate for reporting results of biomarker testing of specimens from patients with carcinoma of the breastArch Pathol Lab Med201413859560110.5858/arpa.2013-0566-CP24236805 TroesterMASunXAllottEHGeradtsJCohenSMTseCKRacial differences in PAM50 subtypes in the Carolina breast cancer studyJ Natl Cancer Inst2017110171:CAS:528:DC%2BC1MXpt1agsL4%3D10.1093/jnci/djx135 ShoushaSOestrogen receptor status of breast carcinoma: Allred/H score conversion tableHistopathology2008533463471:STN:280:DC%2BD1cnmvVGnuw%3D%3D10.1111/j.1365-2559.2008.03075.x18631198 PuMMesserKDaviesSRVickeryTLPittmanEParkerBAResearch-based PAM50 signature and long-term breast cancer survivalBreast Cancer Res Treat20201791972061:CAS:528:DC%2BC1MXhvVakurfL10.1007/s10549-019-05446-y31542876 Fernandez-MartinezAPascualTPerroneGMoralesSde La HabaJGonzález-RiveraMLimitations in predicting PAM50 intrinsic subtype and risk of relapse score with Ki67 in estrogen receptor-positive HER2- negative breast cancerOncotarget20178219302193710.18632/oncotarget.1574828423537 Prosigna Insert (2015) Prosigna ® Breast cancer prognostic gene signature assay: 1–18. DowsettMNielsenTOA’HernRBartlettJCoombesRCCuzickJAssessment of Ki67 in breast cancer: recommendations from the international Ki67 in breast cancer working GroupJ Natl Cancer Inst2011103165616641:CAS:528:DC%2BC3MXhsFantrbF10.1093/jnci/djr393219607073216967 GoldhirschAWoodWCCoatesASGelberRDThurlimannBSennHJStrategies for subtypes-dealing with the diversity of breast cancer: highlights of the St Gallen international expert consensus on the primary therapy of early breast cancer 2011Ann Oncol201122173617471:STN:280:DC%2BC3Mjhs1ygug%3D%3D10.1093/annonc/mdr304217091403144634 CubaschHRuffPJoffeMNorrisSChirwaTNietzSSouth African breast cancer and HIV outcomes study: methods and baseline assessmentJ Glob Oncol2017311412410.1200/JGO.2015.00267528706996 MiguelFLopesLVFerreiraERibasEPelaezAFLealCBreast cancer in Angola, molecular subtypes: a first glanceEcancermedicalscience20171111010.3332/ecancer.2017.763 CoatesASWinerEPGoldhirschAGelberRDGnantMPiccart-GebhartMJTailoring therapies-improving the management of early breast cancer: St Gallen international expert consensus on the primary therapy of early breast cancer 2015Ann Oncol201526153315461:STN:280:DC%2BC2MfgsFWrsw%3D%3D10.1093/annonc/mdv221259398964511219 Department of Health Republic of South Africa (2017) Breast Cancer Control Policy. LundgrenCBendahlPOBorgÅEhingerAHegardtCLarssonCAgreement between molecular subtyping and surrogate subtype classification: a contemporary population-based study of ER-positive/HER2-negative primary breast cancerBreast Cancer Res Treat20191784594671:CAS:528:DC%2BC1MXhs1art73K10.1007/s10549-019-05378-7314323676797629 NielsenTWalldenBSchaperCFerreeSLiuSGaoDAnalytical validation of the PAM50-based prosigna breast cancer prognostic gene signature assay and nCounter analysis system using formalin-fixed paraffin-embedded breast tumor specimensBMC Cancer2014141771:CAS:528:DC%2BC2cXhvVymt7vM10.1186/1471-2407-14-177246250034008304 AchilonuOJSinghENimakoGEijkemansRMJCMusengeERule-based information extraction from free-text pathology reports reveals trends in South african female breast cancer molecular subtypes and Ki67 expressionBiomed Res Int202220221171:CAS:528:DC%2BB38XkvFCisbY%3D10.1155/2022/6157861 StefanDCCancer care in Africa: an overview of resourcesJ Glob Oncol20151303610.1200/jgo.2015.000406288047695551648 HarbeckNThomssenCGnantMSt. GallenBrief preliminary summary of the consensus discussionBreast Care20132013810210910.1159/000351193 BastienRRLRodríguez-LescureÁEbbertMTWPratAMunárrizBRoweLPAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markersBMC Med Genomics20125441:CAS:528:DC%2BC38XhslehsrvN10.1186/1755-8794-5-44230358823487945 WisemanRJRiddinJJugathpalJParrishAGRuffPBlockmanMAdjuvant trastuzumab in early HER2-positi G Viale (6886_CR6) 2012; 23 HJ Burstein (6886_CR28) 2019; 30 RJ Wiseman (6886_CR33) 2020; 110 VA McCormack (6886_CR43) 2013; 15 D Huo (6886_CR36) 2017; 3 KD Awadelkarim (6886_CR42) 2012; 8 S Shousha (6886_CR9) 2008; 53 HK Kim (6886_CR46) 2019; 51 M Galukande (6886_CR48) 2014; 17 A Goldhirsch (6886_CR5) 2011; 22 MA Troester (6886_CR38) 2017; 110 A Noske (6886_CR12) 2020; 49 J Harvey (6886_CR24) 1999; 17 (6886_CR22) 2017 AA Adeniji (6886_CR50) 2020; 11 CA Anyigba (6886_CR3) 2021; 246 6886_CR31 A Fernandez-Martinez (6886_CR29) 2017; 8 M Dowsett (6886_CR11) 2011; 103 DC Allred (6886_CR8) 2010; 23 6886_CR1 MCU Cheang (6886_CR10) 2009; 101 V Vanderpuye (6886_CR47) 2017; 12 C Lundgren (6886_CR35) 2019; 178 H Sung (6886_CR41) 2019; 125 C Dickens (6886_CR15) 2014; 23 P Popli (6886_CR45) 2021 S Robertson (6886_CR34) 2018; 71 GC Nwagu (6886_CR40) 2021 H Cubasch (6886_CR21) 2017; 3 DC Stefan (6886_CR2) 2015; 1 N Harbeck (6886_CR23) 2013; 2013 F Miguel (6886_CR52) 2017; 11 CM Perou (6886_CR4) 2000; 406 H Parada (6886_CR37) 2017; 19 RRL Bastien (6886_CR26) 2012; 5 OJ Achilonu (6886_CR20) 2022; 2022 J Ping (6886_CR39) 2021; 41 SNC Elmore (6886_CR53) 2021; 10 CA Adebamowo (6886_CR49) 2008; 110 ER Paquet (6886_CR32) 2015; 107 S Sayed (6886_CR44) 2014; 23 AS Coates (6886_CR13) 2015; 26 PL Fitzgibbons (6886_CR25) 2014; 138 EJ Van Den Berg (6886_CR17) 2021; 29 B Phakathi (6886_CR19) 2019; 43 T Nielsen (6886_CR27) 2014; 14 M Brandão (6886_CR51) 2020; 5 LN Harris (6886_CR14) 2016; 34 D Allred (6886_CR7) 1998; 11 M Pu (6886_CR30) 2020; 179 6886_CR18 6886_CR16 |
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population-based study of ER-positive/HER2-negative primary breast cancerBreast Cancer Res Treat20191784594671:CAS:528:DC%2BC1MXhs1art73K10.1007/s10549-019-05378-7314323676797629 – reference: PingJGuoXYeFLongJLipworthLCaiQDifferences in gene-expression profiles in breast cancer between African and European-ancestry womenCarcinogenesis20214188789310.1093/CARCIN/BGAA035 – reference: ElmoreSNCMushongaMIyerHSKandaCChibondaSChipidzaFBreast cancer in Zimbabwe: patterns of care and correlates of adherence in a national referral hospital radiotherapy center cohort from 2014 to 2018Cancer Med2021103489349810.1002/cam4.3764339733998178482 – reference: DickensCDuarteRZietsmanACubaschHKellettPSchuzJRacial comparison of receptor-defined breast cancer in Southern African women: Subtype prevalence and age—incidence analysis of nationwide cancer registry dataCancer Epidemiol Biomarkers Prev2014232311232110.1158/1055-9965.EPI-14-060325143359 – reference: 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Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are... Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using... Purpose Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are... PurposeBreast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified... |
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| SubjectTerms | Biomarkers, Tumor - genetics Biomarkers, Tumor - metabolism Breast cancer Breast Neoplasms - pathology Cancer research Care and treatment Discordance ErbB-2 protein Female Gene expression Genes Genomics Humans Immunohistochemistry Ki-67 Antigen - genetics Medical research Medicine Medicine & Public Health Medicine, Experimental Oncology Patients Preclinical Study Receptor, ErbB-2 - genetics Receptor, ErbB-2 - metabolism Receptors, Progesterone - genetics Receptors, Progesterone - metabolism South Africa - epidemiology Tumors Women |
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| Title | Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer |
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