Ershov Pavel, Poyarkov Stanislav, Konstantinova Yulia, Veselovsky Egor, Makarova Anna
Department of Analysis and Forecasting of Medical and Biological Health Risks, Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia.
Oncology Department, Federal Research and Clinical Center of Specialized Kinds of Medical Care and Medical Technology of the Federal Medical Biological Agency, Moscow, Russia.
Curr Mol Med. 2023;23(3):239-249. doi: 10.2174/1566524022666220427102048.
Due to a large number of identified hub-genes encoding key molecular regulators, which are involved in signal transduction and metabolic pathways in cancers, it is relevant to systemize and update these findings.
Colorectal cancer (CRC) is the third leading cause of cancer death in the world, with high metastatic potential. Elucidating the pathogenic mechanisms and selection of novel biomarkers in CRC is of great clinical significance.
This analytical review aims at the systematization of bioinformatics and experimental identification of hub-genes associated with CRC for a more consolidated understanding of common features in networks and pathways in CRC progression as well as hub-genes selection.
In total, 301 hub-genes were derived from 40 articles. The "core" consisted of 28 hub-genes (CCNB1, LPAR1, BGN, CXCL3, COL1A2, UBE2C, NMU, COL1A1, CXCL2, CXCL11, CDK1, TOP2A, AURKA, SST, CXCL5, MMP3, CCND1, TIMP1, CXCL8, CXCL1, CXCL12, MYC, CCNA2, GCG, GUCA2A, PAICS, PYY and THBS2) mentioned in not less than three articles and having clinical significance in cancerassociated pathways. Of them, there were two discrete clusters enriched in chemokine signaling and cell cycle regulatory genes. High expression levels of BGN and TIMP1 and low expression levels of CCNB1, CXCL3, CXCL2, CXCL2 and PAICS were associated with unfavorable overall survival of patients with CRC. Differently expressed genes such as LPAR1, SST, CXCL12, GUCA2A, and PYY were shown as down regulated, whereas BGN, CXCL3, UBE2C, NMU, CXCL11, CDK1, TOP2A, AURKA, MMP3, CCND1, CXCL1, MYC, CCNA2, PAICS were up regulated genes in CRC. It was also found that MMP3, THBS2, TIMP1 and CXCL12 genes were associated with metastatic CRC. Network analysis in ONCO.IO showed that upstream master regulators RELA, STAT3, SOX2, FOXM1, SMAD3 and NF-kB were connected with "core" hub-genes. Conclusión: Results obtained are of useful fundamental information on revealing the mechanism of pathogenicity, cellular target selection for optimization of therapeutic interventions, as well as transcriptomics prognostic and predictive biomarkers development.
由于已鉴定出大量编码关键分子调节因子的枢纽基因，这些基因参与癌症的信号转导和代谢途径，因此有必要对这些发现进行系统化和更新。
结直肠癌（CRC）是全球癌症死亡的第三大主要原因，具有很高的转移潜力。阐明CRC的致病机制并选择新的生物标志物具有重要的临床意义。
本分析性综述旨在对与CRC相关的枢纽基因进行生物信息学系统化和实验鉴定，以便更全面地了解CRC进展过程中网络和途径的共同特征以及枢纽基因的选择。
总共从40篇文章中获得了301个枢纽基因。“核心”由28个枢纽基因组成（CCNB1、LPAR1、BGN、CXCL3、COL1A2、UBE2C、NMU、COL1A1、CXCL2、CXCL11、CDK1、TOP2A、AURKA、SST、CXCL5、MMP3、CCND1、TIMP1、CXCL8、CXCL1、CXCL12、MYC、CCNA2、GCG、GUCA2A、PAICS、PYY和THBS2），这些基因在不少于三篇文章中被提及，并且在癌症相关途径中具有临床意义。其中，有两个离散的簇富含趋化因子信号和细胞周期调节基因。BGN和TIMP1的高表达水平以及CCNB1、CXCL3、CXCL2、CXCL2和PAICS的低表达水平与CRC患者的不良总生存期相关。LPAR1、SST、CXCL12、GUCA2A和PYY等差异表达基因显示为下调，而BGN、CXCL3、UBE2C、NMU、CXCL11、CDK1、TOP2A、AURKA、MMP3、CCND1、CXCL1、MYC、CCNA2、PAICS在CRC中为上调基因。还发现MMP3、THBS2、TIMP1和CXCL12基因与转移性CRC相关。ONCO.IO中的网络分析表明，上游主调节因子RELA、STAT3、SOX2、FOXM1、SMAD3和NF-κB与“核心”枢纽基因相连。结论：所获得的结果对于揭示致病机制、优化治疗干预的细胞靶点选择以及转录组学预后和预测生物标志物的开发具有有用的基础信息。
