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Regulated cell death (RCD) is a fundamental biological process that determines tumor progression and treatment response. Although high-throughput sequencing technologies have revealed a large number of tumor-related long noncoding RNAs (lncRNAs), systematically analyzing the regulatory landscape of lncRNAs under multiple RCD patterns remains a challenge. Here, we present LncRCD ( https://lncrcddb.bio-database.com/ ), a comprehensive resource and analysis platform specifically for cancer cell death-related lncRNAs. This study systematically integrated 1,595 core genes involved in 12 types of RCD and identified 4,624 pairs of RCD–lncRNA regulatory relationships in 18 cancer types, covering 2,088 lncRNAs with potential functional significance. To demonstrate the clinical translational value of this large-scale dataset, we conducted a comprehensive downstream bioinformatics analysis, including constructing a robust prognostic evaluation model based on RCD–lncRNA signatures, using the non-negative matrix factorization (NMF) algorithm to identify molecular subtypes with unique immune characteristics and survival outcomes, and predicting potential treatment drug sensitivity based on cancer treatment response portal data, thereby linking molecular phenotypes to clinical therapeutic guidance. The LncRCD database is a comprehensive resource database and a discovery-oriented platform, integrating user-friendly search, analysis, browsing, download, and visualization functions. Its aim is to provide a convenient resource for exploring the complex regulatory relationships between RCD and lncRNAs in human cancers. Ultimately, this study not only presents a panoramic view of lncRNAs participating in the regulation of multiple RCD patterns but also provides a valuable resource for linking omics data to biological interpretation, which may help elucidate tumor death mechanisms and offer insights for future precision immuno-oncology strategies.
Zhao et al. (Sun,) studied this question.