Expression profiling of ion channel genes predicts clinical outcome in breast cancer

Abstract

BackgroundIon channels play a critical role in a wide variety of biological processes, including the development of human cancer. However, the overall impact of ion channels on tumorigenicity in breast cancer remains controversial.MethodsWe conduct microarray meta-analysis on 280 ion channel genes. We identify candidate ion channels that are implicated in breast cancer based on gene expression profiling. We test the relationship between the expression of ion channel genes and p53 mutation status, ER status, and histological tumor grade in the discovery cohort. A molecular signature consisting of ion channel genes (IC30) is identified by Spearman’s rank correlation test conducted between tumor grade and gene expression. A risk scoring system is developed based on IC30. We test the prognostic power of IC30 in the discovery and seven validation cohorts by both Cox proportional hazard regression and log-rank test.Results22, 24, and 30 ion channel genes are found to be differentially expressed with a change in p53 mutation status, ER status, and tumor histological grade in the discovery cohort. We assign the 30 tumor grade associated ion channel genes as the IC30 gene signature. We find that IC30 risk score predicts clinical outcome (P < 0.05) in the discovery cohort and 6 out of 7 validation cohorts. Multivariate and univariate tests conducted in two validation cohorts indicate that IC30 is a robust prognostic biomarker, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node status, tumor size, tumor grade, estrogen and progesterone receptor status, and p53 mutation status.ConclusionsWe identified a molecular gene signature IC30, which represents a promising diagnostic and prognostic biomarker in breast cancer. Our results indicate that information regarding the expression of ion channels in tumor pathology could provide new targets for therapy in human cancers.

Randomness and preserved patterns in cancer network

“…The fourth localized eigenvector has eight TCNs of which KCND3 elevates the influx of potassium ions in breast cancer cells44. The others appear in the three most localized eigenvector and have been already discussed.…”

Synthesis of Small‐Molecule Fluorescent Probes for the In Vitro Imaging of Calcium‐Activated Potassium Channel KCa3.1

“…This points to the predictive power of analyzing K Ca 3.1 channel expression with respect to patient survival. [8,9] Therefore,d eveloping tools for the visualization of K Ca 3.1-expressing cells would be ag reat asset for ab etter understanding of its (diagnostic) role and predictive value in cancer. Currently,only indirect immunoflourescence staining is available for optical imaging of the K Ca 3.1 channel, making the process time-consuming and expensive.H erein, we present the development and synthesis of novel smallmolecule probes,w hich show promising results in in vitro imaging of the K Ca 3.1-expressing cells by fluorescence microscopy.Simple,fast, and efficient staining protocols are the advantages of these novel imaging probes,w hich can be instrumental for elucidating the mechanisms by which K Ca 3.1 channels contribute to cancer progression and metastasis.…”

miRDriver: A Tool to Infer Copy Number Derived miRNA-Gene Networks in Cancer

“…This result suggests that these genes tend to be acting as tumor suppressor genes. Among these high degree genes, CLIC6 was found to be associated in ion channels, which are implicated in breast cancer [58]. In a recent work [59], the mechanism of CLIC proteins in promoting an aggressive invasive carcinoma was explored.…”