A bioinformatic analysis of the Duchenne muscular dystrophy gene and associated gene variants across human cancers

Lee Machado*

*Corresponding author for this work

Research output: Types of ThesisMaster's Thesis


The Duchenne muscular dystrophy (DMD) gene and its major translated protein product Dystrophin (Dp427m) have for decades been associated with musculoskeletal function, with specific mutations giving rise to dysfunction in Duchenne and Becker muscular dystrophies. Alterations in the expression of the DMD gene have recently been associated with the development, progression, and survival outcomes of several tumours.

A bioinformatic workflow employing an outcome-based cutpoint selection method was developed. It was implemented to provide a comprehensive approach to examine the association of DMD mRNA expression and survival outcomes across 33 different tumour types and used bulk RNAseq data of primary tumours from the cancer genome atlas project.

Nine of the 33 tumours had significant survival outcomes using Kaplan Meier log-rank statistics and were the focus of further downstream analysis. High DMD expression was significantly associated with poor survival in low grade glioma, thymoma, rectal and kidney cancer. Conversely, low expression of DMD was associated with poor survival in uveal melanoma, pancreatic, lung adenocarcinoma, acute myeloid leukemia, and breast carcinoma.

Univariate Cox proportional hazard modelling was used to calculate DMD hazard ratios. In combination with hazard ratios from other dystrophin associated glycoprotein complex genes, hierarchical clustering was used to identify clusters that may potentially be used as candidate biomarkers for different cancer types and help identify potentially common underlying causal factors in these tumours.

The expression of the individual DMD gene products was examined and were also significantly associated with overall survival, with specific patterns of expression likely to have differential biological effects relevant to the pathogenesis of each tumour. The smallest gene product,

Dp40 was expressed across all tumours and most tumours expressed at least one Dp71 isoform. Full length Dp427m was expressed in breast cancer, low grade glioma, lung adenocarcinoma, pancreatic adenocarcinoma, rectal cancer, and uveal melanoma. Low grade glioma had the broadest expression of different DMD gene products and acute myeloid leukemia was restricted to just Dp40 expression.

To explore differences between tumours expressing high or low amounts of total DMD RNA, differential gene expression and preliminary pathway analysis identified dysregulated genes with gene ontology biological terms that related to motility and adhesion which is concordant with dystrophin’s known role as a structural/scaffold protein that facilitates cellular interaction of the actin cytoskeleton with the extracellular matrix. However, in some cancers novel terms relating to ion homeostasis (pancreatic and rectal) and chemical/sensory perception (lung) were identified, and the biological significance of this is currently unclear.

Future work will require confirmation of dystrophin protein expression in these tumours with follow-up functional experiments to demonstrate that dysregulated dystrophin is a contributor to individual hallmarks of cancer. DMD gene or protein product expression may have potential utility as an independent prognostic marker which can further stratify patients to identify those with risk of poor survival. This knowledge may ultimately improve risk stratification, patient management and aid our understating of the role dystrophin in these cancers.
Original languageEnglish
QualificationMaster of Science
Awarding Institution
  • University of Nottingham
  • Emes, Richard, Supervisor, External person
  • Brook, David, Supervisor, External person
Award date15 Dec 2022
Publication statusPublished - 7 Mar 2023


  • DMD
  • Dystrophin
  • Cancer


Dive into the research topics of 'A bioinformatic analysis of the Duchenne muscular dystrophy gene and associated gene variants across human cancers'. Together they form a unique fingerprint.

Cite this