Cancer, also known as malignancy, is irregular cell growth. More than 100 different types of cancer exist, in which most common are breast, skin, prostate, lungs, colon, and lymphoma . Cancer is present in human as the most considerable public health concern worldwide, and liver cancer adds greatly to the morbidity and mortality in cancer . Liver cancer (hepatocellular carcinoma) is the fourth leading cause of cancer-related death globally, ranking sixth in prevalence [3, 4]. Hepatocellular carcinoma (HCC) constitutes about 85–90% of all primary malignant liver tumors. Chronic hepatitis B virus (HBV) infection, hepatitis C virus (HCV), smoking, aflatoxin, obesity, chronic liver disease, and type 2 diabetes are the main risk factors [3, 5, 6]. Of these variables, recurrent liver disease is the primary cause of liver cancer .
The prevalence of viral infection in HCC cases varies from developed to developing nations, where HBV reflects 60% in developing nations and 23% in developed nations, while HCV infection is responsible for 23% in emerging nations, and 20% of patients in developed nations . Moreover, the highest incidence of HBV is in sub-Saharan Africa, South-eastern Asia, and East Asia, while HCV is high in the USA, Europe, and Japan . The prevalence of non-alcoholic fatty liver disease (NAFLD) also adversely affects individual health causing an increase in obesity and other metabolic disorders . Around 25–30% of patients having a western lifestyle possess more fats in their liver, 2–5% of which have NAFLD, and 1–2% suffer from non-alcoholic steatohepatitis cirrhosis .
The World Health Organization (WHO) estimates that in 2030 over one million people are going to die of liver cancer . The key factor that affects HCC mortality is a poor diagnosis, which results in just 18% survival  less than the cancers of the breast (77.1%), renal pelvic (74.8%), and myeloma (52.2%). The high risk of recurrence and metastasis of the HCCs also contribute to a shorter life span and poor survival after hepatectomy . Different variables participate in HCC diagnoses, such as cell proliferation, apoptosis, and genes linked to the mTOR pathway . HCC is on a global increase, but early detection and therapy of HCC remain a concern . In developing countries, the HCC prevalence is growing as a consequence of low levels of health and treatment, with a global rate of liver cancer per 100000 people approximately at 9.3 in 2018 , as well as poor prognosis .
The diverse factors implicated in liver cancer are cellular tumor antigen p53 (TP53), axin-1 (AXIN1), catenin β-1 (CTNNB1), and telomerase reverse transcriptase (TERT) promoters as well as other primary genes for mutation generation, p53 cell cycle system, WNT/β-catenin, oxidative stress, RAS/RAF/MAPK, and PI3K/AKT/MTOR pathways along with other main primary signaling pathways. Liu et al. (2018) used highly efficient microarray technology to screen molecular indicators across all human cancerous tumors, especially for liver cancer, by using Gene Expression Omnibus (GEO) datasets, The Cancer Genome Atlas (TCGA) RNA-sequence and analyzed with the help of bioinformatics methods . Gene chip technology can also reliably represent the molecular expression profile and detect genetic variants correlated with HCC in liver cancer studies [18, 19]. The data, information, knowledge, and wisdom (DIKW) model is widely used in life, including medicine [20–22]. Recently, genome-wide screening has significantly improved the knowledge of the genetic context and pathways that lead to HCC [23–26].
Four core genes and two essential pathways of developing HCC from cirrhosis have been established by GEO dataset using a bioinformatics methodology, including DEG screening and networking of protein-protein interactions (PPIs) . Zhang et al. screened the genes and pathways associated with HCC development and prevalence through a series of bioinformatics observations, such as DEG recognition, functional enrichment analysis, PPI network and module analysis, and weighted network correlation analysis . Zhou et al. identified HCC critical genes and microRNAs through raw data processing by using Gene Ontology (GO), GEO2R, and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment processing and PPI network creation . Established research, nevertheless, have been of small scale, and the lack of molecular prognostic indexes might have restricted the ability to recognize possible important molecular biomarkers and emerging clinical goals.
Applied bioinformatics research with the current genomic evidence offers an in-depth insight into therapeutic resistance and disease progression processes. This study focuses on the expression profiling of HCC patients compared to healthy ones. GSE62232 dataset (GEO: https://www.ncbi.nlm.nih.gov/geo/) has been chosen. GSE62232 was analysed through GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2R)  to evaluate and recalculate the genes that are differentially expressed in healthy and diseased samples. However, new diagnostic and prognostic biomarkers are needed to improving HCC diagnosis and treatment.