Construction and analysis of pseudogene-related ceRNA network in breast cancer.

Breast cancer (BC) is one of the leading causes of cancer-related deaths in women. The present study explored the potential role of pseudogenes in BC via construction and analysis of a competing endogenous RNA (ceRNA) network through a three-step process. First, we screened differentially expressed genes in nine BC datasets. Then the gene-pseudogenes pairs (nine hub genes) were selected according to the functional enrichment and correlation analysis. Second, the candidate hub genes and interacting miRNAs were used to construct the ceRNA network. Further analysis of the ceRNA network revealed a crucial ceRNA module with two genes-pseudogene pairs and two miRNAs. The in-depth analysis identified the GBP1/hsa-miR-30d-5p/GBP1P1 axis as a potential tumorigenic axis in BC patients. In the third step, the GBP1/hsa-miR-30d-5p/GBP1P1 axis expression level was assessed in 40 tumor/normal BC patients and MCF-7 cell lines. The expression of GBP1 and GBP1P1 was significantly higher in the tumor compared to the normal tissue. However, the expression of hsa-miR-30d-5p was lower in tumor samples. Then, we introduced the GBP1P1 pseudogene into the MCF-7 cell line to evaluate its effect on GBP1 and hsa-miR-30d-5p expression. As expected, the GBP1 level increased while the hsa-miR-30d-5p level decreased in the GBP1P1-overexprsssing cell line. In addition, the oncogenic properties of MCF-7 (cell viability, clonogenicity, and migration) were improved after GBP1P1 overexpression. In conclusion, we report a ceRNA network that may provide new insight into the role of pseudogenes in BC development.

In silico drug repurposing against SARS-CoV-2 using an integrative transcriptomic profiling approach: Hydrocortisone and Benzhydrocodone as potential drug candidates against COVID-19.

COVID-19 pathogenesis is mainly attributed to dysregulated antiviral immune response, the prominent hallmark of COVID-19. As no established drugs are available against SARS-CoV-2 and developing new ones would be a big challenge, repurposing of existing drugs holds promise against COVID-19. Here, we used a signature-based strategy to delve into cellular responses to SARS-CoV-2 infection in order to identify potential host contributors in COVID-19 pathogenesis and to find repurposable drugs using in silico approaches. We scrutinized transcriptomic profile of various human alveolar cell sources infected with SARS-CoV-2 to determine up-regulated genes specific to COVID-19. Enrichment analysis revealed that the up-regulated genes were involved mainly in viral infectious disease, immune system, and signal transduction pathways. Analysis of protein-protein interaction network and COVID-19 molecular pathway resulted in identifying several anti-viral proteins as well as 11 host pro-viral proteins, ADAR, HBEGF, MMP9, USP18, JUN, FOS, IRF2, ICAM1, IFI35, CASP1, and STAT3. Finally, molecular docking of up-regulated proteins and all FDA-approved drugs revealed that both Hydrocortisone and Benzhydrocodone possess high binding affinity for all pro-viral proteins. The suggested repurposed drugs should be subject to complementary in vitro and in vivo experiments in order to be evaluated in detail prior to clinical studies in potential management of COVID-19.

A panel of blood-derived miRNAs with a stable expression pattern as a potential pan-cancer detection signature.

Introduction: MicroRNAs have a significant role in the regulation of the transcriptome. Several miRNAs have been proposed as potential biomarkers in different malignancies. However, contradictory results have been reported on the capability of miRNA biomarkers in cancer detection. The human biological clock involves molecular mechanisms that regulate several genes over time. Therefore, the sampling time becomes one of the significant factors in gene expression studies. Method: In the present study, we have tried to find miRNAs with minimum fluctuation in expression levels at different time points that could be more accurate candidates as diagnostic biomarkers. The small RNA-seq raw data of ten healthy individuals across nine-time points were analyzed to identify miRNAs with stable expression. Results: We have found five oscillation patterns. The stable miRNAs were investigated in 779 small-RNA-seq datasets of eleven cancer types. All miRNAs with the highest differential expression were selected for further analysis. The selected miRNAs were explored for functional pathways. The predominantly enriched pathways were miRNA in cancer and the P53-signaling pathway. Finally, we have found seven miRNAs, including miR-142-3p, miR-199a-5p, miR-223-5p, let-7d-5p, miR-148b-3p, miR-340-5p, and miR-421. These miRNAs showed minimum fluctuation in healthy blood and were dysregulated in the blood of eleven cancer types. Conclusion: We have found a signature of seven stable miRNAs which dysregulate in several cancer types and may serve as potential pan-cancer biomarkers.