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Understanding breast cancer heterogeneity through non-genetic heterogeneity

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Abstract

Intricacy in treatment and diagnosis of breast cancer has been an obstacle due to genotype and phenotype heterogeneity. Understanding of non-genetic heterogeneity mechanisms along with considering role of genetic heterogeneity may fill the gaps in landscape painting of heterogeneity. The main factors contribute to non-genetic heterogeneity including: transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division and various signal transduction from tumor ecosystem. Throughout this review, we desired to provide a conceptual framework focused on non-genetic heterogeneity, which has been intended to offer insight into prediction, diagnosis and treatment of breast cancer.

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Fig. 1

source of the heterogeneity. Transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division belong to intrinsic sources of non-genetic phenotypic and functional heterogeneity. Various signal transduction from TME in line with variation in TME component and topography cause extrinsic source of non-genetic heterogeneity in cancer

Fig. 2
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Fig. 4

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Abbreviations

CAFs:

Cancer-associated fibroblasts

TADs:

Topologically associating domains

CTCF:

CCCTC-binding factor

lncRNAs:

Long noncoding RNA

DMGs:

Methylated DNA regions

MDSCs:

Myeloid-derived suppressor cells

TAMs:

Tumor-associated macrophages

VECs:

Vascular endothelial cells

Program death ligand 1:

Expressing PD-L1

EMT/MET:

Epithelial to mesenchymal/mesenchymal to epithelial transition

CSCs:

Cancer stem-like cells

TME:

Tumor microenvironment

ICD:

Immunogenic cell death

HMGB1:

High-mobility group box 1 protein

HIF1α:

Hypoxia inducible factor 1 alpha

CTCs:

Circulating tumor cells

ctDNA:

Circulating tumor DNA

EVs:

Extracellular vesicles

MCT1:

Monocarboxylate transporter 1

BCSCs:

Breast cancer CSCs

CK14:

Cytokeratin-14

PDGF:

Platelet-derived growth factor

NSCCs:

Non-stem cancer cells

IHC:

Immunohistochemistry

IF:

Immunofluorescence

MERFISH:

Multiplexed error robust FISH

WGA:

Genome analysis

NGS:

Next-generation sequence

FACS:

Fluorescence-activated cell sorting

WTS:

Whole transcriptome sequencing

CyTOF:

Cytometry time of flight

MALDI:

Matrix-assisted laser desorption/ionization

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Acknowledgements

This research project was financially supported by Immunology Research Center at Tabriz University of Medical Sciences. This grant supported MSC thesis of Neda Barzgar Barough (The thesis code: 97/12/14 and ethical code: IR.TBZMED.VCR.REC.1398.288).

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Authors and Affiliations

  1. Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

    Neda Barzgar Barough, Fakhrosadat Sajjadian, Nazila Jalilzadeh & Kobra Velaei

  2. Department of Anatomical Sciences, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran

    Neda Barzgar Barough, Hajar Shafaei & Kobra Velaei

  3. Department of Radiology, Faculty of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran

    Fakhrosadat Sajjadian

  4. Department of Biochemistry, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

    Nazila Jalilzadeh

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  1. Neda Barzgar Barough
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  2. Fakhrosadat Sajjadian
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  3. Nazila Jalilzadeh
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  4. Hajar Shafaei
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  5. Kobra Velaei
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Correspondence to Kobra Velaei.

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N.B.B., F.S., and N.J. have participated in writing of main body of review article. In addition, H. Sh. has reviewed and edited the manuscript. Finally, K.V. was responsible for conceptualization, validation of different sections and illustration of figures.

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Barzgar Barough, N., Sajjadian, F., Jalilzadeh, N. et al. Understanding breast cancer heterogeneity through non-genetic heterogeneity. Breast Cancer 28, 777–791 (2021). https://doi.org/10.1007/s12282-021-01237-w

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