{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:41:35Z","timestamp":1776897695649,"version":"3.51.2"},"reference-count":29,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To construct a prognostic risk model for thyroid cancer based on immune genes and analyze the correlation between immune genes and immune infiltration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective study was conducted on 180 patients with thyroid cancer treated in our hospital during May 2022 to April 2025. Based on the prognosis, the subjects were graded as good prognosis group of 126 cases and poor prognosis group of 54 cases. The influencing factors were analyzed by a binary logistic regression model, receiver operating characteristic curve and goodness of fit test. Single sample gene set enrichment analysis was used to perform immune infiltration analysis on the expression matrix of peripheral blood mononuclear cells. The GSEA algorithm was used to calculate the abundance of tumor associated immune cell infiltration. Pearson correlation analysis was used to investigate the correlation. The TCGA-THCA database was used to analyze the differential expression of genes, as well as the correlation with clinical pathological features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The expression levels of CDK1, B3GNT7, S100A9, and MMP9 genes were higher in the poor prognosis group than the good prognosis group (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.05). A prognostic prediction model was constructed according to formula [1\/1 + exp (4.125 + 1.250 \u00d7 CDK1 + 1.880 \u00d7 B3GNT7 + 0.920 \u00d7 S100A9 + 1.050 \u00d7 MMP9)]. The average C-index of the model was 0.919 (95% CI: 0.882\u20130.961). The AUC of the prognosis prediction model was 0.880. The poor prognosis group had much lower infiltration abundance of B lymphocytes, CD4\n                      <jats:sup>+<\/jats:sup>\n                      T lymphocytes, and CD8\n                      <jats:sup>+<\/jats:sup>\n                      T lymphocytes, and higher infiltration abundance of neutrophils and macrophages than the good prognosis group (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.05). CDK1, B3GNT7, S100A9, and MMP9 were negatively correlated with the infiltration abundance of B lymphocytes, CD4\n                      <jats:sup>+<\/jats:sup>\n                      T lymphocytes, and CD8\n                      <jats:sup>+<\/jats:sup>\n                      T lymphocytes, and positively correlated with the infiltration abundance of neutrophils and macrophages (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.05). Further analysis from the TCGA-THCA database showed that the high expression of S100A9 and MMP9 was correlated with advanced lymph node metastasis (pN stage), distant metastasis (pM stage) and overall TNM stage (\n                      <jats:italic>P &amp;lt; 0.05<\/jats:italic>\n                      ).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>CDK1, B3GNT7, S100A9, and MMP9 were independent risk factors for poor prognosis in thyroid cancer. The prognostic prediction model may provide objective evidence for early screening of high-risk cases in clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2026.1752017","type":"journal-article","created":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:10:13Z","timestamp":1776895813000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Charting the immune terrain: a novel risk model for thyroid cancer prognosis"],"prefix":"10.3389","volume":"17","author":[{"given":"Qi","family":"Qi","sequence":"first","affiliation":[{"name":"Department of General Surgery, Shanghia Pudong New Area Gongli Hospital","place":["Shanghai, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Shanghia Pudong New Area Gongli Hospital","place":["Shanghai, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Lv","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Shanghia Pudong New Area Gongli Hospital","place":["Shanghai, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,23]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"2902","DOI":"10.1007\/s12094-024-03736-6","article-title":"SEOM-GETNE-TTCC clinical guideline thyroid cancer","volume":"26","author":"Alonso-Gordoa","year":"2024","journal-title":"Clin. Transl. Oncol."},{"key":"B2","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1001\/jama.2023.26348","article-title":"Thyroid cancer: a review","volume":"331","author":"Boucai","year":"2024","journal-title":"JAMA"},{"key":"B3","doi-asserted-by":"publisher","first-page":"102263","DOI":"10.1016\/j.jbc.2022.102263","article-title":"Phosphorylation of mixed lineage kinase MLK3 by cyclin-dependent kinases CDK1 and CDK2 controls ovarian cancer cell division","volume":"298","author":"Cedeno-Rosario","year":"2022","journal-title":"J. Biol. Chem."},{"key":"B4","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1016\/S0140-6736(23)00020-X","article-title":"Thyroid cancer","volume":"401","author":"Chen","year":"2023","journal-title":"Lancet"},{"key":"B5","doi-asserted-by":"publisher","first-page":"188891","DOI":"10.1016\/j.bbcan.2023.188891","article-title":"S100A8 and S100A9 in cancer","volume":"1878","author":"Chen","year":"2023","journal-title":"Biochim. Biophys. Acta Rev. Cancer"},{"key":"B6","doi-asserted-by":"publisher","first-page":"23574","DOI":"10.1038\/s41598-024-74695-9","article-title":"The role of the S100A8\/S100A9 in gastric tumor progression","volume":"14","author":"Fang","year":"2024","journal-title":"Sci. Rep."},{"key":"B7","doi-asserted-by":"publisher","first-page":"181","DOI":"10.48550\/arXiv.1806.09347","article-title":"Partial least squares discriminant analysis: a dimensionality reduction method to classify hyperspectral data","volume":"29","author":"Fordellone","year":"2020","journal-title":"Statistica Appl. - Italian J. Appl. Statistics"},{"key":"B8","doi-asserted-by":"publisher","first-page":"18693","DOI":"10.1038\/s41598-019-54917-1","article-title":"Myc stimulates cell cycle progression through the activation of Cdk1 and phosphorylation of p27","volume":"9","author":"Garc\u00eda-Guti\u00e9rrez","year":"2019","journal-title":"Sci. Rep."},{"key":"B9","doi-asserted-by":"publisher","first-page":"2238","DOI":"10.26355\/eurrev_202204_28454","article-title":"Matrix metalloproteinase 12 (MMP12) as an adverse prognostic biomarker of vascular invasion in hepatic cell carcinoma","volume":"26","author":"Guo","year":"2022","journal-title":"Eur. Rev. Med. Pharmacol. Sci."},{"key":"B10","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1186\/s12874-025-02694-z","article-title":"Comparison of machine learning methods versus traditional cox regression for survival prediction in cancer using real-world data: a systematic literature review and meta-analysis","volume":"25","author":"Huang","year":"2025","journal-title":"BMC Med. Res. Methodol."},{"key":"B11","first-page":"4157","article-title":"S100A8 and S100A9 expression is a crucial factor for dedifferentiation in thyroid carcinoma","volume":"29","author":"Ito","year":"2009","journal-title":"Anticancer Res."},{"key":"B12","doi-asserted-by":"publisher","first-page":"14232","DOI":"10.1038\/s41598-024-64573-9","article-title":"Cox proportional hazards regression in small studies of predictive biomarkers","volume":"14","author":"J\u00f3\u017awiak","year":"2024","journal-title":"Sci. Rep."},{"key":"B13","doi-asserted-by":"publisher","first-page":"e2500264122","DOI":"10.1073\/pnas.2500264122","article-title":"Regulatory mimicry of cyclin-dependent kinases by a conserved herpesvirus protein kinase","volume":"122","author":"Koyanagi","year":"2025","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"B14","doi-asserted-by":"publisher","first-page":"3287","DOI":"10.3390\/ijms26073287","article-title":"Interleukin-1\u03b2 inhibits ovarian cancer cell proliferation and metastasis through the MAPK\/MMP12 pathway","volume":"26","author":"Ma","year":"2025","journal-title":"Int. J. Mol. Sci."},{"key":"B15","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1186\/s12967-023-04419-6","article-title":"CD39 and LDHA affects the prognostic role of NLR in metastatic melanoma patients treated with immunotherapy","volume":"21","author":"Mallardo","year":"2023","journal-title":"J. Transl. Med."},{"key":"B16","doi-asserted-by":"publisher","first-page":"9345","DOI":"10.3390\/ijms25179345","article-title":"A combined proteomic and transcriptomic signature is predictive of response to anti-PD-1 treatment: a retrospective study in metastatic melanoma patients","volume":"25","author":"Mallardo","year":"2024","journal-title":"Int. J. Mol. Sci."},{"key":"B17","doi-asserted-by":"publisher","first-page":"3380","DOI":"10.1038\/s41467-018-05931-w","article-title":"Structure and mechanism of cancer-associated N-acetylglucosaminyltransferase-V","volume":"9","author":"Nagae","year":"2018","journal-title":"Nat. Commun."},{"key":"B18","doi-asserted-by":"publisher","first-page":"624","DOI":"10.3390\/cancers15030624","article-title":"Clinical significance of the lymph node ratio of the second operation to predict re-recurrence in thyroid carcinoma","volume":"15","author":"Park","year":"2023","journal-title":"Cancers (Basel)"},{"key":"B19","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/S2213-8587(22)00035-3","article-title":"The epidemiological landscape of thyroid cancer worldwide: GLOBOCAN estimates for incidence and mortality rates in 2020","volume":"10","author":"Pizzato","year":"2022","journal-title":"Lancet Diabetes Endocrinol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"3816","DOI":"10.3390\/ijms26083816","article-title":"Identification of CDK1 as a biomarker for the treatment of liver fibrosis and hepatocellular carcinoma through bioinformatics analysis","volume":"26","author":"Qin","year":"2025","journal-title":"Int. J. Mol. Sci."},{"key":"B21","doi-asserted-by":"publisher","first-page":"17459","DOI":"10.1002\/jcp.28367","article-title":"Human CD8+ CD25 + CD127 low regulatory T cells: microRNA signature and impact on TGF-\u03b2 and IL-10 expression","volume":"234","author":"Rouas","year":"2019","journal-title":"J. Cell Physiol."},{"key":"B22","doi-asserted-by":"publisher","first-page":"4755","DOI":"10.1158\/1078-0432.CCR-24-0729","article-title":"KIR2DL2\/DL3+ NKs and Helios+ Tregs in peripheral blood predict nivolumab response in patients with metastatic renal cell cancer","volume":"30","author":"Santagata","year":"2024","journal-title":"Clin. Cancer Res."},{"key":"B23","doi-asserted-by":"publisher","first-page":"2953","DOI":"10.3390\/biomedicines11112953","article-title":"Matrix metalloproteinase 9\/microRNA-145 ratio: bridging genomic and immunological variabilities in thyroid cancer","volume":"11","author":"Toraih","year":"2023","journal-title":"Biomedicines"},{"key":"B24","doi-asserted-by":"publisher","first-page":"16957","DOI":"10.1007\/s00432-023-05345-2","article-title":"Identification of glycogene-based prognostic signature and validation of B3GNT7 as a potential biomarker and therapeutic target in breast cancer","volume":"149","author":"Wang","year":"2023","journal-title":"J. Cancer Res. Clin. Oncol."},{"key":"B25","doi-asserted-by":"publisher","first-page":"2322","DOI":"10.7150\/jca.64747","article-title":"CDCA8 contributes to the development and progression of thyroid cancer through regulating CDK1","volume":"13","author":"Xiang","year":"2022","journal-title":"J. Cancer"},{"key":"B26","doi-asserted-by":"publisher","first-page":"823911","DOI":"10.3389\/fmolb.2022.823911","article-title":"Immune cell infiltration and relevant gene signatures in the tumor microenvironment that significantly associates with the prognosis of patients with breast cancer","volume":"9","author":"Xu","year":"2022","journal-title":"Front. Mol. Biosci."},{"key":"B27","doi-asserted-by":"publisher","first-page":"35","DOI":"10.3892\/ijo.2019.4793","article-title":"S100A9 promotes the proliferation and migration of cervical cancer cells by inducing epithelial-mesenchymal transition and activating the Wnt\/\u03b2-catenin pathway","volume":"55","author":"Zha","year":"2019","journal-title":"Int. J. Oncol."},{"key":"B28","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1166\/jbn.2022.3296","article-title":"Study on the expression of \u03b2-1,3-N-acetylglucosaminyltransferase 3 in gastric cancer and the mechanism promoting gastric cancer progression based on the extraction method of nanomagnetic beads","volume":"18","author":"Zhou","year":"2022","journal-title":"J. Biomed. Nanotechnol."},{"key":"B29","doi-asserted-by":"publisher","first-page":"2310","DOI":"10.18632\/aging.202255","article-title":"B3GNT3 overexpression promotes tumor progression and inhibits infiltration of CD8+ T cells in pancreatic cancer","volume":"13","author":"Zhuang","year":"2020","journal-title":"Aging (Albany NY)"}],"container-title":["Frontiers in Genetics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fgene.2026.1752017\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:10:14Z","timestamp":1776895814000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fgene.2026.1752017\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,23]]},"references-count":29,"alternative-id":["10.3389\/fgene.2026.1752017"],"URL":"https:\/\/doi.org\/10.3389\/fgene.2026.1752017","relation":{},"ISSN":["1664-8021"],"issn-type":[{"value":"1664-8021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,23]]},"article-number":"1752017"}}