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Mutation density analyses on long noncoding RNA reveal comparable patterns to protein-coding RNA and prognostic

Troy Zhang¹, Hui Yu¹, Yongsheng Bai²

¹Department of Public Health and Sciences, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136, USA.

Computational and Structural Biotechnology Journal

|October 20, 2023

Summary

Long non-coding RNAs (lncRNAs) show mutation density patterns similar to protein-coding messenger RNAs (mRNAs) in cancer. This finding highlights the potential role of lncRNA mutations in cancer research.

Keywords:

Long Noncoding RNA Mutation Density Mutation Strand Bias Transcription Start Site

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miRNA Expression Analyses in Prostate Cancer Clinical Tissues

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Published on: September 8, 2015

Area of Science:

Genomics
Cancer Biology
Molecular Oncology

Background:

Genomic research traditionally focuses on mutations and gene expression in protein-coding genes.
Advances in genomic technology and computational methods have expanded research to include mutation density and noncoding RNAs.
Integration of mutation density analysis with noncoding RNAs, specifically long non-coding RNAs (lncRNAs), remained unexplored.

Purpose of the Study:

To investigate long non-coding RNA (lncRNA) mutation density patterns across diverse cancer types.
To compare lncRNA mutation patterns with those of protein-coding messenger RNAs (mRNAs).
To explore the association between lncRNA mutation patterns, transcription strand bias, and patient prognosis.

Main Methods:

Analysis of lncRNA mutation density patterns in 80 cancer cohorts spanning 57 cancer types.
Comparison of lncRNA mutation patterns with protein-coding mRNA mutation patterns.
Statistical analysis of transcription strand bias and its correlation with prognosis using a Log Odds Ratio metric.

Main Results:

lncRNAs exhibit mutation density patterns similar to protein-coding mRNAs, including peaks and dips near transcription start sites.
Statistically significant transcription strand biases were observed in many cohorts for both lncRNAs and mRNAs.
Certain transcription strand biases were associated with patient prognosis, potentially linked to transcription-coupled repair mechanisms.

Conclusions:

This study is the first to combine mutation density patterns with lncRNA mutations.
lncRNAs display mutation patterns comparable to protein-coding mRNAs, underscoring their significance in cancer.
The findings suggest lncRNAs play a crucial role in cancer development and progression, warranting further investigation.