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Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq.

ABSTRACT: Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conducted single-cell RNA-sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Here, we show that intercellular heterogeneity of gene expression programs within each tumor is variable and largely correlates with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation predicts long-term outcomes for TNBC patients in a large cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.

SUBMITTER: Karaayvaz M

PROVIDER: S-EPMC6123496 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq.

Karaayvaz Mihriban M Cristea Simona S Gillespie Shawn M SM Patel Anoop P AP Mylvaganam Ravindra R Luo Christina C CC Specht Michelle C MC Bernstein Bradley E BE Michor Franziska F Ellisen Leif W LW

Nature communications 20180904 1

Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conducted single-cell RNA-sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Here, we show that intercellular heterogeneity of gene expression programs within each tumor is variable and largely correlates with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of indiv ...[more]

PMID: 30181541

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Project description:BackgroundBreast cancer (BC) is a heterogeneous disease, with the ductal subtype exhibiting significant cellular diversity that influences prognosis and response to treatment. Single-cell RNA sequencing data from the GEO database were utilized in this study to investigate the underlying mechanisms of cellular heterogeneity and to identify potential prognostic markers and therapeutic targets.MethodsBioinformatics analysis was conducted using R packages to analyze the single-cell sequencing data. The presence of highly variable genes and differences in malignant potency within the same BC samples were examined. Differential gene expression and biological function between Type 1 and Type 2 ductal epithelial cells were identified. Lasso regression and Cox proportional hazards regression analyses were employed to identify genes associated with patient prognosis. Experimental validation was performed in vitro and in vivo to confirm the functional relevance of the identified genes.ResultsThe analysis revealed notable heterogeneity among BC cells, with the presence of highly variable genes and differences in malignant behavior within the same samples. Significant disparities in gene expression and biological function were identified between Type 1 and Type 2 ductal epithelial cells. Through regression analyses, CYP24A1 and TFPI2 were identified as pivotal genes associated with patient prognosis. Kaplan-Meier curves demonstrated their prognostic significance, and experimental validation confirmed their inhibitory effects on malignant behaviors of ductal BC cells.ConclusionThis study highlights the cellular heterogeneity in ductal subtype breast cancer and delineates the differential gene expressions and biological functions between Type 1 and Type 2 ductal epithelial cells. The genes CYP24A1 and TFPI2 emerged as promising prognostic markers and therapeutic targets, exhibiting inhibitory effects on BC cell malignancy in vitro and in vivo. These findings offer the potential for improved BC management and the development of targeted treatment strategies.

Dataset Information

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq.

Publications

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq.

Similar Datasets

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