Evidence map›Paper›PMID 42231908›Full record

ArticleComputational and structural biotechnology journal2026

LncRCD: A Comprehensive Database for Pan-Cancer Characterization of lncRNAs Related to 12 Regulated Cell Death Types.

Hongying Zhao, Lin Bai, Shiyi Li, Yanwu Sun, Wangyang Liu, Zushun Chen, Lu Wang, Chuncheng Hao, Li Wang

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Article in Computational and structural biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Hongying ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Lin BaiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Shiyi LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanwu SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.ORCID https://orcid.org/0009-0008-2005-4651
Wangyang LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Zushun ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Lu WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Chuncheng HaoDepartment of Head and Neck Radiation Oncology, Harbin Medical University Cancer Hospital, Harbin 150081, China.
Li WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.ORCID https://orcid.org/0000-0002-1936-8513

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID42231908
PMCPMC13223398

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.