{"title":"基于脂质代谢相关基因的甲状腺癌预后预测模型的构建与评价","authors":"","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Thyroid cancer is one of the most common tumors worldwide, and the molecular studies on lipid metabolism disorders in thyroid cancer remain unclear.</p><p><strong>Aim: </strong>This study intends to explore the model constructed by lipid metabolism genes to evaluate the prognosis of thyroid cancer.</p><p><strong>Methods: </strong>The data of thyroid cancer patients were obtained by The Cancer Genome Atlas database. The cancerous tissue from the thyroid gland was used to evaluate specific genes. Besides, Gene Set Enrichment Analysis (GSEA) and Cox proportional hazard regression models were adopted to identify the lipid metabolism genes of thyroid cancer. The survival status of patients with a risk score was analyzed by the Kaplan-Meier method, and the accuracy of the risk score was evaluated by the receiver operating characteristic (ROC) curve.</p><p><strong>Findings: </strong>Age, tumor node metastasis stage, and risk score were independent prognostic factors for thyroid cancer. FADS1, WNT3A, PCDHA2 and ITGA5 were high-risk genes. The prognostic risk score model was established according to the four lipid metabolism genes. The overall survival of patients with high-risk thyroid cancer was significantly lower than that of low-risk patients in this study.</p><p><strong>Discussion: </strong>According to the above findings, FADS1, WNT3A, PCDHA2, and ITGA5 are unfavorable factors for the prognosis of thyroid cancer in the pathway of lipid metabolism. A prognostic model composed of the above four genes was constructed, and it was confirmed that the model was not affected by age and sex.</p><p><strong>Conclusion: </strong>The prognosis prediction model for thyroid cancer based on lipid metabolism related genes was successfully constructed, and the model had good predictive ability for the prognosis of thyroid cancer patients.</p>","PeriodicalId":19098,"journal":{"name":"Neuro endocrinology letters","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction and evaluation of a prognosis prediction model for thyroid carcinoma based on lipid metabolism-related genes.\",\"authors\":\"\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Thyroid cancer is one of the most common tumors worldwide, and the molecular studies on lipid metabolism disorders in thyroid cancer remain unclear.</p><p><strong>Aim: </strong>This study intends to explore the model constructed by lipid metabolism genes to evaluate the prognosis of thyroid cancer.</p><p><strong>Methods: </strong>The data of thyroid cancer patients were obtained by The Cancer Genome Atlas database. The cancerous tissue from the thyroid gland was used to evaluate specific genes. Besides, Gene Set Enrichment Analysis (GSEA) and Cox proportional hazard regression models were adopted to identify the lipid metabolism genes of thyroid cancer. The survival status of patients with a risk score was analyzed by the Kaplan-Meier method, and the accuracy of the risk score was evaluated by the receiver operating characteristic (ROC) curve.</p><p><strong>Findings: </strong>Age, tumor node metastasis stage, and risk score were independent prognostic factors for thyroid cancer. FADS1, WNT3A, PCDHA2 and ITGA5 were high-risk genes. The prognostic risk score model was established according to the four lipid metabolism genes. The overall survival of patients with high-risk thyroid cancer was significantly lower than that of low-risk patients in this study.</p><p><strong>Discussion: </strong>According to the above findings, FADS1, WNT3A, PCDHA2, and ITGA5 are unfavorable factors for the prognosis of thyroid cancer in the pathway of lipid metabolism. A prognostic model composed of the above four genes was constructed, and it was confirmed that the model was not affected by age and sex.</p><p><strong>Conclusion: </strong>The prognosis prediction model for thyroid cancer based on lipid metabolism related genes was successfully constructed, and the model had good predictive ability for the prognosis of thyroid cancer patients.</p>\",\"PeriodicalId\":19098,\"journal\":{\"name\":\"Neuro endocrinology letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuro endocrinology letters\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuro endocrinology letters","FirstCategoryId":"3","ListUrlMain":"","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
摘要
背景:甲状腺癌是世界范围内最常见的肿瘤之一，对甲状腺癌脂质代谢紊乱的分子研究尚不清楚。目的:探讨脂质代谢基因构建的甲状腺癌预后评价模型。方法:通过cancer Genome Atlas数据库获取甲状腺癌患者资料。来自甲状腺的癌组织被用来评估特定的基因。此外，采用基因集富集分析(Gene Set Enrichment Analysis, GSEA)和Cox比例风险回归模型鉴定甲状腺癌脂质代谢基因。采用Kaplan-Meier法分析风险评分患者的生存状况，采用受试者工作特征(ROC)曲线评价风险评分的准确性。结果:年龄、肿瘤淋巴结转移分期和危险评分是甲状腺癌的独立预后因素。FADS1、WNT3A、PCDHA2、ITGA5为高危基因。根据4种脂质代谢基因建立预后风险评分模型。本研究中高危甲状腺癌患者的总生存率明显低于低危患者。讨论:综上所述，FADS1、WNT3A、PCDHA2、ITGA5在脂质代谢途径中是影响甲状腺癌预后的不利因素。构建了由上述四种基因组成的预后模型，并证实该模型不受年龄和性别的影响。结论:成功构建了基于脂质代谢相关基因的甲状腺癌预后预测模型，该模型对甲状腺癌患者的预后有较好的预测能力。
Construction and evaluation of a prognosis prediction model for thyroid carcinoma based on lipid metabolism-related genes.
Background: Thyroid cancer is one of the most common tumors worldwide, and the molecular studies on lipid metabolism disorders in thyroid cancer remain unclear.
Aim: This study intends to explore the model constructed by lipid metabolism genes to evaluate the prognosis of thyroid cancer.
Methods: The data of thyroid cancer patients were obtained by The Cancer Genome Atlas database. The cancerous tissue from the thyroid gland was used to evaluate specific genes. Besides, Gene Set Enrichment Analysis (GSEA) and Cox proportional hazard regression models were adopted to identify the lipid metabolism genes of thyroid cancer. The survival status of patients with a risk score was analyzed by the Kaplan-Meier method, and the accuracy of the risk score was evaluated by the receiver operating characteristic (ROC) curve.
Findings: Age, tumor node metastasis stage, and risk score were independent prognostic factors for thyroid cancer. FADS1, WNT3A, PCDHA2 and ITGA5 were high-risk genes. The prognostic risk score model was established according to the four lipid metabolism genes. The overall survival of patients with high-risk thyroid cancer was significantly lower than that of low-risk patients in this study.
Discussion: According to the above findings, FADS1, WNT3A, PCDHA2, and ITGA5 are unfavorable factors for the prognosis of thyroid cancer in the pathway of lipid metabolism. A prognostic model composed of the above four genes was constructed, and it was confirmed that the model was not affected by age and sex.
Conclusion: The prognosis prediction model for thyroid cancer based on lipid metabolism related genes was successfully constructed, and the model had good predictive ability for the prognosis of thyroid cancer patients.
期刊介绍：
Neuroendocrinology Letters is an international, peer-reviewed interdisciplinary journal covering the fields of Neuroendocrinology, Neuroscience, Neurophysiology, Neuropsychopharmacology, Psychoneuroimmunology, Reproductive Medicine, Chronobiology, Human Ethology and related fields for RAPID publication of Original Papers, Review Articles, State-of-the-art, Clinical Reports and other contributions from all the fields covered by Neuroendocrinology
Letters.
Papers from both basic research (methodology, molecular and cellular biology, anatomy, histology, biology, embryology, teratology, normal and pathological physiology, biophysics, pharmacology, pathology and experimental pathology, biochemistry, neurochemistry, enzymology, chronobiology, receptor studies, endocrinology, immunology and neuroimmunology, animal physiology, animal breeding and ethology, human ethology, psychology and others) and from clinical research (neurology, psychiatry and child psychiatry, obstetrics and gynecology, pediatrics, endocrinology, immunology, cardiovascular studies, internal medicine, oncology and others) will be considered.
The Journal publishes Original papers and Review Articles. Brief reports, Special Communications, proved they are based on adequate experimental evidence, Clinical Studies, Case Reports, Commentaries, Discussions, Letters to the Editor (correspondence column), Book Reviews, Congress Reports and other categories of articles (philosophy, art, social issues, medical and health policies, biomedical history, etc.) will be taken under consideration.
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