Erceylan Ömer Faruk, Savaş Ayşe, Göv Esra
Department of Bioengineering, Faculty of Engineering, Adana Alparslan Türkeş Science and Technology University, Adana Turkey.
Turk J Biol. 2021 Apr 20;45(2):127-137. doi: 10.3906/biy-2010-39. eCollection 2021.
Tumor stroma interaction is known to take a crucial role in cancer growth and progression. In the present study, it was performed gene expression analysis of stroma samples with ovarian and breast cancer through an integrative analysis framework to identify common critical biomolecules at multiomics levels. Gene expression datasets were statistically analyzed to identify common differentially expressed genes (DEGs) by comparing tumor stroma and normal stroma samples. The integrative analyses of DEGs indicated that there were 59 common core genes, which might be feasible to be potential marks for cancer stroma targeted strategies. Reporter molecules (i.e. receptor, transcription factors and miRNAs) were determined through a statistical test employing the hypergeometric probability density function. Afterward, the tumor microenvironment protein-protein interaction and the generic network were reconstructed by using identified reporter molecules and common core DEGs. Through a systems medicine approach, it was determined that hub biomolecules, AR, GATA2, miR-124, TOR1AIP1, ESR1, EGFR, STAT1, miR-192, GATA3, COL1A1, in tumor microenvironment generic network. These molecules were also identified as prognostic signatures in breast and ovarian tumor samples via survival analysis. According to literature searching, GATA2 and TORYAIP1 might represent potential biomarkers and candidate drug targets for the stroma targeted cancer therapy applications.
肿瘤基质相互作用在癌症生长和进展中起着关键作用。在本研究中,通过综合分析框架对卵巢癌和乳腺癌的基质样本进行基因表达分析,以在多组学水平上识别常见的关键生物分子。通过比较肿瘤基质和正常基质样本,对基因表达数据集进行统计分析,以识别常见的差异表达基因(DEG)。对DEG的综合分析表明,有59个共同的核心基因,它们可能有望成为癌症基质靶向策略的潜在标志物。通过使用超几何概率密度函数的统计检验确定报告分子(即受体、转录因子和miRNA)。随后,利用鉴定出的报告分子和共同的核心DEG重建肿瘤微环境蛋白质-蛋白质相互作用和通用网络。通过系统医学方法,确定了肿瘤微环境通用网络中的枢纽生物分子AR、GATA2、miR-124、TOR1AIP1、ESR1、EGFR、STAT1、miR-192、GATA3、COL1A1。通过生存分析,这些分子在乳腺和卵巢肿瘤样本中也被鉴定为预后标志物。根据文献检索,GATA2和TOR1AIP1可能代表基质靶向癌症治疗应用的潜在生物标志物和候选药物靶点。