Hu Jianwen, Ning Yingze, Ma Yongchen, Sun Lie, Chen Guowei
Gastrointestinal Surgery Department, Peking University First Hospital, Beijing, China.
Laboratory Department of Anzhen Hospital, Capital Medical University, Beijing, China.
Biomark Insights. 2024 Aug 18;19:11772719241258642. doi: 10.1177/11772719241258642. eCollection 2024.
Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.
In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.
An RNA processing-related prognostic risk model based on 10 genes including , , , , , , , , , and was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8 T cells and poorer clinical prognosis than the low-risk group.
This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.
结肠癌与多个层面的分子异质性相关。RNA加工将初级转录RNA转化为成熟RNA，这推动肿瘤发生及其维持。结肠癌中RNA加工基因的特征亟待阐明。
在本研究中，我们从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）获取了1033个相关样本，以探索结肠癌中RNA加工表型的异质性。首先，无监督层次聚类分析通过对485个RNA加工基因的分析检测到具有特定临床结局和生物学特征的4个亚型。接下来，我们采用最小绝对收缩和选择算子（LASSO）以及带惩罚的Cox回归模型来表征与RNA加工相关的预后特征。
最终确定了一个基于10个基因（包括 、 、 、 、 、 、 、 、 、和 ）的与RNA加工相关的预后风险模型。通过将此特征与包括TNM、年龄、性别和分期在内的其余临床变量相结合，构建了一个综合预后列线图。还通过生物信息学方法分析了具有风险特征的基因变异、通路激活和免疫异质性。结果表明，与低风险组相比，高风险亚组与更高的基因组不稳定性、增加的增殖和周期特征、减少的肿瘤杀伤性CD8 T细胞以及更差的临床预后相关。
这种基于RNA编辑基因的预后分类器有助于根据TNM和临床结局、基因变异、通路激活和免疫异质性将结肠癌分层为特定亚组。它可用于诊断、分类和靶向治疗策略，与精准医学中的当前标准相当。它为阐明RNA编辑基因在结肠癌中作为预后标志物的作用及其临床意义提供了理论依据。
