FDC-SP as a diagnostic and prognostic biomarker and modulates immune infiltrates in renal cell carcinoma

Author:

Chang Fan,Zhang Jiang-Hui,Wu Wen-Song,Tang Shuai,lv Zheng,Chen Fang-Min

Abstract

Abstract Background Renal cell carcinoma (RCC), one of the top 10 causes of cancer death, is responsible for more than 90% of all cases of primary renal cancer worldwide. Follicular dendritic cell-secreted protein (FDC-SP) specifically binds to activated B cells and regulates the generation of antibodies. It is also thought to promote cancer cell invasion and migration, which could help with tumor metastases. This study aimed to assess the efficacy of FDC-SP in the diagnosis and prognosis of RCC and to investigate the relationship between immune infiltration in RCC and these outcomes. Results RCC tissues had significantly higher levels of FDC-SP protein and mRNA than normal tissues. The high level of FDC-SP expression was linked to the T stage, histological grade, pathological stage, N stage, M stage, and OS event. Functional enrichment analysis identified the major pathways that were enriched as immune response regulation, complement, and coagulation. Immunological checkpoints and immune cell infiltration were observed to substantially correlate with the levels of FDC-SP expression. FDC-SP expression levels showed the ability to precisely distinguish high-grade or high-stage renal cancer (area under the curve (AUC) = 0.830, 0.722), and RCC patients with higher FDC-SP expression levels had worse prognoses. The AUC values for one-, two-, and five-year survival rates were all greater than 0.600. Moreover, the FDC-SP expression is an independent predictive biomarker of OS in RCC patients. Conclusion FDC-SP may be a prospective therapeutic target in RCC as well as a possible diagnostic and prognostic biomarker associated with immune infiltration.

Funder

Tianjin Health Science and Technology Project

Tianjin Science and Technology Program Project

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

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