{"title":"免疫相关基因对甲状腺癌症的诊断和预后。","authors":"Jinze Li, Zhenjun Li, Ping Zhao","doi":"10.1097/COC.0000000000001048","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.</p><p><strong>Methods: </strong>Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.</p><p><strong>Results: </strong>Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.</p><p><strong>Conclusion: </strong>Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.</p>","PeriodicalId":50812,"journal":{"name":"American Journal of Clinical Oncology-Cancer Clinical Trials","volume":" ","pages":"1-10"},"PeriodicalIF":1.6000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnosis and Prognosis of Thyroid Cancer by Immune-related Genes.\",\"authors\":\"Jinze Li, Zhenjun Li, Ping Zhao\",\"doi\":\"10.1097/COC.0000000000001048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.</p><p><strong>Methods: </strong>Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.</p><p><strong>Results: </strong>Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.</p><p><strong>Conclusion: </strong>Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.</p>\",\"PeriodicalId\":50812,\"journal\":{\"name\":\"American Journal of Clinical Oncology-Cancer Clinical Trials\",\"volume\":\" \",\"pages\":\"1-10\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Clinical Oncology-Cancer Clinical Trials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/COC.0000000000001048\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/10/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Clinical Oncology-Cancer Clinical Trials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/COC.0000000000001048","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/10/2 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
Diagnosis and Prognosis of Thyroid Cancer by Immune-related Genes.
Background: Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.
Methods: Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.
Results: Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.
Conclusion: Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.
期刊介绍:
American Journal of Clinical Oncology is a multidisciplinary journal for cancer surgeons, radiation oncologists, medical oncologists, GYN oncologists, and pediatric oncologists.
The emphasis of AJCO is on combined modality multidisciplinary loco-regional management of cancer. The journal also gives emphasis to translational research, outcome studies, and cost utility analyses, and includes opinion pieces and review articles.
The editorial board includes a large number of distinguished surgeons, radiation oncologists, medical oncologists, GYN oncologists, pediatric oncologists, and others who are internationally recognized for expertise in their fields.