LncRNA signature associated with amino acid metabolism: A novel prognostic tool for Clear Cell Renal Cell Carcinoma

introduction: The progression of clear cell renal cell carcinoma (ccRCC) is influenced by amino acid metabolism (AAM) and long non-coding RNAs (lncRNAs). However, the prognostic significance of AAM-related lncRNAs (AAMLRs) in ccRCC remains to be further investigated. materials and methods: Differentially expressed lncRNAs (DELRs) was identified with R package “limma”. AAMLRs signature were constructed via univariate Cox and LASSO analyses. The impact of risk scores on survival outcomes were evaluated via survival curve analysis. GSEA was used in pathway enrichment. The "survivalROC" R package was applied in Receiver operating characteristic (ROC) curve analysis. The R package "oncoPredic" was employed in drug sensitivity analysis. A local cohort was used for validation. results: Patients with low risk scores showed longer survival time than those with high risk scores. Several immune checkpoints were upregulated in the patients classified as high-risk group. Differences were observed between the high- and low-risk groups in terms of immune cell subtypes, including CD8+ T cells, macrophages, and NK cells. High-risk patients showed increased drug sensitivity towards 5-fluorouracil, paclitaxel, vorinostat, sorafenib, and cisplatin. discussion: The nine-AAMLR signature independently predicts ccRCC outcome better than prior models; high-risk tumors activate KRAS-driven metabolic/immune-escape pathways and immune-checkpoint genes, rendering them more sensitive to 5-FU, paclitaxel, vorinostat, sorafenib and cisplatin, whereas low-risk cases respond better to cediranib. Functional validation and prospective multi-ethnic trials are warranted to translate this ceRNA-based classifier into precision practice. conclusion: The prognostic AAMLRs signature acts as a prognostic predictor in ccRCC and provide novel insights into treatment.