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To investigate the relationship between Bacille Calmette‐Guérin (BCG) vaccination and SARS‐CoV‐2 by a bioinformatics approach, two datasets for the SARS‐CoV‐2 infection group and BCG‐vaccinated group were downloaded. Differentially Expressed Genes were identified. Gene ontology and pathways were functionally enriched, and networking was constructed in NetworkAnalyst. Lastly, the correlation between post‐BCG vaccination and COVID‐19 transcriptome signatures was established. A total of 161 DEGs (113 upregulated DEGs and 48 downregulated genes) were identified in the SARS‐CoV‐2 group. In the pathway enrichment analysis, a cross‐reference of upregulated Kyoto Encyclopedia of Genes and Genomes pathways in SARS‐CoV‐2 with downregulated counterparts in the BCG‐vaccinated group, resulted in the intersection of 45 common pathways, accounting for 86.5% of SARS‐CoV‐2 upregulated pathways. Of these intersecting pathways, a vast majority were immune and inflammatory pathways with top significance in interleukin‐17, tumor necrosis factor, NOD‐like receptors, and nuclear factor‐κB signaling pathways. Given the inverse relationship of the specific differentially expressed gene pathways highlighted in our results, the BCG‐vaccine may play a protective role against COVID‐19 by mounting a nonspecific immunological response and further investigation of this relationship is warranted. [ABSTRACT FROM AUTHOR]

Background: Although well-differentiated papillary thyroid cancer may remain indolent, lymph node metastases and the recurrence rates are approximately 50% and 20%, respectively. No current biomarkers are able to predict metastatic lymphadenopathy and recurrence in early stage papillary thyroid cancer. Hence, identifying prognostic biomarkers predicting cervical lymph-node metastases would prove very helpful in determining treatment., Methods: The database of the Cancer Genome Atlas included 495 papillary thyroid cancer samples. Using this database, we developed a machine learning model to define a gene signature that could predict lymph-node metastasis (N0 or N1). Kruskal-Wallis tests, univariate and multivariate logistic and Cox regression models, and Kaplan-Meier analyses were performed to correlate the gene signature with clinical outcomes., Results: We identified a panel of 25 genes and constructed a risk score that can differentiate N0 and N1 papillary thyroid cancer samples (P < .001) with a sensitivity of 86%, a specificity of 62%, a positive predictive value of 93%, and a negative predictive value of 42%. This panel represents an independent biomarker to predict metastatic lymphadenopathy (OR = 8.06, P < .001) specifically in patients with T1 lesions (OR = 7.65, P = .002) and disease-free survival (HR = 2.64, P = .043)., Conclusion: This novel 25-gene panel may be used as a potential prognostic marker for accurately predicting lymph-node metastasis and disease-free survival in patients with early-stage papillary thyroid cancer., (Copyright © 2019 Elsevier Inc. All rights reserved.)