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Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer

机译:单细胞转录谱揭示结直肠癌中的异质性

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Background: Colorectal Cancer (CRC) is a highly heterogeneous disease. RNA profiles of bulk tumors have enabled transcriptional classification of CRC. However, such ways of sequencing can only target a cell colony and obscure the signatures of distinct cell populations. Alternatively, single-cell RNA sequencing (scRNA-seq), which can provide unbiased analysis of all cell types, opens the possibility to map cellular heterogeneity of CRC unbiasedly. Methods: In this study, we utilized scRNA-seq to profile cells from cancer tissue of a CRC patient. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to understand the roles of genes within the clusters. Results and Conclusion: The 2824 cells were analyzed and categorized into 5 distinct clusters by scRNA-seq. For every cluster , specific cell markers can be applied, indicating each 1 of them different from another. We discovered that the tumor of CRC displayed a clear sign of heterogenicity , while genes within each cluster serve different functions. GO term analysis also stated that different cluster 's relatedness towards the tumor of CRC differs. Three clusters participate in peripheral works in cells, including, energy transport, extracellular matrix generation, etc; Genes in other 2 clusters participate more in immunology processes. Lastly, trajectory plot analysis also supports the viewpoint, in that some clusters present in different states and pseudo-time, while others present in a single state or pseudo time. Our analysis provides more insight into the heterogeneity of CRC, which can provide assistance to further researches on this topic.
机译:背景:结肠直肠癌(CRC)是一种高度异质的疾病。散装肿瘤的RNA谱具有CRC的转录分类。然而,这些测序方式只能靶向细胞群体并模糊不同细胞群的签名。或者,可以提供所有细胞类型的单细胞RNA测序(ScRNA-SEQ),其可提供所有细胞类型的无偏异分析,这可能是对CRC的细胞异质性进行偏见的可能性。方法:在本研究中,我们利用ScrNA-SEQ从CRC患者的癌症组织剖面细胞。进行基因本体(GO)和京都基因和基因组(KEGG)途径分析以了解基因在簇内的作用。结果和结论:分析了2824个细胞,并通过ScRNA-SEQ分为5个不同的簇。对于每个群集,可以应用特定的小区标记,指示它们中的每个1与另一个相同。我们发现CRC的肿瘤显示出透明的异质性迹象,而每个簇内的基因可以用于不同的功能。 GO术语分析还表示,不同的集群对CRC肿瘤的相关性不同。三簇参与细胞中的外周工作,包括能量传输,细胞外基质生成等;其他2个集群中的基因更多地参与免疫过程。最后,轨迹绘图分析还支持观点,其中一些群体存在于不同状态和伪时,而其他群体存在于单个状态或伪时间。我们的分析提供了对CRC的异质性的更多洞察力,这可以为进一步研究本主题提供援助。

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