Single-Cell Characterization of Malignant Phenotypes and Developmental Trajectories of
Adrenal Neuroblastoma
文章的亮點(diǎn)
（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
接下來我們進(jìn)入正題
SUMMARY
神經(jīng)母細(xì)胞瘤（NB）是神經(jīng)-衍生的惡性腫瘤的一種亞型劫灶，是兒童時(shí)期最常見的顱外實(shí)體瘤本昏。盡管進(jìn)行了廣泛的研究涌穆，NB的潛在發(fā)展起源尚不清楚。使用單細(xì)胞RNA測序朱监，我們從16位患者的160,910個(gè)細(xì)胞中生成了腎上腺NB轉(zhuǎn)錄組，并在相對較早的發(fā)育階段從早期人類胚胎和胎兒腎上腺的12,103個(gè)細(xì)胞中生成了NB起源的推定發(fā)育細(xì)胞的轉(zhuǎn)錄組奋隶。 我們發(fā)現(xiàn)大多數(shù)腎上腺NB腫瘤細(xì)胞轉(zhuǎn)錄鏡像去甲腎上腺素嗜鉻細(xì)胞唯欣。 在正常發(fā)育過程中搬味，惡性狀態(tài)還概括了嗜鉻細(xì)胞的增殖/分化狀態(tài)碰纬。 我們的發(fā)現(xiàn)提供了對NB的人類起始和發(fā)展的發(fā)展軌跡和細(xì)胞狀態(tài)的見解悦析。
INTRODUCTION
1、已經(jīng)提出了這樣的概念亭螟，即兒童惡性腫瘤很可能是在胚胎發(fā)育或出生后早期發(fā)育期間由前體細(xì)胞引起的预烙。NB被認(rèn)為是源自交感神經(jīng)系統(tǒng)的原始細(xì)胞（它們是交感神經(jīng)元和神經(jīng)內(nèi)分泌（NE）嗜鉻細(xì)胞的前體）并且是兒童常見的顱外實(shí)體瘤扁掸，NB被認(rèn)為起源于trunk neural crest cells （NCCs），也被稱為交感腎上腺祖細(xì)胞炼蹦，它們是交感神經(jīng)元和神經(jīng)內(nèi)分泌嗜鉻細(xì)胞（NE）的前體掐隐。然而genetic lineage tracing results（遺傳譜系追蹤結(jié)果）have challenged this hypothesis虑省，表明two waves of NCC遷移是交感腎上腺譜系發(fā)展的原因僧凰。NB tumor cells can also harbor committed adrenergic and undifferentiated NCC-like phenotypes训措。這表明绩鸣，NB腫瘤的發(fā)生可能早于NCC移入交感腎上腺命運(yùn)之前的遷移階段。
2化借、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.
（介紹永遠(yuǎn)是那么的費(fèi)勁蓖康，專業(yè)詞匯實(shí)在是太多了蒜焊，??）
主要結(jié)果
（1）Single-Cell Transcriptome Profiling of Early Embryos and Fetal Adrenal Glands
胎兒腎上腺交感腎上腺細(xì)胞亞型的發(fā)育遵循不同的時(shí)間表
scRNAseq-----孕后4周的胚胎（NCCs）specified and delaminated from the dorsal neural tube (NT).
scRNAseq ----孕后8-14周的胎兒腎上腺（NCCs遷移到腎上腺皮質(zhì)并形成腎上腺髓質(zhì)）
After quality control including doublet removal（單細(xì)胞測序之后進(jìn)行多細(xì)胞去除山涡，我們在方法里面討論）唆迁，降維聚類識別細(xì)胞類型（這里主要用經(jīng)典的marker 和TFs）
Taken together, by profiling whole embryos and fetal adrenal glands at single-cell
resolution, we were able to identify biologically distinct cells of interest唐责。
（2）Cellular Diversity within Developing Neural Lineages of Early Embryos
為了更為詳細(xì)的了解分化分層的過程鼠哥，對識別的細(xì)胞進(jìn)行重新聚類，we computationally isolated and re-clustered cells assigned to NTCs, SNs, MNs, and NCCs from early embryos允蚣。 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嚷兔。
對于重新分群后摸棱兩可的群作者采用了一種（we then investigated the identity of this ambiguous population by visualizing lineage relationships using partition-based
graph abstraction (PAGA)）這個(gè)我們在后面解釋冒晰。
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)壶运。
Overall, re-clustering analyses enabled us to identify discrete subpopulations within early neural lineages and depict their relevance to NCCs.
RNA速率分析我們也在后面所以個(gè)解釋
（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蒋情。
發(fā)現(xiàn)三種細(xì)胞類型之間存在明顯的細(xì)胞周期異質(zhì)性恕出，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刷后。
A recent single-cell study in mice showed that SCPs preferentially gave rise to chromaffin cells through a ‘‘bridge’’ cell state尝胆。為了了解SCP對人類交感神經(jīng)元和嗜鉻細(xì)胞的細(xì)胞命運(yùn)偏倚含衔，我們接下來應(yīng)用Palantir（擬時(shí)分析軟件）來模擬細(xì)胞分化狀態(tài)的格局并預(yù)測細(xì)胞命運(yùn)轉(zhuǎn)變的可能性贪染。
found that SCPs had a higher probability to differentiate toward chromaffin
cells杭隙，Cycling chromaffin progenitors also preferentially gave rise to more differentiated chromaffin cells因妙。（這部分結(jié)果是對擬時(shí)過程的一個(gè)推斷）。
（4）Single-Cell Transcriptome Profiling of Primary NB
Tumors
腫瘤樣本的單細(xì)胞測序After stringent quality filtering, 160,910 cells were obtained
from the 16 tumors with an average of 2,104 genes detected per cell洽沟。We used the Harmony algorithm for dataset integration and found shared cellular types across tumors（Harmony算法對數(shù)據(jù)進(jìn)行整合）裆操，識別細(xì)胞類型鳄乏。
單細(xì)胞轉(zhuǎn)錄組CNV分析識別惡性和非惡性的細(xì)胞類型朽缴。More importantly, segmental chromosome 17q gain, 11q loss, and 1p loss were mostly observed in NE cells水援。NE cells represented malignant cells in each tumor蜗元。
5.Identifying Malignant Programs of NB
應(yīng)用非負(fù)矩陣分解（NMF）分析來確定腫瘤內(nèi)異質(zhì)性的完整轉(zhuǎn)錄譜奕扣，We used
hierarchical clustering to group all 160 identified signatures into nine main meta-programs惯豆。The nine meta-programs spanned diverse functions as reflected by their topscoring genes（這個(gè)地方需要注意）
Genes from these nine meta-programs were then used for analyzing heterogeneity of the microarray data of 498 primary tumors楷兽。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 芯杀。 This finding suggested a strong association between these malignant meta-programs and clinical heterogeneity。
（這個(gè)地方對惡性細(xì)胞進(jìn)行了一個(gè)劃分却特，需要一定的生物學(xué)背景）
6核偿、Relationship between Malignant Cell Identity and the Origin of Developmental Cells（惡性細(xì)胞身份與發(fā)育細(xì)胞起源之間的關(guān)系）
For comprehensive mapping of tumor cell phenotypes, we included all relevant NCC types to generate a reference transcriptome atlas漾岳，（為了全面映射腫瘤細(xì)胞表型，我們納入了所有相關(guān)的NCC類型以生成參考轉(zhuǎn)錄組圖譜）左腔，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.（惡性細(xì)胞與正常細(xì)胞的相關(guān)性分析）液样。
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聚類識別起源）巧还。most cancer cells showed a
strong chromaffin-cell-like feature鞭莽。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.
（這里我們需要注意的是正常組織和癌癥組織是不放在一起做整合分析的，這一點(diǎn)基本得到了共識）麸祷。
7澎怒、Tracking Developmental Cell-Type-Related Signatures
in Bulk Samples
（這部分bulk數(shù)據(jù)的分析我們不作為重點(diǎn)進(jìn)行討論了）
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.
解卷積的方式對腫瘤樣本的細(xì)胞成分進(jìn)行識別阶牍。
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喷面。
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）
（這個(gè)圖不清晰惧辈，大家可以看原文）。
nearly all tumors markedly upregulated chromaffincell-associated regulons磕瓷。
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盒齿、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.
We next applied RNA velocity analysis to gain more insight into intratumoral cellular state dynamics.
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：
多細(xì)胞預(yù)測的軟件Scrublet
R package Survival v3.1-8
擬時(shí)分析軟件Palantir
解卷積的方法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.
后續(xù)我們好好分析一下這些軟件的使用方法。
