A Computational Approach to Predict the Role of Genetic Alterations in Methyltransferase Histones Genes With Implications in Liver Cancer.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Cancer Informatics Pub Date : 2023-01-01 DOI:10.1177/11769351231161480
Tania Isabella Aravena, Elizabeth Valdés, Nicolás Ayala, Vívian D'Afonseca
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引用次数: 1

Abstract

Histone methyltransferases (HMTs) comprise a subclass of epigenetic regulators. Dysregulation of these enzymes results in aberrant epigenetic regulation, commonly observed in various tumor types, including hepatocellular adenocarcinoma (HCC). Probably, these epigenetic changes could lead to tumorigenesis processes. To predict how histone methyltransferase genes and their genetic alterations (somatic mutations, somatic copy number alterations, and gene expression changes) are involved in hepatocellular adenocarcinoma processes, we performed an integrated computational analysis of genetic alterations in 50 HMT genes present in hepatocellular adenocarcinoma. Biological data were obtained through the public repository with 360 samples from patients with hepatocellular carcinoma. Through these biological data, we identified 10 HMT genes (SETDB1, ASH1L, SMYD2, SMYD3, EHMT2, SETD3, PRDM14, PRDM16, KMT2C, and NSD3) with a significant genetic alteration rate (14%) within 360 samples. Of these 10 HMT genes, KMT2C and ASH1L have the highest mutation rate in HCC samples, 5.6% and 2.8%, respectively. Regarding somatic copy number alteration, ASH1L and SETDB1 are amplified in several samples, while SETD3, PRDM14, and NSD3 showed a high rate of large deletion. Finally, SETDB1, SETD3, PRDM14, and NSD3 could play an important role in the progression of hepatocellular adenocarcinoma since alterations in these genes lead to a decrease in patient survival, unlike patients who present these genes without genetic alterations. Our computational analysis provides new insights that help to understand how HMTs are associated with hepatocellular carcinoma, as well as provide a basis for future experimental investigations using HMTs as genetic targets against hepatocellular carcinoma.

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预测甲基转移酶组蛋白基因遗传改变在肝癌中的作用的计算方法。
组蛋白甲基转移酶(hmt)包括一个亚类的表观遗传调控因子。这些酶的失调导致异常的表观遗传调控,通常在各种肿瘤类型中观察到,包括肝细胞腺癌(HCC)。这些表观遗传变化可能导致肿瘤发生过程。为了预测组蛋白甲基转移酶基因及其遗传改变(体细胞突变、体细胞拷贝数改变和基因表达改变)如何参与肝细胞腺癌过程,我们对肝细胞腺癌中存在的50个HMT基因的遗传改变进行了综合计算分析。生物学数据通过公共存储库获得,其中包括360例肝细胞癌患者的样本。通过这些生物学数据,我们在360个样本中鉴定出10个HMT基因(SETDB1, ASH1L, SMYD2, SMYD3, EHMT2, SETD3, PRDM14, PRDM16, KMT2C和NSD3)具有显著的遗传变异率(14%)。在这10个HMT基因中,KMT2C和ASH1L在HCC样本中的突变率最高,分别为5.6%和2.8%。在体细胞拷贝数改变方面,ASH1L和SETDB1在多个样本中被扩增,而SETD3、PRDM14和NSD3则表现出较高的大缺失率。最后,SETDB1、SETD3、PRDM14和NSD3可能在肝细胞腺癌的进展中发挥重要作用,因为这些基因的改变会导致患者生存期降低,而不像没有遗传改变的患者。我们的计算分析提供了新的见解,有助于了解hmt如何与肝细胞癌相关,并为未来使用hmt作为肝细胞癌遗传靶点的实验研究提供了基础。
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来源期刊
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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