Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has high infectivity in humans, attributed to the strong affinity of its spike (S) protein to human angiotensin-converting enzyme 2 (ACE2). Here, we analyzed the structural similarity of the S protein between SARS-CoV-2 and other SARS-related coronaviruses (CoVs). Methods We performed multiple alignment analysis of nine amino acid sequences of CoV S proteins from NCBI with MAFFT web-based software, followed by phylogeny analysis. Three-dimensional structure modeling was performed by SWISS-MODEL. We calculated the template modeling score between the S protein of SARS-CoV-2 and that of other SARS-related CoVs. Results The S1 domain of the unclassified CoV RaTG13 (the host of which is the intermediate horseshoe bat) was structurally very similar to that of SARS-CoV-2, implying that RaTG13 could be the origin of SARS-CoV-2. In addition, the folding property of the entire S protein was nearly the same between SARS-CoV-2 and RaTG13 after the PRRA amino acid insertion was removed from SARS-CoV-2. Conclusions RaTG13 could have a high binding affinity to ACE2, similar to SARS-CoV-2, and it is therefore highly likely to infect other animals. Therefore, massive research and monitoring of CoVs in animals is necessary to prevent future COVID-19-like disasters.

Glioma accounts for 80% of all malignant brain tumors and is the most common adult primary brain tumor. Age is an important factor affecting the development of cancer as somatic mutations accumulate with age. In this study, we aimed to analyze the significance of age-related non-silent somatic mutations in glioma prognosis. Histological tumor grade depends on age at diagnosis in patients with IDH1, TP53, ATRX, and EGFR mutations. The hierarchical clustering of patients was dominantly separated by IDH1 and EGFR mutations. Furthermore, patients with IDH1 mutation were dominantly separated by TP53 and ATRX double mutation and its double wildtype counterpart. Patients with the double mutation showed poorer prognosis than those with the double wild type genotype. In conclusion, among the many somatic mutations, those in IDH1, TP53, ATRX, and EGFR are important for glioma classification based on histological grade. Patients with EGFR mutation had the poorest prognosis, whereas those with only IDH1 mutation showed the best prognosis.