Lysine crotonylation-related long non-coding RNAs: a novel prognostic framework for gastric carcinoma.

Background: Despite advances in oncology, gastric carcinoma (GC) persists as a major contributor to global cancer mortality. Lysine crotonylation (Kcr) has emerged as a pivotal post-translational modification governing gene transcription and chromatin dynamics. Yet, the specific impact of crotonylation-related long non-coding RNAs (lncRNAs) on the clinical prognosis and immune landscape of GC remains to be elucidated. Therefore, this study aimed to construct a novel prognostic framework based on Kcr-related lncRNAs and comprehensively investigate its association with the immune landscape in GC. Methods: RNA sequencing profiles and corresponding clinical metadata were acquired from The Cancer Genome Atlas (TCGA). Through co-expression analysis, we screened for lncRNAs associated with crotonylation modifications. We then constructed a novel prognostic signature using a stepwise approach comprising univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regularization, and multivariate Cox regression. The predictive performance of this model was evaluated via Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, we explored correlations between the risk signature and the tumor microenvironment (TME), tumor mutation burden (TMB), and therapeutic response. Finally, Results: Our research established a novel predictive framework centered on nine lncRNAs associated with crotonylation. The study findings demonstrated that patients classified as high-risk faced considerably poorer overall and progression-free survival rates than those in the low-risk category. While this risk assessment tool demonstrates standalone prognostic capabilities, its predictive power substantially increases when integrated with established clinical parameters. Functional enrichment analyses indicated an association between these identified lncRNAs and cancer-related signaling cascades. Furthermore, the risk score correlated with multiple TME characteristics, including immune cell infiltration patterns, extracellular matrix remodeling, and tumor mutational burden. Notably, low-risk patients displayed reduced indices of tumor immune dysfunction and exclusion, suggesting enhanced responsiveness to immunotherapeutic interventions. Additionally, the model accurately predicted patient sensitivity to specific chemotherapeutic agents like afatinib and dasatanib. Finally, our experimental evidence suggests UBOX5-AS1 as critical in promoting GC cell growth and advancement. Conclusions: We developed a signature of lncRNAs linked to crotonylation that offers dependable prognostic insights and characterizes the immune microenvironment within GC. However, additional investigation is necessary to confirm its practical applications in clinical settings.