Chen Danxia, Guo Wenhao, Yu Hailan, Yang Jianhua
Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Hangzhou, China.
Transl Cancer Res. 2022 Sep;11(9):3064-3079. doi: 10.21037/tcr-22-881.
Cervical cancer (CESC) is the second most common cancer death in middle-aged women. The N6-methyladenosine (m6A) plays an essential role in the epitranscriptomics of cancer and affects immune cell infiltration. Our study used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data to construct and validate prognostic prediction established on m6A-related genes in CESC.
We gained gene expression and clinical characteristics from TCGA and GEO. After differentially expression analysis of the m6A-related genes, we identified eight genes of CESC development. Next, we executed consensus clustering to analyze CESC types established on the differential expression of the m6A-related genes and found different subtypes significantly correlate with survival prognosis, immune microenvironment, and PD-L1 expression. Then, based on Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, a five-gene () predictive model was built in the TCGA training cohort. Finally, we checked the predictive model with survival analysis and receiver operating characteristic (ROC) curve both in the training cohort (TCGA) and in the validation cohort (GSE44001). We found the expression and variation of the five genes significantly correlate with immune cell infiltration.
The CESC could be divided into subtypes according to eight expression m6A-related genes. Different subtypes are related to various immune cells, immune scores, and the expression of the PD-L1. We develop a risk prediction model: risk score = (0.023558929) * Exp IGF2BP1 + (0.021148829) * Exp IGF2BP2 + (0.045035491) * Exp HNRNPA2B1 + (-0.106566550) * Exp YTHDF1 + (-0.001037932) * Exp RBM15. Moreover, different m6A-related genes significantly correlated with immune cells.
The m6A-related genes risk prediction model plays an essential role in predicting CESC patients. The m6A-related genes affected the immune cell infiltration in CESC. These results suggest that the expression of m6A-related genes may influence the immune therapy of CESC and be the potential therapeutic target.
宫颈癌（CESC）是中年女性中第二大常见的癌症死因。N6-甲基腺苷（m6A）在癌症的表观转录组学中起着至关重要的作用，并影响免疫细胞浸润。我们的研究使用癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）的数据来构建和验证基于CESC中m6A相关基因建立的预后预测模型。
我们从TCGA和GEO中获取基因表达和临床特征。在对m6A相关基因进行差异表达分析后，我们鉴定出8个与CESC发展相关的基因。接下来，我们进行共识聚类，以分析基于m6A相关基因的差异表达建立的CESC类型，并发现不同亚型与生存预后、免疫微环境和PD-L1表达显著相关。然后，基于最小绝对收缩和选择算子（LASSO）Cox回归分析，在TCGA训练队列中建立了一个五基因（）预测模型。最后，我们在训练队列（TCGA）和验证队列（GSE44001）中通过生存分析和受试者工作特征（ROC）曲线对预测模型进行了检验。我们发现这五个基因的表达和变异与免疫细胞浸润显著相关。
CESC可根据8个m6A相关基因的表达分为不同亚型。不同亚型与各种免疫细胞、免疫评分和PD-L1的表达有关。我们开发了一个风险预测模型：风险评分 = （0.023558929）*Exp IGF2BP1 + （0.021148829）*Exp IGF2BP2 + （0.045035491）*Exp HNRNPA2B1 + （-0.106566550）*Exp YTHDF1 + （-0.001037932）*Exp RBM15。此外，不同的m6A相关基因与免疫细胞显著相关。
m6A相关基因风险预测模型在预测CESC患者方面起着至关重要的作用。m6A相关基因影响CESC中的免疫细胞浸润。这些结果表明，m6A相关基因的表达可能影响CESC的免疫治疗，并成为潜在的治疗靶点。
