通过基于计算的方法鉴定结直肠癌相关的基因特征和转录因子

IF 0.5 Q4 GENETICS & HEREDITY
Shoufia Jabeen Mubarak, Hemamalini Vedagiri
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引用次数: 0

摘要

结直肠癌(Colorectal cancer, CRC)是世界范围内分布最广的恶性肿瘤,包括结肠癌和直肠癌。此外,不同的结直肠癌分期使病情的诊断复杂化。这项工作阐明了鉴定潜在mRNA-miRNA-lncRNA作为CRC 4期预后标志的想法。选择GSE41011 (mRNA)、GSE39833(miRNA)和GSE196006 (lncRNA)数据集。共检索到62种mrna、157种作为微rna靶点的mrna和101种用于lncRNAs的mrna。在I期和II期发现的突出基因为RGMB、MND1、CBX2、GDPD5、DUSP15、SPC25和SPP1。III期和IV期特异性基因为RNF183、PRMT3、NOTCH3、CPNE7、GDPD5、DSCC1、KLHL35和SPC25。在结直肠癌所有阶段发挥作用的基因有PRMT3、SERPINB7、RORA、ARHGAP30、BUB1、CXCL3、EGR1、PXN、PTGES2-AS1、LINC03040和hsa-miR-126、hsa-miR-1228。此外,监管措施也与结直肠癌的进展有关。此外,我们应用python加权基因共表达网络分析进一步证实了相关基因表达在CRC不同阶段的显著变化。这些相关基因从mRNA、miRNA和lncRNA数据集中预测了680,194和937个转录因子(tf)。随后,17个TFs被发现是与特定阶段的主要相互作用靶点,即阶段I - JUN、NR3C1、FOS、ESR1、GATA3;第二阶段- NANOG, GATA2;III期- MYC、CEBPA、MYCN、POU5F1、SOX17、OTX2、MYB、TFAP2C、PBX1和iv期- tal1。考虑到这一因素,这些发现将作为有效的候选基因标记,用于早期CRC阶段预测的治疗干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identification of gene signatures and transcription factors associated with colorectal cancer through computational based approach

Identification of gene signatures and transcription factors associated with colorectal cancer through computational based approach
Colorectal cancer (CRC), including colon and rectal cancer, is the most widespread malignant tumor worldwide. Besides, different staging groups in CRC complicate the diagnosis of disease conditions. This work explicates the idea of identifying the potential mRNA-miRNA-lncRNA as a prognostic signature for 4 stages of CRC. Datasets of GSE41011 (mRNA), GSE39833(miRNA) and GSE196006 (lncRNA) were chosen. In total, 62 mRNAs, 157 mRNAs as micro-RNA targets, and 101 mRNAs for lncRNAs were retrieved. Prominent genes were identified in stages I and II as RGMB, MND1, CBX2, GDPD5, DUSP15, SPC25 and SPP1. Genes specific for stages III and IV were RNF183, PRMT3, NOTCH3, CPNE7,GDPD5, DSCC1, KLHL35 and SPC25. Genes that play a role in all stages of CRC are PRMT3, SERPINB7, RORA, ARHGAP30, BUB1, CXCL3, EGR1, PXN, PTGES2-AS1, LINC03040 and hsa-miR-126, hsa-miR-1228.In addition, regulatory actions were also related to CRC progression. Moreover, we applied python weighted gene co-expression network analysis to further confirm the related gene expressions significantly altered in different stages of CRC. These correlated genes predicted 680,194 and 937 transcription factors (TFs) from mRNA, miRNA and lncRNA datasets. Subsequently, 17 TFs were revealed as a major interacting target with specific stages namely stage I - JUN, NR3C1, FOS, ESR1, GATA3; stage II - NANOG, GATA2; stage III - MYC, CEBPA, MYCN, POU5F1,SOX17, OTX2, MYB, TFAP2C, PBX1 and stage IV-TAL1.Taken to this factor, these findings will act as potent candidate gene signatures for therapeutic intervention at an early stage of CRC stage prediction.
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来源期刊
Human Gene
Human Gene Biochemistry, Genetics and Molecular Biology (General), Genetics
CiteScore
1.60
自引率
0.00%
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0
审稿时长
54 days
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