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. 2024 Sep:47:102055.
doi: 10.1016/j.tranon.2024.102055. Epub 2024 Jul 13.

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Affiliations

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Mudassir Hassan et al. Transl Oncol. 2024 Sep.

Abstract

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

Keywords: Breast cancer; Drug resistance; Immune subtypes; Non-genetic heterogeneity; Tumor immune microenvironment.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image, graphical abstract
Graphical abstract
Fig 1
Fig. 1
Sources of non-genetic heterogeneity. Intrinsic sources of non-genetic heterogeneity are 1) epigenetics, 2) transcriptomic, 3) proteomic, 4) metabolic alterations, and 5) cell plasticity. While extrinsic variables have variations in signaling pathways which are caused by changes in the tumor microenvironment or therapy-induced changes.
Fig 2
Fig. 2
Immune-related subtypes of breast cancer. Cluster A is classified as the Immune Cold and shows low immune infiltration, Cluster B is labeled as Pro-tumorigenic (Promoting tumorigenesis) while Cluster C is termed as Immune Hot and exhibits a high presence of the activated immune cells.
Fig 3
Fig. 3
Immunostimulatory and immunosuppressive response of tumor microenvironment complex and role of transcription factors in breast cancer progression.

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References

    1. Siegel R.L., Miller K.D., Jemal A. Cancer statistics, 2018. CA Cancer J. Clin. 2018;68(1):7–30. - PubMed
    1. Bray F., Ferlay J., Soerjomataram I., Siegel R.L., Torre L.A., Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018;68(6):394–424. - PubMed
    1. DeSantis C.E., Ma J., Gaudet M.M., Newman L.A., Miller K.D., Sauer A.G., Jemal A., Siegel R.L. Breast cancer statistics, 2019. CA Cancer J. Clin. 2019;69(6):438–451. - PubMed
    1. Shaath H., Elango R., Alajez N.M. Molecular classification of breast cancer utilizing long non-coding RNA (lncRNA) transcriptomes identifies novel diagnostic lncRNA panel for triple-negative breast cancer. Cancers (Basel) 2021;13(21):5350. - PMC - PubMed
    1. Cornwell J.A., Hallett R.M., Auf der Mauer S., Motazedian A., Schroeder T., Draper J.S., Harvey R.P., Nordon R.E. Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis. Sci. Rep. 2016;6:27100. - PMC - PubMed

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