Understanding breast cancer heterogeneity through non-genetic heterogeneity

Barough, Neda Barzgar; Sajjadian, Fakhrosadat; Jalilzadeh, Nazila; Shafaei, Hajar; Velaei, Kobra

doi:10.1007/s12282-021-01237-w

Cited by 8 publications

(2 citation statements)

References 137 publications

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“…Breast cancer is characterized by high heterogeneity in terms of the clinical course, prognosis, method of treatment, and histopathological features, which is why it is so important to determine the subtype of the cancer before choosing a treatment [ 28 ]. The selection of the appropriate therapy in breast cancer is based on a combination of the cancer staging system, the patient’s age at diagnosis, the tumor histotype and stage, the hormone receptor status, and the TNM classification.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Changes in the Expression of Selected Genes from the ABC Family in Patients with Triple-Negative Breast Cancer

Makuch-Kocka

Kocki

Brzozowska

et al. 2023

IJMS

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Triple-negative breast cancer (TNBC) is characterized by a lack of expression of hormone receptors (estrogen and progesterone), as cancer cells also do not overexpress the HER2 receptor. Due to their molecular profile, treatments for this type of breast cancer are limited. In some cases, the pharmacotherapy of patients with TNBC is hindered by the occurrence of multidrug resistance, which is largely conditioned by proteins encoded by genes from the ABC family. The aim of our study was to determine the expression profile of 14 selected genes from the ABC family using real-time PCR in 68 patients with TNBC by comparing the obtained results with clinical data and additionally using bioinformatics tools (Ualcan and The Breast Cancer Gene Expression Miner v4.8 (bc -GenExMiner v4.8)), as well as by comparing experimental data with data in the Cancer Genome Atlas (TCGA) database. Based on the conducted studies, we found different levels of gene expression depending on the age of patients, tumor sizes, metastases to lymph nodes, cell infiltration into adipose tissue, tumor stages, or lymphovascularinvasion. The results of the presented studies demonstrate the effect of the expression level of the studied genes on the clinical course and prognosis of patients with TNBC, and suggest how profiling the expression level of genes from the ABC family may be a useful tool in determining personalized TNBC treatment.

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Section: Discussionmentioning

confidence: 99%

Analysis of Changes in the Expression of Selected Genes from the ABC Family in Patients with Triple-Negative Breast Cancer

Makuch-Kocka

Kocki

Brzozowska

et al. 2023

IJMS

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“…Veening et al, 2008). However, unlike genetic heterogeneity that has been extensively investigated for decades (Mcgranahan and Swanton, 2017), understanding the underlying mechanisms and implications of non-genetic heterogeneity in cancer research is still in its infancy (Barzgar Barough et al, 2021;Lewis and Kats, 2021;Marine et al, 2020;Shlyakhtina et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Cancer: More Than a Geneticist’s Pandora’s Box

Saxena¹,

Subbalakshmi²,

Kulkarni³

et al. 2021

Preprint

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Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as non-genetic/non-mutational heterogeneity. Such heterogeneity – a ubiquitous nature of biological systems – has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/ noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systems-level approach integrating mathematical modelling and in vitro/in vivo experiments can map the diverse phenotypic repertoire, and identify therapeutic vulnerabilities of an otherwise clonal cell population.

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