Regulation of cancer stem cells in triple negative breast cancer

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Abstract

Triple Negative Breast Cancer (TNBC) is the most lethal subtype of breast cancer. Despite the successes of emerging targeted therapies, relapse, recurrence, and therapy failure rates in TNBC significantly outpace other subtypes of breast cancer. Mounting evidence suggests accumulation of therapy resistant Cancer Stem Cell (CSC) populations within TNBCs contributes to poor clinical outcomes. These CSCs are enriched in TNBC compared to non-TNBC breast cancers. The mechanisms underlying CSC accumulation have been well-characterized and discussed in other reviews. In this review, we focus on TNBC-specific mechanisms that allow the expansion and activity of self-renewing CSCs. We highlight cellular signaling pathways and transcription factors, specifically enriched in TNBC over non-TNBC breast cancer, contributing to stemness. We also analyze publicly available single-cell RNA-seq data from basal breast cancer tumors to highlight the potential of emerging bioinformatic approaches in identifying novel drivers of stemness in TNBC and other cancers.

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Most cited references 224

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Integrating single-cell transcriptomic data across different conditions, technologies, and species

Rahul Satija, Efthymia Papalexi, Peter Smibert … (2018)

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

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Molecular mechanisms of epithelial-mesenchymal transition.

Samy Lamouille, Jian Xu, Rik Derynck (2014)

The transdifferentiation of epithelial cells into motile mesenchymal cells, a process known as epithelial-mesenchymal transition (EMT), is integral in development, wound healing and stem cell behaviour, and contributes pathologically to fibrosis and cancer progression. This switch in cell differentiation and behaviour is mediated by key transcription factors, including SNAIL, zinc-finger E-box-binding (ZEB) and basic helix-loop-helix transcription factors, the functions of which are finely regulated at the transcriptional, translational and post-translational levels. The reprogramming of gene expression during EMT, as well as non-transcriptional changes, are initiated and controlled by signalling pathways that respond to extracellular cues. Among these, transforming growth factor-β (TGFβ) family signalling has a predominant role; however, the convergence of signalling pathways is essential for EMT.

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Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.

Anoop Patel, Itay Tirosh, John J. Trombetta … (2014)

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy. Copyright © 2014, American Association for the Advancement of Science.

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Author and article information

Journal

Journal ID (nlm-ta): Cancer Drug Resist

Journal ID (iso-abbrev): Cancer Drug Resist

Title: Cancer Drug Resistance

Publisher: OAE Publishing Inc.

ISSN (Electronic): 2578-532X

Publication date Collection: 2021

Publication date (Electronic): 19 June 2021

Volume: 4

Issue: 2

Pages: 321-342

Affiliations

¹Department of Pathology and Laboratory Medicine, University of Pennsylvania , Philadelphia, PA 19140, USA.

²Department of Biological Sciences, The University of the Sciences , Philadelphia, PA 19140, USA.

Author notes

Correspondence Address: Dr. Bela Peethambaran, Department of Biological Sciences, The University of the Sciences, 600 S 34rd St, Philadelphia, PA 19104, USA. E-mail: b.peethambaran@ 123456usciences.edu

Academic Editor: Godefridus J. Peters | Copy Editor: Yue-Yue Zhang | Production Editor: Jing Yu

Article

DOI: 10.20517/cdr.2020.106

PMC ID: 9019272

PubMed ID: 35582030

SO-VID: f2d81d1f-a43d-49fb-a2b1-e97bfa38d34e

License:

© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

History

Date received : 24 November 2020

Date revision received : 28 December 2020

Date accepted : 06 January 2021

Funding

Funded by: the Endowed Roth Funds for Natural Products awarded to Dr. Bela Peethambaran by The University of the Sciences, Philadelphia 19104

Regulation of cancer stem cells in triple negative breast cancer

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Karger: Oncology

Most cited references 224

Integrating single-cell transcriptomic data across different conditions, technologies, and species

Molecular mechanisms of epithelial-mesenchymal transition.

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.

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