[数据库 1] "癌症细胞系百科全书"CCLE数据库简介-天涯论坛

7wu1wm0 发表于 2024-6-15 12:42:38

[数据库 1] "癌症细胞系百科全书"CCLE数据库简介

这篇文案包含：CCLE数据库的诞生CCLE通讯作者介绍CCLE数据库运用
<h3 style="color: black; text-align: left; margin-bottom: 10px;">诞生：</h3>
CCLE数据库，全叫作“Cancer Cell Line Encyclopedia”，能够看做是【癌症细胞系的百科全书】。
要紧性：供给了系统性科研细胞系的平台，能够帮忙研发抗癌药品，加速“个人定制医疗”的显现~
12年3月发布于<a style="color: black;">Nature</a>。
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic3.zhimg.com/80/v2-bdd6e7a806da1c87aa0f24fe7fa3d86e_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>文案
<h3 style="color: black; text-align: left; margin-bottom: 10px;">通讯作者：</h3>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic4.zhimg.com/80/v2-a8b5eeb9df534917b72ef52d88a9052b_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>Levi GarrawayLevi Garraway, M.D., Ph.D. The Broad Institute of Harvard and MITbest known for his contributions to genomics-driven (or “precision”) cancer medicine油管上有他的演讲视频，能够看一下~Robert Schlegel, Ph.D. Vice President, Oncology Translational Research at Novartis - retired.离休了看到“MIT”、“Harvard”、“Vice President”，有点仰慕和佩服。我像颗柠檬，酸了。
话不多说，接下来瞧瞧这些大牛团队的作品~
<h3 style="color: black; text-align: left; margin-bottom: 10px;">CCLE有什么数据？</h3>a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines.亦便是包括人类多个癌症细胞系的：基因表达数据染色体拷贝数据 (using Affymetrix SNP 6.0)Affymetrix Genome-Wide Human SNP Array 6.0 is a commercial SNP Array product by Affymetrix containing genetic markers, including single nucleotide polymorphisms (SNPs) and probes for the detection of copy number variation.3. 大规模平行测序数据
<h3 style="color: black; text-align: left; margin-bottom: 10px;">日前数据量（截止19.4.3）</h3>Cell Lines: 1457Genes: 84,434Unique Data Sets: 136,488Mutation Entries: 1,159,663Distribution Scores: 118,661,636Methylation Scores: 411,948,577<h3 style="color: black; text-align: left; margin-bottom: 10px;">CCLE能够帮咱们干什么？</h3>
CCLE重点用来查看表达谱的数据，例如：查看不同cancer cell type中某个基因的表达，主页直接输入要查找的gene名或ID就可。<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic2.zhimg.com/80/v2-78fbe3b8de98f2775280119bcaa88245_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>CCLE主页这儿提一句RNA-seq~
RNA-Seq的基本假设是什么？简单来讲便是对细胞/组织/个体的两种不同状态进行比较，寻找差异表达gene，而后从差异表达gene来推断导致生理状态不同的原由。举个例子，查看TP53在不同癌症细胞系中的表达：
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic4.zhimg.com/80/v2-558e4651037468d81b701c426edfccbb_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>boxplot结论便是：TP53 is highly expressed in all cancer types. Data was obtained through the Cancer Cell Line Encyclopedia (CCLE).
TP53为何会在所有癌症中高表达呢？
TP53基因又叫作为P53，是一种抑癌基因，该基因编码一种分子量为53kDa的蛋白质。在所有恶性肿瘤中，50%以上会显现该基因的突变，由这种基因编码的蛋白质是一种转录因子，掌控着细胞周期的起步，从细胞分裂初始这个蛋白就起着决定性功效了。倘若这个细胞受损，又不可得到修复，则P53蛋白将参与起步过程，使这个细胞在细胞凋亡中死去。有TP53缺陷的细胞无这种掌控，乃至在有害前提下继续分裂。亦点击标题栏的“data”下载原始数据，自动分析
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic2.zhimg.com/80/v2-f38492d2764d9cef51ee235f097be199_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>
2. 选择某个癌症的所有细胞系，进行聚类分析
例子1：<a style="color: black;">Evaluating cell lines as tumour models by comparison of genomic profiles</a> 经过比较不同的细胞系，寻找最适宜科研某种癌症的细胞系Our comparison of data from TCGA and the CCLE reveals striking differences between some of the most commonly used cell line models and the majority of HGSOC samples.<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic3.zhimg.com/80/v2-2dbb926d4ffb487ec814d1eab0330132_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>Expression-based clustering of all 963 CCLE cell lines from diverse tumour types.horizontal labels at bottom indicate the dominating tissue types within the respective branches of the dendrogram. Most ovarian cancer cell lines (magenta) cluster together, interspersed with endometrial cell lines.例子2：<a style="color: black;">Molecular Integrative Clustering of Asian Gastric Cell Lines Revealed Two Distinct Chemosensitivity Clusters</a>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://pic1.zhimg.com/80/v2-16b9ea42dc4764ec32a7c8210d7efd9c_720w.webp" style="width: 50%; margin-bottom: 20px;"></div>Molecular clustering of the Asian gastric cancer cell lines.The pathway enrichment score heatmap of the 380 subtype-specific pathways from the 27 gastric cell lines in CCLE is shown in<a style="color: black;">Fig. 2C</a>. Cell lines in the IC1 cluster have enrichment of genes associated with oxidative phosphorylation and mitochondria functions. On the other hand, cell lines in the IC2 cluster have enrichment of genes associated with higher inflammatory response, epithelial-mesenchymal transition, TGF-beta, Notch, RAS, and NFκB signaling. Clustering of gastric cancers to IC1 emphasizes on metabolism and energy generation while IC2 emphasizes on cell signaling and regulation of transcriptions suggesting that there are two mechanistically very distinct groups of gastric cancers.参考：<a style="color: black;">CCLE数据库几个知识点-生信菜鸟团</a> <a style="color: black;">The Ca</a>ncer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity <a style="color: black;">生物信息学100个基本问题 —— 第35题 RNA-Seq 数据的定量之RPKM和FPKM</a> <a style="color: black;">Evaluating cell lin</a>es as tumour models by comparison of genomic profiles <a style="color: black;">TP53基因突变与药品（一）——翱宇</a>

4zhvml8 发表于 2024-10-6 20:39:44

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[数据库 1] "癌症细胞系百科全书"CCLE数据库简介