Huang Enmin, Ma Tao, Zhou Junyi, Ma Ning, Yang Weisheng, Liu Chuangxiong, Hou Zehui, Chen Shuang, de Castria Tiago Biachi, Zeng Bing, Zong Zhen, Zhou Taicheng
Department of Gastroenterological Surgery and Hernia Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Ann Transl Med. 2022 Jul;10(14):766. doi: 10.21037/atm-22-3348.
The epigenetic regulators of cellular senescence, especially long non-coding RNAs (lncRNAs), remain unclear. The expression levels of lncRNA were previously known to be prognostic indicators for tumors. We hypothesized that lncRNAs regulating cellular senescence could also predict prognosis in patients with hepatocellular carcinoma (HCC) and developed a novel lncRNA predictive signature.
Using RNA sequencing data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database, a co-expression network of senescence-related messenger RNAs (mRNAs) and lncRNAs was constructed. Using univariate Cox regression analysis and a stepwise multiple Cox regression analysis, we constructed a prognostic HCC senescence-related lncRNA signature (HCCSenLncSig). Kaplan-Meier analysis was used to compare the overall survival (OS) of high- and low-risk groups stratified by the HCCSenLncSig. Furthermore, the HCCSenLncSig risk score and other clinical characteristics were included to develop an HCC prognostic nomogram. The accuracy of the model was evaluated by the time dependent receiver operating characteristic (ROC) and calibration curves, respectively.
We obtained a prognostic risk model consisting of 8 senescence-related lncRNAs: AL117336.3, AC103760.1, FOXD2-AS1, AC009283.1, AC026401.3, AC021491.4, AC124067.4, and RHPN1-AS1. The HCCSenLncSig high-risk group was associated with poor OS [hazard ratio (HR) =1.125, 95% confidence interval (CI): 1.082-1.169; P<0.001]. The accuracy of the model was further supported by ROC curves (the area under the curve is 0.783, sensitivity of 0.600, and specificity of 0.896 at the cut-off value of 1.447). The HCCSenLncSig was found to be an independent prognostic factor from other clinical factors in both univariate and multivariate Cox regression analyses. The prognostic nomogram shows HCCSenLncSig has a good prognostic effect for survival risk stratification. Finally, we found that a higher number of immunosuppressed Treg cells infiltrate in high-risk patients (P<0.001 compared to low-risk patients), possibly explaining why these patients have a poor prognosis. On the other hand, the expression of immunotherapy markers, such as CD276, PDCD1, and CTLA4, was also up-regulated in the high-risk patients, indicating potential immunotherapy response in these patients.
The development of HCCSenLncSig allows us to better predict HCC patients' survival outcomes and disease risk, as well as contribute to the development of novel HCC anti-cancer therapeutic strategies.
细胞衰老的表观遗传调节因子，尤其是长链非编码RNA（lncRNA），仍不清楚。lncRNA的表达水平此前被认为是肿瘤的预后指标。我们推测调节细胞衰老的lncRNA也可预测肝细胞癌（HCC）患者的预后，并开发了一种新的lncRNA预测特征。
利用来自癌症基因组图谱肝细胞癌（TCGA-LIHC）数据库的RNA测序数据，构建衰老相关信使RNA（mRNA）和lncRNA的共表达网络。使用单变量Cox回归分析和逐步多变量Cox回归分析，构建了一个预后性HCC衰老相关lncRNA特征（HCCSenLncSig）。采用Kaplan-Meier分析比较由HCCSenLncSig分层的高风险和低风险组的总生存期（OS）。此外，纳入HCCSenLncSig风险评分和其他临床特征以开发HCC预后列线图。分别通过时间依赖性受试者工作特征（ROC）曲线和校准曲线评估模型的准确性。
我们获得了一个由8个衰老相关lncRNA组成的预后风险模型：AL117336.3、AC103760.1、FOXD2-AS1、AC009283.1、AC026401.3、AC021491.4、AC124067.4和RHPN1-AS1。HCCSenLncSig高风险组与较差的OS相关[风险比（HR）=1.125，95%置信区间（CI）：1.082-1.169；P<0.001]。ROC曲线进一步支持了模型的准确性（曲线下面积为0.783，在临界值1.447时灵敏度为0.600，特异性为0.896）。在单变量和多变量Cox回归分析中，HCCSenLncSig被发现是独立于其他临床因素的预后因素。预后列线图显示HCCSenLncSig对生存风险分层具有良好的预后效果。最后，我们发现高风险患者中有更多免疫抑制性调节性T细胞浸润（与低风险患者相比，P<0.001），这可能解释了为什么这些患者预后较差。另一方面，免疫治疗标志物如CD276、PDCD1和CTLA4的表达在高风险患者中也上调，表明这些患者可能有免疫治疗反应。
HCCSenLncSig的开发使我们能够更好地预测HCC患者的生存结果和疾病风险，并有助于开发新的HCC抗癌治疗策略。
