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Exploring functions of long noncoding RNAs across multiple cancers through co-expression network
Suqing Li1, Bin Li2, Yuanting Zheng2,3
1College of Chemistry, Sichuan University, Chengdu, 610064, China.
Abstract:
In contrast to protein-coding genes, long-noncoding RNAs (lncRNAs) are much less well understood, despite increasing evidence indicating a wide range of their biological functions, and possible roles in various cancers. Based on public RNA-seq datasets of four solid cancer types, we here utilize Weighted Correlation Network Analysis (WGCNA) to propose a strategy for exploring the functions of lncRNAs altered in more than two cancer types, which we call onco-lncRNAs. Results indicate that cancer-expressed lncRNAs show high tissue specificity and are weakly expressed, more so than protein-coding genes. Most of the 236 onco-lncRNAs we identified have not been reported to have associations with cancers before. Our analysis exploits co-expression network to reveal that onco-lncRNAs likely play key roles in the multistep development of human cancers, covering a wide range of functions in genome stability maintenance, signaling, cell adhesion and motility, morphogenesis, cell cycle, immune and inflammatory response. These observations contribute to a more comprehensive understanding of cancer-associated lncRNAs, while demonstrating a novel and efficient strategy for subsequent functional studies of lncRNAs.
Insights
Long non-coding RNAs (lncRNAs) play crucial roles in cancer development. This study identifies 236 cancer-associated lncRNAs (onco-lncRNAs) and reveals their diverse functions in cancer progression.
Area of Science:
- Genomics
- Cancer Biology
- Molecular Biology
Background:
- Long non-coding RNAs (lncRNAs) are increasingly recognized for their diverse biological roles, including involvement in cancer.
- Understanding the specific functions of lncRNAs in various solid tumors remains a challenge.
Purpose of the Study:
- To develop a strategy for identifying and functionally exploring lncRNAs significantly altered across multiple cancer types.
- To identify novel cancer-associated lncRNAs (onco-lncRNAs) and elucidate their potential roles in tumorigenesis.
Main Methods:
- Utilized Weighted Correlation Network Analysis (WGCNA) on public RNA-sequencing datasets from four solid cancer types.
- Analyzed co-expression networks to infer functional roles of identified onco-lncRNAs.
Main Results:
- Identified 236 onco-lncRNAs, many previously unreported in cancer association.
- Found that cancer-expressed lncRNAs exhibit high tissue specificity and low expression levels compared to protein-coding genes.
- Onco-lncRNAs are implicated in critical cancer processes including genome stability, signaling, cell motility, and immune response.
Conclusions:
- The proposed WGCNA-based strategy effectively identifies functionally relevant onco-lncRNAs.
- Onco-lncRNAs are integral to the multistep development of human cancers, highlighting their potential as diagnostic or therapeutic targets.
- This study provides a foundation for further functional investigation of lncRNAs in oncology.