4.7 Article

The Clinical Significance of Genetic Variation in Ovarian Cancer

Journal

Publisher

MDPI
DOI: 10.3390/ijms241310823

Keywords

ovarian cancer; cancer progression; genomic profiles; tumor mutational burden; chromosomal alterations

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The study aims to comprehensively examine the nucleotide and chromosomal variation associated with the onset and progression of serous ovarian cancer. Computational and statistical methods were used to analyze the exome sequence profiles of genetic variants in 432 ovarian cancer patient samples. The results show that genetic variation is a significant contributor to ovarian cancer and can be used as a predictor of tumor aggressiveness and resistance to chemotherapy.
Genetic variation is a well-known contributor to the onset and progression of cancer. The goal of this study is to provide a comprehensive examination of the nucleotide and chromosomal variation associated with the onset and progression of serous ovarian cancer. Using a variety of computational and statistical methods, we examine the exome sequence profiles of genetic variants present in the primary tumors of 432 ovarian cancer patient samples to compute: (1) the tumor mutational burden for all genes and (2) the chromosomal copy number alterations associated with the onset/progression of ovarian cancer. Tumor mutational burden is reduced in the late vs. early stages, with the highest levels being associated with loss-of-function mutations in DNA-repair genes. Nucleotide variation and copy number alterations associated with known cancer driver genes are selectively favored over ovarian cancer development. The results indicate that genetic variation is a significant contributor to the onset and progression of ovarian cancer. The measurement of the relative levels of genetic variation associated with individual ovarian cancer patient tumors may be a clinically valuable predictor of potential tumor aggressiveness and resistance to chemotherapy. Tumors found to be associated with high levels of genetic variation may help in the clinical identification of high-risk ovarian cancer patients who could benefit from more frequent monitoring.

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