Fatty acid metabolism influences the immune microenvironment in papillary thyroid cancer and identifies SCD as a novel biomarker.
1/5 보강
[BACKGROUND] Papillary thyroid carcinoma (PTC) is a common endocrine tumor with a rapidly increasing incidence.
APA
Shen B, Zhang Y, Tie Y (2025). Fatty acid metabolism influences the immune microenvironment in papillary thyroid cancer and identifies SCD as a novel biomarker.. Frontiers in endocrinology, 16, 1534393. https://doi.org/10.3389/fendo.2025.1534393
MLA
Shen B, et al.. "Fatty acid metabolism influences the immune microenvironment in papillary thyroid cancer and identifies SCD as a novel biomarker.." Frontiers in endocrinology, vol. 16, 2025, pp. 1534393.
PMID
40084144 ↗
Abstract 한글 요약
[BACKGROUND] Papillary thyroid carcinoma (PTC) is a common endocrine tumor with a rapidly increasing incidence. While surgery and radioactive iodine treatment are effective for most patients, they impose significant economic and psychological burdens. Metabolic dysregulation, particularly in fatty acid metabolism (FAM), plays a critical role in cancer progression and immune responses. Identifying key FAM-related genes in PTC may provide valuable biomarkers and potential treatment candidates.
[MATERIALS AND METHODS] We analyzed 309 FAM-related genes to build a prognostic signature. DEGs were identified and a multivariate Cox regression model was utilized to establish a robust prognostic signature, which was validated by evaluating its associations with clinical features, immune responses, and tumor progression. Lastly, we examined the expression of key FAM-related genes in PTC cell lines and assessed that silencing disturbs the proliferation, invasion, and migration of PTC cells.
[RESULTS] We identified three key FAM-related genes, , , and , as significant prognostic markers. Immunological analysis uncovered that low-risk patients exhibited higher immune cell abundance and increased expression of immune checkpoints, indicating a better response to immunotherapy. In contrast, high-risk patients showed lower immune cell abundance and immune checkpoint expression, suggesting poorer immunotherapy outcomes. Experimental validation demonstrated that and were downregulated, while was upregulated in PTC cell lines. Furthermore, silencing inhibited PTC cell proliferation, migration, and invasion.
[CONCLUSION] Our study underscores the pivotal role of FAM-related genes, particularly , , and , in the progression and immune regulation of PTC. The prognostic signature derived from these genes represents a valuable tool for predicting clinical outcomes and guiding personalized treatment strategies. Among these, stands out as a promising therapeutic target for PTC, warranting further research to validate these findings and uncover its underlying molecular mechanisms.
[MATERIALS AND METHODS] We analyzed 309 FAM-related genes to build a prognostic signature. DEGs were identified and a multivariate Cox regression model was utilized to establish a robust prognostic signature, which was validated by evaluating its associations with clinical features, immune responses, and tumor progression. Lastly, we examined the expression of key FAM-related genes in PTC cell lines and assessed that silencing disturbs the proliferation, invasion, and migration of PTC cells.
[RESULTS] We identified three key FAM-related genes, , , and , as significant prognostic markers. Immunological analysis uncovered that low-risk patients exhibited higher immune cell abundance and increased expression of immune checkpoints, indicating a better response to immunotherapy. In contrast, high-risk patients showed lower immune cell abundance and immune checkpoint expression, suggesting poorer immunotherapy outcomes. Experimental validation demonstrated that and were downregulated, while was upregulated in PTC cell lines. Furthermore, silencing inhibited PTC cell proliferation, migration, and invasion.
[CONCLUSION] Our study underscores the pivotal role of FAM-related genes, particularly , , and , in the progression and immune regulation of PTC. The prognostic signature derived from these genes represents a valuable tool for predicting clinical outcomes and guiding personalized treatment strategies. Among these, stands out as a promising therapeutic target for PTC, warranting further research to validate these findings and uncover its underlying molecular mechanisms.
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