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lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...

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Related Experiment Video

Updated: Jun 4, 2026

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells

Published on: May 30, 2025

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

Hongying Zhao¹, Lin Bai¹, Shiyi Li¹

¹College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Computational and Structural Biotechnology Journal

|June 3, 2026

Summary

This summary is machine-generated.

This study introduces LncRCD, a database of long noncoding RNAs (lncRNAs) involved in regulated cell death (RCD) across 18 cancer types. It provides insights into cancer progression, treatment response, and precision immuno-oncology strategies.

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Last Updated: Jun 4, 2026

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells

Published on: May 30, 2025

Area of Science:

Oncology
Molecular Biology
Bioinformatics

Background:

Regulated cell death (RCD) is crucial for tumor progression and treatment response.
Analyzing long noncoding RNAs (lncRNAs) in RCD is challenging due to data complexity.
Existing resources lack comprehensive analysis of lncRNAs across diverse RCD patterns in cancer.

Purpose of the Study:

To develop LncRCD, a database and analysis platform for cancer cell death-related lncRNAs.
To systematically identify and analyze RCD-lncRNA regulatory relationships in various cancers.
To explore the clinical translational value of RCD-lncRNA signatures for cancer treatment and immuno-oncology.

Main Methods:

Integrated 1,595 core genes from 12 RCD types with lncRNA data across 18 cancer types.
Identified 4,624 RCD-lncRNA regulatory pairs involving 2,088 lncRNAs.
Performed downstream bioinformatics analysis, including prognostic model construction, molecular subtyping (NMF), and drug sensitivity prediction.

Main Results:

Established LncRCD, a comprehensive resource with search, analysis, and visualization functions.
Identified significant RCD-lncRNA regulatory networks and potential functional lncRNAs.
Developed prognostic models and identified molecular subtypes linked to immune characteristics and treatment responses.

Conclusions:

LncRCD provides a valuable resource for understanding lncRNA roles in cancer RCD.
The findings link molecular phenotypes to clinical therapeutic guidance, aiding precision immuno-oncology.
This study offers a panoramic view of lncRNAs in RCD regulation and facilitates omics data interpretation for cancer research.