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妇科恶性肿瘤突变图谱的鉴定

Identification of the Mutational Landscape of Gynecological Malignancies.

作者信息

Chava Suresh, Gupta Romi

机构信息

Department of Biochemistry and Molecular Genetics, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.

出版信息

J Cancer. 2020 Jun 8;11(16):4870-4883. doi: 10.7150/jca.46174. eCollection 2020.

Abstract

Cancer is a complex disease that arises from the accumulation of multiple genetic and non-genetic changes. Advances in sequencing technologies have allowed unbiased and global analysis of patient-derived tumor samples and the discovery of genetic and transcriptional changes in key genes and oncogenic pathways. That in turn has facilitated a better understanding of the underlying causes of cancer initiation and progression, resulting in new therapeutic targets. In our study, we have analyzed the mutational landscape of gynecological malignancies using datasets from The Cancer Genome Atlas (TCGA). We have also analyzed Oncomine datasets to establish the impact of their alteration on disease recurrence and survival of patients. In this study, we analyzed a series of different gynecological malignancies for commonly occurring genetic and non-genetic alterations. These studies show that white women have higher incidence of gynecological malignancies. Furthermore, our study identified 16 genes that are altered at a frequency >10% among all of the gynecological malignancies and tumor suppressor TP53 is the most altered gene in these malignancies (>50% of the cases). The top 16 genes fall into the categories of either tumor suppressor or oncogenes and a subset of these genes are associated with poor prognosis, some affecting recurrence and survival of ovarian cancer patients. In sum, our study identified 16 major genes that are broadly mutated in a large majority of gynecological malignancies and in some cases predict survival and recurrence in patients with gynecological malignancies. We predict that the functional studies will determine their relative role in the initiation and progression of gynecological malignancies and also establish if some of them represents drug targets for anti-cancer therapy.

摘要

癌症是一种复杂的疾病,它由多种遗传和非遗传变化的积累而引发。测序技术的进步使得对患者来源的肿瘤样本进行无偏见的全面分析成为可能,并发现关键基因和致癌途径中的遗传和转录变化。这反过来又有助于更好地理解癌症发生和发展的潜在原因,从而产生新的治疗靶点。在我们的研究中,我们使用来自癌症基因组图谱(TCGA)的数据集分析了妇科恶性肿瘤的突变图谱。我们还分析了Oncomine数据集,以确定它们的改变对疾病复发和患者生存的影响。在这项研究中,我们分析了一系列不同的妇科恶性肿瘤,以寻找常见的遗传和非遗传改变。这些研究表明,白人女性妇科恶性肿瘤的发病率更高。此外,我们的研究确定了16个基因,在所有妇科恶性肿瘤中,其改变频率>10%,肿瘤抑制基因TP53是这些恶性肿瘤中改变最多的基因(>50%的病例)。排名前16的基因分为肿瘤抑制基因或癌基因类别,其中一部分基因与预后不良有关,一些影响卵巢癌患者的复发和生存。总之,我们的研究确定了16个主要基因,它们在大多数妇科恶性肿瘤中广泛突变,在某些情况下可预测妇科恶性肿瘤患者的生存和复发。我们预测,功能研究将确定它们在妇科恶性肿瘤发生和发展中的相对作用,并确定其中一些基因是否可作为抗癌治疗的药物靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99c7/7330690/0ad813b7c5ab/jcav11p4870g001.jpg

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