Integrative analyses identified ion channel genes GJB2 and SCNN1B as prognostic biomarkers and therapeutic targets for lung adenocarcinoma

A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer

Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n = 727), healthy controls (HEA, n = 1,092), as well as patients with small cell lung cancer (SCLC, n = 41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p < 0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.

Coexistence of a novel SRBD1-ALK, ALK-CACNA1D double-fusion in a lung adenocarcinoma patient and response to alectinib: A case report

A Chinese male patient with advanced lung adenocarcinoma experienced disease progression one and a half years after receiving first-line immunochemotherapy. The second biopsy was performed and tissue immunohistochemistry revealed Anaplastic lymphoma kinase (ALK) expression in the cytoplasm of tumor cells, so he began to receive Alectinib treatment. Then the next generation sequencing found double fusion variants of S1 RNA binding domain 1 (SRBD1)- ALK and ALK- Calcium voltage-gated channel subunit alpha1 D (CACNA1D). After continuous Alectinib treatment for 7 months, almost complete response (CR) was achieved. The patient is currently taking Alectinib for 13 months, the condition is stable, and is waiting for the next cycle of efficacy evaluation.

A novel method for detecting nine hotspot mutations of deafness genes in one tube

Deafness is a common sensory disorder. In China, approximately 70% of hereditary deafness originates from four common deafness-causing genes: GJB2, SLC26A4, GJB3, and MT-RNR1. A single-tube rapid detection method based on 2D-PCR technology was established for nine mutation sites in the aforementioned genes, and Sanger sequencing was used to verify its reliability and accuracy. The frequency of hotspot mutations in deafness genes was analysed in 116 deaf students. 2D-PCR identified 27 genotypes of nine loci according to the melting curve of the FAM, HEX, and Alexa568 fluorescence channels. Of the 116 deaf patients, 12.9% (15/116) carried SLC26A4 mutations, including c.919-2A > G and c.2168A > G (allele frequencies, 7.3% and 2.2%, respectively). The positivity rate (29.3%; 34/116) was highest for GJB2 (allele frequency, 15.9% for c.235delC, 6.0% for c.299_300delAT, and 2.6% for c.176-191del16). Sanger sequencing confirmed the consistency of results between the detection methods based on 2D-PCR and DNA sequencing. Common pathogenic mutations in patients with non-syndromic deafness in Changzhou were concentrated in GJB2 (c.235delC, c.299_300delAT, and c.176-191del16) and SLC26A4 (c.919-2A > G and c.2168 A > G). 2D-PCR is an effective method for accurately and rapidly identifying deafness-related genotypes using a single-tube reaction, and is superior to DNA sequencing, which has a high cost and long cycle.

Ion channels in lung cancer: biological and clinical relevance

Despite improvements in treatment, lung cancer is still a major health problem worldwide. Among lung cancer subtypes, the most frequent is represented by adenocarcinoma (belonging to the Non-Small Cell Lung Cancer class) although the most challenging and harder to treat is represented by Small Cell Lung Cancer, that occurs at lower frequency but has the worst prognosis. For these reasons, the standard of care for these patients is represented by a combination of surgery, radiation therapy and chemotherapy. In this view, searching for novel biomarkers that might help both in diagnosis and therapy is mandatory. In the last 30 years it was demonstrated that different families of ion channels are overexpressed in both lung cancer cell lines and primary tumours. The altered ion channel profile may be advantageous for diagnostic and therapeutic purposes since most of them are localised on the plasma membrane thus their detection is quite easy, as well as their block with specific drugs and antibodies. This review focuses on ion channels (Potassium, Sodium, Calcium, Chloride, Anion and Nicotinic Acetylcholine receptors) in lung cancer (both Non-Small Cell Lung Cancer and Small Cell Lung Cancer) and recapitulate the up-to-date knowledge about their role and clinical relevance for a potential use in the clinical setting, for lung cancer diagnosis and therapy.

Exome sequencing identifies novel variants associated with non-syndromic hearing loss in the Iranian population

Autosomal recessive non-syndromic hearing loss (ARNSHL) is a public health concern in the Iranian population, with an incidence of 1 in 166 live births. In the present study, the whole exome sequencing (WES) method was applied to identify the mutation spectrum of NSHL patients negative for GJB2 gene mutations. First, using ARMS PCR followed by Sanger sequencing of the GJB2 gene, 63.15% of mutations in patients with NSHL were identified. Among the identified mutations in GJB2:p.Val43Met and p.Gly21Arg were novel. The remaining patients were subjected to WES, which identified novel mutations including MYO15A:p.Gly39LeufsTer188, ADGRV1:p.Ser5918ValfsTer23, MYO7A: c.5856+2T>c (splicing mutation), FGF3:p.Ser156Cys. The present study emphasized the application of WES as an effective method for molecular diagnosis of NSHL patients negative for GJB2 gene mutations in the Iranian population.

Pan-cancer analysis of the prognostic and immunological role of GJB2: a potential target for survival and immunotherapy

Background

GJB2 plays an essential role in the growth and progression of several cancers. However, asystematic pan-cancer analysis of GJB2 is lacking. Therefore, in this study, we performed a comprehensive pan-cancer analysis to determine the potential role of GJB2 in prognostic prediction and cancer immunotherapy response.

Methods

The differential expression of GJB2 in the tumor and adjacent normal tissues of various cancer types was analyzed using the TIMER, GEPIA, and Sangerbox databases. GEPIA and Kaplan-Meier plotter databases were used to analyze the survival outcomes based on GJB2 expression levels in pan-cancer. Furthermore, the association of GJB2 expression with the immune checkpoint (ICP) genes, tumor mutational load (TMB), microsatellite instability (MSI), neoantigens, and tumor infiltration of immune cells was analyzed using via the Sangerbox database. The cBioPortal database was used to determine the characteristics of GJB2 gene alterations in the cancer tissues. The STRING database was used to identify the GJB2-binding proteins. GEPIA database was used to identify the GJB2 co-expressed genes. DAVID was used to perform the functional enrichment analysis of gene ontology (GO) terms and KEGG pathways associated with GJB2. Finally, the mechanistic role of GJB2 in pancreatic adenocarcinoma (PAAD) was analyzed using the LinkedOmics database.

Results

The GJB2 gene was highly expressed in a variety of tumors. Furthermore, GJB2 expression levels showed significant positive or negative association with the survival outcomes in various cancers. GJB2 expression levels cor related with tumor mutational burden, microsatellite instability, neoantigens, and tumor infiltration of immune cells in multiple cancers. This suggested that GJB2 played a critical role in the tumor microenvironment. Functional enrichment analysis showed that the biological role of GJB2 in tumors included modulation of gap junction-mediated intercellular transport, regulation of cell communication by electrical coupling, ion transmembrane transport, autocrine signaling, apoptotic signaling pathway, NOD-like receptor signaling pathway, p53 signaling pathway, and PI3K-Akt signaling pathway.

Conclusions

Our study demonstrated that GJB2 played a significant role in tumorigenesis and tumor immunity in multiple cancers. Furthermore, GJB2 is a potential prognostic biomarker and a promising therapeutic target in multiple types of cancers.

Bioinformatic analysis of hub markers and immune cell infiltration characteristics of gastric cancer

Background

Gastric cancer (GC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Due to the lack of specific markers, the early diagnosis of gastric cancer is very low, and most patients with gastric cancer are diagnosed at advanced stages. The aim of this study was to identify key biomarkers of GC and to elucidate GC-associated immune cell infiltration and related pathways.

Methods

Gene microarray data associated with GC were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia, Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks. Weighted gene coexpression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to identify pivotal genes for GC and to assess the diagnostic accuracy of GC hub markers using the subjects' working characteristic curves. In addition, the infiltration levels of 28 immune cells in GC and their interrelationship with hub markers were analyzed using ssGSEA. And further validated by RT-qPCR.

Results

A total of 133 DEGs were identified. The biological functions and signaling pathways closely associated with GC were inflammatory and immune processes. Nine expression modules were obtained by WGCNA, with the pink module having the highest correlation with GC; 13 crossover genes were obtained by combining DEGs. Subsequently, the LASSO algorithm and validation set verification analysis were used to finally identify three hub genes as potential biomarkers of GC. In the immune cell infiltration analysis, infiltration of activated CD4 T cell, macrophages, regulatory T cells and plasmacytoid dendritic cells was more significant in GC. The validation part demonstrated that three hub genes were expressed at lower levels in the gastric cancer cells.

Conclusion

The use of WGCNA combined with the LASSO algorithm to identify hub biomarkers closely related to GC can help to elucidate the molecular mechanism of GC development and is important for finding new immunotherapeutic targets and disease prevention.

Ion Channels as Potential Tools for the Diagnosis, Prognosis, and Treatment of HPV-Associated Cancers

The human papilloma virus (HPV) group comprises approximately 200 genetic types that have a special affinity for epithelial tissues and can vary from producing benign symptoms to developing into complicated pathologies, such as cancer. The HPV replicative cycle affects various cellular and molecular processes, including DNA insertions and methylation and relevant pathways related to pRb and p53, as well as ion channel expression or function. Ion channels are responsible for the flow of ions across cell membranes and play very important roles in human physiology, including the regulation of ion homeostasis, electrical excitability, and cell signaling. However, when ion channel function or expression is altered, the channels can trigger a wide range of channelopathies, including cancer. In consequence, the up- or down-regulation of ion channels in cancer makes them attractive molecular markers for the diagnosis, prognosis, and treatment of the disease. Interestingly, the activity or expression of several ion channels is dysregulated in HPV-associated cancers. Here, we review the status of ion channels and their regulation in HPV-associated cancers and discuss the potential molecular mechanisms involved. Understanding the dynamics of ion channels in these cancers should help to improve early diagnosis, prognosis, and treatment in the benefit of HPV-associated cancer patients.

Ion channel gene GJB2 influences the intercellular communication by Up-regulating the SPP1 signaling pathway identified by the single-cell RNA sequencing in lung adenocarcinoma

Objective

Firstly, observe the prognostic significance and the biological functional effects of gap junction protein beta 2 (GJB2 or Cx26) in lung adenocarcinoma (LUAD). Subsequently, explore the role played by GJB2 in intercellular communication by single-cell RNA sequencing.

Method

We made a differential analysis of GJB2 expression through public databases and investigated the clinical characteristics and prognostic significance. ESTIMATE analysis and Tumor Immune Estimation Resource (TIMER) database were utilized to illustrate the association of GJB2 with immune infiltration and components of the tumor microenvironment. Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSEA) were performed to study the biological function of GJB2. Cell-cell communication was analyzed using the CellChat R package through sc-RNA data.

Results

GJB2 has an outstanding prognosis value in LUAD and a close relationship was found between GJB2 and immune infiltration in LUAD. GJB2 could participate in several tumor biological processes, including extracellular matrix remodeling and upregulation of multiple cancer-related active pathways. GJB2 related hub-genes influence intercellular communication through the SPP1 signaling pathway.

Conclusion

Our study illustrates one mechanism by which GJB2 exerts its cancer-specific relevant effects, that is, causing changes in intercellular communication through the SPP1 signaling pathway. Blockade of this pathway may limit the functional role of GJB2 and provide us with promising new perceptions for LUAD treatment.

Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes

We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to TCGA data from EGFR-mutant, KRAS-mutant, and NEK (non-EGFR/KRAS) lung adenocarcinomas. We find frequent overlap of evolutionarily selected non-synonymous gene mutations among the subtypes suggesting enrichment for adaptations to common local tissue selection forces. Overlap of conserved genes in the LUAD subtypes is rare suggesting negative evolutionary selection is strongly dependent on initiating mutational events during carcinogenesis. Highly expressed genes are more likely to be conserved and significant changes in expression (>20% increased/decreased) are common in genes with evolutionarily selected mutations but not in conserved genes. EGFR-mut cancers have fewer average mutations (89) than KRAS-mut (228) and NEK (313). Subtype-specific variation in conserved and mutated genes identify critical molecular components in cell signaling, extracellular matrix remodeling, and membrane transporters. These findings demonstrate subtype-specific patterns of co-adaptations between the defining driver mutation and somatically conserved genes as well as novel insights into epigenetic versus genetic contributions to cancer evolution.

Sodium channel 1 subunit alpha SCNN1A exerts oncogenic function in pancreatic cancer via accelerating cellular growth and metastasis

The identification of new diagnostic and therapeutic biomarkers might be helpful to understand molecular mechanism of cancer pathogenesis and develop anti-cancer targets. This study reported the alteration of Sodium channel 1 subunit alpha (SCNN1A) expression, its prognostic significance and biological roles in pancreatic cancer. Bioinformatics database was searched to explore the expression of SCNN1A in pancreatic cancer specimens and analysis results were further validated by qRT-PCR and Western blot assay. The correlation between SCNN1A expression and clinicopathological characteristics and its impact on survival outcome of pancreatic cancer patients were investigated using GEPIA database and Kaplan-Meier plotter. Loss- and gain-of-functional experiments in vitro were done to investigate the biological function of SCNN1A in pancreatic cancer. Bioinformatics analysis and validation experiment showed that SCNN1A was frequently overexpressed in pancreatic cancer specimens and cell lines (P < 0.001), and there were significant relevance between high SCNN1A expression and TP53 mutation (P < 0.05) as well as unfavorable prognosis of pancreatic cancer patients (HR for overall survival: 1.9, P = 0.003 and HR for disease-free survival: 1.7, P = 0.014). The silencing of SCNN1A suppressed cell proliferation, migration and invasion and induced cell apoptosis (P < 0.05), while its overexpression promoted aggressive phenotypes of pancreatic cancer cells in vitro (P < 0.05). SCNN1A possessed oncogenic function and its dysregulation could be implicated in the development and metastasis of pancreatic cancer.

Network-Based Data Analysis Reveals Ion Channel-Related Gene Features in COVID-19: A Bioinformatic Approach

Coronavirus disease 2019 (COVID-19) seriously threatens human health and has been disseminated worldwide. Although there are several treatments for COVID-19, its control is currently suboptimal. Therefore, the development of novel strategies to treat COVID-19 is necessary. Ion channels are located on the membranes of all excitable cells and many intracellular organelles and are key components involved in various biological processes. They are a target of interest when searching for drug targets. This study aimed to reveal the relevant molecular features of ion channel genes in COVID-19 based on bioinformatic analyses. The RNA-sequencing data of patients with COVID-19 and healthy subjects (GSE152418 and GSE171110 datasets) were obtained from the Gene Expression Omnibus (GEO) database. Ion channel genes were selected from the Hugo Gene Nomenclature Committee (HGNC) database. The RStudio software was used to process the data based on the corresponding R language package to identify ion channel-associated differentially expressed genes (DEGs). Based on the DEGs, Gene Ontology (GO) functional and pathway enrichment analyses were performed using the Enrichr web tool. The STRING database was used to generate a protein-protein interaction (PPI) network, and the Cytoscape software was used to screen for hub genes in the PPI network based on the cytoHubba plug-in. Transcription factors (TF)-DEG, DEG-microRNA (miRNA) and DEG-disease association networks were constructed using the NetworkAnalyst web tool. Finally, the screened hub genes as drug targets were subjected to enrichment analysis based on the DSigDB using the Enrichr web tool to identify potential therapeutic agents for COVID-19. A total of 29 ion channel-associated DEGs were identified. GO functional analysis showed that the DEGs were integral components of the plasma membrane and were mainly involved in inorganic cation transmembrane transport and ion channel activity functions. Pathway analysis showed that the DEGs were mainly involved in nicotine addiction, calcium regulation in the cardiac cell and neuronal system pathways. The top 10 hub genes screened based on the PPI network included KCNA2, KCNJ4, CACNA1A, CACNA1E, NALCN, KCNA5, CACNA2D1, TRPC1, TRPM3 and KCNN3. The TF-DEG and DEG-miRNA networks revealed significant TFs (FOXC1, GATA2, HINFP, USF2, JUN and NFKB1) and miRNAs (hsa-mir-146a-5p, hsa-mir-27a-3p, hsa-mir-335-5p, hsa-let-7b-5p and hsa-mir-129-2-3p). Gene-disease association network analysis revealed that the DEGs were closely associated with intellectual disability and cerebellar ataxia. Drug-target enrichment analysis showed that the relevant drugs targeting the hub genes CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5 were gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine. The results of this study provide a valuable basis for exploring the mechanisms of ion channel genes in COVID-19 and clues for developing therapeutic strategies for COVID-19.

The global change of gene expression pattern caused by PTEN mutation affects the prognosis of glioblastoma

Glioblastoma (GBM), an aggressive primary tumor, is common in humans, accounting for 12–15% of all intracranial tumors, and has median survival of fewer than 15 months. Since a growing body of evidence suggests that conventional drugs are ineffective against GBM, our goal is to find emerging therapies that play a role in its treatment. This research constructs a risk model to predict the prognosis of GBM patients. A set of genes associated with GBM was taken from a GBM gene data bank, and clinical information on patients with GBM was retrieved from the Cancer Genome Atlas (TCGA) data bank. One-way Cox and Kaplan–Meier analyses were performed to identify genes in relation to prognosis. Groups were classified into high and low expression level of PTEN expression. Prognosis-related genes were further identified, and multi-factor Cox regression analysis was used to build risk score equations for the prognostic model to construct a survival prognostic model. The area under the ROC curve suggested that the pattern had high accuracy. When combined with nomogram analysis, GJB2 was considered an independent predictor of GBM prognosis. This study provides a potential prognostic predictive biological marker for GBM patients and confirms that GJB2 is a key gene for GBM progression.

The prognostic value and biological significance of gap junction beta protein 2 (GJB2 or Cx26) in cervical cancer

Objective

To evaluate the prognostic value and explore the biological significance of gap junction protein beta 2 (GJB2 or Cx26) in cervical cancer (CC).

Methods

We first compared GJB2 expression between CC and normal tissues using public databases and immunohistochemistry (IHC). Based on The Cancer Genome Atlas data (TCGA cohort, n = 304) and tissue microarray samples (OBC cohort, n = 111), we explored the prognostic value of GJB2 for CC patients using bioinformatics analysis and IHC scoring. To explore the biological significance of GJB2, Gene set enrichment analysis (GSEA) and Gene Ontology (GO) were performed. The impact of GJB2 on the immune microenvironment was analyzed by CIBERSORTx and ESTIMATE algorithms. We finally investigated the relationship between GJB2 and drug sensitivity based on the Genomics of Drug Sensitivity in Cancer (GDSC).

Results

The expression of GJB2 was significantly increased in CC over normal tissues. Both the TCGA and OBC cohort found that patients with high GJB2 expression had shorter overall survival (OS) time, and high GJB2 expression was the independent risk factor for prognosis (TCGA: HR, 2.566; 95% CI, 1.066–6.180; p = 0.036; OBC: HR, 2.198; 95% CI, 1.019–4.741; p = 0.045). GJB2 was correlated with patient clinical factors such as tumor size and differentiation grade. The p53 signaling pathway and toll-like receptor pathway may be regulated by GJB2. The abundance of various immune cells was significantly different between the low and high GJB2 expression groups. The ImmuneScore was significantly increased in the high GJB2 expression group. In addition, the expression level of GJB2 was positively correlated with the natural log of the half-maximal inhibitory concentration (LN_IC50) value of cisplatin/paclitaxel (Spearman r = 0.238/0.153, p &lt; 0.001).

Conclusion

GJB2 can serve as a potential prognostic marker of poor survival and a therapeutic target in CC. Moreover, GJB2 may affect the immune microenvironment and is correlated with chemoresistance.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Background

Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients.

Methods

OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration.

Results

We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells.

Conclusion

In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.

In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

Simple Summary

Breast cancer involves changes in the healthy cells of the breast resulting in rapid and abnormal division of cells that later spread to other parts of the body through the process of metastasis, which involves epithelial mesenchymal transition (EMT). Ion channels play a significant role in the switch from epithelial to mesenchymal transition through their contributions to cellular motility, cell volume regulation and cell cycle progression. Comprehensive computational analyses were performed to understand the role of ion channels in tumor/metastatic samples of breast cancer and their correlation with EMT.

Abstract

Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.