Discovery of cell-type-specific mtDNA common deletion in nasopharyngeal carcinoma

Abstract Background The human mitochondrial genome (mtDNA) plays a key role in maintaining cellular functions. However, mtDNA is vulnerable to mutations due to the lack of protective histones and low efficiency in DNA repair mechanisms. Among these mutations, the 4977 bp mtDNA common deletion (mtDNA-CD) encompasses twelve essential genes that are essential for oxidative phosphorylation. Aim In previous studies, mtDNA-CD was identified in nasopharyngeal carcinoma (NPC) patient samples. However, bulk sequencing protocols employed in past studies were unable to distinguish whether those mtDNA-CD were specific to the cancer cells or from other non-cancer cell types in the samples. Single-cell RNA sequencing (scRNA-seq) enables the discovery of different cell types within a population and facilitates the identification of cell-type-specific mutation signatures. In this study, we propose to use scRNA-seq data to identify cell-type-specific deletion signatures in NPC samples. Methods We developed a custom computational pipeline to detect large-scale deletions using scRNA-seq data. The pipeline harnesses both clipped read profiles and secondary alignments to overcome the typical limitations of low sequencing depth and uneven read coverage in scRNA-seq data. We tested our pipeline on an NPC data set consisting of nine patients. Results Our result suggests the presence of mtDNA-CD mutations specific to malignant cancer cells in NPC tumour samples. This study proposes the use of scRNA-seq of cell-type-specific mtDNA-CD in NPC samples, offering new insights into the genetic and molecular pathogenesis of cancer and guiding the development of specific biomarkers for NPC.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2025-12-01
DOI
https://doi.org/10.1093/bib/bbaf631.057
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Discovery of cell-type-specific mtDNA common deletion in nasopharyngeal carcinoma

Joshua W. K. Ho, Mun Kay Ho
Briefings in Bioinformatics
Single-cell and spatial transcriptomics
article

Discovery of cell-type-specific mtDNA common deletion in nasopharyngeal carcinoma

Joshua W. K. Ho, Mun Kay Ho
article en

Abstract

Abstract Background The human mitochondrial genome (mtDNA) plays a key role in maintaining cellular functions. However, mtDNA is vulnerable to mutations due to the lack of protective histones and low efficiency in DNA repair mechanisms. Among these mutations, the 4977 bp mtDNA common deletion (mtDNA-CD) encompasses twelve essential genes that are essential for oxidative phosphorylation. Aim In previous studies, mtDNA-CD was identified in nasopharyngeal carcinoma (NPC) patient samples. However, bulk sequencing protocols employed in past studies were unable to distinguish whether those mtDNA-CD were specific to the cancer cells or from other non-cancer cell types in the samples. Single-cell RNA sequencing (scRNA-seq) enables the discovery of different cell types within a population and facilitates the identification of cell-type-specific mutation signatures. In this study, we propose to use scRNA-seq data to identify cell-type-specific deletion signatures in NPC samples. Methods We developed a custom computational pipeline to detect large-scale deletions using scRNA-seq data. The pipeline harnesses both clipped read profiles and secondary alignments to overcome the typical limitations of low sequencing depth and uneven read coverage in scRNA-seq data. We tested our pipeline on an NPC data set consisting of nine patients. Results Our result suggests the presence of mtDNA-CD mutations specific to malignant cancer cells in NPC tumour samples. This study proposes the use of scRNA-seq of cell-type-specific mtDNA-CD in NPC samples, offering new insights into the genetic and molecular pathogenesis of cancer and guiding the development of specific biomarkers for NPC.

Briefings in BioinformaticsVol. 26(Supplement_1)
University of Hong Kong (HK)
Openalex Percentile: Top 64%
Single-cell and spatial transcriptomics
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