Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Oct 31;11(21):3438.
doi: 10.3390/cells11213438.

The Ion Channel Gene KCNAB2 Is Associated with Poor Prognosis and Loss of Immune Infiltration in Lung Adenocarcinoma

Affiliations

The Ion Channel Gene KCNAB2 Is Associated with Poor Prognosis and Loss of Immune Infiltration in Lung Adenocarcinoma

Yin Lyu et al. Cells. .

Abstract

The malignancy with the greatest global mortality rate is lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype. The evidence demonstrated that voltage-gated potassium channel subunit beta-2 (KCNAB2) significantly participated in the initiation of colorectal cancer and its progression. However, the biological function of KCNAB2 in LUAD and its effect on the tumor immune microenvironment are still unknown. In this study, we found that the expression of KCNAB2 in tissues of patients with LUAD was markedly downregulated, and its downregulation was linked to accelerated cancer growth and poor clinical outcomes. In addition, low KCNAB2 expression was correlated with a deficiency in immune infiltration. The mechanism behind this issue might be that KCNAB2 influenced the immunological process such that the directed migration of immune cells was affected. Furthermore, overexpression of KCNAB2 in cell lines promoted the expression of CCL2, CCL3, CCL4, CCL18, CXCL9, CXCL10, and CXCL12, which are necessary for the recruitment of immune cells. In conclusion, KCNAB2 may play a key function in immune infiltration and can be exploited as a predictive biomarker for evaluating prognosis and a possible immunotherapeutic target.

Keywords: KCNAB2; chemokine; immune infiltration; immunotherapy; lung adenocarcinoma.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Expression of KCNAB2 in LUAD. (A) KCNAB2 expression levels in different tumor tissues were detected using TIMER. (B) Decreased expression of KCNAB2 was investigated in the GEPIA database. (C) The mRNA and (D) protein expression of KCNAB2 in LUAD were examined in the UALCAN database. (EG) KCNAB2 mRNA expression levels were validated by GEO datasets. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 2
Figure 2
Validation of the decreased expression of KCNAB2 in LUAD using clinical tissues and cell lines. (A) Immunohistochemical (IHC) staining of KCNAB2 was performed in tumor tissues (n = 10) and normal tissues (n = 10). Representative images are shown. Score bars, 50 μm. (B) The staining was quantified. The dot plot depicts the means and standard deviation of 10 images of LUAD patient tissues and normal lung tissues. (C) Transcriptional levels of KCNAB2 in three different cell lines were examined by real-time PCR. (D) Western blot detected the protein expression level of KCNAB2 in three cell lines. ** p < 0.01, *** p < 0.001.
Figure 3
Figure 3
Clinical significance of KCNAB2 in LUAD. Correlation between KCNAB2 expression and clinical parameters, including (A) pathological stage, (BD) TNM stage, (E) primary therapy outcomes, (F) gender, (G) age, and (H) smoker. Primary therapy outcome: PD, progressive disease; SD, stable disease; PR, partial response; CR, complete response. * p < 0.05, *** p < 0.001.
Figure 4
Figure 4
Prognostic value of KCNAB2 in LUAD. (AC) Kaplan–Meier survival curves showed that patients with low KCNAB2 expression exhibited poor overall survival, progress free survival, and disease specific survival. (D,E) The validation of the prognostic value of KCNAB2 in LUAD by GEO datasets.
Figure 5
Figure 5
Associations between the expression of KCNAB2 and the overall survival based on LUAD patients with different clinical parameters. (A) Stage I–II, (B) N0, (C) N1–N3, (D) M0, (E) age over 65 years old, and (F) smoker over 40 years.
Figure 6
Figure 6
KCNAB2−related differentially expressed genes (DEGs) and functional enrichment analysis using GO and KEGG. (A) Volcano plot of DEGs. Blue and red dots indicate the significantly downregulated and upregulated DEGs. (B) Top 10 terms of KEGG analysis of upregulated DEGs. (CE) Top 20 terms of GO analysis of DEGs, including biological process (BP), molecular function (MF), and cellular component (CC).
Figure 7
Figure 7
Identification of KCNAB2−related signaling pathways in LUAD using GSEA.
Figure 8
Figure 8
The relationship between KCNAB2 expression an immune cell infiltration. (A) The expression level of KCNAB2 is positively correlated with the infiltration of different immune cells using the TIMER database. (B) KCNAB2 expression has a significant correlation with the infiltration of immune cells in LUAD using the ssGSEA method. (CE) Correlations between KCNAB2 expression and overall survival in different immune cell subgroups in LUAD patients were estimated by Kaplan–Meier plotter.
Figure 9
Figure 9
Real-time PCR results for analyzing the expression of tumor immune-related chemokines. (A) The overexpression effect of KCNAB2 in A549 cell line and H23 cell line was verified at the mRNA and protein levels. (B,C) Chemokines, including CCL2, CCL3, CCL4, CCL18, CXCL9, CXCL10, and CXCL12, were upregulated by KCNAB2 in A549 (B) and H23 cell lines (C). * p < 0.05, ** p < 0.01, *** p < 0.001.

Similar articles

Cited by

References

    1. Siegel R.L., Miller K.D., Jemal A. Cancer statistics, 2020. CA Cancer J. Clin. 2020;70:7–30. doi: 10.3322/caac.21590. - DOI - PubMed
    1. Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021;71:209–249. doi: 10.3322/caac.21660. - DOI - PubMed
    1. The Cancer Genome Atlas Research Network Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511:543–550. doi: 10.1038/nature13385. - DOI - PMC - PubMed
    1. Pasche B., Grant S.C. Non-small cell lung cancer and precision medicine: A model for the incorporation of genomic features into clinical trial design. J. Am. Med. Assoc. 2014;311:1975–1976. doi: 10.1001/jama.2014.3742. - DOI - PubMed
    1. Thomas A., Liu S.V., Subramaniam D.S., Giaccone G. Refining the treatment of NSCLC according to histological and molecular subtypes. Nat. Rev. Clin. Oncol. 2015;12:511–526. doi: 10.1038/nrclinonc.2015.90. - DOI - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources