A comprehensive analysis of somatic alterations in Chinese ovarian cancer patients

Abstract

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Figure 1

Mutational landscape of 65 ovarian cancer patients. The X-axis represents each case sample and the Y-axis represents each mutated gene. The bar graph above shows the tumor mutational burden (TMB) value of each sample, and the bar graph on the right shows the mutation frequency of each mutated gene in 65 samples. Green represents substitution/Indel mutations, red represents gene amplification mutations, blue represents gene homozygous deletion mutations, yellow represents fusion/rearrangement mutations, and purple represents truncation mutations.

Figure 2

Correlated analysis of mutated genes and clinical characteristics. (A) Correlation analysis of mutated genes and the age of patients; (B) Correlation analysis of mutated genes and tumor stage; (C) Correlation analysis of mutated genes and tumor differentiation; and (D) Correlation analysis of mutated genes and TMB. The X-axis shows the mutated genes and the Y-axis represent the mutational frequency of each gene. Fisher’s exact test was used to analyze significant differences and bonferroni correction were performed for multiple test correction. ns P > 0.05, * P < 0.05, ** P < 0.01, and *** P < 0.001.

Figure 3

Different molecular characteristics of high-grade serous ovarian cancer patients in China and Western countries. (A) Differences of somatic mutations between Chinese and Western patients. (B) Differences of germline mutations between Chinese and Western patients. The X-axis shows the mutated genes and the Y-axis represents the mutational frequency of genes. Fisher’s exact test was used to analyze significant differences. ns P > 0.05, ** P < 0.01, and *** P < 0.001.

Figure 4

Most frequent mutated genes in 6 platinum sensitive patients. Green represents SNV mutations, red represents gene amplification mutations, and yellow represents rearrangement. SD, stable disease; PD, progressive disease.