scholarly journals Epigenome erosion drives neural crest-like phenotypic mimicry in triple-negative breast cancer and other SOX10+ malignancies

2021 ◽  
Author(s):  
Jodi M Saunus ◽  
Xavier M De Luca ◽  
Korinne Northwood ◽  
Ashwini Raghavendra ◽  
Alexander Hasson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Phenotypic Plasticity ◽  
Network Analysis ◽  
Neural Crest ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Open Chromatin ◽  
Ancestral Gene ◽  
Normal Human Breast ◽  
Intratumoural Heterogeneity

Background: Intratumoural heterogeneity is a poor prognostic feature in triple-negative breast cancer (TNBC) and other high-grade malignancies. It is caused by genomic instability and phenotypic plasticity, but how these features co-evolve during tumour development remains unclear. SOX10 is a transcription factor, neural crest stem cell (NCSC) specifier and candidate mediator of cancer-associated phenotypic plasticity. Methods: Using immunophenotyping, we investigated the expression of SOX10 in normal human breast tissue and breast cancer (n=21 cosmetic breast reduction and 1,860 tumour samples with clinical annotation). We then defined the context and evolution of its expression in TNBC compared to 21 other malignancies using systems-level transcriptomics. Results: SOX10 was detected in nuclei of normal mammary luminal progenitor cells, the histogenic origin of most TNBCs. In breast cancer, nuclear SOX10 predicted poor outcome amongst cross-sectional (log-rank p=0.0015, hazard ratio 2.02, n=224) and metaplastic (log-rank p=0.04, n=66) TNBCs. Systems-level transcriptional network analysis identified a core module in SOX10′s normal mammary epithelial transcription program that is rewired to NCSC genes in TNBC. Reprogramming was proportional to DNA damage and genome-wide promoter hypomethylation, particularly at CpG island shores. Using a novel network analysis pipeline, we found that NCSC-like transcriptional reprogramming is also strongly associated with promoter hypomethylation in other SOX10+ malignancies: glioma and melanoma. Conclusions: We propose that cancer-associated genome hypomethylation simulates the open chromatin landscape of more primitive cell states, and that on this relatively unrestricted background, SOX10 recreates its ancestral gene regulatory circuits by default. These findings provide new insights about the basis of intratumoural heterogeneity and resurrection of developmental phenotypes in cancer; and highlight the potential for therapeutics that limit chromatin remodelling.

scholarly journals Berberine Impairs the Survival of Triple Negative Breast Cancer Cells: Cellular and Molecular Analyses

Molecules ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 506 ◽  
Author(s):  
Lamyae El Khalki ◽  
Virginie Maire ◽  
Thierry Dubois ◽  
Abdelmajid Zyad
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Subtype ◽  
Potential Candidate ◽  
Tnbc Cell ◽  
Normal Human Breast ◽  
Good Potential ◽  
Breast Cells

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype. Non-available targeted therapy for TNBC represents its biggest treatment challenge. Thus, finding new promising effective drugs is urgently needed. In the present study, we investigated how berberine, a natural isoquinoline, impairs the survival of TNBC cells in both cellular and molecular levels. Our experimental model was based on the use of eight TNBC cell lines: MDA-MB-468, MDA-MB-231, HCC70, HCC38, HCC1937, HCC1143, BT-20, and BT-549. Berberine was cytotoxic against all treated TNBC cell lines. The most sensitive cell lines were HCC70 (IC50 = 0.19 µM), BT-20 (IC50 = 0.23 µM) and MDA-MB-468 (IC50 = 0.48 µM). Using flow cytometry techniques, berberine, at 0.5 and 1 µM for 120 and 144 h, not only induced cell cycle arrest, at G1 and/or G2/M phases, but it also triggered significant apoptosis. At the molecular level, these results are consistent with the expression of their related proteins using Western blot assays. Interestingly, while berberine was cytotoxic against TNBC cells, it had no effect on the viability of normal human breast cells MCF10A cultured in a 3D matrigel model. These results suggest that berberine may be a good potential candidate for TNBC drug development.

Abstract LB-409: Network analysis of RNA-seq data comparing triple negative breast cancer to normal breast tissues

2012 ◽  
Author(s):  
Milan Radovich ◽  
Susan E. Clare ◽  
George W. Sledge ◽  
Ivanesa Pardo ◽  
Theresa Mathieson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Normal Breast ◽  
Rna Seq ◽  
Breast Tissues

Novel key genes in triple‐negative breast cancer identified by weighted gene co‐expression network analysis

2019 ◽  
Vol 120 (10) ◽  
pp. 16900-16912 ◽  
Author(s):  
Jian Chen ◽  
Xiaojun Qian ◽  
Yifu He ◽  
Xinghua Han ◽  
Yueyin Pan
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Key Genes

scholarly journals Evidence for Phenotypic Plasticity in Aggressive Triple-Negative Breast Cancer: Human Biology Is Recapitulated by a Novel Model System

PLoS ONE ◽  
2012 ◽  
Vol 7 (9) ◽  
pp. e45684 ◽  
Author(s):  
Nicholas C. D’Amato ◽  
Julie H. Ostrander ◽  
Michelle L. Bowie ◽  
Christopher Sistrunk ◽  
Alexander Borowsky ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Phenotypic Plasticity ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Model System ◽  
Human Biology ◽  
Novel Model

scholarly journals Identification of Metastasis-Associated Genes in Triple-Negative Breast Cancer Using Weighted Gene Co-expression Network Analysis

2020 ◽  
Vol 16 ◽  
pp. 117693432095486
Author(s):  
Wenting Xie ◽  
Zhongshi Du ◽  
Yijie Chen ◽  
Naxiang Liu ◽  
Zhaoming Zhong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Candidate Genes ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Characteristic Curve ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Diagnosis And Prognosis

Triple-negative breast cancer (TNBC) is the most aggressive and fatal sub-type of breast cancer. This study aimed to identify metastasis-associated genes that could serve as biomarkers for TNBC diagnosis and prognosis. RNA-seq data and clinical information on TNBC from the Cancer Genome Atlas were used to conduct analyses. Expression data were used to establish co-expression modules using average linkage hierarchical clustering. We used weighted gene co-expression network analysis to explore the associations between gene sets and clinical features and to identify metastasis-associated candidate biomarkers. The K-M plotter website was used to explore the association between the expression of candidate biomarkers and patient survival. In addition, receiver operating characteristic curve analysis was used to illustrate the diagnostic performance of candidate genes. The pale turquoise module was significantly associated with the occurrence of metastasis. In this module, 64 genes were identified, and its functional enrichment analysis revealed that they were mainly associated with transcriptional misregulation in cancer, microRNAs in cancer, and negative regulation of angiogenesis. Further, 4 genes, IGSF10, RUNX1T1, XIST, and TSHZ2, which were negatively associated with relapse-free survival and have seldom been reported before in TNBC, were selected. In addition, the mRNA expression levels of the 4 candidate genes were significantly lower in TNBC tumor tissues compared with healthy tissues. Based on the K-M plotter, these 4 genes were correlated with poor prognosis of TNBC. The area under the curve of IGSF10, RUNX1T1, TSHZ2, and XIST was 0.918, 0.957, 0.977, and 0.749. These findings provide new insight into TNBC metastasis. IGSF10, RUNX1T1, TSHZ2, and XIST could be used as candidate biomarkers for the diagnosis and prognosis of TNBC metastasis.

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