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

Research Paper

Identification of the Mutational Landscape of Gynecological Malignancies

Suresh Chava, Romi Gupta

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

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Chava S, Gupta R. Identification of the Mutational Landscape of Gynecological Malignancies. J Cancer 2020; 11(16):4870-4883. doi:10.7150/jca.46174. Available from http://www.jcancer.org/v11p4870.htm

File import instruction


Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: gynecological malignancies, TCGA, Oncomine, biomarker, therapeutic