The hepatocellular carcinoma (HCC) stage carcinogenesis is associated with genomic instability features

Abstract

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, which accounts for over 80% of liver tumors. In the study, the current objective is investigating the entire mutational background of the HCC tumors in a single study because it is challenging to explore the many genomic disparities. The study collected DNA-dependent gene sets such as epigenetic modifications, DNA repair, DNA damage response, replication stress, and other related signatures from the molecular signatures database. It investigated their expression patterns in genome-wide expression profiles of liver cancer cohorts by Z score-based pathway activation scoring. Furthermore, these gene set features were validated with a pan-cancer atlas profile. Recurrence is the primary concern in tumors that have regeneration features. Hence, these effects are also further reconfirmed at the recurrence level. Based on activation pattern results, most genomic instabilities feature gene sets activated in the HCC stage tumors rather than other stages. Moreover, these genomic instabilities features are further concluded from that i) The signatures of epigenetic modifications, loss of DNA repair activity, dysregulation of DNA damage response, and replication stress are highly elevated in the HCC stage because of mutation and carcinogenic effects, ii) In addition, hyper DNA helicase activity, transcriptional dysregulation, telomere maintenance, and cell division-related gene sets are also highly enhanced due to proliferation and survival properties of the HCC tumors, and iii) This gene sets an activated in genomic instability comprising subtypes (chromosomal instability and microsatellite instability) of pan-cancer tumor cohort, and these results also reconfirm that these gene sets have genomic instability features. This instability and its dysregulation also have similar impacts at the level of recurrence HCC tumor carcinogenesis. Thus, the potential relevance of molecular signatures identified in terms of outcome prediction and research study in this direction would probably produce significant biological information that may aid in classifying the patients more accurately and providing suggestions for appropriate therapy.