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. 2019 Apr 19;11(4):561.
doi: 10.3390/cancers11040561.

Expression Profiling of Calcium Channels and Calcium-Activated Potassium Channels in Colorectal Cancer

Sajida Ibrahim  1 , Hassan Dakik  2   3 , Christophe Vandier  4 , Romain Chautard  5   6 , Gilles Paintaud  7   8 , Frédéric Mazurier  9   10 , Thierry Lecomte  11   12 , Maxime Guéguinou  13 , William Raoul  14
Affiliations

Expression Profiling of Calcium Channels and Calcium-Activated Potassium Channels in Colorectal Cancer

Sajida Ibrahim et al. Cancers (Basel). .

Abstract

Background: Colorectal cancer (CRC) is a highly devastating cancer. Ca2+-dependent channels are now considered key regulators of tumor progression. In this study, we aimed to investigate the association of non-voltage gated Ca2+ channels and Ca2+-dependent potassium channels (KCa) with CRC using the transcriptional profile of their genes. Methods: We selected a total of 35 genes covering KCa channels KCNN1-4, KCNMA1 and their subunits KCNMB1-4, endoplasmic reticulum (ER) calcium sensors STIM1 and STIM2, Ca2+ channels ORAI1-3 and the family of cation channels TRP (TRPC1-7, TRPA1, TRPV1/2,4-6 and TRPM1-8). We analyzed their expression in two public CRC datasets from The Cancer Genome Atlas (TCGA) and GSE39582. Results: KCNN4 and TRPM2 were induced while KCNMA1 and TRPM6 were downregulated in tumor tissues comparing to normal tissues. In proximal tumors, STIM2 and KCNN2 were upregulated while ORAI2 and TRPM6 were downregulated. ORAI1 decreased in lymph node metastatic tumors. TRPC1 and ORAI3 predicted poor prognosis in CRC patients. Moreover, we found that ORAI3/ORAI1 ratio is increased in CRC progression and predicted poor prognosis. Conclusions: KCa and Ca2+ channels could be important contributors to CRC initiation and progression. Our results provide new insights on KCa and Ca2+ channels remodeling in CRC.

Keywords: calcium channels; calcium signaling; calcium-activated potassium channels; colorectal cancer; prognosis; survival.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparison of the gene expression between CRC tumors vs. adjacent normal mucosa in TCGA (A,B) and GSE39582 (C,D) patients. (A) Heatmap presenting the expression profile of 35 Ca2+ and KCa channels coding-genes between CRC and matched normal tissues from the TCGA dataset; (B) Boxplots of differentially expressed genes between normal and CRC tissues in the TCGA dataset; (C) Heatmap presenting the expression profile of 34 Ca and KCa channels coding-genes between CRC and unmatched normal tissues from GSE39582 dataset; (D) Boxplots of differentially expressed genes between normal and CRC tissues in the GSE39582 dataset. Hierarchical clustering was done using Euclidean distance and average linkage method from both genes and samples. Signed-rank Wilcoxon’s test and unpaired t-test were used to perform pairwise comparisons between CRC and normal tissues in the TCGA and GSE39582 datasets, respectively and were followed by BH adjustment, respectively. (***: BH-adjusted p < 0.001). CRC: colorectal cancer; TCGA: The Cancer Genome Atlas; Ca: calcium; KCa: Ca2+-dependent potassium channels. BH: Benjamini-Hochberg.
Figure 2
Figure 2
Pearson’s correlation heatmaps of gene expression in TCGA and GSE39582 datasets. (A) Pearson’s correlation heatmaps of KCa channels family coding genes; (B) Pearson’s correlation heatmaps of TRPM channels family coding genes; (C) Pearson’s correlation heatmaps of ORAI family and TRPC1 genes. Pearson’s correlation coefficients were shown with continuous gradient colors. Red represents positive correlation whereas blue represents negative correlation. Asterisk symbol correspond to correlations with BH-adjusted p-value < 0.05. TCGA: The Cancer Genome Atlas; KCa: Ca2+-dependent potassium channels. BH: Benjamini-Hochberg.
Figure 3
Figure 3
Differentially expressed genes between proximal and distal/rectal tumors in TCGA and GSE39582 datasets. (A) Boxplots of genes downregulated in distal/rectal tumors compared to proximal tumors in TCGA. (B) Boxplots of genes upregulated in distal/rectal tumors compared to proximal tumors in TCGA. (C) Boxplots of genes downregulated in distal tumors compared to proximal tumors in GSE39582. (D) Boxplots of genes upregulated in distal tumors compared to proximal tumors in GSE39582. ANOVA test was used for multiple comparisonsThe student’s t-test was used for pairwise comparison. (* p < 0.05; *** p < 0.001). ANOVA: analysis of variance; TCGA: The Cancer Genome Atlas.
Figure 4
Figure 4
ORAI1 is downregulated with lymph node metastases in TCGA and GSE39582 datasets. N0 represents tumors with no lymph node metastases and N+ represents tumors with N1 or N2 lymph node metastases. The student’s t-test was used for pairwise comparison. (* p < 0.05). TCGA: The Cancer Genome Atlas.
Figure 5
Figure 5
Kaplan-Meier survival curves of ORAI3 and TRPC1 genes in TCGA and GSE39582. (A) OS and EFS survival curves for ORAI3 in the TCGA dataset; (B) OS and RFS survival curves for ORAI3 in the GSE39582 dataset; (C) OS and EFS survival curves for TRPC1 in the TCGA dataset; (D) OS and RFS survival curves for ORAI3 in the GSE39582 dataset. High and Low scores were attributed to patients using gene-median expression as a threshold. Comparison between High and Low categories was done using a Log-Rank test. Abbreviations: OS: Overall survival. EFS: Event-free survival. RFS: Relapse-free survival.
Figure 6
Figure 6
ORAI3/ORAI1 ratio predicts poor prognosis in CRC. High and Low scores were attributed to patients using ratio ORAI3/ORAI1 median expression as a threshold. High and Low categories were done using a Log-Rank test; (A) OS and EFS survival curves of ORAI3/ORAI1 ratio in the TCGA dataset. (B) OS and RFS survival curves of ORAI3/ORAI1 ratio in the GSE39582; (C) ORAI3/ORAI1 ratio expression according to tumor stages. The ANOVA test was used for multiple comparisons. The BH-adjusted student t-test was used for pairwise comparisons (Stage I was considered a reference). (* p < 0.05; ** p < 0.01; *** p < 0.001).
Figure 6
Figure 6
ORAI3/ORAI1 ratio predicts poor prognosis in CRC. High and Low scores were attributed to patients using ratio ORAI3/ORAI1 median expression as a threshold. High and Low categories were done using a Log-Rank test; (A) OS and EFS survival curves of ORAI3/ORAI1 ratio in the TCGA dataset. (B) OS and RFS survival curves of ORAI3/ORAI1 ratio in the GSE39582; (C) ORAI3/ORAI1 ratio expression according to tumor stages. The ANOVA test was used for multiple comparisons. The BH-adjusted student t-test was used for pairwise comparisons (Stage I was considered a reference). (* p < 0.05; ** p < 0.01; *** p < 0.001).
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