看完这篇文章,你应该对数据挖掘充满信心

废话不多说,我们直接上文章:Identification of Key Genes in Thyroid Cancer Microenvironment

文章摘要:

Background: Tumor microenvironment (TME) plays important roles in the development of cancer. However, the roles of TME in thyroid cancer are not well studied. In our study, we aimed to identify genes related to thyroid cancer microenvironment.

Material/Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of STromal and Immune cells in Malignant Tumortissues using Expression data (ESTIMATE) datasets to identify differentially expressed genes in thyroid cancer microenvironment. Then, using these differentially expressed genes, we constructed protein-protein interaction(PPI) network and conducted functional enrichment analysis. Genes with degree beyond 12 in the PPI network were regarded as hub genes. Finally, we conducted Kaplan-Meier curve and log-rank test and functional enrichment analysis on these hub genes.

Results: There were 793 differentially expressed genes identified to be associated with immune score and stromal score in thyroid cancer microenvironment. We screened out 30 hub genes by construction of PPI network. The functions of these hub genes were enriched in immune cell activity, cytokine and chemokine activity, cell adhesion molecules, and extracellular matrix, which provided further insight into the roles of these genes in the tumor microenvironment. CXCL10, with the highest degrees in the PPI network, were positively related to overall survival of thyroid cancer patients (P=0.02467).

Conclusions: We identified 30 tumor microenvironment related genes in thyroid cancer. Among these hub genes, CXCL10 can be regarded as a prognostic biomarker in thyroid cancer.

操作步骤:

第一步,将TCGA基因矩阵与免疫评分、基质评分合并,分别根据评分的中位值分为高分组(high)与低分组(low),分别进行high vs low的差异分析

第二步,对上面得到的差异基因取交集

第三步,将交集的差异基因做功能分析(GO,KEGG,PPI分析)

第四步,筛选出30个hub基因

第五步,对hub基因做GO与KEGG分析

第六步,对hub基因进行批量生存分析

文章出现的图:

就是按照这些操作,一篇SCI就搞定了,上面的分析一两个小时就搞定了。

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