Department of Laboratory Medicine, Ningbo First Hospital, Ningbo, Zhejiang, China.
Department of Hepatobiliary and Pancreatic Surgery, Ningbo First Hospital, Ningbo, Zhejiang, China.
Cancer Biomark. 2023;37(1):13-26. doi: 10.3233/CBM-220259.
Hepatocellular carcinoma (HCC) is one of the most serious malignant tumors with a poor prognosis worldwide. Cuproptosis is a novel copper-dependent cell death form, involving mitochondrial respiration and lipoylated components of the tricarboxylic acid (TCA) cycle. Long non-coding RNAs (lncRNAs) have been demonstrated to affect the tumorigenesis, growth, and metastasis of HCC.
We explored the potential roles of cuproptosis-related lncRNAs in predicting the prognosis for HCC.
The RNA-seq transcriptome data, mutation data, and clinical information data of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analyses were performed to identify a prognostic cuproptosis-related lncRNA signature. The receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of the lncRNA signature for HCC. The enrichment pathways, immune functions, immune cell infiltration, tumor mutation burden, and drug sensitivity were also analyzed.
We constructed a prognostic model consisting of 8 cuproptosis-related lncRNAs for HCC. The patients were divided into high-risk group and low-risk group according to the riskscore calculated using the model. Kaplan-Meier analysis revealed that the high-risk lncRNA signature was correlated with poor overall survival [hazard ratio (HR) =1.009, 95% confidence interval (CI) = 1.002-1.015; p= 0.010)] of HCC. A prognostic nomogram incorporated the lncRNA signature and clinicopathological features were constructed and showed favorable performance for predicting prognosis of HCC patients. In addition, the most immune-related functions were significantly different between the high-risk and low-risk groups. Tumor mutation burden (TMB) and immune checkpoints were also expressed differently between the two risk groups. Finally, HCC patients with low-risk score were more sensitive to several chemotherapy drugs.
The novel cuproptosis-related lncRNA signature could be used to predict prognosis and evaluate the effect of chemotherapy for HCC.
肝细胞癌（HCC）是全球预后最差的最严重恶性肿瘤之一。铜死亡是一种新型的铜依赖性细胞死亡形式，涉及线粒体呼吸和三羧酸（TCA）循环的脂酰化成分。长链非编码 RNA（lncRNA）已被证明影响 HCC 的发生、生长和转移。
我们探讨了铜死亡相关 lncRNA 预测 HCC 预后的潜在作用。
从癌症基因组图谱（TCGA）数据库下载 HCC 患者的 RNA-seq 转录组数据、突变数据和临床信息数据。使用最小绝对收缩和选择算子（LASSO）算法和 Cox 回归分析确定预后铜死亡相关 lncRNA 特征。使用接收者操作特征（ROC）分析评估 lncRNA 特征对 HCC 的预测价值。还分析了富集途径、免疫功能、免疫细胞浸润、肿瘤突变负担和药物敏感性。
我们构建了一个由 8 个铜死亡相关 lncRNA 组成的 HCC 预后模型。根据模型计算的风险评分，将患者分为高风险组和低风险组。Kaplan-Meier 分析表明，高风险 lncRNA 特征与 HCC 的总生存期不良相关[风险比（HR）=1.009，95%置信区间（CI）=1.002-1.015；p=0.010)]。结合 lncRNA 特征和临床病理特征构建了预后列线图，对 HCC 患者的预后预测具有良好的性能。此外，高风险和低风险组之间的大多数免疫相关功能差异显著。两组之间的肿瘤突变负担（TMB）和免疫检查点也有不同的表达。最后，低风险评分的 HCC 患者对几种化疗药物更敏感。
新型铜死亡相关 lncRNA 特征可用于预测 HCC 患者的预后，并评估化疗的效果。
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