Wan Jian, Chen Shizhen, Zhang Anqin, Liu Yiting, Zhang Yangyang, Li Qinghua, Yu Ziqi, Wan Yuwei, Yang Lei, Wang Qi
The First Affiliated Hospital, Jinan University, Guangzhou, China.
Breast Disease Center, Guangdong Women and Children Hospital, Guangzhou, China.
Front Oncol. 2022 Apr 12;12:861439. doi: 10.3389/fonc.2022.861439. eCollection 2022.
Adenosine-to-inosine RNA editing (ATIRE) is increasingly being used to characterize cancer. However, no studies have been conducted to identify an ATIRE signature for predicting cancer survival.
Breast cancer (BRCA) samples with ATIRE profiles from The Cancer Genome Atlas were divided into training (n = 452) and internal validation cohorts (n = 311), and 197 additional BRCA patients were recruited as an external validation cohort. The ATIRE signature for BRCA overall survival (OS) and disease-free survival (DFS) were identified using forest algorithm analysis and experimentally verified by direct sequencing. An ATIRE-based risk score (AIRS) was established with these selected ATIRE sites. Significantly prognostic factors were incorporated to generate a nomogram that was evaluated using Harrell's C-index and calibration plot for all cohorts.
Seven ATIRE sites were revealed to be associated with both BRCA OS and DFS, of which four sites were experimentally confirmed. Patients with high AIRS displayed a higher risk of death than those with low AIRS in the training (hazard ratio (HR) = 3.142, 95%CI = 1.932-5.111), internal validation (HR = 2.097, 95%CI = 1.123-3.914), and external validation cohorts (HR = 2.680, 95%CI = 1.000-7.194). A similar hazard effect of high AIRS on DFS was also observed. The nomogram yielded Harrell's C-indexes of 0.816 (95%CI = 0.784-0.847), 0.742 (95%CI = 0.684-0.799), and 0.869 (95%CI = 0.835-0.902) for predicting OS and 0.767 (95%CI = 0.708-0.826), 0.684 (95%CI = 0.605-0.763), and 0.635 (95%CI = 0.566-0.705) for predicting DFS in the three cohorts.
AIRS nomogram could help to predict OS and DFS of patients with BRCA.
腺苷到肌苷的RNA编辑(ATIRE)越来越多地用于癌症特征分析。然而,尚未开展研究来确定用于预测癌症生存的ATIRE特征。
将来自癌症基因组图谱的具有ATIRE谱的乳腺癌(BRCA)样本分为训练队列(n = 452)和内部验证队列(n = 311),另外招募197例BRCA患者作为外部验证队列。使用森林算法分析确定BRCA总生存(OS)和无病生存(DFS)的ATIRE特征,并通过直接测序进行实验验证。利用这些选定的ATIRE位点建立基于ATIRE的风险评分(AIRS)。纳入显著的预后因素以生成列线图,并使用Harrell's C指数和校准图对所有队列进行评估。
七个ATIRE位点被揭示与BRCA的OS和DFS均相关,其中四个位点经实验确认。在训练队列(风险比(HR)= 3.142,95%置信区间(CI)= 1.932 - 5.111)、内部验证队列(HR = 2.097,95%CI = 1.123 - 3.914)和外部验证队列(HR = 2.680,95%CI = 1.000 - 7.194)中,高AIRS患者的死亡风险高于低AIRS患者。在DFS方面也观察到高AIRS有类似的风险效应。该列线图在三个队列中预测OS的Harrell's C指数分别为0.816(95%CI = 0.784 - 0.847)、0.742(95%CI = 0.684 - 0.799)和0.869(95%CI = 0.835 - 0.902),预测DFS的Harrell's C指数分别为0.767(95%CI = 0.708 - 0.826)、0.684(95%CI = 0.605 - 0.763)和0.635(95%CI = 0.566 - 0.705)。
AIRS列线图有助于预测BRCA患者的OS和DFS。