Literature DB >> 28428285

Characterisation of GATA3 expression in invasive breast cancer: differences in histological subtypes and immunohistochemically defined molecular subtypes.

Tang Shaoxian1,2, Yu Baohua1,2, Xu Xiaoli1,2, Cheng Yufan1,2, Tu Xiaoyu1,2, Lu Hongfen1,2, Bi Rui1,2, Sun Xiangjie1,2, Shui Ruohong1,2, Yang Wentao1,2.   

Abstract

AIMS: GATA-binding protein 3 (GATA3) is a sensitive and relatively specific marker in breast and urothelial carcinomas. Its diagnostic utility in primary and metastatic breast cancers has been explored and confirmed. However, the relationship between GATA3 expression and different breast carcinoma intrinsic subtypes has not been specifically defined in the literature despite a few reports with a small number of cases. The aim of the current investigation is to clarify GATA3 expression among different histological subtypes and surrogate molecular breast carcinoma subtypes in a large series of cases.
METHODS: Immunohistochemical staining of GATA3, GCDFP15 and mammaglobin was performed in a cohort of 1637 cases of primary invasive breast carcinoma. The association of GATA3 expression with different histological and surrogate intrinsic subtypes was assessed and compared with the expression of GCDFP15 and mammaglobin.
RESULTS: The overall positivity of GATA3 across the various immunohistochemistry-based surrogate intrinsic subtypes was 99.51% for luminal A-like, 97.70% for luminal B-like, 68.50% for HER2 overexpression and 20.16% for triple negative breast cancers. GATA3 expression was positively correlated with estrogen receptor (ER)-positive (luminal subtypes) breast carcinomas. For luminal-like and HER2 overexpression subtypes, GATA3 was much more sensitive than GCDFP15 and mammaglobin. For triple negative tumours, GATA3 was less sensitive than GCDFP15.
CONCLUSIONS: GATA3 exhibits a relatively high sensitivity for breast carcinomas. It is more sensitive than GCDFP15 and mammaglobin in luminal-like and HER2 overexpression subtypes. GATA3 expression is associated with breast carcinomas of luminal subtype and low histological grade. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Entities:  

Keywords:  BREAST; CARCINOMA; IMMUNOHISTOCHEMISTRY

Mesh:

Substances:

Year:  2017        PMID: 28428285     DOI: 10.1136/jclinpath-2016-204137

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  9 in total

1.  Clinical outcomes and prognostic biomarkers among pregnant, post-partum and nulliparous women with breast cancer: a prospective cohort study.

Authors:  Katarzyna J Jerzak; Nechama Lipton; Sharon Nofech-Mozes; Dina Boles; Elzbieta Slodkowska; Gregory R Pond; Ellen Warner
Journal:  Breast Cancer Res Treat       Date:  2021-07-27       Impact factor: 4.872

2.  Identification of candidate genes associated with triple negative breast cancer.

Authors:  Audrey Player; Nissi Abraham; Kayla Burrell; Iria Ondo Bengone; Anthony Harris; Lisa Nunez; Telisa Willaims; Sharon Kwende; Wiley Walls
Journal:  Genes Cancer       Date:  2017-07

3.  Detection and genomic characterization of a mammary-like adenocarcinoma.

Authors:  Jasleen K Grewal; Peter Eirew; Martin Jones; Kenrry Chiu; Basile Tessier-Cloutier; Anthony N Karnezis; Aly Karsan; Andy Mungall; Chen Zhou; Stephen Yip; Anna V Tinker; Janessa Laskin; Marco Marra; Steven J M Jones
Journal:  Cold Spring Harb Mol Case Stud       Date:  2017-11-21

4.  Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Authors:  Mingxin Tao; Tianci Song; Wei Du; Siyu Han; Chunman Zuo; Ying Li; Yan Wang; Zekun Yang
Journal:  Genes (Basel)       Date:  2019-03-07       Impact factor: 4.096

5.  Cytokeratin 7-negative and GATA binding protein 3-negative breast cancers: Clinicopathological features and prognostic significance.

Authors:  Shaolei Lu; Evgeny Yakirevich; Li Juan Wang; Murray B Resnick; Yihong Wang
Journal:  BMC Cancer       Date:  2019-11-12       Impact factor: 4.430

6.  Temporal Heterogeneity of HER2 Expression and Spatial Heterogeneity of 18F-FDG Uptake Predicts Treatment Outcome of Pyrotinib in Patients with HER2-Positive Metastatic Breast Cancer.

Authors:  Chengcheng Gong; Cheng Liu; Zhonghua Tao; Jian Zhang; Leiping Wang; Jun Cao; Yannan Zhao; Yizhao Xie; Xichun Hu; Zhongyi Yang; Biyun Wang
Journal:  Cancers (Basel)       Date:  2022-08-17       Impact factor: 6.575

7.  Characterization of PIK3CA and PIK3R1 somatic mutations in Chinese breast cancer patients.

Authors:  Li Chen; Liu Yang; Ling Yao; Xia-Ying Kuang; Wen-Jia Zuo; Shan Li; Feng Qiao; Yi-Rong Liu; Zhi-Gang Cao; Shu-Ling Zhou; Xiao-Yan Zhou; Wen-Tao Yang; Jin-Xiu Shi; Wei Huang; Xin Hu; Zhi-Ming Shao
Journal:  Nat Commun       Date:  2018-04-10       Impact factor: 14.919

8.  Convolutional neural network models for cancer type prediction based on gene expression.

Authors:  Milad Mostavi; Yu-Chiao Chiu; Yufei Huang; Yidong Chen
Journal:  BMC Med Genomics       Date:  2020-04-03       Impact factor: 3.063

9.  GATA3 as an Adjunct Prognostic Factor in Breast Cancer Patients with Less Aggressive Disease: A Study with a Review of the Literature.

Authors:  Patrizia Querzoli; Massimo Pedriali; Rosa Rinaldi; Paola Secchiero; Paolo Giorgi Rossi; Elisabetta Kuhn
Journal:  Diagnostics (Basel)       Date:  2021-03-28
  9 in total

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