School of Stomatology, Henan University, Jinming Road, Kaifeng, Henan, 475000, China.
Department of Pediatric General Surgery, The Third Affiliated Hospital of Zhengzhou University, No. 7 Kangfu Qian Street, Zhengzhou, Henan, 450052, China.
BMC Urol. 2024 Jan 31;24(1):26. doi: 10.1186/s12894-024-01404-z.
Kidney clear cell carcinoma (KIRC) is the most common subtype of renal cell carcinoma. Peroxisomes play a role in the regulation of tumorigenesis and cancer progression, yet the prognostic significance of peroxisome-related genes (PRGs) remains rarely studied. The study aimed to establish a novel prognostic risk model and identify potential biomarkers in KIRC.
The significant prognostic PRGs were screened through differential and Cox regression analyses, and LASSO Cox regression analysis was performed to establish a prognostic risk model in the training cohort, which was validated internally in the testing and entire cohorts, and further assessed in the GSE22541 cohort. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function and pathway differences between the high-risk and low-risk groups. The relationship between risk score and immune cell infiltration levels was evaluated in the CIBERSORT, ESTIMATE and TIMER databases. Finally, potential biomarkers were identified and validated from model genes, using immunohistochemistry.
Fourteen significant prognostic PRGs were identified using multiple analyses, and 9 genes (ABCD1, ACAD11, ACAT1, AGXT, DAO, EPHX2, FNDC5, HAO1, and HNGCLL1) were obtained to establish a prognostic model via LASSO Cox regression analysis. Combining the risk score with clinical factors to construct a nomogram, which provided support for personalized treatment protocols for KIRC patients. GO and KEGG analyses highlighted associations with substance metabolism, transport, and the PPAR signaling pathways. Tumor immune infiltration indicated immune suppression in the high-risk group, accompanied by higher tumor purity and the expression of 9 model genes was positively correlated with the level of immune cell infiltration. ACAT1 has superior prognostic capabilities in predicting the outcomes of KIRC patients.
The peroxisome-related prognostic risk model could better predict prognosis in KIRC patients.
肾透明细胞癌（KIRC）是肾细胞癌中最常见的亚型。过氧化物酶体在肿瘤发生和癌症进展的调节中发挥作用，但过氧化物酶体相关基因（PRGs）的预后意义仍很少被研究。本研究旨在建立一种新的预后风险模型，并鉴定 KIRC 中的潜在生物标志物。
通过差异和 Cox 回归分析筛选出有显著预后意义的 PRGs，在训练队列中进行 LASSO Cox 回归分析，建立预后风险模型，在测试队列和整个队列中进行内部验证，并在 GSE22541 队列中进行进一步评估。通过基因本体论（GO）富集和京都基因与基因组百科全书（KEGG）通路分析，探讨高危组和低危组之间的功能和通路差异。在 CIBERSORT、ESTIMATE 和 TIMER 数据库中评估风险评分与免疫细胞浸润水平的关系。最后，通过免疫组化从模型基因中鉴定和验证潜在的生物标志物。
通过多分析鉴定出 14 个有显著预后意义的 PRGs，通过 LASSO Cox 回归分析得到 9 个基因（ABCD1、ACAD11、ACAT1、AGXT、DAO、EPHX2、FNDC5、HAO1 和 HNGCLL1）来建立预后模型。结合风险评分和临床因素构建列线图，为 KIRC 患者的个体化治疗方案提供支持。GO 和 KEGG 分析突出了与物质代谢、运输和过氧化物酶体增殖物激活受体信号通路的关联。肿瘤免疫浸润表明高危组存在免疫抑制，同时伴有更高的肿瘤纯度，9 个模型基因的表达与免疫细胞浸润水平呈正相关。ACAT1 具有预测 KIRC 患者预后的优越能力。
过氧化物酶体相关预后风险模型可更好地预测 KIRC 患者的预后。
