Analysis of SARS-CoV-2 infection associated cell entry proteins ACE2, CD147, PPIA, and PPIB in datasets from non SARS-CoV-2 infected neuroblastoma patients, as potential prognostic and infection biomarkers in neuroblastoma

Abstract

SARS-CoV-2 viral contagion has given rise to a worldwide pandemic. Although most children experience minor symptoms from SARS-CoV-2 infection, some have severe complications including Multisystem Inflammatory Syndrome in Children. Neuroblastoma patients may be at higher risk of severe infection as treatment requires immunocompromising chemotherapy and SARS-CoV-2 has demonstrated tropism for nervous cells. To date, there is no sufficient epidemiological data on neuroblastoma patients with SARS-CoV-2. Therefore, we evaluated datasets of non-SARS-CoV-2 infected neuroblastoma patients to assess for key genes involved with SARS-CoV-2 infection as possible neuroblastoma prognostic and infection biomarkers. We hypothesized that ACE2, CD147, PPIA and PPIB, which are associated with viral-cell entry, are potential biomarkers for poor prognosis neuroblastoma and SARS-CoV-2 infection. We have analysed three publicly available neuroblastoma gene expression datasets to understand the specific molecular susceptibilities that high-risk neuroblastoma patients have to the virus. Gene Expression Omnibus (GEO) GSE49711 and GEO GSE62564 are the microarray and RNA-Seq data, respectively, from 498 neuroblastoma samples published as part of the Sequencing Quality Control initiative. TARGET, contains microarray data from 249 samples and is part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. ACE2, CD147, PPIA and PPIB were identified through their involvement in both SARS-CoV-2 infection and cancer pathogenesis. In-depth statistical analysis using Kaplan-Meier, differential gene expression, and Cox multivariate regression analysis, demonstrated that overexpression of ACE2, CD147, PPIA and PPIB is significantly associated with poor-prognosis neuroblastoma samples. These results were seen in the presence of amplified MYCN, unfavourable tumour histology and in patients older than 18 months of age. Previously, we have shown that high levels of the nerve growth factor receptor NTRK1 together with low levels of the phosphatase PTPN6 and TP53 are associated with increased relapse-free survival of neuroblastoma patients. Interestingly, low levels of expression of ACE2, CD147, PPIA and PPIB are associated with this NTRK1-PTPN6-TP53 module, suggesting that low expression levels of these genes are associated with good prognosis. These findings have implications for clinical care and therapeutic treatment. The upregulation of ACE2, CD147, PPIA and PPIB in poor-prognosis neuroblastoma samples suggests that these patients may be at higher risk of severe SARS-CoV-2 infection. Importantly, our findings reveal ACE2, CD147, PPIA and PPIB as potential biomarkers and therapeutic targets for neuroblastoma.

Keywords: ACE2; Biomarkers; CD147; NTRK1; Neuroblastoma; PPIA; PPIB; PTPN6; SARS-CoV-2; TP53.

Fig. 1

Kaplan-Meier survival curves and Box plots (GSE49711) for 492 neuroblastoma samples expressing ACE2, CD147, PPIA, and PPIB. For each gene analysed, samples were stratified into low, medium and high expression groups. Kaplan-Meier curves were plotted for each group, and survival distributions curves were compared with the log-rank test. Samples with high expression show significantly decreased EFS when compared to samples with low expression A) ACE2, B) CD147, C) PPIA and D) PPIB Samples were stratified into groups by MYCN amplification and Box plots were plotted using EFS data. Independent t-tests and log-rank tests were used to determine significance E) ACE2, F) CD147, G) PPIA and H) PPIB.

Fig. 2

Kaplan-Meir survival curves for 492 neuroblastoma samples expressing high levels of NTRK1 together with low levels of PTPN6 and TP53 (presence of module) or low levels of NTRK1 together with high levels of PTPN6 and TP53 (absence of module). Survival distributions curves were compared with the log-rank test A) GEO GSE49711 dataset and B) TARGET dataset. Box plots were plotted for both datasets using EFS data. Independent t-tests and log-rank tests were used to determine significance C) GEO GSE49711 dataset and D) TARGET dataset. Samples were stratified by presence of the NTRK1-PTPN6-TP53 module (GEO GSE49711 dataset). Box plots were plotted using EFS data. Independent t-tests and log-rank tests were used to determine significance E) ACE2, F) CD147, G) PPIA and H) PPIB. In samples with the NTRK1-PTPN6-TP53 module, low expression of ACE2, CD147, PPIA or PPIB show significantly increased EFS.