Department of Obstetrics and Gynecology, Handan Central Hospital, Handan, China.
Cancer Med. 2022 Dec;11(23):4641-4655. doi: 10.1002/cam4.4844. Epub 2022 Jul 2.
Endometrial cancer (EC) is one of the most common malignant tumors in female reproductive system. The incidence of lymph node metastasis (LNM) is only about 10% in clinically suspected early-stage EC patients. Discovering prognostic models and effective biomarkers for early diagnosis is important to reduce the mortality rate.
A least absolute shrinkage and selection operator (LASSO) regression was conducted to identify the characteristic dimension decrease and distinguish porgnostic LNM related genes signature. Subsequently, a novel prognosis-related nomogram was constructed to predict overall survival (OS). Survival analysis was carried out to explore the individual prognostic significance of the risk model and key gene was validated in vitro.
In total, 89 lymph node related genes (LRGs) were identified. Based on the LASSO Cox regression, 11 genes were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (p = 3.583e-08). The area under the ROC curve (AUC) of this model was 0.718 at 5 years of OS. Then, we developed an OS-associated nomogram that included the risk score and clinicopathological features. The concordance index of the nomogram was 0.769. The survival verification performed in three subgroups from the nomogram demonstrated the validity of the model. The AUC of the nomogram was 0.787 at 5 years OS. Proliferation and metastasis of HMGB3 were explored in EC cell line. External validation with 30 patients in our hospital showed that patients with low-risk scores had a longer OS (p-value = 0.03). Finally, we revealed that the most frequently mutated genes in the low-risk and high-risk groups are PTEN and TP53, respectively.
Our results suggest that LNM plays an important role in the prognosis, and HMGB3 was potential as a biomarker for EC patients.
子宫内膜癌（EC）是女性生殖系统最常见的恶性肿瘤之一。在临床疑似早期 EC 患者中，淋巴结转移（LNM）的发生率仅约为 10%。发现用于早期诊断的预后模型和有效生物标志物对于降低死亡率非常重要。
使用最小绝对收缩和选择算子（LASSO）回归来识别特征维度降低，并区分与预后相关的 LNM 基因特征。随后，构建了一种新的预后相关列线图以预测总生存期（OS）。进行生存分析以探讨风险模型的个体预后意义，并在体外验证关键基因。
总共鉴定出 89 个淋巴结相关基因（LRGs）。基于 LASSO Cox 回归，选择了 11 个基因来开发风险评估模型。Kaplan-Meier 曲线表明，低危组患者的 OS 明显更好（p=3.583e-08）。该模型在 5 年 OS 时的 ROC 曲线下面积（AUC）为 0.718。然后，我们开发了一个与 OS 相关的列线图，其中包含风险评分和临床病理特征。该列线图的一致性指数为 0.769。在列线图的三个亚组中进行的生存验证表明了模型的有效性。该列线图在 5 年 OS 时的 AUC 为 0.787。在 EC 细胞系中探索了 HMGB3 的增殖和转移。对我院的 30 例患者进行外部验证表明，低风险评分患者的 OS 更长（p 值=0.03）。最后，我们揭示了低风险和高风险组中最常突变的基因分别是 PTEN 和 TP53。
我们的结果表明，LNM 在预后中起重要作用，HMGB3 可能是 EC 患者的潜在生物标志物。
