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

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

Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein–protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2

Table3_Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma.xlsx

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.</p

DataSheet2_Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma.docx

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.</p

Table1_Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma.xlsx

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.</p

Table2_Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma.xlsx

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.</p

DataSheet1_Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma.docx

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.</p