Regulatory mechanism and prognostic value of sex hormone pathways connected with metabolism and immune signaling in clear cell renal cell carcinoma

性激素通路与代谢和免疫信号传导相关的调控机制及其在透明细胞肾细胞癌中的预后价值

阅读:2

Abstract

Clear cell renal cell carcinoma (ccRCC) represents a major subtype of kidney cancer with variable prognosis. A comprehensive understanding of sex hormone-related pathways could potentially refine the prediction of patient outcomes in ccRCC. Patients from TCGA-KIRC (n = 528) and GSE22541 (n = 40) cohorts were analyzed. Sex-hormone-associated pathways were manually collected and calculated with the activated score, then subtypes were identified. Differential gene expression, pathway enrichment, and tumor-infiltrating immunocytes were assessed. A prognostic signature was developed using Cox analysis and LASSO regression. Immunohistochemistry (IHC) was performed to validate the protein level of key model gene in ccRCC tissues. Three distinct subtypes (C1, C2, C3) based on sex hormone pathway activation were discovered. C1 showed the most favorable prognosis (P = 0.00029). 1,094 genes were upregulated in C1 and 197 in C3. 20 risk-associated and 172 protective genes for ccRCC prognosis were identified. LASSO regression narrowed down to 33 genes for the sex-hormone-related-gene (SHAG) prognostic model. In the TCGA-KIRC cohort, the high-SHAG score group had a worse prognosis with an HR of 3.26 (95% CI: 2.334-4.555, P < 0.001). Validation in the GSE22541 cohort corroborated these findings. The nomogram incorporating the SHAG model demonstrated robust predictive accuracy higher than 0.75. IHC validation confirmed that ARHGEF17 protein levels were higher in early-stage ccRCC (stage I-II) compared to advanced-stage (stage III) tumors, supporting its prognostic relevance. The SHAG signature serves as a promising prognostic tool for ccRCC, providing insights into the role of sex hormone-related pathways in tumor progression. Further experimental and clinical validation is warranted to explore its potential in personalized therapy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。