Assessment of Weighted Gene Co-Expression Network Analysis to Explore Key Pathways and Novel Biomarkers in Muscular Dystrophy

Identifying hub genes and dysregulated pathways in Duchenne muscular dystrophy

PURPOSE

The aim of this study was to identify the hub genes and dysregulated pathways in the progression of duchenne muscular dystrophy (DMD) and to unveil detailedly the cellular and molecular mechanisms associated with DMD for developing efficacious treatments in the future.

MATERIAL AND METHODS

Three mRNA microarray datasets (GSE13608, GSE38417 and GSE109178) were downloaded from Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) between DMD and normal tissues were obtained via R package. Function enrichment analyses were implemented respectively using DAVID online database. The network analysis of protein-protein interaction network (PPI) was conducted using String. Cytoscape and String were used to analyse modules and screen hub genes. The expression of the identified hub genes was confirmed in mdx mice through using qRT-PCR.

RESULTS

In total, 519 DEGs were identified, consisting of 393 upregulated genes and 126 downregulated genes. The enriched functions and pathways of the DEGs mainly involve extracellular matrix organization, collagen fibril organization, interferon-gamma-mediated signaling pathway, muscle contraction, endoplasmic reticulum lumen, MHC class II receptor activity, phagosome, graft-versus-host disease, cardiomyocytes, calcium signaling pathway. Twelve hub genes were discovered and biological process analysis proved that these genes were mainly enriched cell cycle, cell division. The result of qRT-PCR suggested that increase in expression of CD44, ECT2, TYMS, MAGEL2, HLA-DMA, SERPINH1, TNNT2 was confirmed in mdx mice and the downregulation of ASB2 and LEPREL1 was also observed.

CONCLUSION

In conclusion, DEGs and hub genes identified in the current research help us probe the molecular mechanisms underlying the pathogenesis and progression of DMD, and provide candidate targets for diagnosis and treatment of DMD.

Entrectinib a Plausible Inhibitor for Osteopontin (SPP1) in Cervical Cancer-Integrated Bioinformatic Approach

Cervical cancer is one of the major causes of death in women, especially in developing countries bearing more than a quarter of the global burden. Secreted phosphoprotein-1, also known as OPN (osteopontin), is an integrin-binding glycophosphoprotein that is overexpressed in a variety of tumors. OPN is a chemokine-like calcified ECM-associated protein that plays a crucial role in evaluating the metastatic potential of various cancers. However, the role of SPP1 in the tumor microenvironment and associated signaling pathways in CC is still unclear. In our study, three CC microarray datasets (GSE9750, GSE46857, and GSE67522) were obtained from the GEO database to identify the differentially expressed genes. Enrichment analysis was carried out by Enrichr and ShinyGO and the PPI interaction network was created by using String and Cytoscape. GEPIA datasets were used to validate the top 10 hub genes, and virtual screening, docking, and dynamic simulation studies were used to identify a suitable inhibitor against the OPN protein using MVD, PyRx, and GROMACS respectively. Our results show that a total of 11 DEGs were common for three datasets and gene ontology pathway enrichment analysis revealed that 2 biological processes i.e. programmed cell death and animal organ development commonly affected mechanisms in all three datasets. Docking and dynamic studies revealed that Entrectinib showed excellent binding affinity against OPN protein. Based on the results, we conclude that OPN is one of the most upregulated genes in cervical cancer and Entrectinib emerges to be a promising potential OPN inhibitor to curtail cervical cancer progression. Schematic representation: The schematic representation of methodology steps is illustrated in the graphical abstract. Schematic representation of methodology.

A human skeletal muscle stem/myotube model reveals multiple signaling targets of cancer secretome in skeletal muscle

Skeletal muscle dysfunction or reprogramming due to the effects of the cancer secretome is observed in multiple malignancies. Although mouse models are routinely used to study skeletal muscle defects in cancer, because of species specificity of certain cytokines/chemokines in the secretome, a human model system is required. Here, we establish simplified multiple skeletal muscle stem cell lines (hMuSCs), which can be differentiated into myotubes. Using single nuclei ATAC-seq (snATAC-seq) and RNA-seq (snRNA-seq), we document chromatin accessibility and transcriptomic changes associated with the transition of hMuSCs to myotubes. Cancer secretome accelerated stem to myotube differentiation, altered the alternative splicing machinery and increased inflammatory, glucocorticoid receptor, and wound healing pathways in hMuSCs. Additionally, cancer secretome reduced metabolic and survival pathway associated miR-486, AKT, and p53 signaling in hMuSCs. hMuSCs underwent myotube differentiation when engrafted into NSG mice and thus providing a humanized in vivo skeletal muscle model system to study cancer cachexia.

Identification of Auxiliary Biomarkers and Description of the Immune Microenvironmental Characteristics in Duchenne Muscular Dystrophy by Bioinformatical Analysis and Experiment

Background

Duchenne muscular dystrophy (DMD) is a genetic muscle disorder characterized by progressive muscle wasting associated with persistent inflammation. In this study, we aimed to identify auxiliary biomarkers and further characterize the immune microenvironment in DMD.

Methods

Differentially expressed genes (DEGs) were identified between DMD and normal muscle tissues based on Gene Expression Omnibus (GEO) datasets. Bioinformatical analysis was used to screen and identify potential diagnostic signatures of DMD which were further validated by real-time quantitative reverse transcription PCR (RT-qPCR). We also performed single-sample gene-set enrichment analysis (ssGSEA) to characterize the proportion of tissue-infiltrating immune cells to determine the inflammatory state of DMD.

Results

In total, 182 downregulated genes and 263 upregulated genes were identified in DMD. C3, SPP1, TMSB10, TYROBP were regarded as adjunct biomarkers and successfully validated by RT-qPCR. The infiltration of macrophages, CD4+, and CD8+ T cells was significantly higher (p < 0.05) in DMD compared with normal muscle tissues, while the infiltration of activated B cells, CD56dim natural killer cells, and type 17 T helper (Th17) cells was lower. In addition, the four biomarkers (C3, SPP1, TMSB10, TYROBP) were strongly associated with immune cells and immune-related pathways in DMD muscle tissues.

Conclusion

Analyses demonstrated C3, SPP1, TMSB10, and TYROBP may serve as biomarkers and enhance our understanding of immune responses in DMD. The infiltration of immune cells into the muscle microenvironment might exert a critical impact on the development and occurrence of DMD.

Application of Droplet Digital PCR Technology in Muscular Dystrophies Research

Although they are considered rare disorders, muscular dystrophies have a strong impact on people’s health. Increased disease severity with age, frequently accompanied by the loss of ability to walk in some people, and the lack of treatment, have directed the researchers towards the development of more effective therapeutic strategies aimed to improve the quality of life and life expectancy, slow down the progression, and delay the onset or convert a severe phenotype into a milder one. Improved understanding of the complex pathology of these diseases together with the tremendous advances in molecular biology technologies has led to personalized therapeutic procedures. Different approaches that are currently under extensive investigation require more efficient, sensitive, and less invasive methods. Due to its remarkable analytical sensitivity, droplet digital PCR has become a promising tool for accurate measurement of biomarkers that monitor disease progression and quantification of various therapeutic efficiency and can be considered a tool for non-invasive prenatal diagnosis and newborn screening. Here, we summarize the recent applications of droplet digital PCR in muscular dystrophy research and discuss the factors that should be considered to get the best performance with this technology.

Proteome-wide systems genetics identifies UFMylation as a regulator of skeletal muscle function

Improving muscle function has great potential to improve the quality of life. To identify novel regulators of skeletal muscle metabolism and function, we performed a proteomic analysis of gastrocnemius muscle from 73 genetically distinct inbred mouse strains, and integrated the data with previously acquired genomics and >300 molecular/phenotypic traits via quantitative trait loci mapping and correlation network analysis. These data identified thousands of associations between protein abundance and phenotypes and can be accessed online (https://muscle.coffeeprot.com/) to identify regulators of muscle function. We used this resource to prioritize targets for a functional genomic screen in human bioengineered skeletal muscle. This identified several negative regulators of muscle function including UFC1, an E2 ligase for protein UFMylation. We show UFMylation is up-regulated in a mouse model of amyotrophic lateral sclerosis, a disease that involves muscle atrophy. Furthermore, in vivo knockdown of UFMylation increased contraction force, implicating its role as a negative regulator of skeletal muscle function.