Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane that leads to the destruction of cartilage and bone. Currently, pharmacological targeting of ion channels is being increasingly recognized as an attractive and feasible strategy for the treatment of RA. The present work employs a network analysis approach to predict the most promising ion channel target for potential RA-treating drugs. A protein-protein interaction map was generated for 343 genes associated with inflammation in RA and ion channel genes using Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. Based on the betweenness centrality and traffic values as key topological parameters, 17 hub nodes were identified, including FOS (9800.85), tumor necrosis factor (3654.60), TGFB1 (3305.75), and VEGFA (3052.88). The backbone network constructed with these 17 hub genes was intensely analyzed to identify the most promising ion channel target using network analyzer. Calcium permeating ion channels, especially store-operated calcium entry channels, and their associated regulatory proteins were found to highly interact with RA inflammatory hub genes. This significant ion channel target for RA identified by theoretical and statistical studies was further validated by a pilot case-control gene expression study. Experimental verification of the above findings in 75 RA cases and 25 controls showed increased ORAI1 expression. Thus, with a combination of network analysis approach and gene expression studies, we have explored potential targets for RA treatment.