Recently an outbreak that emerged in Wuhan, China in December 2019, spread to the whole world in a short time and killed >1,410,000 people. It was determined that a new type of beta coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) was causative agent of this outbreak and the disease caused by the virus was named as coronavirus disease 19 (COVID19). Despite the information obtained from the viral genome structure, many aspects of the virus-host interactions during infection is still unknown. In this study we aimed to identify SARS-CoV-2 encoded microRNAs and their cellular targets. We applied a computational method to predict miRNAs encoded by SARS-CoV-2 along with their putative targets in humans. Targets of predicted miRNAs were clustered into groups based on their biological processes, molecular function, and cellular compartments using GO and PANTHER. By using KEGG pathway enrichment analysis top pathways were identified. Finally, we have constructed an integrative pathway network analysis with target genes. We identified 40 SARS-CoV-2 miRNAs and their regulated targets. Our analysis showed that targeted genes including NFKB1, NFKBIE, JAK1–2, STAT3–4, STAT5B, STAT6, SOCS1–6, IL2, IL8, IL10, IL17, TGFBR1–2, SMAD2–4, HDAC1–6 and JARID1A-C, JARID2 play important roles in NFKB, JAK/STAT and TGFB signaling pathways as well as cells' epigenetic regulation pathways. Our results may help to understand virus-host interaction and the role of viral miRNAs during SARS-CoV-2 infection. As there is no current drug and effective treatment available for COVID19, it may also help to develop new treatment strategies.

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Polymorphism of AXIN2, a component of Wnt signaling, has been shown to play a role in tumorigenesis and dysregulated in cancer cells. In order to find out if AXIN2 polymorphism is a risk factor for prostate cancer, we analyzed eight polymorphic regions of this gene in 84 patients with prostate cancer and compared the results with 100 healthy controls in a Turkish population using PCR-RFLP methods. The genotype frequencies and risk factors of prostate cancer and control groups were analyzed by Chi-square test. We found a statistically significant result between prostate cancer risk and AXIN2 Intron2-956+16A/G (rs35285779) SNP. The frequency of the homozygous G/G (0%) and heterozygous A/G (18%) genotypes was significantly less in patients with prostate cancer than in healthy controls (7 and 32%, respectively) (P<0.05) for this SNP. When compared with the wild-type A/A genotype of the controls, prostate cancer patients with the A/G and G/G genotype showed reduced risk of cancer; the adjusted odds ratio (OR) for patients with the homozygous G/G genotype was 0.87 (95% CI: 0.81-0.95) and for heterozygous A/G genotype was 0.42 (95% CI: 0.20-0.85). We found no statistically significant association between controls and prostate cancer for other seven SNPs of AXIN2 including Exon1-148 C/T (rs2240308), Exon1-432 T/C (rs2240308), Exon5-1365 G/A (rs9915936), Exon5-1386 C/T (rs1133683), Intron5-1712+19 T/G, Exon7-2062 C/T, and Intron7-2141+73 G/A (rs4072245) (P>0.05). These results suggest that the AXIN2 Intron2 rs35285779 SNP is associated with development of prostate cancer as a protective SNP, while an association between other seven SNPs of the AXIN2 and risk of prostate cancer was not observed.

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