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Is SARS-CoV-2 an oncogenic virus?

  • Alberto Gómez-Carballa
    Affiliations
    Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain

    Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
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  • Federico Martinón-Torres
    Affiliations
    Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain

    Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
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  • Antonio Salas
    Correspondence
    Corresponding author.
    Affiliations
    Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain

    Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
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Published:August 09, 2022DOI:https://doi.org/10.1016/j.jinf.2022.08.005

      Highlights

      • Npa2 and Npa3 SARS-CoV-2 protein have the ability to hijack and degrade p53.
      • Gene expression of p53 is downregulated in blood of COVID-19 patients.
      • Downregulation of p53 persists at least 24 weeks after infection in long COVID-19 patients.
      • Long-term reduction of p53 could have impact on carcinogenesis.

      Keywords

      Dear Editor
      Recently, in this journal, Wu et al. (
      • Wu X.
      • Peng H.
      • Xiong S.
      • Li C.
      • Zhong R.
      • He J.
      • et al.
      Novel evidence revealed genetic association between COVID-19 infection, severity and endometrial cancer.
      ) and Gao et al. (
      • Gao R.
      • Xu Y.
      • Zhu G.
      • Zhou S.
      • Li H.
      • Han G.
      • et al.
      Genetic variation associated with COVID-19 is also associated with endometrial cancer.
      ) have both indicated that host genetic variation related to COVID-19 might be associated to endometrial cancer. We here add evidence from gene expression analysis supporting that the connection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and cancer could be more general, in line with several other viral infections that represent serious risks for carcinogenesis in humans. The SARS-CoV-2 has developed similar strategies to Epstein-Barr virus (EBV) and hepatitis B virus (HSV1) to control p53 by hijacking the protein via virus antigens, and ultimately leading to its degradation (
      • Stingi A.
      • Cirillo L.
      SARS-CoV-2 infection and cancer: evidence for and against a role of SARS-CoV-2 in cancer onset.
      ,
      • Cardozo C.M.
      • Hainaut P.
      Viral strategies for circumventing p53: the case of severe acute respiratory syndrome coronavirus.
      ). Specifically, the Nsp2 viral protein of the SARS-CoV-2 interacts with the prohibitin 1 and 2 (PHB1, PHB2) that are primarily located in the mitochondrion and play an essential role in maintaining mitochondrial DNA activity. Their depletion triggers a chain of cell responses that lead to a leakage of reactive oxygen species (ROS) to the nucleus and oxidative damage, that ultimately provokes the impairment of the transactivation of p53-dependent genes. In addition, the Nsp3 SARS-CoV-2 protein binds and activates the RING finger and CHY zinc finger domain-cotainin protein 1 (RCHY1) and E3 ubiquitin ligase, promoting p53 degradation (
      • Ma-Lauer Y.
      • Carbajo-Lozoya J.
      • Hein M.Y.
      • Muller M.A.
      • Deng W.
      • Lei J.
      • et al.
      p53 down-regulates SARS coronavirus replication and is targeted by the SARS-unique domain and PLpro via E3 ubiquitin ligase RCHY1.
      ). Therefore, SARS-CoV-2 has the ability to trigger external and internal apoptotic pathways of the host cells, facilitating its spread. Impairment of p53 could be seen as a strategy of the virus to take advantage of the cell pathways controlled by this protein for its own benefit during acute phase of infection, therefore evading host immune response and facilitating its replication (
      • Stingi A.
      • Cirillo L.
      SARS-CoV-2 infection and cancer: evidence for and against a role of SARS-CoV-2 in cancer onset.
      ). In this context, a reduced expression of p53 during the acute phase of infection is also a biomarker of severe disease.
      Although it has not been demonstrated yet, it has been hypothesized that a long-term inhibition of p53 by the SARS-CoV-2 could be carcinogenic. The onco-suppressive protein p53 is a key player within the apoptotic signaling pathway and regulates the expression of about 500 target genes; therefore, it plays a role in cell cycle arrest, cell aging, cell death, etc. (
      • Zamaraev A.V.
      • Zhivotovsky B.
      • Kopeina G.S.
      Viral Infections: negative Regulators of Apoptosis and Oncogenic Factors.
      ). We examine three gene expression datasets to demonstrate that p53 is downregulated during acute SARS-CoV-2 infection and long coronavirus-disease 19 (COVID-19); a long-term reduction of p53 could be interpreted as a risk factor in carcinogenesis.
      We analyzed TP53 gene expression in blood from COVID-19 patients stratified by severity as well as healthy controls using the RNAseq data from Jackson et al. (
      • Jackson H.
      • Rivero-Calle I.
      • Broderick C.
      • Habgood‑Coote D.
      • D'Souza G.
      • Nichols S.
      • et al.
      Characterisation of the blood RNA host response underpinning severity in COVID‑19 patients.
      ) and n-Counter (overlapping) data from Gómez-Carballa et al. (
      • Gómez-Carballa A.
      • Rivero-Calle I.
      • Pardo-Seco J.
      • Gómez-Rial J.
      • Rivero-Velasco C.
      • Rodriguez-Nunez N.
      • et al.
      A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity.
      ) (n = 65 and n =30, respectively). Processing of raw data was carried out as in the original articles. In addition, gene expression data of long-COVID-19 patients and healthy controls (n = 44) from another RNAseq convalescence study (
      • Ryan F.J.
      • Hope C.M.
      • Masavuli M.G.
      • Lynn M.A.
      • Mekonnen Z.A.
      • Yeow A.E.L.
      • et al.
      Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.
      ) (12-, 16-, and 24-weeks post infection) were also analyzed. For the three studies, severity was determined during the acute phase of the infection. Data normalization was undertaken as in (
      • Jackson H.
      • Rivero-Calle I.
      • Broderick C.
      • Habgood‑Coote D.
      • D'Souza G.
      • Nichols S.
      • et al.
      Characterisation of the blood RNA host response underpinning severity in COVID‑19 patients.
      ). Wilcoxon test was used to assess statistical significance between groups, and Spearman test for the computation of the correlation indices (r) and P-values. We also evaluated whether the overall expression of a p53 related pathways is up- or down-regulated using the Fast Approximation to ROAST Gene Set Test with Mean Aggregated Set Statistics (fry; https://f1000research.com/slides/5–2605) by selecting Gene Ontology (GO) processes including the term ‘p53’ in the description as well as TP53 gene within the gene-set. We carried out two independent comparisons: (i) severe patients vs. non severe patients (including healthy controls) from the acute COVID-19 cohort, and (ii) 24 w.p.i severe/critical patients vs. healthy controls from the long-COVID-19 cohort. We used edgeR package (https://bioconductor.org/packages/release/bioc/html/edgeR.html) to process raw count data for the fry analysis.
      The data show that TP53 is downregulated in patients with the highest WHO severity scores in both the RNAseq (Fig. 1A) and the n-Counter datasets (Fig. 1B). These differences are statistically significant when compared against controls and mild patients. In addition, we have also observed that TP53 gene expression is negatively correlated with the length of symptoms until sample collection only in severe patients (Fig. 1A and 1B).
      Fig. 1
      Fig. 1(A) TP53 gene expression in blood samples from COVID-19 patients and healthy controls from the RNAseq dataset (
      • Jackson H.
      • Rivero-Calle I.
      • Broderick C.
      • Habgood‑Coote D.
      • D'Souza G.
      • Nichols S.
      • et al.
      Characterisation of the blood RNA host response underpinning severity in COVID‑19 patients.
      ) and stratified by WHO severity score (left). Correlation between days of symptoms to sample collection and TP53 expression in the RNAseq dataset (right). (B) TP53 gene expression in blood samples from COVID-19 patients and healthy controls from the n-Counter dataset (
      • Gómez-Carballa A.
      • Rivero-Calle I.
      • Pardo-Seco J.
      • Gómez-Rial J.
      • Rivero-Velasco C.
      • Rodriguez-Nunez N.
      • et al.
      A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity.
      ) and stratified by WHO severity score (left); patients from this cohort partially overlap with those in the RNAseq dataset. Correlation between days of symptoms to sample collection and TP53 expression in the n-Counter dataset (right). Asymptomatic patients were not included in the correlation analyses (r = spearman correlation coefficient). (C) TP53 gene expression in blood samples from mild/moderate (left) and severe/critical (right) long-COVID-19 patients as well as healthy controls from Ryan et al. (
      • Ryan F.J.
      • Hope C.M.
      • Masavuli M.G.
      • Lynn M.A.
      • Mekonnen Z.A.
      • Yeow A.E.L.
      • et al.
      Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.
      ) collected at different timepoints post infection (w.p.i = weeks post infection); here we used the authors’ scores of severity (
      • Ryan F.J.
      • Hope C.M.
      • Masavuli M.G.
      • Lynn M.A.
      • Mekonnen Z.A.
      • Yeow A.E.L.
      • et al.
      Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.
      ).
      We further re-analyzed TP53 blood gene expression data available in a follow-up study of long-COVID-19 patients (
      • Ryan F.J.
      • Hope C.M.
      • Masavuli M.G.
      • Lynn M.A.
      • Mekonnen Z.A.
      • Yeow A.E.L.
      • et al.
      Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.
      ) also stratified by severity (in the acute phase) and sampled at different timepoints, namely, 12-, 16- and 24-weeks post-infection (w.p.i) (Gene Expression Omnibus acc. n°: GSE169687). Mild / moderate patients showed statistically significant downregulation of TP53 expression when compared to healthy controls at 16 w.p.i, and a reactivation towards normal values at 24 w.p.i (Fig. 1C). However, in severe / critical patients TP53 is progressively downregulated to at least 24 w.p.i (statistically significant when compared to controls) with no evidence of recovery to the TP53 expression level observed in controls (Fig. 1D).
      In addition, the data indicate that the downregulation of TP53 has a significant impact on a number of its interacting genes. Thus, there are a total of eight pathways (GO terms) related to TP53 that are significantly up- and down-regulated in acute severe patients and in 24 w.p.i long-COVID-19 severe / critical patients when compared to non-severe (including healthy controls) and a healthy control group, respectively (Table S1). The affected pathways are related to e.g., apoptosis, DNA damage response and signal transduction (Table S1).
      We show convergent evidence from three different transcriptomic datasets and techniques that represent a molecular proof of concept that p53 may be acutely and persistently reduced after severe SARS-CoV-2 infection. A persistent reduction of the p53 tumor suppression functions, as might be the case in long-COVID-19 severe patients, may constitute a risk factor for oncogenesis comparable to pathogenic mutations in TP53. Such long-term reduction of p53 might trigger cancer onset or contribute to worsen the course of patients with an ongoing tumoral process (
      • Wu X.
      • Peng H.
      • Xiong S.
      • Li C.
      • Zhong R.
      • He J.
      • et al.
      Novel evidence revealed genetic association between COVID-19 infection, severity and endometrial cancer.
      ,
      • Gao R.
      • Xu Y.
      • Zhu G.
      • Zhou S.
      • Li H.
      • Han G.
      • et al.
      Genetic variation associated with COVID-19 is also associated with endometrial cancer.
      ). Future efforts should target larger cohorts and follow-up time, and assess additional types of samples, including lung tissue. A causal relationship between SAR-CoV-2 and cancer has not been demonstrated but, if confirmed, it would have enormous impact on public health.

      Acknowledgements

      We would like to thank all researchers in GEN-COVID (www.gencovid.eu) and the Imperial College London (UK) for collaboration (in particular to Myrsini Kaforou).

      Funding

      This study received support from Instituto de Salud Carlos III ( ISCIII ): GePEM ( PI16/01478 /Cofinanciado FEDER; A.S.), DIAVIR ( DTS19/00049 /Cofinanciado FEDER, A.S.), Resvi-Omics ( PI19/01039 /Cofinanciado FEDER, A.S.), Agencia Gallega de Innovación ( GAIN ): Grupos con Potencial de Crecimiento ( IN607B 2020/08 , A.S.); Agencia Gallega para la Gestión del Conocimiento en Salud ( ACIS ): BI-BACVIR ( PRIS-3 , A.S.), and CovidPhy ( SA 304 C , A.S.); ReSVinext ( PI16/01569 /Cofinanciado FEDER, F.M.T.), Enterogen ( PI19/01090 /Cofinanciado FEDER, F.M.T.) and consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias ( CB21/06/00103 ; F.M.T.); GEN COVID ( IN845D 2020/23 , F.M-T.) and Grupos de Referencia Competitiva ( IIN607A2021/05 , F.M-T). The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

      Declaration of Competing Interest

      The authors report no conflict of interest.

      Appendix. Supplementary materials

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