Identification of Key Gene Modules of Neuropathic Pain by Co-Expression Analysis

Weighted gene co-expression network analysis reveals specific modules and hub genes related to neuropathic pain in dorsal root ganglions

Neuropathic pain is a common, debilitating clinical issue. Here, the weighted gene co-expression network analysis (WGCNA) was used to identify the specific modules and hub genes that are related to neuropathic pain. The microarray dataset of a neuropathic rat model induced by tibial nerve transection (TNT), including dorsal root ganglion (DRG) tissues from TNT model (n=7) and sham (n=8) rats, was downloaded from the ArrayExpress database (E-MTAB-2260). The co-expression network modules were identified by the WGCNA package. The protein–protein interaction (PPI) network was constructed, and the node with highest level of connectivity in the network were identified as the hub gene. A total of 1739 genes and seven modules were identified. The most significant module was the brown module, which contained 215 genes that were primarily associated with the biological process (BP) of the defense response and molecular function of calcium ion binding. Furthermore, C–C motif chemokine ligand 2 (Ccl2), Fos and tissue inhibitor of metalloproteinase 1 (Timp1) which were identified as the hub genes in the PPI network and two subnetworks separately. The in vivo studies validated that mRNA and protein levels of Ccl2, Fos and Timp1 were up-regulated in DRG and spinal cord tissues after TNT. The present study offers novel insights into the molecular mechanisms of neuropathic pain in the context of peripheral nerve injury.

A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma

Background

Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown.

Methods

We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein–protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank.

Results

Ten co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXP_DEPDC1 * 0.32636 + EXP_CNFN * (− 0.07544)]. The low-risk group showed better overall survival than the high-risk group (P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC (P < 0.05).

Conclusions

The two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.

PPWD1 is associated with the occurrence of postmenopausal osteoporosis as determined by weighted gene co‑expression network analysis

Postmenopausal osteoporosis (PMO) is the most common type of primary osteoporosis (OP), a systemic skeletal disease. Although many factors have been revealed to contribute to the occurrence of PMO, specific biomarkers for the early diagnosis and therapy of PMO are not available. In the present study, a weighted gene co-expression network analysis (WGCNA) was performed to screen gene modules associated with menopausal status. The turquoise module was verified as the clinically significant module, and 12 genes (NUP133, PSMD12, PPWD1, RBM8A, CRNKL1, PPP2R5C, RBM22, PIK3CB, SKIV2L2, PAPOLA, SRSF1 and COPS2) were identified as ‘real’ hub genes in both the protein-protein interaction (PPI) network and co-expression network. Furthermore, gene expression analysis by microarray in blood monocytes from pre- and post-menopausal women revealed an increase in the expression of these hub genes in postmenopausal women. However, only the expression of peptidylprolyl isomerase domain and WD repeat containing 1 (PPWD1) was correlated with bone mineral density (BMD) in postmenopausal women. In the validation set, a similar expression pattern of PPWD1 was revealed. Functional enrichment analysis revealed that the fatty acid metabolism pathway was significantly abundant in the samples that exhibited a higher expression of PPWD1. Collectively, PPWD1 is indicated as a potential diagnostic biomarker for the occurrence of PMO.

Comprehensive analysis of long noncoding RNA expression in dorsal root ganglion reveals cell-type specificity and dysregulation after nerve injury

Dorsal root ganglion (DRG) neurons provide connectivity between peripheral tissues and the spinal cord. Transcriptional plasticity within DRG sensory neurons after peripheral nerve injury contributes to nerve repair but also leads to maladaptive plasticity, including the development of neuropathic pain. This study presents tissue and neuron-specific expression profiling of both known and novel long noncoding RNAs (LncRNAs) in the rodent DRG after nerve injury. We have identified a large number of novel LncRNAs expressed within the rodent DRG, a minority of which were syntenically conserved between the mouse, rat, and human, and including, both intergenic and antisense LncRNAs. We have also identified neuron type-specific LncRNAs in the mouse DRG and LncRNAs that are expressed in human IPS cell-derived sensory neurons. We show significant plasticity in LncRNA expression after nerve injury, which in mice is strain and gender dependent. This resource is publicly available and will aid future studies of DRG neuron identity and the transcriptional landscape in both the naive and injured DRG. We present our work regarding novel antisense and intergenic LncRNAs as an online searchable database, accessible from PainNetworks (http://www.painnetworks.org/). We have also integrated all annotated gene expression data in PainNetworks, so they can be examined in the context of their protein interactions.

Emerging roles of long non-coding RNAs in neuropathic pain

Neuropathic pain, a type of chronic and potentially disabling pain resulting from primary injury/dysfunction of the somatosensory nervous system and spinal cord injury, is one of the most intense types of chronic pain, which incurs a significant economic and public health burden. However, our understanding of its cellular and molecular pathogenesis is still far from complete. Long non‐coding RNAs (lncRNAs) are important regulators of gene expression and have recently been characterized as key modulators of neuronal functions. Emerging evidence suggested that lncRNAs are deregulated and play pivotal roles in the development of neuropathic pain. This review summarizes the current knowledge about the roles of deregulated lncRNAs (eg, KCNA2‐AS, uc.48+, NONRATT021972, MRAK009713, XIST, CCAT1) in the development of neuropathic pain. These studies suggested that specific regulation of lncRNAs or their downstream targets might provide novel therapeutic avenues for this refractory disease.

Spinal RNF20-Mediated Histone H2B Monoubiquitylation Regulates mGluR5 Transcription for Neuropathic Allodynia

To date, histone H2B monoubiquitination (H2Bub), a mark associated with transcriptional elongation and ongoing transcription, has not been linked to the development or maintenance of neuropathic pain states. Here, using male Sprague Dawley rats, we demonstrated spinal nerve ligation (SNL) induced behavioral allodynia and provoked ring finger protein 20 (RNF20)-dependent H2Bub in dorsal horn. Moreover, SNL provoked RNF20-mediated H2Bub phosphorylated RNA polymerase II (RNAPII) in the promoter fragments of mGluR5, thereby enhancing mGluR5 transcription/expression in the dorsal horn. Conversely, focal knockdown of spinal RNF20 expression reversed not only SNL-induced allodynia but also RNF20/H2Bub/RNAPII phosphorylation-associated spinal mGluR5 transcription/expression. Notably, TNF-α injection into naive rats and specific neutralizing antibody injection into SNL-induced allodynia rats revealed that TNF-α-associated allodynia involves the RNF20/H2Bub/RNAPII transcriptional axis to upregulate mGluR5 expression in the dorsal horn. Collectively, our findings indicated TNF-α induces RNF20-drived H2B monoubiquitination, which facilitates phosphorylated RNAPII-dependent mGluR5 transcription in the dorsal horn for the development of neuropathic allodynia.SIGNIFICANCE STATEMENT Histone H2B monoubiquitination (H2Bub), an epigenetic post-translational modification, positively correlated with gene expression. Here, TNF-α participated in neuropathic pain development by enhancing RNF20-mediated H2Bub, which facilitates phosphorylated RNAPII-dependent mGluR5 transcription in dorsal horn. Our finding potentially identified neuropathic allodynia pathophysiological processes underpinning abnormal nociception processing and opens a new avenue for the development of novel analgesics.