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 Dec:32:101350.
doi: 10.1016/j.bbrep.2022.101350. Epub 2022 Sep 22.

In silico prediction of COVID-19 cytokine storm in lung cancer types

Affiliations

In silico prediction of COVID-19 cytokine storm in lung cancer types

Surabhi Suchanti et al. Biochem Biophys Rep. 2022 Dec.

Abstract

Lung cancer is one of the most frequently diagnosed malignant tumors and the leading cause of cancer-related death worldwide. Mainly, Non-small-cell lung cancer (NSCLC), which accounts for more than eighty-five percent of all lung cancers, consists of two major subtypes: lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Novel coronavirus disease (COVID-19) affected millions of people caused by acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) around the globe. Lung cancer patients and COVID-19 present unique and unfortunate lethal combinations because the lungs are the primary target organ of SARS-CoV-2 infection. Clinical studies have demonstrated that an over-activated inflammatory response associated with severe COVID-19 cases is characterized by excessive auto-amplifying cytokine release, which is defined as a "cytokine storm." ACE2 and TMPRSS2 receptors play an essential role in SARS-CoV-2 infection; therefore, using in silico analysis, we did correlation analysis with immune infiltration markers in LUAD and LUSC patient groups. Our study identified a promising correlation between immune-modulators and receptor proteins (ACE-2 and TMPRSS2), creating a domain that requires further laboratory studies for clinical authentication.

Keywords: ACE-2; COVID-19; Cytokine storm; Immune-modulators; Lung cancer; TMPRSS2.

PubMed Disclaimer

Conflict of interest statement

No potential conflicts of interest were disclosed.

Figures

Fig. 1
Fig. 1
The distribution of ACE2 and TMPRSS2 mRNA expression trends in lung tissues: (A) the distribution of ACE2 mRNA expression in LUAD and LUSC between tumor tissue represented in red and normal tissues represented in green; (B) correlation between ACE2 expression level trends in different LUAD pathological stages; (C) correlation between ACE2 expression level trends in different LUSC pathological stages; (D) the distribution of TMPRSS2 mRNA expression in LUAD and LUSC between tumor tissue represented in red and normal tissues represented in green; (E) Correlation between TMPRSS2 expression level trends in different LUAD pathological stages; (F) Correlation between TMPRSSS22 expression level trends in different LUSC pathological stages Abbreviations: LUSC, lung squamous cell carcinoma; LUAD, lung adenocarcinoma; GEPIA, gene expression profiling interactive analysis; T, tumor; N, normal control. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2
Fig. 2
Correlation between ACE2 and TMPRSS2 expression and lymphocytes. The pan-cancer analysis of relationship between abundance of the 28 tumor-infiltrating lymphocytes (TILs) and (A) ACE2 and (B) TMPRSS2 expression.
Fig. 3
Fig. 3
Correlation analysis between ACE2 and TMPRSS2 with immune infiltration level. Heatmap clustering analysis performed in MetaboAnalyst 4.0 showed the spearman correlation-based analysis with the level of significance of immune-modulators with ACE2 and TMPRSS2 expression in LUAD and LUSC using TIMER analysis. MetaboAnalyst 4.0 was used for generating the Heat map (https://www.metaboanalyst.ca/MetaboAnalyst/ModuleView.xhtml). Colored bars represent differential levels of Spearman's correlation. Blue represents negative correlation values while the red represents the positive correlation values. TIMER web tool (https://cistrome.shinyapps.io/timer/) was used for statistically analyzing the correlation values. The statistical significance is annotated by the number of stars (*: P-value < 0.05; **: P-value <0.01; ***: P-value <0.001; ****: P-value <0.0001). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4
Fig. 4
- Three steps predictive model of SARS-CoV-2 consortium with lung cancer types: The predictive implications towards the ACE2 inhibitors in lung cancer types has been shown in three major steps i) Infection: As high expression of ACE2 in LUAD leads to increase in virus susceptibility compared to LUSC. ii) Receptor internalization: A major step in immunomodulation and provoking cytokine storm due to negative correlation of ACE2 with immune modulators in LUAD. iii) Call for cytokine storm/Resolution: Hyper-inflammatory response in LUAD while it diminishes the immune response in LUSC.

Similar articles

References

    1. Wang L., Jiang M., Qu J., Zhou N., Zhang X. Clinical management of lung cancer patients during the outbreak of COVID-19 epidemic. Infect. Agent. Cancer15. 2020;(1) - PMC - PubMed
    1. Rowaiye A.B., Okpalefe O.A., Adejoke O.O., et al. Attenuating the effects of novel COVID-19 (SARS-CoV-2) infection-induced cytokine storm and the implications. J. Inflamm. Res. 2021;14 - PMC - PubMed
    1. Wu T., Zuo Z., Kang S., et al. Multi-organ dysfunction in patients with COVID-19: a systematic review and meta-analysis. Aging Dis. 2020;11(4) - PMC - PubMed
    1. Marc F., Moldovan C.M., Hoza A., et al. Comparative study of cytokine storm treatment in patients with COVID-19 pneumonia using Immunomodulators. J. Clin. Med. 2022;11(10):2945. - PMC - PubMed
    1. Hoffmann M., Kleine-Weber H., Schroeder S., et al. SARS-CoV-2 cell entry Depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181(2) - PMC - PubMed

LinkOut - more resources