Molecular profiling reveals novel therapeutic targets and clonal evolution in ovarian clear cell carcinoma

Abstract

Background: Ovarian clear cell carcinoma (OCCC) has a disproportionately high incidence among women in East Asia. Patients diagnosed with OCCC tend to experience worse clinical outcomes than those with high-grade serous carcinoma (HGSC) at advanced stages. The unfavorable prognosis of OCCC can be partly attributed to its frequent resistance to conventional chemotherapy. Within a precision medicine framework, we sought to provide a comprehensive molecular characterization of OCCC using whole-exome sequencing to uncover potential molecular targets that may inform novel therapeutic strategies.

Methods: We performed whole-exome sequencing analysis on tumor-normal paired samples from 102 OCCC patients. This comprehensive genomic characterization of a substantial cohort of OCCC specimens was coupled with an analysis of clonal progression.

Results: On analyzing 102 OCCC samples, ARID1A (67%) and PIK3CA (49%) emerged as the most frequently mutated driver genes. We identified tier 1 or 2 clinically actionable molecular targets in 40% of cases. This included DNA mismatch repair deficiency (n = 1), as well as BRCA2 (n = 1), PIK3CA (n = 36), KRAS^G12C (n = 1), and ATM (n = 4) mutations. Furthermore, 45% of OCCC samples displayed ARID1A biallelic loss. Interestingly, we identified previously unreported mutations in the 5' untranslated region of the TERT gene that harbored an adverse prognostic significance. Clock-like mutational processes and activated APOBECs were major drivers of somatic point mutations. Mutations arising from DNA mismatch repair deficiency were uncommon. Reconstruction of clonal evolution revealed that early genetic events likely driving tumorigenesis included mutations in the ARID1A, PIK3CA, TERT, KRAS, and TP53 genes.

Conclusions: Our study provides a comprehensive characterization of the genomic landscape and clonal evolution in OCCC within a substantial cohort. These findings unveil potentially actionable molecular alterations that could be leveraged to develop targeted therapies.

Keywords: TERT mutation; Clinical actionability; Clonal evolution; Mutational signature; Ovarian clear cell carcinoma; Whole-exome sequencing.

Fig. 1

Study flowchart. Patients diagnosed with ovarian clear cell carcinoma were retrospectively enrolled based on the registry data. The Systemized Nomenclature of Medicine (SNOMED) codes 87,000-A-M83103, 87,000-B-M83103, and 87,000-C-M83103 were used to identify the relevant cases. FFPE, formalin-fixed paraffin-embedded; WES, whole-exome sequencing

Fig. 2

Genomic landscape of 102 ovarian clear cell carcinoma samples. The rows represent the following data: counts of non-silent mutations, genome instability index, tumor stage, genome doubling (GD) status, mutational signature (MS) group, membership in somatic copy number alteration (SCNA) cluster, and non-silent somatic mutations in established cancer-driver genes (mutated in five or more tumors), as well as mutations in the TERT upstream region. Supplementary Fig. 1 illustrates mutations in known cancer-driver genes at lower frequencies

Fig. 3

Types and frequencies of mutations in six driver genes: (A) ARID1A, (B) PIK3CA, (C) KRAS, (D) PPP2R1A, (E) ATM, and (F) TP53 gene. Selected mutation types were annotated accordingly. Mutations that fall within the tier 1 or 2 clinical actionability are emphasized using asterisk (*) markings. G Loss of tumor suppressor genes in the OCCC tumors. Biallelic loss is defined as having either of the following conditions: 1) double truncating mutations with or without loss-of-heterozygosity (LOH), 2) single truncating mutation with LOH, or 3) complete copy number loss (copy number of zero). Uniallelic loss is defined as having either of the following conditions: 1) single truncating mutation without LOH, 2) Copy number loss without truncating mutation

Fig. 4

Clinical actionability of mutations identified in ovarian clear cell carcinoma specimens. Tier 1 alterations are those with direct clinical implications for a specific tumor type, including therapies approved by the FDA. Tier 2 includes alterations for which FDA-approved therapies exist for other tumor types, as well as investigational therapies, consensus findings from meta-analyses, preclinical studies, and case reports

Fig. 5

TERT upstream mutations identified in ovarian clear cell carcinoma samples. A Classification and prevalence of TERT upstream mutations. B The presence 5’ UTR mutations was associated with significantly worse survival than lack of an upstream mutation or a mutation in the promoter region, as shown in both a univariate (HR = 4.49 versus wild type, p = 0.011) and a multivariable Cox proportional hazards analysis (HR = 3.86, versus wild type, p = 0.025, Supplementary Table S5). UTR, untranslated region; CDS, coding sequence

Fig. 6

A Single-base substitution (SBS) mutation signature activities across all 102 OCCCs. Mutation counts and the proportions of signatures contributing to the mutational spectrum of each tumor were shown in the top two panels. The bottom panel indicates tumors classified by the following “mutational signature groups”: (1) DNA mismatch repair deficiency (OCCC-112), (2) APOBEC-dominant (OCCC-83, 128, 337, and 346). B Genome-wide somatic copy number alteration (SCNA) patterns observed in the OCCC cohort

Fig. 7

Driver mutation timing estimates in ovarian clear cell carcinoma specimens. A Based on the timing of somatic mutations relative to somatic copy number change at the same locus, we categorized clonal mutation events as “early clonal” (occurring before the copy-number gain), “untimed clonal” (inability to determine the timing relative to the somatic copy-number gain), and “late clonal” (occurring after the somatic-copy-number gain). B Driver genes were grouped according to the timing and clonality of the identified somatic mutations. Color bars to the right of each gene symbol indicate the proportions of early clonal (dark blue), untimed clonal (light blue), late clonal (orange), and subclonal (dark orange) mutations for each gene. The values displayed to the right of the bar graph indicate the number of clonal mutations and the total mutation count within each specified gene. Genes categorized as “early clonal” are identified as potential key factors in the initiation of OCCC