廢話不多說，我們直接上文章：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.

操作步驟：

第一步，將TCGA基因矩陣與免疫評分、基質評分合並，分別根據評分的中位值分為高分組（high）與低分組（low），分別進行high vs low的差異分析

第二步，對上面得到的差異基因取交集

第三步，將交集的差異基因做功能分析（GO，KEGG，PPI分析）

第四步，篩選出30個hub基因

第五步，對hub基因做GO與KEGG分析

第六步，對hub基因進行批次生存分析

文章出現的圖：

就是按照這些操作，一篇SCI就搞定了，上面的分析一兩個小時就搞定了。