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. 2022 Oct 13;5(12):e202201551.
doi: 10.26508/lsa.202201551.

Whole-exome sequencing of epithelial ovarian carcinomas differing in resistance to platinum therapy

Viktor Hlaváč  1   2 , Petr Holý  1   2   3 , Radka Václavíková  1   2 , Lukáš Rob  4 , Martin Hruda  4 , Marcela Mrhalová  5 , Petr Černaj  6 , Jiří Bouda  6 , Pavel Souček  7   2
Affiliations

Whole-exome sequencing of epithelial ovarian carcinomas differing in resistance to platinum therapy

Viktor Hlaváč et al. Life Sci Alliance. .

Abstract

Epithelial ovarian carcinoma (EOC) is highly fatal because of the risk of resistance to therapy and recurrence. We performed whole-exome sequencing of blood and tumor tissue pairs of 50 patients with surgically resected EOC. Compared with sensitive patients, platinum-resistant patients had a significantly higher somatic mutational rate in <i>TP53</i> and lower in several genes from the Hippo pathway. We confirmed the pivotal role of somatic mutations in homologous recombination repair genes in platinum sensitivity and favorable prognosis of EOC patients. Implementing the germline homologous recombination repair profile significantly improved the prediction. In addition, distinct mutational signatures, for example, SBS6, and overall mutational load, somatic mutations in <i>PABPC1</i>, <i>PABPC3</i>, and <i>TFAM</i> co-segregated with the resistance status, high-grade serous carcinoma subtype, or overall survival of patients. We generated germline and somatic genetic landscapes of prognostically different subgroups of EOC patients for further follow-up studies focused on utilizing the observed associations in precision oncology.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1.
Figure 1.. Summary of the distribution of somatic variants in all epithelial ovarian carcinoma patients.
Footnotes: This figure shows the overall distribution of the variants. Only variants with predicted moderate or high protein impact are shown. (A) The classification of variants according to the functional effect with counts on the x-axis. (B) The type of the variants (TNV stands for trinucleotide variant; SNV, single-nucleotide variant; INS, insertion; DNV, dinucleotide variant; DEL, deletion). Both (A) and (B) have x-axis in the log10 scale to visualize also less frequent variants. (C) The type of nucleotide change. (D) The counts and distribution of the variants for the indicated samples; dashed line represents the median (163 variants per sample). (E) The box and whisker plots of the variant classes. Color coding corresponds to the classification of variants in top left. (F) Top 10 genes with the highest numbers of variants are shown on the x-axis, and percentages of patients harboring any variant in the indicated genes are shown next to the bars.
Figure S1.
Figure S1.. Oncoplot of genes with highest counts of variants in epithelial ovarian carcinoma patients.
Figure S2.
Figure S2.. Epithelial ovarian carcinoma sample portraits.
Figure 2.
Figure 2.. Co-bar plot of 10 genes with highest counts of variants with moderate or high impact in epithelial ovarian carcinoma patients divided by the platinum resistance status.
Figure 3.
Figure 3.. Lollipop plot of topology of TP53 alterations with moderate or high impact in platinum-resistant (upper part) and -sensitive (bottom part) epithelial ovarian carcinoma patients.
Figure S3.
Figure S3.. Lollipop plot of topology of TP53 alterations with high impact in epithelial ovarian carcinoma patients.
Figure S4.
Figure S4.. Co-occurrence plot of somatic alterations in epithelial ovarian carcinoma patients.
Figure S5.
Figure S5.. Maftools pathway analysis of mutated genes in epithelial ovarian carcinoma patients.
(A, B) all pathways, (B) the list of mutated genes in TP53 and Hippo pathways.
Figure 4.
Figure 4.. Enrichment analysis of top 10 canonical oncogenic pathways in patients divided by platinum resistance status.
Footnotes: Odds ratios of resistant versus sensitive patients by the Fisher test are on x-axis (log transformed) and pathway names on the y-axis. Gene number: total number of genes in each pathway.
Figure S6.
Figure S6.. Panther analysis of GO terms in epithelial ovarian carcinoma patients.
Figure S7.C
Figure S7.C. omparison of tumor mutation burden in subgroups of patients with The Cancer Genome Atlas datasets.
Figure S8.
Figure S8.. Comparison of cancer driver predictions in The Cancer Genome Atlas dataset and epithelial ovarian carcinoma patients analyzed in the current study.
Figure 5.
Figure 5.. Co-bar plot of mutated genes with highest counts of variants with moderate or high impact in patients divided by the epithelial ovarian carcinoma tumor subtype.
Figure 6.
Figure 6.. Kaplan–Meier plots of overall survival of patients.
(A, B, C, D) Patients divided by the median count of somatic variants passing all filters (A), gains with three copies (B), four or more copy number variations (C), and share of SBS6 signature (D).
Figure S9.
Figure S9.. Overall survival of epithelial ovarian carcinoma patients divided by the share of mutational signatures.
(A, B) Figure shows patients divided by the share of SBS10b (A) and SBS21 (B).
Figure S10.
Figure S10.. Overall survival of epithelial ovarian carcinoma patients divided by alterations in homologous recombination repair genes.
(A, B) Patients with somatic (A) alterations in any of the 16 homologous recombination repair genes (n = 7) and (B) somatic or germline alterations in BRCA1/2 genes (n = 14).
Figure 7.
Figure 7.. Kaplan–Meier plots of overall survival of patients divided by homologous recombination repair alterations.
Footnote: Patients divided by occurrence of somatic or germline variants in 16 homologous recombination repair genes with functional prediction classified as HIGH.
Figure S11.
Figure S11.. tudy power calculation.
S
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