Target and drug predictions for SARS-CoV-2 infection in hepatocellular carcinoma patients

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the coronavirus disease (COVID-19), which poses a major threat to humans worldwide. With the continuous progress of the pandemic, a growing number of people are infected with SARS-CoV-2, including hepatocellular carcinoma (HCC) patients. However, the relationship between COVID-19 and HCC has not been fully elucidated. In order to provide better treatment for HCC patients infected with SARS-CoV-2, it’s urgently needed to identify common targets and find effective drugs for both. In our study, transcriptomic analysis was performed on both selected lung epithelial cell datasets of COVID-19 patients and the datasets of HCC patients to identify the synergistic effect of COVID-19 in HCC patients. What’s more, common differentially expressed genes were identified, and a protein-protein interactions network was designed. Then, hub genes and basic modules were detected based on the protein-protein interactions network. Next, functional analysis was performed using gene ontology terminology and the Kyoto Encyclopedia of Genes and Genomes pathway. Finally, protein-protein interactions revealed COVID-19 interaction with key proteins associated with HCC and further identified transcription factor (TF) genes and microRNAs (miRNA) with differentially expressed gene interactions and transcription factor activity. This study reveals that COVID-19 and HCC are closely linked at the molecular level and proposes drugs that may play an important role in HCC patients with COVID-19. More importantly, according to the results of our research, two critical drugs, Ilomastat and Palmatine, may be effective for HCC patients with COVID-19, which provides clinicians with a novel therapeutic idea when facing possible complications in HCC patients with COVID-19.

Bioinformatics Approaches to Determine the Effect of SARS-CoV-2 Infection on Patients with Intrahepatic Cholangiocarcinoma

“…Although COVID-19 primarily affects the respiratory system, liver dysfunction is also common in COVID-19 patients, such as elevated liver transaminases and elevations of cholestatic liver enzymes(30). The association between the most common liver cancer, HCC, and COVID-19 has been reported in a previous article (9). ICC, which is the second most common liver cancer and has many similarities with HCC, may also be linked to COVID-19.…”

“…Liver cancer is the sixth most common and the third deadliest malignancy in the world (8). The relationship between COVID-19 and hepatocellular carcinoma (HCC), the most common form of liver cancer, has been reported recently (9). As the second most common liver cancer, ICC is highly similar with HCC, which are both associated with cirrhosis, infection of Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV), and metabolic syndrome (10).…”

Understanding the SARS-CoV-2-Human Liver Interactome Using a Comprehensive Analysis of the Individual Virus-Host Interactions.

“…As mentioned in the Introduction, we carefully selected 11 projects [13][14][15][16][17][18][19][20][21][22][23] out of the 18 projects identified in the scientific literature between 2021 and 2023. These papers deal with the characterization of hepatic metabolic processes that are viral targets in patients affected by COVID-19.…”

“…Some of our searches on PubMed performed using terms such as "COVID-19 AND liver hub genes" or similar terms, extracted eighteen studies, of which we selected eleven (2021-2023) [13][14][15][16][17][18][19][20][21][22][23] because they reported hub genes linked to COVID-19 (see also in the Results). These studies aim to determine regulatory processes from datasets based on microarray or transcriptome sequencing technology.…”

Understanding the SARS-CoV-2–Human Liver Interactome Using a Comprehensive Analysis of the Individual Virus–Host Interactions

“…Many studies on PubMed [11,[13][14][15][16][17][18][19][20][21][22] from 2021 to 2023 reported hub genes linked to COVID-19. They aim to determine regulatory processes from datasets based on microarray or transcriptome sequencing technology.…”