Cong Fu, Lin Sun, Cuncheng Feng, Tong Zhou, Yanzhi Bi
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引用次数: 0
Abstract
Background: Lung adenocarcinoma (LUAD) is a common pathological category of lung cancer. Circadian rhythm (CR) disruption has been demonstrated to impact on lung tumorigenesis in mouse models. The aim of this study was to mine genes relevant to CR in LUAD and construct a corresponding risk model.
Methods: CRRGs from GSEA-MsigDB were filtered by overlapping DEGs in LUAD and NC specimens, two clusters with survival and clinical discrepancies, and CRRGs. Cox regression analysis (univariate and multivariate) was used to establish a CR-relevant risk model, which was validated in both the training and validation sets. Differences in immune infiltration, immunotherapy, and drug sensitivity between subgroups were explored. Prognostic gene expression was tested in clinical cancer and paracancer tissue samples using RT-qPCR.
Results: A grand total of two prognostic genes (CDK1 and HLA-DMA) related to CR were screened. The AUC values of a CR-relevant risk model in predicting 1/3/5-years survival in LUAD patients were greater than 0.6, indicating that the efficiency of the model was decent. Then, the results of CIBERSORT demonstrated noticeable differences in the tumor microenvironment between CR-relevant high- and low-risk subgroups. In addition, the CR-relevant risk score could be performed to estimate the effectiveness of immunotherapy in LUAD patients. The sensitivity of three common drugs (homoharringtonine, lapatinib, and palbociclib) in LUAD could be evaluated by the CR-relevant risk model. Ultimately, the experimental results confirmed that the expression trends of CDK1 and HLA-DMA in our collected clinical samples were in line with the expression trends in the TCGA-LUAD dataset.
Conclusion: In conclusion, a CR-relevant risk model based on CDK1 and HLA-DMA was constructed by using bioinformatics analysis, which might supply a new insight into the improved prognosis of LUAD.
期刊介绍：
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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