Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

Next generation sequencing (NGS)-based tumor profiling identified an overwhelming number of uncharacterized somatic mutations, also known as variants of unknown significance (VUS). The therapeutic significance of EGFR mutations outside mutational hotspots, consisting of >50 types, in nonsmall cell lung carcinoma (NSCLC) is largely unknown. In fact, our pan-nation screening of NSCLC without hotspot EGFR mutations (n = 3,779) revealed that the majority (>90%) of cases with rare EGFR mutations, accounting for 5.5% of the cohort subjects, did not receive EGFR-tyrosine kinase inhibitors (TKIs) as a first-line treatment. To tackle this problem, we applied a molecular dynamics simulation-based model to predict the sensitivity of rare EGFR mutants to EGFR-TKIs. The model successfully predicted the diverse in vitro and in vivo sensitivities of exon 20 insertion mutants, including a singleton, to osimertinib, a third-generation EGFR-TKI (R2 = 0.72, P = 0.0037). Additionally, our model showed a higher consistency with experimentally obtained sensitivity data than other prediction approaches, indicating its robustness in analyzing complex cancer mutations. Thus, the in silico prediction model will be a powerful tool in precision medicine for NSCLC patients carrying rare EGFR mutations in the clinical setting. Here, we propose an insight to overcome mutation diversity in lung cancer.

EGFR-mutated lung cancer accounts for a significant proportion of lung cancer cases worldwide. For these cases, osimertinib, a thirdgeneration EGFR tyrosine kinase inhibitor, is extensively used as a first-line or second-line treatment. However, lung cancer cells acquire resistance to osimertinib in 1 to 2 years. Thus, a thorough clarification of resistance mechanisms to osimertinib is highly anticipated. Recent next-generation sequencing (NGS) of lung cancer samples identified several genetically defined resistance mechanisms to osimertinib, such as EGFR C797S or MET amplification. However, nongenetically defined mechanisms are not well evaluated. For a thorough clarification of osimertinib resistance, both genetic and nongenetic mechanisms are essential. By using our comprehensive protein phosphorylation array, we detected IGF1R bypass pathway activation after EGFR abolishment. Both of our established lung cancer cells and patient-derived lung cancer cells demonstrated IGF2 autocrine-mediated IGF1R pathway activation as a mechanism of osimertinib resistance. Notably, this resistance mechanism was not detected by a previously performed NGS, highlighting the essential roles of living cancer cells for a thorough clarification of resistance mechanisms. Interestingly, the immunohistochemical analysis confirmed the increased IGF2 expression in lung cancer patients who were treated with osimertinib and met the established clinical definition of acquired resistance. The findings highlight the crucial roles of cell-autonomous ligand expression in osimertinib resistance. Here, we report for the first time the IGF2 autocrine-mediated IGF1R activation as a nongenetic mechanism of osimertinib resistance in lung cancer at a clinically relevant level. Implications: Using comprehensive protein phosphorylation array and patient-derived lung cancer cells, we found that IGF2 autocrinemediated IGF1R pathway activation is a clinically relevant and common mechanism of acquired resistance to osimertinib.

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Background We aimed to elucidate differences in the characteristics of patients with coronavirus disease 2019 (COVID-19) requiring hospitalization in Japan, by COVID-19 waves, from conventional strains to the Delta variant. Methods We used secondary data from a database and performed a retrospective cohort study that included 3261 patients aged ≥ 18 years enrolled from 78 hospitals that participated in the Japan COVID-19 Task Force between February 2020 and September 2021. Results Patients hospitalized during the second (mean age, 53.2 years [standard deviation {SD}, ± 18.9]) and fifth (mean age, 50.7 years [SD ± 13.9]) COVID-19 waves had a lower mean age than those hospitalized during the other COVID-19 waves. Patients hospitalized during the first COVID-19 wave had a longer hospital stay (mean, 30.3 days [SD ± 21.5], p < 0.0001), and post-hospitalization complications, such as bacterial infections (21.3%, p < 0.0001), were also noticeable. In addition, there was an increase in the use of drugs such as remdesivir/baricitinib/tocilizumab/steroids during the latter COVID-19 waves. In the fifth COVID-19 wave, patients exhibited a greater number of presenting symptoms, and a higher percentage of patients required oxygen therapy at the time of admission. However, the percentage of patients requiring invasive mechanical ventilation was the highest in the first COVID-19 wave and the mortality rate was the highest in the third COVID-19 wave. Conclusions We identified differences in clinical characteristics of hospitalized patients with COVID-19 in each COVID-19 wave up to the fifth COVID-19 wave in Japan. The fifth COVID-19 wave was associated with greater disease severity on admission, the third COVID-19 wave had the highest mortality rate, and the first COVID-19 wave had the highest percentage of patients requiring mechanical ventilation.