肿瘤相关成纤维细胞异质性

前面我们在什么，你想要的单细胞亚群比例太少了？这个教程里面提到了如果Cancer-associated fibroblasts (CAFs) 细胞比例太少了但是它又是我们的研究目标，就可以实验手段重新富集它，再做一次单细胞数据。

具体来龙去脉大家可以自行阅读发表于2020的文章，标题 是：《Single-cell transcriptomic architecture and intercellular crosstalk of human intrahepatic cholangiocarcinoma》，数据集在；https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709

现在，我们一起解读一下研究者们二次富集后的Cancer-associated fibroblasts (CAFs) 细胞的异质性！

首先看正文描述：2,941 high-quality fibro- blasts that were clustered into 6 subpopulations, of which 5 fibroblast clusters (subcluster 0, 1, 2, 3, 4) were mainly enriched in ICC tissues, whereas subcluster 5 was mainly present in adjacent tissues

可以看到Cancer-associated fibroblasts (CAFs) 细胞的各个亚群基本上都在癌症和癌旁两个分组里面都是存储，除了 subcluster 5 这个比例本来就是超级低的亚群是特异性的存在于癌旁分组里面。

分群和分组比例

这个时候，跟前面的：肿瘤样品的单细胞需要提取上皮细胞继续细分教程类似，也是通过标记基因，生物学功能数据库注释，转录因子分析来对每个亚群进行细致性的探索。

首先看看这个 Cancer-associated fibroblasts (CAFs) 细胞 的 各自高表达量特异性标记基因：

各自高表达量特异性标记基因

可以看到，区分度还挺好的，也展现了每个细分的fibroblast 亚群的各自的top3基因，进行了生物学描述如下：

• Subcluster 0 fibroblasts accounted for the majority of the fibroblast populations (57.6%) and were characterized by microvasculature signature genes such as CD146 (MCAM), MYH11, GJA4, and RGS5, as well as inflammatory chemokines such as IL-6 and CCL8 (Fig. 4E). Thus, we designated them as vascular CAFs (vCAFs, vCAFs-c0-MCAM). Gene ontology (GO) analysis of vCAFs indicated significant enrichment for muscle contraction, response to hypoxia, and mesenchymal cell prolif- eration, consistent with their microvascular signatures (Fig. 4F).
• Subcluster 1 fibroblasts expressed low levels of a-SMA but high levels of extracellular matrix (ECM) signatures, including collagen molecules (COL5A1, COL5A2, and COL6A3), periostin (POSTN), FN1, LUM, DCN, and VCAN. Interestingly, the GO terms enriched for this subtype were associated with ECM and collagen fibril organization, so we accordingly designated them as matrix CAFs (mCAFs, mCAFs–c1–POSTN, Fig. 4E, F). Like mCAFs–c1–POSTN,
• Subcluster 2 fibroblasts expressed low levels of a-SMA but high levels of FBLN1, IGFI, CXCL1, IGFBP6, SLPI, SAA1, and complement genes (C3 and C7). In addition, the GO terms enriched for this Subcluster were related to ECM, inflammatory response regulation, and complement activation, indicating that this Subcluster may engage in immune modulation. Accordingly, fibroblasts in this Subcluster were named inflammatory CAFs (iCAFs, iCAFs–c2–FBLN1; Fig. 4E, F). Consistent with a previous report of mouse KPC tumors (Kras+/LSL-G12D; Trp53+/LSL- R172H; Pdx1-Cre) and human pancreatic ductal adenocarcinoma (PDAC),25 we found that
• Subcluster 3 fibroblasts expressed major histocompatibility complex II (MHC-II) genes such as CD74, HLA- DRA, and HLA-DRB1. Moreover, the GO terms enriched in this Subcluster were related to leukocyte cell-cell adhesion, response to IFN-c, antigen processing, and antigen presentation via MHC- II; we therefore termed them antigen-presenting CAFs (apCAFs, apCAFs–c3–CD74; Fig. 4E, F).
• Subcluster 4 fibroblasts mainly expressed epithelium-specific marker genes such as KRT19, KRT8, and SAA1, which we designated as EMT-like CAFs (eCAFs, eCAFs–c4–KRT19; Fig. 4D). Finally,
• Subcluster 5 fibroblasts were mainly derived from adjacent tissues and expressed high levels of lipid metabolism and processing related genes, including APOA2, FABP1, FABP4, and FRZB, therefore, we named them lip- ofibroblast–c5–FABP1 (Fig. 4D).

很完美的生物学解释，：

• Subcluster 0 被作者定义为 vascular CAFs ，高表达 GJA4, and RGS5 等
• Subcluster 1 被作者定义为 matrix CAFs ，高表达 LUM, DCN, and VCAN等
• Subcluster 2 被作者定义为 inflammatory CAFs ，高表达 complement genes (C3 and C7). 等
• Subcluster 3 被作者定义为 antigen-presenting CAFs ，高表达CD74, HLA- DRA, and HLA-DRB1 等
• Subcluster 4 被作者定义为 EMT-like CAFs ，高表达 KRT19, KRT8 等
• Subcluster 5 被作者定义为 lip- ofibroblast–c5–FABP1 ，高表达APOA2, FABP1, FABP4, and FRZB等

如果以我浅薄的生物学背景，我会认为Subcluster 0 其实是pericyte，而 Subcluster 2和3都是免疫功能性CAF，而 Subcluster 4 干脆就是上皮细胞了，Subcluster 5 我也不会认为它是CAF。

不过，这个文章毕竟不是我来操刀，我们还是尊重作者的生物学故事啦：

各个亚群特异性基因的生物学功能

可以看到，这个Cancer-associated fibroblasts (CAFs) 细胞虽然跟跟前面的：肿瘤样品的单细胞需要提取上皮细胞继续细分教程类似，但是很明显简单太多了，没有gsea或者gsva也没有转录因子分析，也没有拟时序分析！