Department of Gastroenterology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Department of Pediatrics, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang, China.
Cancer Med. 2023 May;12(10):11611-11623. doi: 10.1002/cam4.5833. Epub 2023 Apr 5.
Colorectal cancer (CRC) is a fatal malignant tumor with poor prognosis. Cancer stem cells (CSCs) can cause metastasis, recurrence and drug resistance in CRC. This research aimed to analyze stemness-related prognostic genes of CRC based on single-cell RNA-sequencing (scRNA-seq) data.
DESeq2 was applied to analyze the differentially expressed genes (DEGs). The mRNA stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR). The stemness-related cells were analyzed based on scRNA-seq dataset GSE166555. Monocle 2 algorithm was used for stemness-related cells pseudotime trajectory analysis. The stemness-related prognostic genes were analyzed by clusterProfiler and survival package. The stemness of CRC cells was detected by spheroid formation assay, and the expression of stemness-related prognostic genes was verified by qRT-PCR and Western blot.
7916 DEGs between the CRC and normal tissues were obtained. The mRNAsi of the CRC tissues was shown to be significantly higher than that of the normal tissues. 7 and 8 cell types were annotated respectively in the normal and CRC tissues through analysis of the scRNA-seq data. Cell-cell interactions (CCIs) in the tumor tissues were revealed to be significantly enhanced than that in the normal tissues. By calculating the 'stemness score', CSCs, epithelial cells (EPCs) and cancer-associated fibroblasts (CAFs) were defined as stemness-related cells. Through pseudotime trajectory analysis, 2111 genes were identified as state 2-specific genes. Then, 41 genes were obtained by taking intersection of the up-regulated genes with state 2-specific genes and marker genes of CSCs, EPCs and CAFs. The univariate COX regression analysis revealed 5 stemness-related prognostic genes (TIMP1, PGF, FSTL3, SNAI1 and FOXC1). Kaplan-Meier curve analysis indicated that the higher the expression of 5 genes, the lower the survival rate. In vitro cell experiment confirmed that the expression of TIMP1, PGF and SNAI1 was consistent with that revealed by bioinformatics analysis.
TIMP1, PGF and SNAI1 were identified as stemness-related prognostic genes of CRC, and possibly potential therapeutic targets for CRC.
结直肠癌（CRC）是一种预后不良的致命恶性肿瘤。癌症干细胞（CSC）可导致 CRC 转移、复发和耐药。本研究旨在基于单细胞 RNA 测序（scRNA-seq）数据分析 CRC 与干性相关的预后基因。
采用 DESeq2 分析差异表达基因（DEGs）。通过单类逻辑回归（OCLR）计算 mRNA 干性指数（mRNAsi）。基于 scRNA-seq 数据集 GSE166555 分析干性相关细胞。采用 Monocle 2 算法进行干性相关细胞拟时轨迹分析。通过 clusterProfiler 和 survival 包分析与干性相关的预后基因。通过球体形成实验检测 CRC 细胞的干性，通过 qRT-PCR 和 Western blot 验证与干性相关的预后基因的表达。
在 CRC 组织和正常组织之间获得了 7916 个 DEGs。CRC 组织的 mRNAsi 显著高于正常组织。通过分析 scRNA-seq 数据，分别注释了正常和 CRC 组织中的 7 种和 8 种细胞类型。揭示了肿瘤组织中的细胞-细胞相互作用（CCIs）显著增强。通过计算“干性评分”，将 CSC、上皮细胞（EPC）和癌相关成纤维细胞（CAF）定义为干性相关细胞。通过拟时轨迹分析，鉴定出 2111 个状态 2 特异性基因。然后，通过取上调基因与状态 2 特异性基因和 CSC、EPC 和 CAF 的标记基因的交集，获得 41 个基因。单因素 COX 回归分析显示 5 个与干性相关的预后基因（TIMP1、PGF、FSTL3、SNAI1 和 FOXC1）。Kaplan-Meier 曲线分析表明，5 个基因的表达越高，生存率越低。体外细胞实验证实 TIMP1、PGF 和 SNAI1 的表达与生物信息学分析结果一致。
TIMP1、PGF 和 SNAI1 被鉴定为 CRC 与干性相关的预后基因，可能是 CRC 的潜在治疗靶点。
