Literature DB >> 34437926

Are COVID-19 susceptibility genes related to lung cancer?

Shizheng Qiu1, Yang Hu2.   

Abstract

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Year:  2021        PMID: 34437926      PMCID: PMC8381633          DOI: 10.1016/j.jinf.2021.08.032

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


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Dear Editor, We read with great interest the recently published letter in Journal of Infection by Afshar et al., who suggested that the proportion of severe cases and mortality among cancer patients infected with COVID-19 were higher than those of COVID-19 patients without cancer, due to abnormal autoimmune function. Meanwhile, Liang et al. collected and analyzed 2007 cases from 575 hospitals in China who were diagnosed with COVID-19 and were admitted to hospital for treatment, and found that 1% of COVID-19 patients had a history of cancer, which was much higher than the incidence of cancer in the normal population (0.29%). However, the COVID-19 susceptibility of cancer patients remains a subject of considerable controversy. Observational studies with different samples have even come to opposite conclusions. Gallo et al. suggested that the impaired immune response of cancer patients might be a protective factor for the cytokine storm caused by COVID-19. Therefore, it is necessary to discuss whether susceptibility genes for COVID-19 play a critical role in lung cancers. In this study, we comprehensively analyzed the genetic alteration, mRNA expression, protein expression, prognosis, immune infiltration and lung cancer correlation of COVID-19 susceptibility genes (SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, ABO, RPL24, FOXP4, TMEM65, OAS1, KANSL1, TAC4, DPP9, RAVER1, PLEKHA4 and IFNAR2) in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Among the 17 susceptibility genes, the genetic alteration of RPL24 was as high as 6.37% in LUSC and the genetic alteration of TMEM65 was as high as 5.48% in LUAD, suggesting that genetic alteration in these genes greatly affected the occurrence of lung cancer. Most of COVID-19 susceptibility genes were differential expression in samples of TCGA lung cancer datasets, and the differential expression of LZTFL1, TMEM65, OAS1, DPP9, RAVER1and IFNAR2 were replicated in three cohort studies ( Table 1 ). Using immunohistochemical staining to validate the protein expression of lung cancer tissues and normal lung tissues in the Human Protein Atlas, we observed that six genes, including SLC6A20, FYCO1, FOXP4, TMEM65, XCR1 and OAS1, had significantly different protein expression levels (Fig. 1 A).
Table 1

Differentially expressed genes in the lung cancer patient cohort of ONCOMINE database.

GeneFold ChangePCancer typeStudySample
LZTFL11.6580.009Small Cell Lung CarcinomaGarber Lung73
TMEM651.7380.001Squamous Cell Lung CarcinomaGarber Lung73
OAS13.4163.00E-4Lung AdenocarcinomaBhattacharjee Lung203
DPP92.1230.004Large Cell Lung CarcinomaGarber Lung73
RAVER11.7957.92E-17Lung AdenocarcinomaSelamat Lung116
IFNAR22.0271.64E-14Lung AdenocarcinomaSelamat Lung116

Only genes that were considered to be differentially expressed were shown. The statistically significant differential expression is defined to be P < 0.05 and Fold Change > 1.5.

Fig. 1

The protein expression, prognosis, and lung cancer correlation of COVID-19 susceptibility genes. (A) Representative immunohistochemical staining in lung tumor and normal tissues. (B) Survival curves compared the overall survival of COVID-19 susceptibility genes expression using the cox regression model and log rank test. (C) Correlation of COVID-19 susceptibility genes expression with lung cancer markers.

Differentially expressed genes in the lung cancer patient cohort of ONCOMINE database. Only genes that were considered to be differentially expressed were shown. The statistically significant differential expression is defined to be P < 0.05 and Fold Change > 1.5. The protein expression, prognosis, and lung cancer correlation of COVID-19 susceptibility genes. (A) Representative immunohistochemical staining in lung tumor and normal tissues. (B) Survival curves compared the overall survival of COVID-19 susceptibility genes expression using the cox regression model and log rank test. (C) Correlation of COVID-19 susceptibility genes expression with lung cancer markers. Subsequently, we used the cox regression model and log rank test to calculate the impact of COVID-19 susceptibility gene expression in overall survival (OS). Whether under the cox model or log rank test, high expression of FYCO1, CXCR6, XCR1 and TAC4 were protective factors for LUAD, and TMEM65 and OAS1 were risk factors for LUAD ( Fig. 1 B). Finally, we were pleasantly surprised to find that COVID-19 susceptibility genes were strongly related to almost all of the six main immune cells (B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil and dendritic cell) in lung cancer, further confirming the close interaction of COVID-19 with immune responses in tumors. We also explored the association between COVID-19 susceptibility genes and known markers of lung cancer (P53→TP53 and KRAS) in lung cancer. ABO, DPP9, FOXP4, FYCO1, LZTFL1, RAVER1, TAC4 and XCR1 were strongly correlated with both lung cancer markers ( Fig. 1 C). In conclusion, we verified the results of COVID-19 Host Genetics Initiative that individuals with mutations in these two genes related to lung cancer, DPP9 and FOXP4, increased the risk of severe COVID-19. Furthermore, we suggested XCR1, TMEM65 and OAS1 as independent prognostic markers for lung cancer, and supported the potential partial genetic overlap between COVID-19 and lung cancer. We provided new insights and research directions for the diagnosis, treatment and management of lung cancer patients during the COVID-19 pandemic.

Declaration of Competing Interest

All the authors declare that there are no conflicts of interest.
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