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Heterogeneity at the invasion front of triple negative breast cancer cells.

ABSTRACT: Identifying better predictive and prognostic biomarkers for the diagnosis and treatment of triple negative breast cancer (TNBC) is complicated by tumor heterogeneity ranging from responses to therapy, mutational burden, and clonal evolution. To overcome the gap in our understanding of tumor heterogeneity, we hypothesized that isolating and studying the gene expression profile of invasive tumor cell subpopulations would be a crucial step towards achieving this goal. In this report, we utilized a fluidic device previously reported to be capable of supporting long-term three-dimensional growth and invasion dynamics of cancer cells. Live invading and matched non-invading SUM149 inflammatory breast cancer cells were enriched using this device and these two functionally distinct subpopulations were tested for differences in gene expression using a gene expression microarray. 305 target genes were identified to have altered expression in the invading cells compared to the non-invading tumoroid cells. Gene ontology analysis of the gene panel identified multiple biological roles ranging from extracellular matrix reorganization to modulation of the immune response and Rho signaling. Interestingly, the genes associated with the invasion front differ between different samples, consistent with inter- and intra-tumor heterogeneity. This work suggests the impact of heterogeneity in biomarker discovery should be considered as cancer therapy increasingly heads towards a personalized approach.

SUBMITTER: Aw Yong KM

PROVIDER: S-EPMC7113246 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Heterogeneity at the invasion front of triple negative breast cancer cells.

Aw Yong Koh Meng KM Ulintz Peter J PJ Caceres Sara S Cheng Xu X Bao Liwei L Wu Zhifen Z Jiagge Evelyn M EM Merajver Sofia D SD

Scientific reports 20200401 1

Identifying better predictive and prognostic biomarkers for the diagnosis and treatment of triple negative breast cancer (TNBC) is complicated by tumor heterogeneity ranging from responses to therapy, mutational burden, and clonal evolution. To overcome the gap in our understanding of tumor heterogeneity, we hypothesized that isolating and studying the gene expression profile of invasive tumor cell subpopulations would be a crucial step towards achieving this goal. In this report, we utilized a ...[more]

PMID: 32238832

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Project description:Heterogeneity of triple-negative breast cancer is well known at clinical, histopathological, and molecular levels. Genomic instability and greater mutation rates, which may result in the creation of neoantigens and enhanced immunogenicity, are additional characteristics of this breast cancer type. Clinical outcome is poor due to early age of onset, high metastatic potential, and increased likelihood of distant recurrence. Consequently, efforts to elucidate molecular mechanisms of breast cancer development, progression, and metastatic spread have been initiated to improve treatment options and improve outcomes for these patients. The extremely complex and heterogeneous tumor immune microenvironment is made up of several cell types and commonly possesses disorganized gene expression. Altered signaling pathways are mainly associated with mutated genes including p53, PIK3CA, and MAPK, and which are positively correlated with genes regulating immune response. Of note, particular immunity-associated genes could be used in prognostic indexes to assess the most effective management. Recent findings highlight the fact that long non-coding RNAs also play an important role in shaping tumor microenvironment formation, and can mediate tumor immune evasion. Identification of molecular signatures, through the use of multi-omics approaches, and effector pathways that drive early stages of the carcinogenic process are important steps in developing new strategies for targeted cancer treatment and prevention. Advances in immunotherapy by remodeling the host immune system to eradicate tumor cells have great promise to lead to novel therapeutic strategies. Current research is focused on combining immune checkpoint inhibition with chemotherapy, PARP inhibitors, cancer vaccines, or natural killer cell therapy. Targeted therapies may improve therapeutic response, eliminate therapeutic resistance, and improve overall patient survival. In the future, these evolving advancements should be implemented for personalized medicine and state-of-art management of cancer patients.

Project description:Objective: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer, characterized by extensive intratumoral heterogeneity. We aimed to systematically characterize the tumor heterogeneity of TNBC. Methods: Single-cell RNA sequencing (scRNA-seq) of TNBC cells were obtained from the GSE118389 and GSE75688 datasets. After integration of the two datasets, cell clustering analysis was performed using the Seurat package. According to the marker genes of cell cycle, cell cycle of each cell cluster was determined. Then, function enrichment analysis of marker genes in each cell cluster was performed, followed by ligand-receptor signaling network analysis. CIBERSORT was used to estimate the proportion of 22 immune cells in each sample based on RNA-seq data of 58 normal adjacent tissues and 101 TNBC tissues. After that, prognostic value of immune cells was assessed. Results: In the integrated datasets, five cells types including B cells, myeloid cells, stromal cells, T cells, and tumor cells were clustered. Functional enrichment analysis revealed the functional heterogeneity of genes in each cell. Intercellular communication networks were conducted based on ligand-receptor pairs. The heterogeneity in the fractions of 22 immune cells was found in TNBC tissues. Furthermore, there was a significant difference in the fractions of these immune cells between adjacent normal tissues and TNBC tissues. Among them, M2 macrophages and neutrophils were significantly associated with clinical outcomes of TNBC. Moreover, the fractions of T cells CD4 memory resting, monocytes, neutrophils, M1 macrophages, and T cells CD4 memory activated were significantly correlated with clinical characteristics of TNBC. As shown in PCA results, these immune cells could significantly distinguish TNBC tissues into adjacent normal tissues. Conclusion: Our findings characterized the tumor heterogeneity of TNBC, which deepened the understanding of the complex interactions between tumor cells and their microenvironment, especially immune cells.

Dataset Information

Heterogeneity at the invasion front of triple negative breast cancer cells.

Publications

Heterogeneity at the invasion front of triple negative breast cancer cells.

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