The COVID-19 virus has infected more than 38 million people and resulted in more than one million deaths worldwide as of October 14, 2020. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, economic inequality enhanced the risk of COVID-19 transmission. The per capita hospital beds correlated negatively with COVID-19 deaths. Blood types B and AB were protective factors for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV and influenza and pneumonia was associated with reduced COVID-19 risk. Increased intake of vegetables, edible oil, protein, vitamin D, and vitamin K was associated with reduced COVID-19 risk, while increased intake of alcohol was associated with increased COVID-19 risk. Other factors included age, sex, temperature, humidity, social distancing, smoking, health investment, urbanization level, and race. High temperature is a more compelling factor mitigating COVID-19 transmission than low temperature. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread.

The COVID-19 virus has infected millions of people and resulted in hundreds of thousands of deaths worldwide. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, we found that the unitary state system was counter-intuitively positively associated with increased COVID-19 cases and deaths. Blood type B was a protective factor for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV, influenza and pneumonia, and chronic lower respiratory diseases was associated with reduced COVID-19 risk. Obesity and the condition of unimproved water sources were associated with increased COVID-19 risk. Other factors included temperature, humidity, social distancing, smoking, and vitamin D intake. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread.

Intratumor heterogeneity (ITH) is associated with tumor development, prognosis, immune evasion and therapeutic effects. We proposed the Defining ITH based on EntRopy (DITHER) algorithm for evaluating ITH. We first evaluated the entropies of somatic mutation profiles and copy number alteration (CNA) profiles in a tumor, respectively, and defined their average as the ITH level for the tumor. Using DITHER, we analyzed 33 cancer types from The Cancer Genome Atlas (TCGA) program. We demonstrated that the ITH defined by DITHER had the typical properties of ITH, namely its strong correlations with tumor progression, unfavorable phenotype, genomic instability and immune evasion. Compared with two other ITH evaluation methods: MATH and PhyloWGS, the DITHER ITH had more prominent characteristics of ITH. Moreover, different from MATH and PhyloWGS, DITHER scores were positively correlated with tumor purity, suggesting that DITHER tends to capture the ITH between tumor cells. Interestingly, microsatellite instability (MSI)-high tumors had significantly lower DITHER scores than microsatellite stability (MSS)/MSI-low tumors, although the former had significantly higher tumor mutation loads than the latter. It suggests that the hypermutability of MSI is homogeneous between different cellular populations in bulk tumors. The DITHER ITH may provide novel insights into tumor biology and potential clinical applications.

Backgroundkalirin RhoGEF kinase (KALRN) is mutated in a wide range of cancers. Nevertheless, the association between KALRN mutations and the pathogenesis of cancer remains unexplored. Identification of biomarkers for cancer immunotherapy response is crucial because immunotherapies only show beneficial effects in a subset of patients with cancer.MethodsWe explored the correlation between KALRN mutations and antitumor immunity in 10 cancer cohorts from The Cancer Genome Atlas program by the bioinformatics approach. Moreover, we verified the findings from the bioinformatics analysis with in vitro and in vivo experiments. We explored the correlation between KALRN mutations and immunotherapy response in five cancer cohorts receiving immune checkpoint blockade therapy.ResultsAntitumor immune signatures were more enriched in KALRN-mutated than KALRN-wildtype cancers. Moreover, KALRN mutations displayed significant correlations with increased tumor mutation burden and the microsatellite instability or DNA damage repair deficiency genomic properties, which may explain the high antitumor immunity in KALRN-mutated cancers. Also, programmed cell death 1 ligand (PD-L1) expression was markedly upregulated in KALRN-mutated versus KALRN-wildtype cancers. The increased antitumor immune signatures and PD-L1 expression in KALRN-mutated cancers may favor the response to immune checkpoint blockade therapy in this cancer subtype, as evidenced in five cancer cohorts receiving antiprogrammed cell death protein 1 (PD-1)/PD-L1/cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) immunotherapy. Furthermore, the significant association between KALRN mutations and increased antitumor immunity was associated with the fact that KALRN mutations compromised the function of KALRN in targeting Rho GTPases for the regulation of DNA damage repair pathways. In vitro and in vivo experiments validated the association of KALRN deficiency with antitumor immunity and the response to immune checkpoint inhibitors.ConclusionsThe KALRN mutation is a useful biomarker for predicting the response to immunotherapy in patients with cancer.

Graphical abstract