AbstractLung 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.

摘要肺腺癌是世界上最常见的原发性肺癌，鉴定遗传标记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，昼夜节律的改变与更高的癌症风险有关。

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.

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，我们鉴定了生物钟相关基因。

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.

我们使用获得的TCGA-LUAD数据集构建模型，并从两个GEO数据集中收集了其他647名肺腺癌患者的数据进行外部验证。基于对8个遗传显着基因的鉴定，构建了生物钟相关基因的风险评分模型。

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.

基于ROC分析，风险模型在预测训练褶皱中肺腺癌患者的总生存时间以及外部数据集方面具有很高的准确性。本研究以昼夜节律为基础，成功构建了肺腺癌预后的风险模型。

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..

该模型具有可靠的疾病预后预测能力，可以进一步指导肺腺癌的相关机制，并将行为治疗与治疗相结合，优化治疗决策。。

IntroductionWhile cancer remains an enduring global health challenge of paramount concern. According to the Global Cancer Burden data from the IARC, the year 2020 alone witnessed a staggering 19.29 million new cancer cases worldwide, with lung cancer accounting for a formidable 2.27 million cases, and lung cancer stands as the second most frequently diagnosed malignancy and the leading cause of cancer-related mortality1,2.The American Cancer Society estimates that in 2022, the United States will witness approximately 350 new lung cancer-related fatalities each day3.

引言虽然癌症仍然是一个备受关注的持久的全球健康挑战。根据国际癌症研究机构（IARC）的全球癌症负担数据，仅2020年一年，全世界就新增癌症病例1929万例，其中肺癌占227万例，肺癌是第二大最常被诊断出的恶性肿瘤，也是导致癌症相关死亡的主要原因1,2。美国癌症协会估计，到2022年，美国每天将新增约350例肺癌相关死亡病例3。

Smoking continues to be the predominant risk factor for lung cancer. Beyond smoking, other risk factors further heighten the susceptibility to lung cancer, encompassing environmental and occupational exposures, chronic respiratory conditions, and lifestyle factors4,5,6.Lung adenocarcinoma, which is the most prevalent histological subtype of non-small cell lung cancer (NSCLC), poses a significant global health challenge, accounting for a substantial share of cancer-related morbidity and mortality7.

。除吸烟外，其他危险因素进一步增加了肺癌的易感性，包括环境和职业暴露，慢性呼吸系统疾病和生活方式因素4,5,6。肺腺癌是非小细胞肺癌（NSCLC）最常见的组织学亚型，构成了重大的全球健康挑战，占癌症相关发病率和死亡率的很大一部分7。

This cancer originate from the bronchial mucosal epithelium, and occasionally from the mucous glands of the larger bronchi8. Surgery is currently the most effective treatment for early-stage LUAD. However, non-surgical radiotherapy and chemotherapy have become the primary modalities for managing advanced-stage lung cancer patients, owing to its insidious nature and lack of specificity, often presents with advanced-stage diagnoses9.

这种癌症起源于支气管粘膜上皮，偶尔也来自较大支气管的粘液腺8。手术是目前早期LUAD最有效的治疗方法。然而，非手术放疗和化疗已成为治疗晚期肺癌患者的主要方式，由于其隐蔽性和缺乏特异性，通常表现为晚期诊断9。

Despite considerable progress in deciphering its genetic and molecular intricacies, many facets of this intricate disease remain elusive. The clinical prognosis of lung adenocarcinoma, characterized by inherent heterogeneity and diverse outcomes, continues to be a complex puzzle4,10,11. .

尽管在破译其遗传和分子复杂性方面取得了相当大的进展，但这种复杂疾病的许多方面仍然难以捉摸。肺腺癌的临床预后以固有的异质性和多种结果为特征，仍然是一个复杂的难题4,10,11。

Data availability

数据可用性

The data sets analyzed during the current study are all available in public databases. The gene expression data and clinical data of 535 LUAD samples and 59 control samples were obtained from the TCGA database (https://portal.gdc.cancer.gov/). The immune infiltration-related gene expression validation data sets GSE31210 and GSE68465 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).

当前研究期间分析的数据集都可以在公共数据库中找到。从TCGA数据库中获得了535个LUAD样本和59个对照样本的基因表达数据和临床数据(https://portal.gdc.cancer.gov/)。免疫浸润相关基因表达验证数据集GSE31210和GSE68465来自GEO数据库(https://www.ncbi.nlm.nih.gov/geo/)。

The immune infiltration-related gene data were downloaded from MSigDB (https://www.gsea-msigdb.org/gsea/). The immunohistochemical data of immune infiltration-related genes in HCC and normal liver tissues were obtained from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/)..

免疫浸润相关基因数据从MSigDB下载(https://www.gsea-msigdb.org/gsea/)。HCC和正常肝组织中免疫浸润相关基因的免疫组织化学数据来自人类蛋白质图谱（HPA）数据库(https://www.proteinatlas.org/)。。

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Download referencesAcknowledgementsWe acknowledge TCGA, HPA and GEO database for providing their platforms and contributors for uploading their meaningful datasets.FundingSupported by National Natural Science Foundation of China (81902347).Author informationAuthor notesThese authors contributed equally: Qihang Sun and Shubin Zheng.Authors and AffiliationsDepartment of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, ChinaQihang Sun, Shubin Zheng, Wei Tang, Xiaoyu Wang, Qi Wang, Ruijie Zhang, Ni Zhang & Wei PingAuthorsQihang SunView author publicationsYou can also search for this author in.

下载参考文献致谢我们感谢TCGA，HPA和GEO数据库为上传有意义的数据集提供了平台和贡献者。国家自然科学基金（81902347）资助。作者信息作者注意到这些作者做出了同样的贡献：孙启航和郑淑斌。作者和附属机构华中科技大学同济医学院同济医院胸外科，湖北武汉，孙启航，郑树斌，汤伟，王晓宇，王启旺，张瑞杰，张倪和魏萍作者孙启航作者出版物您也可以在中搜索这位作者。

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PubMed Google ScholarContributionsQ.S., W.P. and N.Z. developed the idea and Q.S. and S.Z. selected the corresponding methodological content; Q.S., W.T. and X.W. performed the preliminary data analysis; Q.S., S.Z., W.T. and X.W. wrote the manuscript; N.Z., W.P., Q.W. and R.Z.

PubMed谷歌学术贡献。S、 ，W.P.和N.Z.提出了这个想法，Q.S.和S.Z.选择了相应的方法论内容；Q、 S.，W.T.和X.W.进行了初步数据分析；Q、 S.，S.Z.，W.T.和X.W.撰写了手稿；N、 Z.，W.P.，Q.W.和R.Z。

reviewed and edited the article. N.Z., W.P., Q.W. and R.Z. reviewed and edited the article; W.P. and N.Z. managed the project. All authors have read and agreed to the published version of the manuscript.Corresponding authorsCorrespondence to.

审阅并编辑了这篇文章。N、 Z.，W.P.，Q.W.和R.Z.审查并编辑了这篇文章；W、 P.和N.Z.管理该项目。所有作者都阅读并同意手稿的出版版本。通讯作者通讯。

Ni Zhang or Wei Ping.Ethics declarations

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Reprints and permissionsAbout this articleCite this articleSun, Q., Zheng, S., Tang, W. et al. Prediction of lung adenocarcinoma prognosis and diagnosis with a novel model anchored in circadian clock-related genes.

转载和许可本文引用本文Sun，Q.，Zheng，S.，Tang，W。等人。使用锚定在生物钟相关基因中的新模型预测肺腺癌的预后和诊断。

Sci Rep 14, 18202 (2024). https://doi.org/10.1038/s41598-024-68256-3Download citationReceived: 27 March 2024Accepted: 22 July 2024Published: 06 August 2024DOI: https://doi.org/10.1038/s41598-024-68256-3Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

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KeywordsLung adenocarcinomaCircadian rhythmBioinformaticsPrognosisImmune infiltration

关键词腺癌昼夜节律生物信息学预后免疫浸润

Subjects

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CancerCancer genomicsCancer modelsLung cancerTumour biomarkers

癌症基因组扫描模型与癌症生物标志物

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