Identification of Breast Cancer Stem Cell Related Genes Using Functional Cellular Assays Combined With Single-Cell RNA Sequencing in MDA-MB-231 Cells

Abstract

Breast cancer tumors display different cellular phenotypes. A growing body of evidence points toward a population of cancer stem cells (CSCs) that is important for metastasis and treatment resistance, although the characteristics of these cells are incomplete. We used mammosphere formation assay and label-retention assay as functional cellular approaches to enrich for cells with different degree of CSC properties in the breast cancer cell line MDA-MB-231 and performed single-cell RNA sequencing. We clustered the cells based on their gene expression profiles and identified three subpopulations, including a CSC-like population. The cell clustering into these subpopulations overlapped with the cellular enrichment approach applied. To molecularly define these groups, we identified genes differentially expressed between the three subpopulations which could be matched to enriched gene sets. We also investigated the transition process from CSC-like cells into more differentiated cell states. In the CSC population we found 14 significantly upregulated genes. Some of these potential breast CSC markers are associated to reported stem cell properties and clinical survival data, but further experimental validation is needed to confirm their cellular functions. Detailed characterization of CSCs improve our understanding of mechanisms for tumor progression and contribute to the identification of new treatment targets.

The mevalonate precursor enzyme HMGCS1 is a novel marker and key mediator of cancer stem cell enrichment in luminal and basal models of breast cancer

“…When the expression of CSC-associated genes was analysed in cells lacking HMGCS1, the three cell lines showed a reduction of proliferation markers whereas the most significant down-regulation in pluripotency (SOX2) and EMT markers (SNAI1 and CD44) were observed in MDA-MB-231. The effect of the HMGCS1 expression in the proliferation markers MKI67 and CCNA2 were confirmed by observations in our previous study where the HMGCS1 expressing cells from mammosphere cultures showed higher expression of these two markers than cells lacking it (S3 Fig) [36]. Besides, these results agree with other studies showing that the blockage of the mevalonate pathway by statins suppressed the expression of a common cluster of genes governing the EMT process in triple negative breast cancer cell line MDA-MB-231 [37].…”

“… Data derived from RNA sequencing experiments in [ 36 ]. The HMGCS1 mean value of the entire population was used as a cutoff for the classification in low/high HMGCS1 expressing cells.…”

Cancer Stem Cell Plasticity – A Deadly Deal

“…In addition to discerning the dynamics of clonal evolution, single cell omics methods have also enabled the identification of transitioning CSCs and their contribution to drug resistance (Puram et al, 2018;Sharma et al, 2018). Considering the rarity of CSCs, combining single cell transcriptomics with enrichment strategies such as flow cytometry or sphere assays are capable of drastically improving the characterization of CSC (Akrap et al, 2016;Jonasson et al, 2019). Single cell multi-omics approaches involving obtaining information from multiple components within a single cell is also gaining interest, because it facilitates the assessment of genotype and phenotype relationship in regulating the individual cell states (Macaulay et al, 2017;Liu et al, 2019).…”

Cancer Stem Cell Plasticity – A Deadly Deal

“…In addition to discerning the dynamics of clonal evolution, single cell OMIC methods have also enabled the identification of cancer stem cell state transitioning and its contribution to drug resistance (Puram, Parikh et al 2018, Sharma, Cao et al 2018. Considering the rarity of a cancer stem cell, combining single cell transcriptomics with enrichment strategies like flow cytometry or sphere assays will drastically improve the characterization of CSC (Akrap, Andersson et al 2016, Jonasson, Ghannoum et al 2019. Single cell multi-omics approaches which involves obtaining information from multiple components within a single cell is also gaining significant interest as it allows the assessment of genotype and phenotype relationship in regulating the cell states (Macaulay, Ponting et al 2017.…”