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基于焦亡相关基因的甲状腺乳头状癌诊断模型的开发与验证:一项生物信息学和体外研究
Authors Ding L, Zheng G, Zhou A, Song F, Zhu L, Cai Y, Guo Y, Hua T , Liu Y, Ma W, Hu Y, Guo Y , Zheng C
Received 19 May 2024
Accepted for publication 17 October 2024
Published 29 October 2024 Volume 2024:17 Pages 7761—7776
DOI https://doi.org/10.2147/JIR.S478989
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Ning Quan
Lingling Ding,1,* Guowan Zheng,1– 3,* Aoni Zhou,4 Fahuan Song,1– 3 Lei Zhu,5 Yefeng Cai,6 Yehao Guo,1 Tebo Hua,7 Yunye Liu,1 Wenli Ma,1 Yiqun Hu,1– 3 Yawen Guo,1– 3 Chuanming Zheng1– 3
1Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, 310000, People’s Republic of China; 2Zhejiang Provincial Clinical Research Center for Malignant Tumor, Hangzhou, Zhejiang, 310000, People’s Republic of China; 3Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou, Zhejiang, 310000, People’s Republic of China; 4Hangzhou Normal University, Hangzhou, Zhejiang, 311121, People’s Republic of China; 5Department of Thyroid Surgery, The Fifth Hospital Affiliated to Wenzhou Medical University, Lishui Central Hospital, Lishui, Zhejiang, 323000, People’s Republic of China; 6Department of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People’s Republic of China; 7Department of Thyroid Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo, Zhejiang, 315000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yawen Guo; Chuanming Zheng, Department of Head and Neck Surgery, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, No. 158, Shangtang Road, Hangzhou, Zhejiang, People’s Republic of China, Email mingdoc@163.com; gyw20072644@126.com
Background: The incidence of papillary thyroid cancer (PTC) has been increasing annually; however, early diagnosis can improve patient outcomes. Pyroptosis is a programmed cell death modality that has received considerable attention recently. However, no studies have reported using pyroptosis-related genes in PTC diagnosis.
Methods: Analyzed 33 pyroptosis-related genes in PTC transcriptome data from the Gene Expression Omnibus database. Subsequently, used the Least Absolute Shrinkage and Selection Operator (LASSO) model to construct a PTC molecular diagnostic model. Furthermore, confirmed differences in the expression of five genes between PTC and non-tumor tissues using immunohistochemistry. Collected 338 PTC and control samples to construct a five-gene PTC diagnostic model, which was then validated using a training set and underwent correlation analysis with immune cell infiltration. Additionally, validated the biological functions of the core gene NOD1 in vitro.
Results: The five-gene PTC diagnostic model demonstrated good diagnostic value for PTC. Moreover, identified three reliable subtypes of pyroptosis and found that NOD1 is involved in tumor-suppressive microenvironment formation. Notably, patients with high NOD1 expression had lower Progression-Free Survival (PFS). Additionally, NOD1 expression was positively correlated with immune markers such as CD47, CD68, CD3, and CD8. Lastly, inhibiting NOD1 showed significant anti-PTC activity in vitro.
Conclusion: Our results suggest that pyroptosis-related genes can be used for PTC diagnosis, and NOD1 could be a promising therapeutic target.
Keywords: pyroptosis-related genes, papillary thyroid cancer, PTC, immune cell infiltration, bioinformatic, diagnosis model