分享一篇单细胞文章（Adrenal Neuroblastoma）

Single-Cell Characterization of Malignant Phenotypes and Developmental Trajectories of
Adrenal Neuroblastoma

文章的亮点

（1） The repertoire of normal developing neural-crest-related cells defines the features of NB
（2）NB has a predominant chromaffin-cell-like phenotype
（3）Chromaffin cell differentiation state is highly predictive of patient outcome
（4）MYCN amplification is robustly linked with enhanced EMT NCC-like phenotype
接下来我们进入正题

SUMMARY

神经母细胞瘤（NB）是神经-衍生的恶性肿瘤的一种亚型，是儿童时期最常见的颅外实体瘤。尽管进行了广泛的研究，NB的潜在发展起源尚不清楚。使用单细胞RNA测序，我们从16位患者的160,910个细胞中生成了肾上腺NB转录组，并在相对较早的发育阶段从早期人类胚胎和胎儿肾上腺的12,103个细胞中生成了NB起源的推定发育细胞的转录组。 我们发现大多数肾上腺NB肿瘤细胞转录镜像去甲肾上腺素嗜铬细胞。 在正常发育过程中，恶性状态还概括了嗜铬细胞的增殖/分化状态。 我们的发现提供了对NB的人类起始和发展的发展轨迹和细胞状态的见解。

INTRODUCTION

1、已经提出了这样的概念，即儿童恶性肿瘤很可能是在胚胎发育或出生后早期发育期间由前体细胞引起的。NB被认为是源自交感神经系统的原始细胞（它们是交感神经元和神经内分泌（NE）嗜铬细胞的前体）并且是儿童常见的颅外实体瘤，NB被认为起源于trunk neural crest cells （NCCs），也被称为交感肾上腺祖细胞，它们是交感神经元和神经内分泌嗜铬细胞（NE）的前体。然而genetic lineage tracing results（遗传谱系追踪结果）have challenged this hypothesis，表明two waves of NCC迁移是交感肾上腺谱系发展的原因。NB tumor cells can also harbor committed adrenergic and undifferentiated NCC-like phenotypes。这表明，NB肿瘤的发生可能早于NCC移入交感肾上腺命运之前的迁移阶段。
2、We performed single-cell RNA sequencing (scRNAseq) on early human embryos and fetal adrenal glands, as well as primary adrenal NB tumors. We then used this unique resource to identify transcriptional characteristics of NB tumor cells and correlated phenotypic diversity with clinical heterogeneity.
（介绍永远是那么的费劲，专业词汇实在是太多了，😂）

主要结果

（1）Single-Cell Transcriptome Profiling of Early Embryos and Fetal Adrenal Glands

胎儿肾上腺交感肾上腺细胞亚型的发育遵循不同的时间表
scRNAseq-----孕后4周的胚胎（NCCs）specified and delaminated from the dorsal neural tube (NT).
scRNAseq ----孕后8-14周的胎儿肾上腺（NCCs迁移到肾上腺皮质并形成肾上腺髓质）

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After quality control including doublet removal（单细胞测序之后进行多细胞去除，我们在方法里面讨论），降维聚类识别细胞类型（这里主要用经典的marker 和TFs）
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Taken together, by profiling whole embryos and fetal adrenal glands at single-cell
resolution, we were able to identify biologically distinct cells of interest。

（2）Cellular Diversity within Developing Neural Lineages of Early Embryos

为了更为详细的了解分化分层的过程，对识别的细胞进行重新聚类，we computationally isolated and re-clustered cells assigned to NTCs, SNs, MNs, and NCCs from early embryos。 This analysis further identified 14 distinct cell subsets and showed three cellular states within the NT compartment that may contribute to the development of NCCs。

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对于重新分群后摸棱两可的群作者采用了一种（we then investigated the identity of this ambiguous population by visualizing lineage relationships using partition-based
graph abstraction (PAGA)）这个我们在后面解释。
NCCs are derived from NTCs and pre-migratory NCCs, which have also been implicated as the potential cellular origin of NB. Therefore, we aimed to determine the fate of NCCs using RNA velocity(RNA速率分析)。
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Overall, re-clustering analyses enabled us to identify discrete subpopulations within early neural lineages and depict their relevance to NCCs.
RNA速率分析我们也在后面所以个解释

（3）Cellular Diversity within the Developing Sympathoadrenal Lineages of Fetal Adrenal Glands

To gain further insight into the cellular state within sympathoadrenal lineages of fetal adrenal glands, we performed a second round of clustering for only SCPs, sympathoblasts, and chromaffin cells。

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发现三种细胞类型之间存在明显的细胞周期异质性，Of them, SCPs were relatively quiescent, while chromaffin cells contained a substantial number of cycling cells。
Interestingly, compared with cycling chromaffin cells, non-cycling chromaffin cells expressed a more differentiated signature, including the PRPH, NPY, and NTRK1 genes, which have previously been used for defining a committed noradrenergic fate。

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A recent single-cell study in mice showed that SCPs preferentially gave rise to chromaffin cells through a ‘‘bridge’’ cell state。为了了解SCP对人类交感神经元和嗜铬细胞的细胞命运偏倚，我们接下来应用Palantir（拟时分析软件）来模拟细胞分化状态的格局并预测细胞命运转变的可能性。
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found that SCPs had a higher probability to differentiate toward chromaffin
cells，Cycling chromaffin progenitors also preferentially gave rise to more differentiated chromaffin cells。（这部分结果是对拟时过程的一个推断）。

（4）Single-Cell Transcriptome Profiling of Primary NB

Tumors
肿瘤样本的单细胞测序After stringent quality filtering, 160,910 cells were obtained
from the 16 tumors with an average of 2,104 genes detected per cell。We used the Harmony algorithm for dataset integration and found shared cellular types across tumors（Harmony算法对数据进行整合），识别细胞类型。

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单细胞转录组CNV分析识别恶性和非恶性的细胞类型。More importantly, segmental chromosome 17q gain, 11q loss, and 1p loss were mostly observed in NE cells。NE cells represented malignant cells in each tumor。

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5.Identifying Malignant Programs of NB

应用非负矩阵分解（NMF）分析来确定肿瘤内异质性的完整转录谱，We used
hierarchical clustering to group all 160 identified signatures into nine main meta-programs。The nine meta-programs spanned diverse functions as reflected by their topscoring genes（这个地方需要注意）

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Genes from these nine meta-programs were then used for analyzing heterogeneity of the microarray data of 498 primary tumors。Further survival analysis showed that signatures of meta-programs 1 and 6 were strongly associated with a poor prognosis, while meta-programs 2, 3, 4, 5, 8, and 9 significantly predicted a better prognosis 。 This finding suggested a strong association between these malignant meta-programs and clinical heterogeneity。
（这个地方对恶性细胞进行了一个划分，需要一定的生物学背景）

6、Relationship between Malignant Cell Identity and the Origin of Developmental Cells（恶性细胞身份与发育细胞起源之间的关系）

For comprehensive mapping of tumor cell phenotypes, we included all relevant NCC types to generate a reference transcriptome atlas，（为了全面映射肿瘤细胞表型，我们纳入了所有相关的NCC类型以生成参考转录组图谱），We then calculated transcriptome similarities between nine malignant meta-programs and the signatures We found that several malignant meta-programs had the most similar molecular features as chromaffin cells and sympathoblasts, which suggested that
tumor cells may be phenotypically closer to chromaffin cells or sympathoblastsof nine developing cell types.（恶性细胞与正常细胞的相关性分析）。

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We next used the k-nearest neighbors algorithm to predict the identity of tumor cells at single-cell resolution. This analysis showed a striking outcome in that all tumors, regardless of histological subtype or differentiation state, consisted primarily of
chromaffin-cell-like tumor cells（KNN聚类识别起源）。most cancer cells showed a
strong chromaffin-cell-like feature。our single-cell analyses showed that most tumors had a unique chromaffin-cell-like feature, while MYCN-amplified tumors represented traits that were exclusively associated with an EMT NCC state.
（这里我们需要注意的是正常组织和癌症组织是不放在一起做整合分析的，这一点基本得到了共识）。

7、Tracking Developmental Cell-Type-Related Signatures

in Bulk Samples
（这部分bulk数据的分析我们不作为重点进行讨论了）

8、Differentiation States of Chromaffin Cells Are Highly Associated with Clinical Heterogeneity of NB

Our analyses of single-cell data and bulk data showed a prevalent, committed and chromaffin-cell-like phenotype of most NBs.However, this finding cannot explain the high clinical and molecular heterogeneity of this disease.
解卷积的方式对肿瘤样本的细胞成分进行识别。

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We next explored the prognostic significance of the three defined NB groups. Group A tumors had the worst survival rate, while group B and C tumors had a better survival rate。

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9、TF Regulatory Network Underlying NB Phenotypes

Cell phenotypes are determined by core regulatory TFs that interact with cis-regulatory elements to direct transcriptional programs.（SCENIC分析）

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（这个图不清晰，大家可以看原文）。
nearly all tumors markedly upregulated chromaffincell-associated regulons。
These findings collectively support the notion that the EMT NCC-like signature observed in MYCN-amplified tumors appears to be associated with MYCN’s transcriptional remodeling capacity in EMT NCCrelated genes.

10、TF Regulatory Network Underlying Malignant Cell States

Taken together, SCENIC analyses showed that the intratumoral proliferation and differentiated states were constructed by a similar transcriptional regulatory network
associated with developing chromaffin cells.

Intratumoral Malignant Cell State Recapitulates the Dynamics of Chromaffin Cell Differentiation

In the final analysis of our study, we aimed to identify whether the signature genes of chromaffin cells can specifically indicate the differentiation state of tumor cells.
5B).
This analysis screened out five genes (NTRK1, PRPH, NPY, PCP4, and PKIB) as best satisfying our criteria of high expression in differentiated chromaffin cells. These five genes showed a remarkable negative relation with the cell-cycle status in developing chromaffin cells and tumor cells. Further survival analysis demonstrated the potential of these genes as a biomarker for clinically estimating differentiation grades because high expression of these genes was significantly predictive of a better prognosis.

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We next applied RNA velocity analysis to gain more insight into intratumoral cellular state dynamics.
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In line with this trend, RNA velocity predicted cycling UCHC-like tumor cells to be the root cells, while it predicted DCHC-like tumor cells to be the end cells.
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RNA velocity analysis suggested that intratumoral tumor cell heterogeneity of NB largely corresponded to cellular states resembling the differentiation status of developmental chromaffin cells. This could improve our understanding of tumor regression behavior occurring in NB.

分析方法：

多细胞预测的软件Scrublet
R package Survival v3.1-8
拟时分析软件Palantir
解卷积的方法MuSiC
Defining Cell Scores
We used the AddModuleScore function in the Seurat R package to evaluate the degree to which individual cells express a certain predefined expression program as described previously
Connectivity of Cell Clusters
We quantified the connectivity of single-cell clusters using the PAGA method (Wolf et al., 2019). Computations were carried out on the same subset of variable genes as for clustering, using default parameters.

后续我们好好分析一下这些软件的使用方法。