Zhu Yi, Zhou Yuan, Jiang HongGang, Chen ZhiHeng, Lu BoHao
Department of Gastrointestinal Surgery, The Affiliated Hospital of Jiaxing University, Jiaxing, China.
PeerJ. 2021 Nov 19;9:e12452. doi: 10.7717/peerj.12452. eCollection 2021.
Colorectal cancer (CRC) is one of the most common malignancies.An early diagnosis and an accurate prognosis are major focuses of CRC research. Tumor microenvironment cells and the extent of infiltrating immune and stromal cells contribute significantly to the tumor prognosis.
Immune and stromal scores were calculated based on the ESTIMATE algorithm using the sample expression profile of the The Cancer Genome Atlas (TCGA) database. GSE102479 was used as the validation database. Differentially expressed genes whose expression was significantly associated with the prognosis of CRC patients were identified based on the immune matrix score. Survival analysis was conducted on the union of the differentially expressed genes. A protein-protein interaction (PPI) network was constructed using the STRING database to identify the closely connected modules. To conduct functional enrichment analysis of the relevant genes, GO and KEGG pathway analyses were performed with Cluster Profiler. Pivot analysis of the ncRNAs and TFs was performed by using the RAID2.0 database and TRRUST v2 database. TF-mRNA regulatory relationships were analyzed in the TRRUST V2 database. Hubgene targeting relationships were screened in the TargetScan, miRTarBase and miRDB databases. The SNV data of the hub genes were analyzed by using the R maftools package. A ROC curve was drawn based on the TCGA database. The proportion of immune cells was estimated using CIBERSORT and the LM22 feature matrix.
The results showed that the matrix score was significantly correlated with colorectal cancer stage T. A total of 789 differentially expressed genes and 121 survival-related prognostic genes were identified. The PPI network showed that 22 core genes were related to the CRC prognosis. Furthermore, four ncRNAs that regulated the core prognosis genes, 11 TFs with regulatory effects on the core prognosis genes, and two drugs, quercetin and pseudoephedrine, that have regulatory effects on colorectal cancer were also identified.
We obtained a list of tumor microenvironment-related genes for CRC patients. These genes could be useful for determining the prognosis of CRC patients. To confirm the function of these genes, additional experiments are necessary.
结直肠癌（CRC）是最常见的恶性肿瘤之一。早期诊断和准确的预后是CRC研究的主要重点。肿瘤微环境细胞以及免疫和基质细胞的浸润程度对肿瘤预后有显著影响。
使用癌症基因组图谱（TCGA）数据库的样本表达谱，基于ESTIMATE算法计算免疫和基质评分。GSE102479用作验证数据库。基于免疫基质评分鉴定出表达与CRC患者预后显著相关的差异表达基因。对差异表达基因的并集进行生存分析。使用STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络以识别紧密连接的模块。使用Cluster Profiler对相关基因进行功能富集分析，进行GO和KEGG通路分析。使用RAID2.0数据库和TRRUST v2数据库对非编码RNA和转录因子进行枢轴分析。在TRRUST V2数据库中分析转录因子-信使核糖核酸调控关系。在TargetScan、miRTarBase和miRDB数据库中筛选枢纽基因靶向关系。使用R软件的maftools包分析枢纽基因的单核苷酸变异（SNV）数据。基于TCGA数据库绘制受试者工作特征（ROC）曲线。使用CIBERSORT和LM22特征矩阵估计免疫细胞比例。
结果表明，基质评分与结直肠癌T分期显著相关。共鉴定出789个差异表达基因和121个与生存相关的预后基因。PPI网络显示22个核心基因与CRC预后相关。此外，还鉴定出4个调控核心预后基因的非编码RNA、11个对核心预后基因有调控作用的转录因子以及2种对结直肠癌有调控作用的药物，槲皮素和伪麻黄碱。
我们获得了一份CRC患者肿瘤微环境相关基因列表。这些基因可能有助于确定CRC患者的预后。为了证实这些基因的功能，还需要进行额外的实验。
