CHEK2p.I157T Mutation Is Associated with Increased Risk of Adult-Type Ovarian Granulosa Cell Tumors

Simple Summary Granulosa cell tumors of the ovary represent a distinct subset of ovarian cancers typically characterized by hormonal disbalance, slow disease progression, and late recurrence years after surgical removal of the primary tumor. Risk factors associated with development of these rare tumors have not yet been established. In this study, we identified an association between increased risk of developing adult-type granulosa cell tumors (AGCTs) and a specific germline mutation in the CHEK2 gene. Our findings further support the relevance of this deleterious mutation in the increased risk of various cancer types, and opens a new avenue that can be exploited for future development of CHEK2-targeted preventive and therapeutic interventions directed at AGCTs. Abstract Pathogenic germline mutations c.1100delC and p.I157T in the CHEK2 gene have been associated with increased risk of breast, colon, kidney, prostate, and thyroid cancers; however, no associations have yet been identified between these two most common European founder mutations of the CHEK2 gene and ovarian cancers of any type. Our review of 78 female heterozygous carriers of these mutations (age > 18 years) found strikingly higher proportion of adult-type granulosa cell tumors of the ovary (AGCTs) among ovarian cancers that developed in these women (~36%) compared to women from the general population (1.3%). Based on this finding, we performed a cross-sectional study that included 93 cases previously diagnosed with granulosa cell tumors, refined and validated their AGCT diagnosis through an IHC study, determined their status for the two CHEK2 mutations, and compared the prevalence of these mutations in the AGCT cases and reference populations. The prevalence ratios for the p.I157T mutation in the AGCT group relative to the global (PR = 26.52; CI95: 12.55–56.03) and European non-Finnish populations (PR = 24.55; CI95: 11.60–51.97) support an association between the CHEK2p.I157T mutation and AGCTs. These rare gynecologic tumors have not been previously associated with known risk factors and genetic predispositions. Furthermore, our results support the importance of the determination of the FOXL2p.C134W somatic mutation for accurate diagnosis of AGCTs and suggest a combination of IHC markers that can serve as a surrogate diagnostic marker to infer the mutational status of this FOXL2 allele.


Introduction
Checkpoint kinase 2 is a serine/threonine protein kinase encoded by the CHEK2 gene involved in cellular responses to genotoxic stress. Depending on the cell context and the DNA damage extent, responses mediated by the CHEK2 kinase can include cell cycle Hematoxylin-eosin slides from all cases were reviewed to confirm the diagnosis of AGCT. The tumors showed a variety of histology patterns. Diffuse growth pattern was the most common, but other patterns, including trabecular, insular, microfollicular (with the presence of rare Call-Exner bodies), and macrofollicular patterns were also present among these cases. Tumor cells featured scant cytoplasm and uniform oval nuclei with irregular nuclear membranes and nuclear grooves. Luteinization was present in rare cases ( Figure 1). In some cases, AGCTs were distinguished from fibromas/thecomas using reticulin stain. The immunohistochemical study was performed using the Ventana Benchmark XT automated stainer (Ventana Medical System, Inc., Tucson, AZ, USA). The following primary antibodies were used: Anti-FOXL2 (polyclonal, Invitrogen, Waltham, MA, USA, dilution 1:100), Anti-inhibin alpha (clone R1, CellMarque, Rocklin, CA, USA, ready-to-use), Anti-calretinin (SP65, Ventana, Tucson, AZ, USA, ready-to-use), and anti-SF1 (EPR19744, AbCam, Cambridge, UK, dilution 1:100), using either DAB/HRP (anti-FOXL2, anti-SF1), or Fast Red/ALP (anti-inhibin α, anti-calretinin) as a chromogen/reporter enzyme combination. Appropriate positive and negative controls were used. Immunostaining in >5% of cells was considered positive, and immunostaining in ≤5% of cells was considered negative. Positive results were recorded as focal (staining in >5% and ≤50% of tumor cells) or diffuse (>50%) patterns ( Figure 2). The immunohistochemical study was performed using the Ventana Benchmark XT automated stainer (Ventana Medical System, Inc., Tucson, AZ, USA). The following primary antibodies were used: Anti-FOXL2 (polyclonal, Invitrogen, Waltham, MA, USA, dilution 1:100), Anti-inhibin alpha (clone R1, CellMarque, Rocklin, CA, USA, ready-to-use), Anti-calretinin (SP65, Ventana, Tucson, AZ, USA, ready-to-use), and anti-SF1 (EPR19744, AbCam, Cambridge, UK, dilution 1:100), using either DAB/HRP (anti-FOXL2, anti-SF1), or Fast Red/ALP (antiinhibin α, anti-calretinin) as a chromogen/reporter enzyme combination. Appropriate positive and negative controls were used. Immunostaining in >5% of cells was considered positive, and immunostaining in ≤5% of cells was considered negative. Positive results were recorded as focal (staining in >5% and ≤50% of tumor cells) or diffuse (>50%) patterns ( Figure 2). DNA extraction DNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue was extracted using QIAsymphony DSP DNA Mini Kit (Qiagen, Hilden, Germany) on an automated extraction system (QIAsymphony SP, Qiagen) according to the manufacturer's supplementary protocol for FFPE samples (Purification of genomic DNA from FFPE tissue using the QIAamp DNA FFPE Tissue Kit and Deparaffinization Solution). Concentration and purity of isolated DNA were determined using NanoDrop ND 1000 (NanoDrop Technologies Inc., Wilmington, DE, USA). DNA integrity was examined by amplification of control genes in a multiplex PCR [11].

Analysis of FOXL2 and CHEK2 mutations
The analyses of hot spot mutation c.402C>G, (p.C134W) of the FOXL2 gene (NCBI RefSeq: NM_023067.4) and two hotspot mutations c.470T>C, (p.I157T) and c.1100delC, (p.T367fs) of the CHEK2 gene (NCBI RefSeq: NM_007194.4) were performed using PCR and Sanger sequencing. PCR reactions were used for amplification of relevant regions of CHEK2 (part of exon 4 containing c.470T>C; part of exon 11 with c.1100delC) and FOXL2 (part of exon 1 containing c.402C>G). Briefly, 100 ng DNA was added to a reaction mixture consisting of 12.5 µL of FastStart PCR Master (Roche Diagnostic, Mannheim, Germany), 10 pmol of forward and reverse primers (Appendix A, Table A1) and distilled water up to 25 µL. The amplification program: initial denaturation (95 °C for 9 min), followed by 40 cycles of denaturation (95 °C for 1 min), annealing (56 °C (CHEK2 c.470) or 60 °C (FOXL2 and CHEK2 c.1100) for 1 min) and extension (72 °C for 1 min). The program was terminated by incubation at 72 °C for 7 min. The PCR products were separated by electrophoresis on a 2% agarose gel. Successfully amplified PCR products selected for sequencing analysis were purified with magnetic particles Agencourt ® AMPure ® (Agencourt Bioscience Corporation, A Beckman Coulter Company, Beverly, MA, USA), according to the manufacturer's protocol, and both sides were sequenced using the Big Dye Terminator Sequencing kit (Applied Biosystems, Waltham, MA, USA) on an automated sequencer ABI Prism 3130xl (Applied Biosystems) at a constant voltage of 13.2 kV for 20 min. The results were analyzed using Geneious 6.1.6 analysis software (Geneious) or visually inspected. DNA sequences were compared to the reference sequence by the online program BLAST [12]. DNA extraction DNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue was extracted using QIAsymphony DSP DNA Mini Kit (Qiagen, Hilden, Germany) on an automated extraction system (QIAsymphony SP, Qiagen) according to the manufacturer's supplementary protocol for FFPE samples (Purification of genomic DNA from FFPE tissue using the QI-Aamp DNA FFPE Tissue Kit and Deparaffinization Solution). Concentration and purity of isolated DNA were determined using NanoDrop ND 1000 (NanoDrop Technologies Inc., Wilmington, DE, USA). DNA integrity was examined by amplification of control genes in a multiplex PCR [11].

Analysis of FOXL2 and CHEK2 mutations
The analyses of hot spot mutation c.402C>G, (p.C134W) of the FOXL2 gene (NCBI RefSeq: NM_023067.4) and two hotspot mutations c.470T>C, (p.I157T) and c.1100delC, (p.T367fs) of the CHEK2 gene (NCBI RefSeq: NM_007194.4) were performed using PCR and Sanger sequencing. PCR reactions were used for amplification of relevant regions of CHEK2 (part of exon 4 containing c.470T>C; part of exon 11 with c.1100delC) and FOXL2 (part of exon 1 containing c.402C>G). Briefly, 100 ng DNA was added to a reaction mixture consisting of 12.5 µL of FastStart PCR Master (Roche Diagnostic, Mannheim, Germany), 10 pmol of forward and reverse primers (Appendix A, Table A1) and distilled water up to 25 µL. The amplification program: initial denaturation (95 • C for 9 min), followed by 40 cycles of denaturation (95 • C for 1 min), annealing (56 • C (CHEK2 c.470) or 60 • C (FOXL2 and CHEK2 c.1100) for 1 min) and extension (72 • C for 1 min). The program was terminated by incubation at 72 • C for 7 min. The PCR products were separated by electrophoresis on a 2% agarose gel. Successfully amplified PCR products selected for sequencing analysis were purified with magnetic particles Agencourt ® AMPure ® (Agencourt Bioscience Corporation, A Beckman Coulter Company, Beverly, MA, USA), according to the manufacturer's protocol, and both sides were sequenced using the Big Dye Terminator Sequencing kit (Applied Biosystems, Waltham, MA, USA) on an automated sequencer ABI Prism 3130xl (Applied Biosystems) at a constant voltage of 13.2 kV for 20 min. The results were analyzed using Geneious 6.1.6 analysis software (Geneious) or visually inspected. DNA sequences were compared to the reference sequence by the online program BLAST [12].

Data analysis and statistics
Cases with focal or diffuse expression of FOXL2, inhibin, calretinin, or SF1 were classified as positive for these IHC markers. The Genome Aggregation Database (gnomAD) [13] was used for retrieval of prevalence of the CHEK2 p.I157T mutation in three different reference populations. This database aggregates and harmonizes exome and genome sequencing data for 141,456 (v2.1) or 76,156 (v3.1) unrelated individuals from various disease-specific and population genetic studies [14]. Confidence intervals of 95% for proportions were determined using Wilson's procedure with a correction for continuity implemented in VassarStats [15]. Association between status of the two germline CHEK2 mutations and group membership (AGCT vs. population reference groups) was assessed from prevalence ratios (PRs) determined using the OpenEpi tool version 3.01 updated 4 June 2013 [16,17]. Confidence intervals of 95% for PRs were approximated by a Taylor series, and the significance of difference from PR = 1 was tested using the Mid-p exact method. The Kaplan--Meier method implemented in GraphPad Prism version 8.0.1 for Windows (GraphPad Software, LaJolla, CA, USA) was used to analyze the time to event (age at AGCT diagnosis) data. Difference between groups of CHEK2 mutation carriers and non-carriers were assessed using the Gehan-Breslow-Wilcoxon test, which does not require a consistent hazard ratio and gives more weight to the diagnosis of AGCT at an earlier age. Performance of IHC markers for diagnosis of FOXL2 p.C134W AGCTs was characterized by sensitivity, specificity, and Youden's J index that summarizes the performance of markers giving equal weight to false positive and false negative values. The 95% confidence intervals for sensitivity and specificity were computed by the Wilson-Brown method using GraphPad Prism version 8.0.1. Youden's J indices, including CI95 intervals, were calculated using the Two-Way Contingency Table Analysis implemented in StatPages [18].
The FOXL2 mutation p.C134W (c.402C>G) was determined in 69 cases and found in 58 cases (57 cases with heterozygous and one with homozygous genotype), which account for 84.1% (CI95: 72.8-91.4%) of cases with determined status of this mutation. A total of 11 cases were negative and the status of the FOXL2 could not be determined in 24 cases (Table 1).

Prevalence of CHEK2 p.I157T Mutation Is Increased among Adult GCT Patients
The CHEK2 c.1100delC mutation was found in a single case of a primary ovarian tumor with the FOXL2 p.C134W somatic mutation, morphologically consistent with AGCT and positive by IHC for inhibin, FOXL2, calretinin, and SF1. However, this mutation was not further considered in the context of its association with AGCTs due to an insufficient number of cases in our group.
For the analysis of the association of CHEK2 founder mutations with GCTs, we only included in the analysis 58 cases with tumors positive for the FOXL2 mutation p.C134W, which is pathognomonic for adult-type GCTs ( Table 1).
The group with the FOXL2 p.C134W mutation displays higher median age at diagnosis than the group negative for this mutation (FOXL2 wild-type). In addition, our FOXL2 p.C134W -positive group includes only cases with a minimum age at diagnosis of 28 years, while the FOXL2 wild-type group includes also women diagnosed at a younger age. As a result, the FOXL2 p.C134W -positive group largely represents cases of bona fide adult-type ovarian granulosa cell tumor (AGCTs). Among the 46 cases with known status for the CHEK2 p.I157T germline mutation, six patients were found to be carriers of this mutation ( Our results indicate significantly higher prevalence of the CHEK2 p.I157T mutation among patients with AGCTs than in the global population (p = 1.2 × 10 −7 ), the European non-Finnish population (p = 1.9 × 10 −7 ), or the European Finnish population (p = 0.0011). Prevalence ratios for the p.I157T mutation in the AGCT group were PR = 26.52 (CI95:12.55-56.03), PR = 24.55 (CI95: 11.60-51.97), and PR = 5.23 (CI95: 2.47-11.06) relative to the global, European non-Finnish, and European Finnish populations, respectively. Of note, this analysis compared the p.I157 mutation prevalence in our GCT group with different reference populations from the gnomAD database v2.1.
Carriers of the CHEK2 p.I157T mutation also displayed a lower median age at diagnosis of the AGCT compared to non-carriers (54 years vs. 60 years). Nevertheless, the difference between the groups was not significant (Gehan-Breslow-Wilcoxon test p = 0.4288). However, the log-rank hazard ratio HR = 1.40 (CI95: 0.52-3.78) between the groups with and without the CHEK2 p.I157T mutation is inconclusive, and the Kaplan-Meier analysis does not support the proportional hazards model (Figure 3). When both CHEK2 founder mutations are considered, mutations carriers' median age at diagnosis is 43 years and thus

Performance of IHC Markers for Detection of Adult GCTs
The  Table 1).
The potential of the four IHC markers to serve as surrogate markers for the FOXL2 p.C134W mutation was assessed individually across 69 specimens with a known mutation status of this FOXL2 allele. The highest sensitivity was found for FoxL2 immunoexpression (~95%) and the highest specificity for inhibin and calretinin (~46%) ( Table 2). FOXL2 immunoexpression was found to be in fair agreement with FOXL2 p.C134W mutation status (~84% agreement; Cohen's kappa = 0.271; CI95: −0.037-0.579).   Table 1).
The potential of the four IHC markers to serve as surrogate markers for the FOXL2 p.C134W mutation was assessed individually across 69 specimens with a known mutation status of this FOXL2 allele. The highest sensitivity was found for FoxL2 immunoexpression (~95%) and the highest specificity for inhibin and calretinin (~46%) ( Table 2). FOXL2 immunoexpression was found to be in fair agreement with FOXL2 p.C134W mutation status (~84% agreement; Cohen's kappa = 0.271; CI95: −0.037-0.579). Association between the expression of all the four IHC markers and FOXL2 p.C134W mutational status was also examined by binary logistic regression. The strongest predictor of FOXL2 mutation status was FOXL2 immunoexpression, recording an odds ratio of 12.44, controlling for immunoexpression of inhibin, calretinin, and SF1 ( Table 3). The logistic model with all four markers (Model 1) displays better data fit than an alternative model with no IHC markers (omnibus test of model coefficients p = 0.009); however, its estimated sensitivity 96.6% (CI95: 88.3-99.4%), specificity 27.3% (CI95: 9.7-56.6%) and Youden's J index (0.238; CI95: 0.010-0.414) are not significantly better than the sensitivity, specificity and Youden's J index of a single FOXL2 IHC marker ( Table 2). A logistic regression model was also built with three IHC markers FOXL2, inhibin, and calretinin (Model 2, Table 3). These IHC markers were included in Model 2, because they were found to be the most sensitive or most specific predictors of CHEK2 mutation status as single IHC markers, and their Wald p-values in Model 1 were p < 0.1. In Model 2, FOXL2 expression remained the strongest predictor of  (Table 3), and it performed better than the logistic Model 1 that included all four IHC markers, although the difference in classification was not statistically significant for our dataset (McNemar's test p = 0.25). The model with three predictors performed better than any single IHC marker ( Table 2), but the differences were also not statistically significant (McNemar's test p > 0.05).
The highest agreement was found between immunostaining by inhibin and SF1 (Cohen's kappa = 0.262; CI95: −0.055-0.580), even though the degree of agreement was inconclusive due to the small sample size and a wide 95% confidence interval. Taken together, SF1 appears to be a redundant IHC marker providing lower performance as well as limited additional information compared to inhibin for the prediction of FOXL2 mutation status.
For the remaining pairs of IHC markers, low values of estimated Cohen's kappa imply only slight agreement between these markers; however, wide confidence intervals do not allow for drawing confident conclusions: calretinin and inhibin (Cohen's kappa = 0.

Discussion
Ovarian granulosa cell tumors (GCTs) are rare gynecologic tumors that represent less than 5% of all ovarian tumors [20]. They account for about 70% of all sex cord-stromal tumors (SCST) that arise from the gonadal primitive sex cords or stromal cells.
Adult-type ovarian granulosa cell tumors (AGCTs) and juvenile-type ovarian granulosa cell tumors (JGCTs) are epidemiologically, clinically, and histopathologically distinct entities that account for 95% and 5% of GCTs, respectively [21]. AGCTs are typically diagnosed in perimenopausal or early postmenopausal women with a median age at diagnosis of 50-54 years, although they can occasionally also be diagnosed in children [22]. In contrast, the average age at diagnosis of JGCT is reportedly 13 years, although 21% of cases were still diagnosed in women over 21 years of age [23]. Of note, these cases were typically classified as AGCTs or JGCTs based on morphological criteria.
Consistent with previous reports [22], we found the median age at diagnosis of ovarian GCTs to be 58 years among all patients and 59 years in a subgroup with the FOXL2 p.C134W mutation. On the other hand, a Korean case-series study of 91 patients with adult-type ovarian GCT reported the median age at diagnosis to be 42 years (range 7-85 years) [24], which is considerably lower than was found in our study or reported by other investigators. This disagreement may be caused by different definitions of AGCT, which is molecular in our study and morphological/clinical in the Korean study. Relatively non-specific histopathologic features of AGCTs have been recognized as a source of misdiagnosis of other cancers as AGCTs and imply the importance of molecularly defined diagnosis of these tumors [25].
The presence of the somatic mutation FOXL2 p.C134W and the expression of FOXL2 protein are characteristic of the adult-type GCT. In contrast, juvenile-type GCTs virtually never display this mutation, and the expression of FOXL2 may be variable, and even reduced in aggressive phenotypes and advanced stages of JGCTs (reviewed in [26]). Ovarian granulosa tumors with the FOXL2 p.C134W mutation reportedly displayed higher expression of FOXL2 on mRNA level than those with wild-type FOXL2, which in turn correlated with the intensity of FOXL2 IHC staining among AGCTs and JGCTs [21]. Consistent with these findings, our results show more prevalent positivity of FOXL2 IHC among cases with the FOXL2 p.C134W mutation than in cases without this mutation (PR = 1.3; CI95:0.90-1.88). We found this association between the FOXL2 p.C134W mutation status and FOXL2 positivity by IHC to be marginally statistically significant (mid-p-value = 0.052).
Consequently, the presence of somatic mutation FOXL2 p.C134W can serve as a defining feature of the AGCTs; therefore, in this study we delineated the AGCTs as cases previously diagnosed with ovarian granulosa cell tumors or granulosa cell-like tumors, in which we additionally found the somatic mutation FOXL2 p.C134W . This approach is in line with that of other investigators, who reappraised FOXL2 wild-type AGCT cases, which were previously diagnosed entirely by morphology, as most likely representing thecomas or fibromas [19,26,27]. It should be noted, however, that FOXL2 p.C134W was also detected in a subset of thecomas [19].
To streamline the diagnosis of AGCTs, we evaluated the performance of selected IHC markers to distinguish ovarian granulosa cell tumors with the FOXL2 p.C134W mutation from granulosa cell tumors with wild-type FOXL2, as the latter cases presumably represent JGCTs and possibly some misdiagnosed SCSTs of other types. Our results show a generally appreciable sensitivity but relatively low specificity of individual IHC markers.
The best diagnostic performance was achieved using a logistic regression model that integrated IHC expression of FOXL2, inhibin, and calretinin. However, due to a relatively small sample size, diagnostic performances were not found to be significantly different across several classifiers discussed in this study. The problem of small sample size affects most studies reporting research on this rare type of ovarian cancer. Nevertheless, research on rare cancers, such as gastrointestinal stromal tumors, acute myeloid leukemia, seminomas, and others, produced fundamental insights translatable into innovative therapeutic strategies for these rare malignancies, as well as in better a molecular understanding of more common types of cancers [28]. This is because rare cancers are usually homogeneous entities that (i) tend to result from a single identifiable genetic cause or exposure to a single identifiable environmental carcinogen, (ii) can be characterized by a small number of mutations, and (iii) typically deviate from normal cells only in a small number of pathways that are amenable to therapeutic targeting.
Thus far, no reproductive, occupational, environmental, or general lifestyle risk factors have been consistently associated with the risk of developing AGCTs [29], and no inherited predispositions have been identified for the development of these tumors. For these reasons, AGCTs have been considered sporadic and unrelated to exposure.
The study presented in this report was motivated by our finding of an unexpectedly high prevalence of AGCTs among female carriers of the CHEK2 p.I157T mutations diagnosed with ovarian cancer. AGCT reportedly represents only 3-5% of all ovarian cancers in the general population [10]. Among the 75,024 ovarian cancers (ICD-O-3 site code C56.9) registered in the US SEER 13 cancer registries over 1992-2018, only 974 cases represented GCTs (ICD-O-3 code 8620/3), which accounted for 1.3% of all ovarian cancers [30]. By contrast, however, GCTs represented 4 of 11 (~36.4%) histologically characterized ovarian cancers in a group of the CHEK2 p.I157T mutation carriers.
Our results further demonstrated a higher prevalence of this germline mutation among AGCT patients relative to three reference populations, which provided support to our hypothesis of the positive association between the CHEK2 p.I157T mutation and adult-type ovarian granulosa cell tumors. Since GCTs are rare tumors that represent no more than 5% of all ovarian malignancies and display a similar occurrence across various populations [10], the risk of bias potentially generated by the selection of reference populations is low. Notably, we also found a higher prevalence of the CHEK2 p.I157T mutation in the group of AGCT patients than in the European Finnish population that displays the highest prevalence of this mutation (Ensembl, release 105 [31]; rs17879961), which further supports our conclusion.
Our study implicated for the first time the CHEK2 p.I157T mutation in granulosa cell carcinogenesis and suggested a specific genetic predisposition in adult-type ovarian granulosa cell tumors. The CHEK2 p.I157T mutation has been previously shown to impede Chek2 protein homodimerization, which is required for its activation, and to interfere with wild-type Chek2 protein in heterozygous cells in a dominant-negative manner [8]. This mutation is considered to confer multi-organ tumor susceptibility through its probable synergism with other genetic factors or environmental exposures [3]; however, no conclusive association has been reported between this mutation and any type of ovarian cancer thus far. A small case-control study of patients with GCT suggested an association with family history of breast (OR = 2.13; 1.19-3.80) or ovarian cancer (OR = 2.89; 1.08-7.72), which implies a possible existence of shared genetic predispositions between these cancers [32].
An underlying mechanism behind the role of the CHEK2 p.I157T germline mutation in the potentially increased risk of AGCTs has yet to be determined. One possible explanation can be that this germline CHEK2 mutation, which affects cell cycle regulation and DNA damage response pathways, can predispose to unique patterns of subsequent somatic mutations, including FoxL2 p.C134W , which is pathognomonic for AGCTs. A similar mechanism has been previously suggested for prostate cancer, since patients with pathogenic germline CHEK2 mutations displayed a significantly higher prevalence of the somatic CDK12 mutation than unselected prostate cancer patients from the TCGA cohort. Consequently, CHEK2 germline mutations have already been associated with increased occurrence of a specific somatic mutation in a cancer-relevant gene [33].
Besides this suggested role of the germline CHEK2 p.I157T mutation in the risk of developing a subsequent FOXL2 p.C134W mutation in granulosa cells, other mechanisms can also be operative in the AGCT-CHEK2 p.I157T association identified in our study. For instance, a wild-type FOXL2 was shown to modulate cell cycle regulators and promote cell cycle arrest in the G1 phase and in the repair of oxidatively damaged DNA [34]. This implies that the presence of the germline CHEK2 mutation impairing the cell cycle and DNA damage response may synergize with the FOXL2 p.C134W mutation that may develop in granulosa cells as a "second hit" and further aggravate the impairment of the cell cycle and DNA damage repair processes, paving the way for ovarian granulosa carcinogenesis. Nevertheless, these suggested mechanisms are not mutually exclusive and can both contribute to the development of granulosa cell tumors.

Conclusions
The CHEK2 missense p.I157T (c.470T>C) germline mutation, which was previously reported to increase the risk of breast, colon, kidney, prostate, and thyroid cancers [4], is also associated with adult granulosa cell tumors (AGCTs). This association suggests that CHEK2 p.I157T can be a predisposing genetic factor for AGCTs.
The FOXL2 p.C134W mutation, which is a pathognomonic defining feature of AGCTs, was detected among~84% of cases previously diagnosed as AGCTs based on clinical and histopathological findings. This finding supports the necessity of including detection of the FOXL2 p.C134W mutation in the diagnosis of AGCT. The presence of this mutation is in fair agreement with IHC positivity of the tumor cells for FOXL2 expression, which allows for application of the FOXL2 expression as a surrogate IHC marker for the FOXL2 p.C134W mutation.
Combination of IHC markers FOXL2, inhibin, and calretinin displayed the best performance for the prediction of FOXL2 p.C134W mutational status among the AGCT cases diagnosed by clinical and histopathological findings.

Institutional Review Board Statement:
The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Bioptická laboratoř (Project identification code 010/20).

Informed Consent Statement:
The informed consent was waived due to the retrospective nature of the study performed on archived and strictly anonymized biospecimens, which did not lead to the change of a previously rendered diagnosis and had no clinical consequences on the patients' management. For these studies, local ethical committees and other authorities in the Czech Republic do not require patient consent for the use of an archived specimen.

Conflicts of Interest:
The authors declare no conflict of interest.