Comprehensive Gene Mutation Profiling of Circulating Tumor DNA in Ovarian Cancer: Its Pathological and Prognostic Impact

• Published in: Cancers 2020-11, Vol.12 (11), p.3382
• Main Authors: Noguchi, Tomoko, Iwahashi, Naoyuki, Sakai, Kazuko, Matsuda, Kaho, Matsukawa, Hitomi, Toujima, Saori, Nishio, Kazuto, Ino, Kazuhiko
• Format: Article
• Language: English
• Subjects: Adenomatous polyposis coli; Biopsy; Cancer therapies; Chemotherapy; Colorectal cancer; Deoxyribonucleic acid; DNA; DNA fingerprinting; DNA sequencing; Epidermal growth factor receptors; Gene mutations; Genes; Genetic aspects; Gynecology; Health aspects; Medical prognosis; Metastasis; Methods; Mutation; Nucleotide sequencing; Ovarian cancer; p53 Protein; Patients; Point mutation; Surgery
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers12113382

Liquid biopsies from circulating tumor DNA (ctDNA) have been employed recently as a non-invasive diagnostic tool for detecting cancer-specific gene mutations. Here, we show the comprehensive gene mutation profiles of ctDNA in 51 patients with different histological subtypes of stage I–IV ovarian cancer, and their association with clinical outcomes. The ctDNA extracted from pre-treatment patients’ plasma were analyzed using Cancer Personalized Profiling by Deep Sequencing targeting 197 genes. Of 51 patients, 48 (94%) showed one or more non-synonymous somatic mutations, including TP53 (37.3%), APC (17.6%), KRAS (15.7%), EGFR (13.7%), MET (11.8%), PIK3CA (11.8%), NPAP1 (11.8%), and ALK (9.8%). The most frequently mutated genes were as follows: TP53 in high-grade serous carcinoma (66.7%), APC in clear cell carcinoma (30.8%), PIK3CA in endometrioid carcinoma (40%), and KRAS in mucinous carcinoma (66.7%). Higher cell-free (cf)DNA concentration significantly correlated with worse progression-free survival (PFS) in all patients as well as stage III–IV patients (p = 0.01 and 0.005, respectively). Further, patients with any pathogenic mutations showed significantly worse PFS (p = 0.048). Blood tumor mutational burden detected from ctDNA did not significantly correlate with the histological subtypes or survival. Collectively, clinico-genomic profiles of individual ovarian cancer patients could be identified using ctDNA and may serve as a useful prognostic indicator. These findings suggest that ctDNA-based gene profiling might help in establishing personalized therapeutic strategies.