Effects of SARS-CoV-2 Spike S1 Subunit on the Interplay Between Hepatitis B and Hepatocellular Carcinoma Related Molecular Processes in Human Liver

Background: This study addresses a particular aspect of the biological behavior of the Spike subunit S1 of SARS-CoV-2. Researchers observed S1 acting freely in the human organism during and after COVID-19 and vaccination. One of its properties is that it interacts one-to-one with human proteins. S1 interacts with 12 specific human proteins in the liver. Methods: We used these proteins as seeds to extract their functional relationships from the human proteome through enrichment. The interactome representing the set of metabolic activities in which they are involved shows several molecular processes (KEGG), including some linked to HBV (hepatitis B) and HCC (hepatocellular carcinoma) with many genes/proteins involved. Reports show that, in some COVID patients, HBV reactivated or progressed to cancer. Results: We analyzed the interactome with several approaches to understand whether the two pathologies have independent progressions or a common progression. All our efforts consistently showed that the molecular processes involving both HBV and HCC are significantly present in all approaches we used, making it difficult to extract any useful information about their fate. Through BioGRID, we extracted experimental data in vivo but derived it from model cell systems. The lack of patient data in STRING results prevents diagnosis or prediction of real disease progression; therefore, we can consider them “aseptic” model data. Conclusion: The interactome tells us that genes involved in HCC and HVB-related pathways have the potential to activate disease processes. We can consider them as a gold standard. It is the comparison with similar molecular interactions found in individual human phenotypes that shows us whether the phenotype favors or hinders their progression. This also suggests how to use these features. These sets of proteins constitute a molecular “toolkit”. In fact, if we compare them with similar molecular sets of the patient, they will provide us with information on the level of the phenotypic state that is driving the disease. The information derived from the composition of an entire group of proteins is broader and more detailed than a single marker. Therefore, these protein compositions can serve as a reference system with which doctors can compare specific cases for personalized molecular medicine diagnoses.