Colorectal cancer (CRC) is a major cause of cancer-associated deaths worldwide. Recently, oral administration of resveratrol (trans-3,5,4'-trihydroxystilbene) has been reported to significantly reduce tumor proliferation in colorectal cancer patients, however, with little specific information on functional connections. The pathogenesis and development of colorectal cancer is a multistep process that can be categorized using three phenotypic pathways, respectively, chromosome instability (CIN), microsatellite instability (MSI), and CpG island methylator (CIMP). Targets of resveratrol, including a high-affinity binding protein, quinone reductase 2 (QR2), have been identified with little information on disease association. We hypothesize that the relationship between resveratrol and different CRC etiologies might be gleaned using publicly available databases. A web-based microarray gene expression data-mining platform, Oncomine, was selected and used to determine whether QR2 may serve as a mechanistic and functional biotarget within the various CRC etiologies. We found that QR2 messenger RNA (mRNA) is overexpressed in CRC characterized by CIN, particularly in cells showing a positive KRAS (Kirsten rat sarcoma viral oncogene homolog) mutation, as well as by the MSI but not the CIMP phenotype. Mining of Oncomine revealed an excellent correlation between QR2 mRNA expression and certain CRC etiologies. Two resveratrol-associated genes, adenomatous polyposis coli (APC) and TP53, found in CRC were further mined, using cBio portal and Colorectal Cancer Atlas which predicted a mechanistic link to exist between resveratrol→QR2/TP53→CIN. Multiple web-based data mining can provide valuable insights which may lead to hypotheses serving to guide clinical trials and design of therapies for enhanced disease prognosis and patient survival. This approach resembles a BioGPS, a capability for mining web-based databases that can elucidate the potential links between compounds to provide correlations of these interactions with specific diseases.

译文

结直肠癌 (CRC) 是全球癌症相关死亡的主要原因。最近,据报道口服白藜芦醇 (trans-3,5,4 '-三羟基二苯乙烯) 可显着降低结直肠癌患者的肿瘤增殖,然而,关于功能连接的具体信息很少。大肠癌的发病机理和发展是一个多步骤的过程,可以使用三种表型途径进行分类,分别是染色体不稳定性 (CIN),微卫星不稳定性 (MSI) 和CpG岛甲基化因子 (CIMP)。白藜芦醇的靶标,包括高亲和力结合蛋白醌还原酶2 (QR2),已被确定,但有关疾病关联的信息很少。我们假设白藜芦醇与不同CRC病因之间的关系可能是使用公开可用的数据库收集的。选择了基于web的微阵列基因表达数据挖掘平台Oncomine,并将其用于确定QR2是否可以作为各种CRC病因中的机械和功能性生物目标。我们发现QR2信使RNA (mRNA) 在以CIN为特征的CRC中过表达,特别是在显示KRAS (Kirsten大鼠肉瘤病毒癌基因同源物) 突变阳性的细胞中,以及MSI但不是CIMP表型。对Oncomine的挖掘显示QR2 mRNA表达与某些CRC病因之间具有极好的相关性。使用cBio portal和结直肠癌图谱,进一步挖掘了在CRC中发现的两个与白藜芦醇相关的基因,即腺瘤性息肉病大肠杆菌 (APC) 和TP53,这预测了白藜芦醇 → QR2/TP53 → cin之间存在机械联系。基于web的多个数据挖掘可以提供有价值的见解,这些观点可能会导致指导临床试验和治疗方法设计的假设,以提高疾病的预后和患者的生存率。这种方法类似于BioGPS,这是一种挖掘基于web的数据库的功能,可以阐明化合物之间的潜在联系,以提供这些相互作用与特定疾病的相关性。

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