Iacobas Dumitru A, Mgbemena Victoria E, Iacobas Sanda, Menezes Kareena M, Wang Huichen, Saganti Premkumar B
Personalized Genomics Laboratory, CRI Center for Computational Systems Biology, Roy G Perry College of Engineering, Prairie View A&M University, Prairie View, TX 77446, USA.
Department of Biology, MD and S Brailsford College of Arts and Sciences, Prairie View A&M University, Prairie View, TX 77446, USA.
Cancers (Basel). 2020 Dec 8;12(12):3678. doi: 10.3390/cancers12123678.
Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma samples were analyzed from the genomic fabric paradigm (GFP) perspective to identify the best targets for gene therapy. GFP considers the transcriptome as a multi-dimensional mathematical object constrained by a dynamic set of expression controls and correlations among genes. Every gene in the chest wall metastasis, two distinct cancer nodules, and the surrounding normal tissue of the right kidney was characterized by three independent measures: average expression level, relative expression variation, and expression correlation with each other gene. The analyses determined the cancer-induced regulation, control, and remodeling of the chemokine and vascular endothelial growth factor (VEGF) signaling, apoptosis, basal transcription factors, cell cycle, oxidative phosphorylation, renal cell carcinoma, and RNA polymerase pathways. Interestingly, the three cancer regions exhibited different transcriptomic organization, suggesting that the gene therapy should not be personalized only for every patient but also for each major cancer nodule. The gene hierarchy was established on the basis of gene commanding height, and the gene master regulators , and were identified in each profiled region. We delineated the molecular mechanisms by which overexpression and silencing would selectively affect the cancer cells with little consequences for the normal cells.
从基因组结构范式（GFP）的角度分析了手术切除的转移性透明细胞肾细胞癌样本的已发表转录组数据，以确定基因治疗的最佳靶点。GFP将转录组视为一个多维数学对象，受一组动态的表达控制和基因间相关性的约束。通过三个独立指标对胸壁转移灶、两个不同的癌结节以及右肾周围正常组织中的每个基因进行了表征：平均表达水平、相对表达变异以及与其他每个基因的表达相关性。分析确定了趋化因子和血管内皮生长因子（VEGF）信号传导、细胞凋亡、基础转录因子、细胞周期、氧化磷酸化、肾细胞癌和RNA聚合酶途径的癌症诱导调节、控制和重塑。有趣的是，这三个癌区表现出不同的转录组组织，这表明基因治疗不仅应该针对每个患者进行个性化定制，还应该针对每个主要癌结节进行个性化定制。基于基因指挥高度建立了基因层次结构，并在每个分析区域中鉴定了基因主调控因子 、 和 。我们阐述了 过表达和 沉默将如何选择性地影响癌细胞而对正常细胞几乎没有影响的分子机制。
