Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis

Abstract

aims: The goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC have remained mostly unknown till now. objective: i) The first goal was to identify key genomic biomarkers related to HCC, highlighting their functions, pathways, and regulatory factors; (ii) the second goal was to investigate candidate drugs for HCC treatments; and (iii) the final goal was to propose potential candidate drugs against HCC based on identified biomarkers. method: The publicly available three mRNA expression profiles from the GEO database were utilized to analyze the differentially expressed genes (DEGs) in HCC. The identification of Hub-DEGs, regulator’s analysis, and survival of HCC patients were conducted by integrated bioinformatics methods. Finally, the top-ranked drug targets and agents were identified by molecular docking study for HCC. result: We identified 160 common differentially expressed genes (cDEGs) and, through protein-protein interaction, ten genes (CDKN3, TK1, NCAPG, CDCA5, RACGAP1, AURKA, PRC1, UBE2T, MELK, and ASPM) were selected as Hub-DEGs. The GO functional and KEGG pathway enrichment analyses of Hub-DEGs revealed several important functions and signaling pathways that are significantly related to HCC. The interaction network analysis identified three TF proteins and eight miRNAs as the key transcriptional and post-transcriptional regulators of Hub-DEGs. Considering Hub-DEGs, 3 key TFs proteins and already published 7 top-ranked meta-genes as drug target receptors, and performed their docking analysis with a list of 172 meta-agent drugs for HCC. We observed that lead five drugs were common with our proposed and published receptors based on their binding affinities. conclusion: Dactinomycin, Vincristine, Sirolimus, Valrubicin, and Navitoclax showed strong binding affinities with proposed receptors, suggesting that the selected drugs may play a vital role in the treatment of HCC. other: The present study emphasizes further wet lab experimental validation for both the proposed target proteins and candidate drugs.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

“…Finally, we recommended our proposed BC-causing five upregulated (COL11A1, COL10A1, CD24, PLK1, UBE2C) and three down-regulated (PDK4, CD36, ACACB) HubGsguided top-ranked six ligands/molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, TG.02) as the candidate drug molecules by molecular docking analysis. It should be mentioned here that both upregulated and down-regulated HubGs were used as drug targets in different studies [166][167][168][169]. Upregulated HubGs-guided drugs inhibit the upregulation of HubGs, while down-regulated HubGs-guided drugs activate the downregulation of HubGs [170].…”

The neurological and non-neurological roles of the primary microcephaly-associated protein ASPM

“…multiple ASPM mutations (Table 2) in tumors. 2 Meanwhile, high levels of ASPM expression correlate with poor prognosis in various types of cancer (Figure 3B), including bladder cancer (Chen et al, 2019(Chen et al, , 2021 2 https://cancer.sanger.ac.uk/cosmic Gao et al, 2020;Liu et al, 2023), prostate cancer (Xie et al, 2017;Pai et al, 2019;Xu et al, 2019), breast cancer (Shubbar et al, 2013;Tang et al, 2019;Wei et al, 2021;Wang et al, 2022), triple-negative breast cancer , esophageal cancer (ESCA; , hepatocellular carcinoma (Lin et al, 2008;Li and Xu, 2020;Yang et al, 2021;Hu et al, 2022;Qiao et al, 2022;Tan et al, 2022;Hasan et al, 2023;Hossen et al, 2023Hossen et al, ), 10.3389/fnins.2023 Frontiers in Neuroscience 13 frontiersin.org glioblastoma (Visnyei et al, 2011;Qin et al, 2023), epithelial ovarian cancer (Brüning-Richardson et al, 2011;Alsiary et al, 2014;, osteosarcoma (Liu et al, 2021), endometrial carcinoma , malignant pleural mesothelioma (Zhang et al, 2020), cervical squamous cell carcinoma (Wen et al, 2020), lung adenocarcinoma (Feng et al, 2021;Hou et al, 2022;Tang et al, 2022;Yin et al, 2022;, anaplastic thyroid carcinoma (Fang et al, 2023), cutaneous squamous cell carcinoma (Su et al, 2022), human sarcomas …”

Knowledge mapping of AURKA in Oncology：An advanced Bibliometric analysis (1998–2023)

“…Dysregulation of AURKA can lead to chromosomal instability, aberrant cell division, and aneuploidy, all of which significantly contribute to the initiation and progression of tumors [ [7] , [8] , [9] ]. Beyond its fundamental involvement in mitosis, AURKA has been implicated in diverse cellular processes, such as centrosome maturation regulation, spindle assembly checkpoint signaling, DNA damage response, and cell migration [ 10 , 11 ] The abnormal expression or activity of AURKA has been detected across various types of cancer, including breast, lung, colorectal, pancreatic, hepatocellular, and ovarian cancers, rendering it an attractive target for anticancer therapies [ [12] , [13] , [14] , [15] ]. Nevertheless, while the transformative potential of AURKA is increasingly recognized, its clinical application spectrum remains relatively limited [ 16 ].…”