Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, P.R. China.
Department of Urinary Surgery, Jinan Third People's Hospital, Jinan, Shandong, P.R. China.
Cell Biol Int. 2024 Jun;48(6):777-794. doi: 10.1002/cbin.12146. Epub 2024 Mar 5.
Urinary cancer is synonymous with clear cell renal cell carcinoma (ccRCC). Unfortunately, existing treatments for this illness are ineffective and unpromising. Finding novel ccRCC biomarkers is crucial to creating successful treatments. The Cancer Genome Atlas provided clear cell renal cell carcinoma transcriptome data. Functional enrichment analysis was performed on ccRCC and control samples' differentially expressed N6-methyladenosine RNA methylation and ferroptosis-related genes (DEMFRGs). Machine learning was used to find and model ccRCC patients' predicted genes. A nomogram was created for clear cell renal cell carcinoma patients. Prognostic genes were enriched. We examined patients' immune profiles by risk score. Our prognostic genes predicted ccRCC treatment drugs. We found 37 DEMFRGs by comparing 1913 differentially expressed ccRCC genes to 202 m6A RNA methylation FRGs. Functional enrichment analysis showed that hypoxia-induced cell death and metabolism pathways were the most differentially expressed methylation functional regulating genes. Five prognostic genes were found by machine learning: TRIB3, CHAC1, NNMT, EGFR, and SLC1A4. An advanced renal cell carcinoma nomogram with age and risk score accurately predicted the outcome. These five prognostic genes were linked to various cancers. Immunological cell number and checkpoint expression differed between high- and low-risk groups. The risk model successfully predicted immunotherapy outcome, showing high-risk individuals had poor results. NIACIN, TAE-684, ROCILETINIB, and others treat ccRCC. We found ccRCC prognostic genes that work. This discovery may lead to new ccRCC treatments.
尿路上皮癌与透明细胞肾细胞癌（ccRCC）同义。不幸的是，目前针对这种疾病的治疗方法无效且前景不佳。寻找新的 ccRCC 生物标志物对于开发成功的治疗方法至关重要。癌症基因组图谱提供了透明细胞肾细胞癌转录组数据。对 ccRCC 和对照样本的差异表达 N6-甲基腺苷 RNA 甲基化和铁死亡相关基因（DEMFRGs）进行了功能富集分析。使用机器学习找到了并构建了 ccRCC 患者预测基因的模型。为透明细胞肾细胞癌患者创建了一个列线图。进行了预后基因的富集分析。我们通过风险评分检查了患者的免疫特征。我们预测了 ccRCC 治疗药物的预后基因。通过将 1913 个差异表达的 ccRCC 基因与 202 个 m6A RNA 甲基化 FRGs 进行比较，我们发现了 37 个 DEMFRGs。功能富集分析表明，缺氧诱导的细胞死亡和代谢途径是差异最大的甲基化功能调节基因。通过机器学习找到了 5 个预后基因：TRIB3、CHAC1、NNMT、EGFR 和 SLC1A4。一个具有年龄和风险评分的高级肾细胞癌列线图可以准确预测结局。这 5 个预后基因与各种癌症有关。高风险和低风险组之间的免疫细胞数量和检查点表达存在差异。风险模型成功预测了免疫治疗的结果，表明高风险个体的结果较差。NIACIN、TAE-684、ROCILETINIB 等药物可治疗 ccRCC。我们发现了可用于治疗 ccRCC 的预后基因。这一发现可能会带来新的 ccRCC 治疗方法。
