前面提到了:肿瘤样品的单细胞需要提取上皮细胞继续细分,就是感兴趣的fibroblasts等细胞亚群占比非常少,所以研究者们做了第二次单细胞转录组数据,见:什么,你想要的单细胞亚群比例太少了?,其实这样的策略屡见不鲜。
让我们一起再看看另外一个示例,关于小鼠模型的!
文章:《Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer》,在这个研究里面,作者 investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors.
之所以选择 这个小鼠模型,就是因为它 high stromatogenic response and immune exclusion.
区分了 six CAF subpopulations,详见文末!
这个研究是常规的10x单细胞转录组数据,10x Genomics Chromium platform ,质控后是 6420 cells ,第一层次降维聚类分群是:
- 免疫细胞(66.4% ):Cells in clusters 0, 2, 3, 5, 7, 8 and 9 expressed CD45 (Ptprc),包括淋巴系和髓系
- 上皮细胞(24.5% ):Epcam (clusters 1 and 6)
- 基质细胞,主要是内皮细胞和成纤维细胞和周细胞
- CAFs(535 cells ) :Cells in cluster 4 had high levels of Thy1, Pdpn and Pdgfra
- 内皮细胞:Cells in cluster 10 expressed high levels of Pecam1 and Mcam
- a small population of pericytes (cluster 11)
如下所示:
可以看到, 虽然CAFs的细胞数量有点少,但是其功能很清晰,主要是下面的3个功能,符合逻辑:
- collagens (Col1a1, Col1a2, Col3a1, Col5a1-3, Col6a1-3 etc.),
- proteoglycans (Dcn, Lum, Bgn, Prg4 etc.)
- glycoproteins (Postn, Dpt, Tnc, Fbln, Fbn1 etc.)
值得注意的是并不是使用的collagens家族基因都应该是在成纤维细胞高表达哦 :
- Col4a1 and Col4a2, the highest expression for these two genes was detected in pericytes and endothelial cells.
为了更好的研究CAFs,重新做单细胞数据,这次首先去除免疫细胞,这样捕获了4000多个细胞,主要是 epithelial (Epcam+), endothelial (Pecam1+), pericytes (Mcam+, Rgs5+) 这3类细胞需要继续排除,剩下 ~1600 cells 是 待研究CAFs,可以区分成为6群:
- Cells in cluster 0 expressed high levels of lymphocyte antigen 6 complex, locus C1 (Ly6c1)
- while cells in cluster 1 were highly enriched for alpha smooth muscle actin (α-SMA/Acta2) (Figure 2C);
- Cells in cluster 2 expressed high levels of cyclin-dependent kinase 1 (Cdk1) and other cell cycle genes including Cenpa and Cenpf and were identified as ‘dividing cells’ (Figure 2C).
- Leukocyte surface antigen Cd53 was highly enriched in cluster 3 and was used as a marker for this cluster (Figure 2C).
- Cells in cluster 4 showed significant enrichment for cellular retinoic acid-binding protein 1 (Crabp1),
- while cells in cluster 5 showed enrichment for Cd74 (Figure 2C).
分群,并且进行比较好的描述:
其实挺容易看懂的,如果你是现在才入坑单细胞的,可以先看看基础10讲:
- 01. 上游分析流程
- 02.课题多少个样品,测序数据量如何
- 03. 过滤不合格细胞和基因(数据质控很重要)
- 04. 过滤线粒体核糖体基因
- 05. 去除细胞效应和基因效应
- 06.单细胞转录组数据的降维聚类分群
- 07.单细胞转录组数据处理之细胞亚群注释
- 08.把拿到的亚群进行更细致的分群
- 09.单细胞转录组数据处理之细胞亚群比例比较
最基础的往往是降维聚类分群,参考前面的例子:人人都能学会的单细胞聚类分群注释