Literature DB >> 30718355

Genetic Ancestry-dependent Differences in Breast Cancer-induced Field Defects in the Tumor-adjacent Normal Breast.

Harikrishna Nakshatri1,2,3, Brijesh Kumar4, Heather N Burney5, Mary L Cox6,3, Max Jacobsen6, George E Sandusky6,3, Crislyn D'Souza-Schorey7, Anna Maria V Storniolo3,8.   

Abstract

PURPOSE: Genetic ancestry influences evolutionary pathways of cancers. However, whether ancestry influences cancer-induced field defects is unknown. The goal of this study was to utilize ancestry-mapped true normal breast tissues as controls to identify cancer-induced field defects in normal tissue adjacent to breast tumors (NATs) in women of African American (AA) and European (EA) ancestry. EXPERIMENTAL
DESIGN: A tissue microarray comprising breast tissues of ancestry-mapped 100 age-matched healthy women from the Komen Tissue Bank (KTB) at Indiana University (Indianapolis, IN) and tumor-NAT pairs from 100 women (300 samples total) was analyzed for the levels of ZEB1, an oncogenic transcription factor that is central to cell fate, mature luminal cell-enriched estrogen receptor alpha (ERα), GATA3, FOXA1, and for immune cell composition.
RESULTS: ZEB1+ cells, which were localized surrounding the ductal structures of the normal breast, were enriched in the KTB-normal of AA compared with KTB-normal of EA women. In contrast, in EA women, both NATs and tumors compared with KTB-normal contained higher levels of ZEB1+ cells. FOXA1 levels were lower in NATs compared with KTB-normal in AA but not in EA women. We also noted variations in the levels of GATA3, CD8+ T cells, PD1+ immune cells, and PDL1+ cell but not CD68+ macrophages in NATs of AA and EA women. ERα levels did not change in any of our analyses, pointing to the specificity of ancestry-dependent variations.
CONCLUSIONS: Genetic ancestry-mapped tissues from healthy individuals are required for proper assessment and development of cancer-induced field defects as early cancer detection markers. This finding is significant in light of recent discoveries of influence of genetic ancestry on both normal biology and tumor evolution. ©2019 American Association for Cancer Research.

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Year:  2019        PMID: 30718355     DOI: 10.1158/1078-0432.CCR-18-3427

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  10 in total

1.  Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.

Authors:  Hanyin Wang; Yikuan Li; Seema A Khan; Yuan Luo
Journal:  Artif Intell Med       Date:  2020-11-01       Impact factor: 5.326

2.  GSIAR: gene-subcategory interaction-based improved deep representation learning for breast cancer subcategorical analysis using gene expression, applicable for precision medicine.

Authors:  Chiranjib Sur
Journal:  Med Biol Eng Comput       Date:  2019-10-07       Impact factor: 2.602

3.  Dual TGFβ/BMP Pathway Inhibition Enables Expansion and Characterization of Multiple Epithelial Cell Types of the Normal and Cancerous Breast.

Authors:  Mayuri Prasad; Brijesh Kumar; Poornima Bhat-Nakshatri; Manjushree Anjanappa; George Sandusky; Kathy D Miller; Anna Maria Storniolo; Harikrishna Nakshatri
Journal:  Mol Cancer Res       Date:  2019-04-16       Impact factor: 5.852

4.  Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer.

Authors:  Denys Rujchanarong; Danielle Scott; Yeonhee Park; Sean Brown; Anand S Mehta; Richard Drake; George E Sandusky; Harikrishna Nakshatri; Peggi M Angel
Journal:  Front Oncol       Date:  2022-06-27       Impact factor: 5.738

5.  A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells.

Authors:  Poornima Bhat-Nakshatri; Hongyu Gao; Liu Sheng; Patrick C McGuire; Xiaoling Xuei; Jun Wan; Yunlong Liu; Sandra K Althouse; Austyn Colter; George Sandusky; Anna Maria Storniolo; Harikrishna Nakshatri
Journal:  Cell Rep Med       Date:  2021-03-16

6.  TF-Marker: a comprehensive manually curated database for transcription factors and related markers in specific cell and tissue types in human.

Authors:  Mingcong Xu; Xuefeng Bai; Bo Ai; Guorui Zhang; Chao Song; Jun Zhao; Yuezhu Wang; Ling Wei; Fengcui Qian; Yanyu Li; Xinyuan Zhou; Liwei Zhou; Yongsan Yang; Jiaxin Chen; Jiaqi Liu; Desi Shang; Xuan Wang; Yu Zhao; Xuemei Huang; Yan Zheng; Jian Zhang; Qiuyu Wang; Chunquan Li
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

7.  Aberrant epigenetic and transcriptional events associated with breast cancer risk.

Authors:  Natascia Marino; Rana German; Ram Podicheti; Douglas B Rusch; Pam Rockey; Jie Huang; George E Sandusky; Constance J Temm; Sandra Althouse; Kenneth P Nephew; Harikrishna Nakshatri; Jun Liu; Ashley Vode; Sha Cao; Anna Maria V Storniolo
Journal:  Clin Epigenetics       Date:  2022-02-09       Impact factor: 6.551

8.  Compliant, Tough, Anti-Fatigue, Self-Recovery, and Biocompatible PHEMA-Based Hydrogels for Breast Tissue Replacement Enabled by Hydrogen Bonding Enhancement and Suppressed Phase Separation.

Authors:  Hongyan Ouyang; Xiangyan Xie; Yuanjie Xie; Di Wu; Xingqi Luo; Jinrong Wu; Yi Wang; Lijuan Zhao
Journal:  Gels       Date:  2022-08-25

9.  Bidirectional Regulatory Cross-Talk between Cell Context and Genomic Aberrations Shapes Breast Tumorigenesis.

Authors:  Brijesh Kumar; Poornima Bhat-Nakshatri; Calli Maguire; Max Jacobsen; Constance J Temm; George Sandusky; Harikrishna Nakshatri
Journal:  Mol Cancer Res       Date:  2021-07-20       Impact factor: 5.852

10.  Haplotypes of single cancer driver genes and their local ancestry in a highly admixed long-lived population of Northeast Brazil.

Authors:  Steffany Larissa Galdino Galisa; Priscila Lima Jacob; Allysson Allan de Farias; Renan Barbosa Lemes; Leandro Ucela Alves; Júlia Cristina Leite Nóbrega; Mayana Zatz; Silvana Santos; Mathias Weller
Journal:  Genet Mol Biol       Date:  2022-02-02       Impact factor: 1.771

  10 in total

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