Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma

doi:10.1007/s11684-024-1081-7

Front. Med.

2024, Vol. 18

Issue (4) : 690-707 https://doi.org/10.1007/s11684-024-1081-7

Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma

Zhe Nian¹, Dan Wang¹, Hao Wang¹, Wenxu Liu¹, Zhenyi Ma², Jie Yan³, Yanna Cao³, Jie Li³, Qiang Zhao³(

), Zhe Liu^1,^2,⁴(

)

¹. Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
². Zhejiang Key Laboratory of Medical Epigenetics, Department of Cell Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou 311121, China
³. Department of Pediatric Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
⁴. Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China

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Abstract

Neuroblastoma (NB) is one of the most common childhood malignancies. Sixty percent of patients present with widely disseminated clinical signs at diagnosis and exhibit poor outcomes. However, the molecular mechanisms triggering NB metastasis remain largely uncharacterized. In this study, we generated a transcriptomic atlas of 15 447 NB cells from eight NB samples, including paired samples of primary tumors and bone marrow metastases. We used time-resolved analysis to chart the evolutionary trajectory of NB cells from the primary tumor to the metastases in the same patient and identified a common ‘starter’ subpopulation that initiates tumor development and metastasis. The ‘starter’ population exhibited high expression levels of multiple cell cycle-related genes, indicating the important role of cell cycle upregulation in NB tumor progression. In addition, our evolutionary trajectory analysis demonstrated the involvement of partial epithelial-to-mesenchymal transition (p-EMT) along the metastatic route from the primary site to the bone marrow. Our study provides insights into the program driving NB metastasis and presents a signature of metastasis-initiating cells as an independent prognostic indicator and potential therapeutic target to inhibit the initiation of NB metastasis.

Keywords single-cell RNA sequencing metastasis neuroblastoma epithelial-to-mesenchymal transition

Corresponding Author(s): Qiang Zhao,Zhe Liu

Just Accepted Date: 29 May 2024 Online First Date: 16 July 2024 Issue Date: 30 August 2024

Cite this article:

Zhe Nian,Dan Wang,Hao Wang, et al. Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma[J]. Front. Med., 2024, 18(4): 690-707.

URL:

https://academic.hep.com.cn/fmd/EN/10.1007/s11684-024-1081-7
https://academic.hep.com.cn/fmd/EN/Y2024/V18/I4/690

Fig.1 Single-cell RNA sequencing of NB cells. (A) Overview of the experimental workflow. Eight NB samples (six primary NB tissues and two matched bone marrow tissues) were collected from six NB patients. Single DAPI⁻CD45⁻ human tumor cells were isolated by flow cytometry, and single-cell cDNA libraries were prepared using 10x Genomics technology (upper). NB samples with molecular and clinical annotations (bottom). (B–D) UMAP plots of the 15 447 high-quality cells showing the sample origin (B), transcriptomic clusters (C), and histological category (D). (E) Inferred CNV profiling (upper) and WGS (bottom) were performed to identify malignant and nonmalignant cells in scRNA-seq data for T57. (F) UMAP plots of the 15 447 high-quality cells showing the cell type classification based on the CNV classification. (G) UMAP plots showing the fibroblast signature scores (COL1A1, COL1A2, COL3A1, TAGLN) (upper), the immune-cell signature scores (PTPRC, CD74, SRGN, LAPTM5) (middle), and the neuroendocrine signature scores (PHOX2A, PHOX2B, CHGA, SYP, NPY) (bottom) (gray to red). (H) UMAP plots of the 15 447 high-quality cells showing the cell type based on marker gene expression shown in Fig. 1G. (I) The proportion of each cell type in the eight samples.

Fig.2 Trajectory modeling of malignant NB cells identifies a ‘starter’ cluster in T57. (A) UMAP plots of 9121 malignant NB cells from T57 and T62 colored by the sample origin. (B) UMAP plots of 9121 malignant NB cells from T57 and T62 colored by the transcriptomic cluster (left). The proportions of cell clusters within each sample (right). (C) UMAP plots of 3060 malignant NB cells from T57 colored by the transcriptomic cluster. (D) UMAP plots split by the sample origin in T57. (E) Heatmap showing the top ten differentially expressed genes in each cluster based on the UMAP plots shown in Fig. 2B. (F) UMAP plots showing the RNA velocity analysis of the malignant NB cells in T57. (G) UMAP plots showing the separate RNA velocity analyses of the malignant NB cells in the primary tumor and metastases of T57. The velocity of cells is shown by black arrows indicating the predicted direction of development. (H–J) Pseudotime analysis of malignant NB cells from T57 by Monocle 2 showing the timing sequence of tumor cell progression colored by pseudotime (H), colored by intratumoral subpopulation (I), and split by the sample origin in T57 (J). (K) NB cell state trajectories during tumor progression in T57 were inferred by Slingshot and are shown using UMAP plots according to the slingPseudotime score.

Fig.3 Tracing of the Cluster 3 cells in T57. (A and B) Unrooted phylogenetic tree of matched pairs of primary (A) and metastatic (B) samples based on the nine selected mutations shown in Fig. 3C. Every cluster of unique cell mutation types is displayed in the same color shown in each branch. Bases were extracted from the reference genome as the contrast branch (Reference). (C) Heatmap showing the nine selected mutations in T57. Dark orange and light orange represent homozygous and heterozygous mutations, respectively. Blue represents wild type (WT). (D) Boxplot showing the mutation number in each cell from paired primary and metastatic samples in T57. P < 0.0001 (Wilcoxon test). (E and F) Pseudotime analysis of malignant NB cells from Cluster 3 in T57 by Monocle 2, showing the timing sequence of tumor cell progression colored by pseudotime (E) and sample origin (F). (G) RNA velocity analysis of malignant NB cells from Cluster 3 in the primary tumor and metastases of T57. (H) PCA of every cell subcluster based on the nine selected mutations shown in Fig. 3C. (I) The dynamically expressed genes and enriched gene signatures were significantly associated with pseudotime from P3 to M3 in T57. (J) The expression levels (upper) and the densities in Monocle space (bottom) of epithelial and mesenchymal signatures along the pseudotime trajectory from P3 to M3 in T57. (K) Representative immunofluorescence staining of (primary and metastatic) human NB sections for EPCAM and VIM expression (upper), and NCAM1 and VIM expression (bottom) in patient 1. Scale bars, 20 μm.

Fig.4 Characterization of the ‘starter’ populations. (A) Functional enrichment analysis showing the ten enriched pathways positively correlated with cells in Cluster 3. Normalized enrichment scores (NES) were shown below. (B) UMAP plots showing the cell cycle states of the tumor cells in T57 and T62 (color code in the right). (C) Heatmap showing the scaled expression values of genes upregulated in Cluster 3 of T57 and T62. Biologically important genes are listed on the left. (D) Heatmap of the highest-scoring TFs inferred by DoRothEA in each cluster in T57. Genes colored in red are the TFs of interest. (E) UMAP plots showing the expression levels and distribution of TFs in T57 (gray to red) based on Fig. 4D. (F) Expression of the four TFs in individual cells ordered by pseudotime along the arms of the trajectory shown in Fig. 2I. (G and H) UMAP plots of 15 307 malignant NB cells from scRNA-seq data for the eight NB samples colored by the transcriptomic cluster (G), and sample origin (H). (I) UMAP plots showing the expression levels and distribution of the ‘starter’-cell signature (gray to red). (J) The proportions of cell clusters within each sample.

Fig.5 Cell–cell interactions between the microenvironment and NB cells. (A) UMAP plots of scRNA-seq data from GSE137804 data set colored by cell types. (B) Schematic diagram illustrating the number of receptor-ligand interactions between the microenvironment and the ‘starter’ cells or between the microenvironment and the other tumor cells; the arrows indicate the direction of the interaction. (C and D) Relative contribution of each signaling pathway to the outgoing communication (C) and the incoming communication (D) network in the ‘starter’ cells. (E and F) The inferred TGFβ signaling networks from NB cells to the microenvironment (E) and from the microenvironment to NB cells (F). Circle sizes are proportional to the number of cells in each cell group and edge width represents the communication probability. (G and H) Dot plot showing the receptor-ligand pairs of the TGFβ pathway from NB cells to the microenvironment (G) and from the microenvironment to NB cells (H). The dot color and size represent the calculated communication probability and P-values. P-values are computed from the one-sided permutation test. (I) Dot plot showing the expression levels of representative receptor-ligand pair genes of TGFβ pathway in our scRNA-seq data from the eight NB samples. (J and K) Multilayer intercellular/intracellular TGFβ signaling network between the ‘starter’ cells and the microenvironment both in forward (NB to microenvironment) (J) and in backward (microenvironment to NB) (K) directions in the GSE137804 data set.

Fig.6 Validation of the ‘starter’-cell signature. (A) The proportion of high- or low-expression groups within major clinical subgroups in the 16 NB patients of previous study (GSE137804). (B) Boxplots depict the expression of the ‘starter’-cell signature in patients of the R2 data set (E-MTAB-8248), categorized based on MYCN status (amplified versus non-amplified), INSS staging (stage 4 versus stages 1, 2, 3, and 4S) or TERT status (TERT rearrangement versus TERT wild-type). Boxplot of the ‘starter’-cell signature expression in patients of the GSE16476 data set, categorized based on the distant metastasis. The P values are reported from two-sided t-tests. (C and D) Kaplan?Meier plots of event-free survival (C) and overall survival (D) for 222 NB patients from the previously published R2 data sets (E-MTAB-8248) based on the expression levels of the ‘starter’-cell signature. Patients were divided into two groups by the median expression level of the signature (n = 111 and 111 tumors in the two groups). P values were determined using the log-rank test to compare both groups. (E) The Cox proportional regression analysis of the data set described in Fig. 6C and 6D, with the ‘starter’-cell signature included.

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