Epidemiologic Characteristics of and Prognostic Factors for COVID-19 Among Hospitalized Patients: Updated Implications From Hubei Province, China.

Introduction: The roles of some indicators in the prognosis of patients with coronavirus disease-19 (COVID-19) remain unclear and controversial. This study aimed to explore the epidemiologic characteristics of and prognostic factors for COVID-19 to provide updated recommendations for its prevention, diagnosis, and treatment. Methods: For this retrospective study, demographic, epidemiologic, and clinical data were extracted from the medical records of patients admitted to the Maternal and Child Hospital of Hubei Province (Optical Valley) with COVID-19 between February 19, 2020, and March 19, 2020. The primary outcome was the prognosis that was determined at discharge as mentioned in the medical records. Descriptive statistics, univariate analyses, and stepwise logistic regression analysis were used for data analysis. Results: Of the 1,765 patients included, 93.1% were cured and the mortality was 1.8%. Univariate analyses identified 63 factors significantly associated with COVID-19 prognosis. Logistic regression analysis revealed that a poorer prognosis was associated with undergoing resuscitation, complex disease manifestations, consultation with outside specialists, elevated basophil or lymphocyte counts, an albumin (ALB)/globulin (A/G) ratio > 2.4, and elevated levels of serum aspartate aminotransferase (AST) or creatinine. Patients had a better prognosis if the following conditions were met: dry cough reported as an initial symptom, fatigue as a clinical manifestation, and a diagnosis based on laboratory testing. Conclusion: To prevent clinical deterioration, clinicians should provide special care to patients who underwent resuscitation, with a critical disease, or requiring consultation with outside specialists. Extra attention should be paid to patients with high basophil or lymphocyte counts, a high A/G ratio, and elevated AST or creatinine levels.

miR-1/133a and miR-206/133b clusters overcome HGF induced gefitinib resistance in non-small cell lung cancers with EGFR sensitive mutations.

It has been reported that clustered miRNAs can be transcribed coordinately and exhibit similar functions by regulating the same targets. miR-1/133a and miR-206/133b are well-characterized miRNA clusters. However, the effect of these clusters on EGFR-TKI resistance is not clear. In this study, we demonstrated that lentivirus-mediated HGF overexpression was able to induce gefitinib resistance in non-small cell lung cancers with EGFR sensitive mutations. miR-1/133a and miR-206/133b clusters could overcome HGF induced gefitinib resistance. Furthermore, the clusters were more effective than individual miRNA. Transcriptome RNA sequencing and bioinformatics analysis revealed that multiple pathways, including 'EGFR tyrosine kinase inhibitor resistance' pathway, were involved in anti-resistance mechanisms of miR-1/133a and miR-206/133b clusters. Western blotting results confirmed the inhibitory effect of miRNA clusters on MET expression and downstream pathway activation. In conclusion, miR-1/133a and miR-206/133b clusters are able to exhibit the synergetic effect on overcoming HGF-induced gefitinib resistance in NSCLC and the mechanisms are through targeting multiple genes related to gefitinib resistance.