基于生物信息学分析NPC1L1 mRNA在结肠癌中的表达及临床意义

Bioinformatic analysis of NPC1L1 mRNA expression in colon cancer and its clinical significance

摘要

目的: 基于生物信息学方法分析尼曼匹克C1型类似蛋白1(Niemann-Pick C1 like-1,NPC1L1)mRNA在结肠癌中的表达及其临床价值。方法: 收集TIMER2.0、TCGA、GEO公共数据库中结肠癌患者的NPC1L1 mRNA数据、临床病理特征数据及生存数据,比较NPC1L1 mRNA在结肠癌组织与癌旁组织中的差异;根据NPC1L1 mRNA最佳截断值将结肠癌患者分为NPC1L1 mRNA高表达组和低表达组,结合临床数据分析两组临床病理特征差异。采用Kaplan-Meier生存曲线、Log-rank检验分析NPC1L1 mRNA高表达组与低表达组患者5年生存率差异;Cox回归分析结肠癌患者预后的影响因素;通过R软件Cluster Profiler包输出GSEA图。选择两株人结肠癌细系HCT116、SW620进行细胞培养、传代,分别分为阴性对照组、si-NPC1L1-1、si-NPC1L1-2、si-NPC1L1-3、si-NPC1L1-4组,用对应小干扰RNA(small interfering RNA,siRNA)进行瞬时转染,采用蛋白质印迹法在蛋白质水平进行验证,筛选敲减效率最高的序列进行后续实验;将HCT116、SW620细胞分别分为si-NC组(对照)和si-NPC1L1组(敲减si-NPC1L1),采用平板克隆形成实验计算细胞克隆形成数。结果: 结肠癌组织中NPC1L1 mRNA相对表达显著高于癌旁组织(P<0.001)。NPC1L1 mRNA高表达与结肠癌患者淋巴结转移显著相关(χ²=2.126,P=0.034)。ROC曲线下面积为0.785(95%CI:0.728~0.839)。NPC1L1 mRNA高表达组5年生存率显著低于低表达组(P=0.003);单因素及多因素Cox回归分析结果显示,NPC1L1 mRNA可能为影响结肠癌患者预后的独立因素(P<0.05)。GSEA结果显示,NPC1L1 mRNA高表达组含有包括Wnt信号通路在内的10条信号通路(P<0.05)。细胞实验结果显示,si-NPC1L1-3序列对HCT116、SW620细胞中NPC1L1敲减效率最高,达65%以上;平板克隆形成实验结果显示,si-NPC1L1组HCT116、SW620细胞克隆形成数显著低于阴性对照组(P<0.001)。结论: NPC1L1 mRNA在结肠癌中呈高表达,且与结肠癌患者预后呈负相关,可作为结肠癌诊治的生物学标志物。

Abstract

Objective: To analyze the expression of Niemann-Pick C1 like-1 (NPC1L1) mRNA in colon cancer and its clinical significance based on bioinformatics methods. Methods: NPC1L1 mRNA expression data, clinicopathological characteristics, and survival data of colon cancer patients were collected from public databases including TIMER2.0, TCGA and GEO. Differences in NPC1L1 mRNA expression between tumor and adjacent non-tumor tissues were analyzed using R software. Patients were stratified into high- and low-expression groups based on the optimal cutoff value of NPC1L1 mRNA data. The correlation between NPC1L1 expression and clinicopathological features was assessed. Kaplan-Meier survival curves and Log-rank tests were used to compare 5-year survival rates between groups. Cox regression analysis was performed to identify prognostic factors for colon cancer. Gene Set Enrichment Analysis (GSEA) was performed using the Cluster Profiler package in R. Two human colon cancer cell lines, HCT116 and SW620, were cultured and passaged. Cells were divided into negative control, si-NPC1L1-1, si-NPC1L1-2, si-NPC1L1-3, and si-NPC1L1-4 groups, transiently transfected with corresponding small interfering RNAs (siRNAs). Protein levels were verified by Western blotting, and the most effective siRNA sequence was selected for further experiments. HCT116 and SW620 cells were then divided into si-NC (control) and si-NPC1L1 (knockdown) groups, and colony formation assays were performed to assess clonogenic potential. Results: NPC1L1 mRNA expression was significantly higher in colon cancer tissues than that in adjacent normal tissues (P<0.001). High NPC1L1 mRNA expression was significantly associated with lymph node metastasis in colorectal cancer patients (χ ²=2.126, P=0.034). The area under the ROC curve was 0.785 (95%CI: 0.728-0.839). The 5-year survival rate in the high-expression of NPC1L1 mRNA group was significantly lower than that in the low-expression group (P=0.003). Univariate and multivariate Cox regression analyses indicated that NPC1L1 mRNA may be an independent prognostic factor for colorectal cancer patients (P<0.05). GSEA revealed that the high-expression group was enriched in 10 signaling pathways, including the Wnt pathway (P<0.05). Cell experiments showed that the si-NPC1L1-3 sequence achieved the highest knockdown efficiency (>65%) in both HCT116 and SW620 cells. Colony formation assays demonstrated that the number of colonies formed by si-NPC1L1-treated HCT116 and SW620 cells was significantly lower than those in the negative control group (P<0.001). Conclusion: NPC1L1 mRNA is significantly overexpressed in colon cancer and negatively correlated with patient prognosis, suggesting its potential as a biomarker for diagnosis and treatment.

关键词

结肠癌 / NPC1L1 / 生物信息学 / 基因表达 / 预后

Key words

colon cancer / NPC1L1 / bioinformatics / gene expression / prognosis

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基金资助

江苏省老年健康科研项目(LKM2022031)