Single-cell analyses of metastatic bone marrow in human neuroblastoma reveals microenvironmental remodeling and metastatic signature
Shenglin Mei, Adele M. Alchahin, Bethel Tesfai Embaie, Ioana Maria Gavriliuc, Bronte Manouk Verhoeven, Ting Zhao, Xiangyun Li, Nathan Elias Jeffries, Adena Pepich, Hirak Sarkar, Thale Kristin Olsen, Malin Wickström, Jakob Stenman, Oscar Reina-Bedoya, Peter V. Kharchenko, Philip J. Saylor, John Inge Johnsen, David B. Sykes, Per Kogner, Ninib Baryawno
Shenglin Mei, Adele M. Alchahin, Bethel Tesfai Embaie, Ioana Maria Gavriliuc, Bronte Manouk Verhoeven, Ting Zhao, Xiangyun Li, Nathan Elias Jeffries, Adena Pepich, Hirak Sarkar, Thale Kristin Olsen, Malin Wickström, Jakob Stenman, Oscar Reina-Bedoya, Peter V. Kharchenko, Philip J. Saylor, John Inge Johnsen, David B. Sykes, Per Kogner, Ninib Baryawno
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Resource and Technical Advance Bone biology Oncology

Single-cell analyses of metastatic bone marrow in human neuroblastoma reveals microenvironmental remodeling and metastatic signature

Abstract

Neuroblastoma is an aggressive pediatric cancer with a high rate of metastasis to the BM. Despite intensive treatments including high-dose chemotherapy, the overall survival rate for children with metastatic neuroblastoma remains dismal. Understanding the cellular and molecular mechanisms of the metastatic tumor microenvironment is crucial for developing new therapies and improving clinical outcomes. Here, we used single-cell RNA-Seq to characterize immune and tumor cell alterations in neuroblastoma BM metastases by comparative analysis with patients without metastases. Our results reveal remodeling of the immune cell populations and reprogramming of gene expression profiles in the metastatic niche. In particular, within the BM metastatic niche, we observed the enrichment of immune cells, including tumor-associated neutrophils, macrophages, and exhausted T cells, as well as an increased number of Tregs and a decreased number of B cells. Furthermore, we highlighted cell communication between tumor cells and immune cell populations, and we identified prognostic markers in malignant cells that are associated with worse clinical outcomes in 3 independent neuroblastoma cohorts. Our results provide insight into the cellular, compositional, and transcriptional shifts underlying neuroblastoma BM metastases that contribute to the development of new therapeutic strategies.

Authors

Shenglin Mei, Adele M. Alchahin, Bethel Tesfai Embaie, Ioana Maria Gavriliuc, Bronte Manouk Verhoeven, Ting Zhao, Xiangyun Li, Nathan Elias Jeffries, Adena Pepich, Hirak Sarkar, Thale Kristin Olsen, Malin Wickström, Jakob Stenman, Oscar Reina-Bedoya, Peter V. Kharchenko, Philip J. Saylor, John Inge Johnsen, David B. Sykes, Per Kogner, Ninib Baryawno

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Figure 5

Metastatic signature predicts neuroblastoma patient overall survival.

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Metastatic signature predicts neuroblastoma patient overall survival. (A...
(A) Gene set enrichment (GSEA) plot depicting the enrichment pathways of genes upregulated in bone metastatic tumor cells against to primary NB tumor cells. (B) A Venn diagram illustrating the overlap of upregulated genes in bone metastatic tumor cells compared with non-malignant cells and primary NB tumor cells (see method). (C) Boxplot representing metastatic signature score in low-risk (n = 273) and high-risk (n = 172) patients with NB (GSE49711). Significance was assessed using 2-sided Wilcoxon ranked-sum test (***P < 0.001). (D) Boxplot showing the CRIPSR screen effect score of metastatic signature genes in neuroblastoma cell lines (n = 35). Effect Scores indicate whether gene knockout (gene loss) has a positive or negative effect on the growth or survival of cancer cells. (E) KM survival curves showing patients with NB with higher metastatic signature gene expression have worse overall survival in 3 independent NB data sets (GSE49711 n = 488, Target n = 247, GSE16476 n = 76). Patients were stratified into 2 groups based on the gene expression (binary: top 25% versus bottom 25%). Statistics are accessed by 2-side log-rank test. (F) Boxplot showing cell growth of neuroblastoma cell line (TET21N) on day3 after shRNA infection (n = 3). (G) Barplot showing relative mRNA expression (n = 3). Data are expressed using the 2−ΔΔCt method. Gene expression levels were normalized to the sh control. Statistical significance determined using 2-sided t-test. (H) Overview of potential ligand-receptor interactions of cell subpopulations. (I) Dot plot showing significant ligand (tumor cells and T cell subsets) and receptor (myeloid cell subsets) expression. Dot size indicates expression ratio, color represents average gene expression (Methods). Boxplots include center line, median; box limits, upper and lower quartiles; whiskers are highest and lowest values no greater than 1.5× IQR. ****P < 0.0001.