直肠癌中基因生物标志物的鉴定及免疫细胞浸润特征
Identification of gene biomarkers and immune cell infiltration characteristics in rectal cancer.
作者信息
Wen Lina, Han Zongqiang, Du Yanlin
机构信息
Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Department of Oncology, Capital Medical University; Beijing Institute of Integrated Chinese and Western Medicine Oncology, Beijing, China.
出版信息
J Gastrointest Oncol. 2021 Jun;12(3):964-980. doi: 10.21037/jgo-21-255.
BACKGROUND
Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer.
METHODS
Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots.
RESULTS
A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes.
CONCLUSIONS
The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer.
背景
与结肠癌相比，直肠癌发病率的增长更为显著。本研究旨在确定新的关键生物标志物或特征，这些标志物或特征可作为直肠癌早期诊断和治疗监测的有前景的靶点。
方法
从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据库下载了最小样本量为30的直肠癌微阵列数据集以及直肠腺癌（READ）的RNA测序数据集。采用稳健秩聚合方法整合差异表达基因（DEG）。使用STRING平台构建DEG的蛋白质-蛋白质相互作用（PPI）网络，并使用Cytoscape插件cytoHubba和UpSet图识别枢纽基因。采用R软件进行功能富集分析。绘制基于GEO数据的受试者工作特征（ROC）曲线和基于TCGA数据的Kaplan-Meier曲线，以评估枢纽基因的诊断和预后价值。使用CIBERSORT进行免疫细胞浸润分析，并通过主成分分析（PCA）、ROC曲线和相关散点图分析预后基因与浸润免疫细胞之间的诊断价值和相关性。
结果
通过整合GEO中的数据集，共获得137个稳健的DEG。包括CHGA、TTR、SAA1、SPP1、MMP1、TGFBI、COL1A1和PCK1在内的24个枢纽基因被确定为直肠癌的诊断基因生物标志物组，SAA1、SPP1和SI被确定为潜在的新预后生物标志物。在功能上，枢纽基因主要参与与直肠癌相关的白细胞介素（IL）-17和近端小管碳酸氢盐回收途径。确定了12种敏感的浸润免疫细胞，并与预后基因相关。
结论
整合的基因生物标志物组与免疫细胞浸润相结合可有效指示直肠癌。
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