Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Sci Rep. 2024 Aug 6;14(1):18202. doi: 10.1038/s41598-024-68256-3.
Lung adenocarcinoma is the most common primary lung cancer seen in the world, and identifying genetic markers is essential for predicting the prognosis of lung adenocarcinoma and improving treatment outcomes. It is well known that alterations in circadian rhythms are associated with a higher risk of cancer. Moreover, circadian rhythms play a regulatory role in the human body. Therefore, studying the changes in circadian rhythms in cancer patients is crucial for optimizing treatment. The gene expression data and clinical data were sourced from TCGA database, and we identified the circadian clock-related genes. We used the obtained TCGA-LUAD data set to build the model, and the other 647 lung adenocarcinoma patients' data were collected from two GEO data sets for external verification. A risk score model for circadian clock-related genes was constructed, based on the identification of 8 genetically significant genes. Based on ROC analyses, the risk model demonstrated a high level of accuracy in predicting the overall survival times of lung adenocarcinoma patients in training folds, as well as external data sets. This study has successfully constructed a risk model for lung adenocarcinoma prognosis, utilizing circadian rhythm as its foundation. This model demonstrates a dependable capacity to forecast the outcome of the disease, which can further guide the relevant mechanism of lung adenocarcinoma and combine behavioral therapy with treatment to optimize treatment decision-making.
肺腺癌是世界上最常见的原发性肺癌，鉴定遗传标志物对于预测肺腺癌的预后和改善治疗结果至关重要。众所周知，昼夜节律的改变与癌症的高风险相关。此外，昼夜节律在人体中起着调节作用。因此，研究癌症患者昼夜节律的变化对于优化治疗至关重要。基因表达数据和临床数据来自 TCGA 数据库，我们鉴定了与昼夜节律相关的基因。我们使用获得的 TCGA-LUAD 数据集来构建模型，并从两个 GEO 数据集收集了另外 647 例肺腺癌患者的数据进行外部验证。基于鉴定的 8 个具有遗传意义的基因，构建了与昼夜节律相关基因的风险评分模型。基于 ROC 分析，该风险模型在训练折叠和外部数据集中均显示出对肺腺癌患者总生存期的高度准确预测能力。这项研究成功构建了肺腺癌预后的风险模型，以昼夜节律为基础。该模型展示了可靠的疾病预后预测能力，这可以进一步指导肺腺癌的相关机制，并结合行为疗法与治疗，以优化治疗决策。
