Epithelial ovarian cancer: rationale for changing the one-fits-all standard treatment regimen to subtype-specific treatment

Landscape of somatic mutated genes and inherited susceptibility genes in gynecological cancer

Traditionally, gynecological cancers have been classified based on histology. Since remarkable advancements in next-generation sequencing technology have enabled the exploration of somatic mutations in various cancer types, comprehensive sequencing efforts have revealed the genomic landscapes of some common forms of human cancer. The genomic features of various gynecological malignancies have been reported by several studies of large-scale genomic cohorts, including The Cancer Genome Atlas. Although recent comprehensive genomic profiling tests, which can detect hundreds of genetic mutations at a time from cancer tissues or blood samples, have been increasingly used as diagnostic clinical biomarkers and in therapeutic management decisions, germline pathogenic variants associated with hereditary cancers can also be detected using this test. Gynecological cancers are closely related to genetic factors, with approximately 5% of endometrial cancer cases and 20% of ovarian cancer cases being caused by germline pathogenic variants. Hereditary breast and ovarian cancer syndrome and Lynch syndrome are the two major cancer susceptibility syndromes among gynecological cancers. In addition, several other hereditary syndromes have been reported to be associated with gynecological cancers. In this review, we highlight the genes for somatic mutation and germline pathogenic variants commonly seen in gynecological cancers. We first describe the relationship between clinicopathological attributes and somatic mutated genes. Subsequently, we discuss the characteristics and clinical management of inherited cancer syndromes resulting from pathogenic germline variants in gynecological malignancies.

Primary Mucinous Tumors of the Ovary: An Interobserver Reproducibility and Detailed Molecular Study Reveals Significant Overlap Between Diagnostic Categories

Primary ovarian mucinous tumors represent a heterogeneous group of neoplasms, and their diagnosis may be challenging. We analyzed 124 primary ovarian mucinous tumors originally diagnosed as mucinous borderline tumors (MBTs) or mucinous carcinomas (MCs), with an emphasis on interobserver diagnostic agreement and the potential for diagnostic support by molecular profiling using a next-generation sequencing targeted panel of 727 DNA and 147 RNA genes. Fourteen experienced pathologists independently assigned a diagnosis from preset options, based on a review of a single digitized slide from each tumor. After excluding 1 outlier participant, there was a moderate agreement in diagnosing the 124 cases when divided into 3 categories (κ = 0.524, for mucinous cystadenoma vs MBT vs MC). A perfect agreement for the distinction between mucinous cystadenoma/MBT as a combined category and MC was found in only 36.3% of the cases. Differentiating between MBTs and MCs with expansile invasion was particularly problematic. After a reclassification of the tumors into near-consensus diagnostic categories on the basis of the initial participant results, a comparison of molecular findings between the MBT and MC groups did not show major and unequivocal differences between MBTs and MCs or between MCs with expansile vs infiltrative pattern of invasion. In contrast, HER2 overexpression or amplification was found only in 5.3% of MBTs and in 35.3% of all MCs and in 45% of MCs with expansile invasion. Overall, HER2 alterations, including mutations, were found in 42.2% of MCs. KRAS mutations were found in 65.5% and PIK3CA mutations in 6% of MCs. In summary, although the diagnostic criteria are well-described, diagnostic agreement among our large group of experienced gynecologic pathologists was only moderate. Diagnostic categories showed a molecular overlap. Nonetheless, molecular profiling may prove to be therapeutically beneficial in advanced-stage, recurrent, or metastatic MCs.

Ex vivo assessment of cancer drug sensitivity in epithelial ovarian cancer and its association with histopathological type, treatment history and clinical outcome

Epithelial ovarian cancer (EOC) is divided into type I and type II based on histopathological features. Type I is clinically more indolent, but also less sensitive to chemotherapy, compared with type II. The basis for this difference is not fully clarified. The present study investigated the pattern of drug activity in type I and type II EOC for standard cytotoxic drugs and recently introduced tyrosine kinase inhibitors (TKIs), and assessed the association with treatment history and clinical outcome. Isolated EOC tumor cells obtained at surgery were investigated for their sensitivity to seven standard cytotoxic drugs and nine TKIs using a short-term fluorescent microculture cytotoxicity assay (FMCA). Drug activity was compared with respect to EOC subtype, preoperative chemotherapy, cross-resistance and association with progression-free survival (PFS). Out of 128 EOC samples, 120 samples, including 21 type I and 99 type II, were successfully analyzed using FMCA. Patients with EOC type I had a significantly longer PFS time than patients with EOC type II (P=0.01). In line with clinical experience, EOC type I samples were generally more resistant than type II samples to both standard cytotoxic drugs and the TKIs, reaching statistical significance for cisplatin (P=0.03) and dasatinib (P=0.002). A similar pattern was noted in samples from patients treated with chemotherapy prior to surgery compared with treatment-naive samples, reaching statistical significance for fluorouracil, irinotecan, dasatinib and nintedanib (all P<0.05). PFS time gradually shortened with increasing degree of drug resistance. Cross-resistance between drugs was in most cases statistically significant yet moderate in degree (r<0.5). The clinically observed relative drug resistance of EOC type I, as well as in patients previously treated, is at least partly due to mechanisms in the tumor cells. These mechanisms seemingly also encompass kinase inhibitors. Ex vivo assessment of drug activity is suggested to have a role in the optimization of drug therapy in EOC.

The Uncertain Benefit of Adjuvant Chemotherapy in Advanced Low-Grade Serous Ovarian Cancer and the Pivotal Role of Surgical Cytoreduction

In our center, adjuvant chemotherapy is routinely offered in high-grade serous ovarian cancer (HGSOC) patients but less commonly as a standard treatment in low-grade serous ovarian cancer (LGSOC) patients. This study evaluates the efficacy of this paradigm by analysing survival outcomes and by comparing the influence of different clinical and surgical characteristics between women with advanced LGSOC (n = 37) and advanced HGSOC (n = 300). Multivariate analysis was used to identify independent prognostic features for survival in LGSOC and HGSOC. Adjuvant chemotherapy was given in 99.7% of HGSOC patients versus in 27% of LGSOC (p < 0.0001). The LGSOC patients had greater surgical complexity scores (p < 0.0001), more frequent postoperative ICU/HDU admissions (p = 0.0002), and higher peri-/post-operative morbidity (p < 0.0001) compared to the HGSOC patients. The 5-year OS and progression-free survival (PFS) was 30% and 13% for HGSOC versus 57% and 21.6% for LGSOC, p = 0.016 and p = 0.044, respectively. Surgical complexity (HR 5.3, 95%CI 1.2-22.8, p = 0.024) and complete cytoreduction (HR 62.4, 95% CI 6.8-567.9, p < 0.001) were independent prognostic features for OS in LGSOC. This study demonstrates no clear significant survival advantage of chemotherapy in LGSOC. It highlights the substantial survival benefit of dynamic multi-visceral surgery to achieve complete cytoreduction as the primary treatment for LGSOC patients.

Cellular Mechanism of Gene Mutations and Potential Therapeutic Targets in Ovarian Cancer

Ovarian cancer is a common and complex malignancy with poor prognostic outcome. Most women with ovarian cancer are diagnosed with advanced stage disease due to a lack of effective detection strategies in the early stage. Traditional treatment with cytoreductive surgery and platinum-based combination chemotherapy has not significantly improved prognosis and 5-year survival rates are still extremely poor. Therefore, novel treatment strategies are needed to improve the treatment of ovarian cancer patients. Recent advances of next generation sequencing technologies have both confirmed previous known mutated genes and discovered novel candidate genes in ovarian cancer. In this review, we illustrate recent advances in identifying ovarian cancer gene mutations, including those of TP53, BRCA1/2, PIK3CA, and KRAS genes. In addition, we discuss advances in targeting therapies for ovarian cancer based on these mutated genes in ovarian cancer. Further, we associate between detection of mutation genes by liquid biopsy and the potential early diagnostic value in ovarian cancer.

Whole solid tumor volume histogram parameters for predicting the recurrence in patients with epithelial ovarian carcinoma: a feasibility study on quantitative DCE-MRI

BACKGROUND

Preoperative prediction of the recurrence of epithelial ovarian carcinoma (EOC) can guide the clinical treatment and improve the prognosis. However, there are still no reliable predictive biomarkers.

PURPOSE

To evaluate whether whole solid tumor volume histogram parameters measured from quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the recurrence in patients with EOC.

MATERIAL AND METHODS

We followed up 56 patients with surgical and histopathologically diagnosed EOC who underwent quantitative DCE-MRI scans. The differences of the histogram parameters between patients with and without recurrence were compared. Mann-Whitney U test, Pearson's Chi-squared test, or Fisher's exact test, and receiver operating characteristic (ROC) curves were used for statistical analysis.

RESULTS

All histogram parameters of K^trans, k_ep, and v_e were not significantly different between EOC patients with and without recurrence (P>0.05). For 30 patients with high-grade serous ovarian carcinoma (HGSOC), the histogram parameters of K^trans (mean and 5th, 10th, 25th, 50th, 75th percentiles) and k_ep (mean and 50th percentile) in 12 patients with recurrence were significantly lower than those in 18 patients without recurrence (all P<0.05). ROC curves showed that the 5th percentile of K^trans had the largest area under the curve (AUC) of 0.792 for predicting the recurrence in patients with HGSOC. When the threshold value was ≤0.0263/min, the sensitivity, specificity, and accuracy were 100%, 66.7%, and 80%, respectively.

CONCLUSION

Instead of predicting the recurrence of EOC, whole solid tumor volume quantitative DCE-MRI histogram parameters could predict the recurrence of HGSOC and may be potential biomarkers for the prediction of HGSOC recurrence.

MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers

OBJECTIVES

Epithelial ovarian cancers (EOC) can be divided into type I and type II according to etiology and prognosis. Accurate subtype differentiation can substantially impact patient management. In this study, we aimed to construct an MR image-based radiomics model to differentiate between type I and type II EOC.

METHODS

In this multicenter retrospective study, a total of 294 EOC patients from January 2010 to February 2019 were enrolled. Quantitative MR imaging features were extracted from the following axial sequences: T2WI FS, DWI, ADC, and CE-T1WI. A combined model was constructed based on the combination of these four MR sequences. The diagnostic performance was evaluated by ROC-AUC. In addition, an occlusion test was carried out to identify the most critical region for EOC differentiation.

RESULTS

The combined radiomics model exhibited superior diagnostic capability over all four single-parametric radiomics models, both in internal and external validation cohorts (AUC of 0.806 and 0.847, respectively). The occlusion test revealed that the most critical region for differential diagnosis was the border zone between the solid and cystic components, or the less compact areas of solid component on direct visual inspection.

CONCLUSIONS

MR image-based radiomics modeling can differentiate between type I and type II EOC and identify the most critical region for differential diagnosis.

KEY POINTS

• Combined radiomics models exhibited superior diagnostic capability over all four single-parametric radiomics models, both in internal and external validation cohorts (AUC of 0.834 and 0.847, respectively). • The occlusion test revealed that the most crucial region for differentiating type Ι and type ΙΙ EOC was the border zone between the solid and cystic components, or the less compact areas of solid component on direct visual inspection on T2WI FS. • The light-combined model (constructed by T2WI FS, DWI, and ADC sequences) can be used for patients who are not suitable for contrast agent use.

HIST1H2BB and MAGI2 Methylation and Somatic Mutations as Precision Medicine Biomarkers for Diagnosis and Prognosis of High-grade Serous Ovarian Cancer

Molecular alterations that contribute to long-term (LT) and short-term (ST) survival in ovarian high-grade serous carcinoma (HGSC) may be used as precision medicine biomarkers. DNA promoter methylation is an early event in tumorigenesis, which can be detected in blood and urine, making it a feasible companion biomarker to somatic mutations for early detection and targeted treatment workflows. We compared the methylation profile in 12 HGSC tissue samples to 30 fallopian tube epithelium samples, using the Infinium Human Methylation 450K Array. We also used 450K methylation arrays to compare methylation among HGSCs long-term survivors (more than 5 years) and short-term survivors (less than 3 years). We verified the array results using bisulfite sequencing and methylation-specific PCR (qMSP). in another cohort of HGSC patient samples (n = 35). Immunoblot and clonogenic assays after pharmacologic unmasking show that HIST1H2BB and MAGI2 promoter methylation downregulates mRNA expression levels in ovarian cancer cells. We then used qMSP in paired tissue, ascites, plasma/serum, vaginal swabs, and urine from a third cohort of patients with HGSC cancer (n = 85) to test the clinical potential of HIST1H2BB and MAGI2 in precision medicine workflows. We also performed next-generation exome sequencing of 50 frequently mutated in human cancer genes, using the Ion AmpliSeqCancer Hotspot Panel, to show that the somatic mutation profile found in tissue and plasma can be quantified in paired urine samples from patients with HGSC. Our results suggest that HIST1H2BB and MAGI2 have growth-suppressing roles and can be used as HGSC precision medicine biomarkers.

An international, phase III randomized trial in patients with mucinous epithelial ovarian cancer (mEOC/GOG 0241) with long-term follow-up: and experience of conducting a clinical trial in a rare gynecological tumor

OBJECTIVES

We evaluated four different treatment regimens for advanced-stage mucinous epithelial ovarian cancer.

METHODS

We conducted a multicenter randomized factorial trial (UK and US). Patients were diagnosed with primary mEOC: FIGO stage II-IV or recurrence after stage I disease. Treatment arms were paclitaxel-carboplatin, oxaliplatin-capecitabine, paclitaxel-carboplatin-bevacizumab, or oxaliplatin-capecitabine-bevacizumab. Chemotherapy was given 3-weekly for 6 cycles, and bevacizumab (3-weekly) was continued as maintenance (for 12 cycles). Endpoints included overall-survival (OS), progression-free survival (PFS), toxicity and quality of life (QoL).

RESULTS

The trial stopped after 50 patients were recruited due to slow accrual. Median follow-up was 59 months. OS hazard ratios (HR) for the two main comparisons were: 0.78 (p = 0.48) for Oxal-Cape vs. Pac-Carbo (each with/without bevacizumab), and 1.04 (p = 0.92) for bevacizumab vs. no bevacizumab. Corresponding PFS HRs were: 0.84 and 0.80. Retrospective central pathology review revealed only 45% (18/40) cases with available material had confirmed primary mEOC. Among these, OS HR for Oxal-Cape vs. Pac-Carbo was 0.36 (p = 0.14); PFS HR = 0.62 (p = 0.40). Grade 3-4 toxicity was seen in 61% Pac-Carbo, 61% Oxal-Cape, 54% Pac-Carbo-Bev, and 85% Oxal-Cape-Bev. QoL was similar between the four arms.

CONCLUSION

mEOC/GOG0241 represents an example of a randomized rare tumor trial. Logistical challenges led to early termination, including difficulties in local histopathological diagnosis and accessing drugs outside their labelled indication. There was misalignment between central funders who support clinical trials in rare cancers and the deprioritisation of such work by those managing and funding research at a local level. Rare cancer trials should include centralised pathology review before treatment. Clinical trial registry number: ISRCTN83438782.

Loss of 1p36.33 Frequent in Low-Grade Serous Ovarian Cancer

BACKGROUND: Low-grade serous ovarian cancer (LGSOC) is a rare subtype of epithelial ovarian carcinoma. Limited data regarding the molecular-genetic background exist beyond mutations in the RAS signaling pathway. There is a growing need to better characterize these tumors due to chemoresistance and limited therapeutic options in advanced or recurrent disease. METHODS: We performed genome-wide copy number aberration (CNA) profiles and mutation hotspot screening (KRAS, BRAF, NRAS, ERBB2, PIK3CA, TP53) in 38 LGSOC tumor samples. RESULTS: We detected mutations in the RAS-signaling pathway in 36.8% of cases, including seven KRAS, four BRAF, and three NRAS mutations. We identified two mutations in PIK3CA and one mutation in MAP3K1, EGFR, and TP53. CNAs were detected in 86.5% of cases. None of the focal aberrations was correlated with specific clinical characteristics. The most frequently detected CNA was loss of 1p36.33 in 54.1% of cases, with a trend towards lower progression-free survival and overall survival in patients with 1p36.33 loss. CONCLUSIONS: Activating RAS mutations were dominant in our series, with supplementary detection of two PIK3CA mutations which may lead to therapeutic options. Furthermore, we detected 1p36.33 deletions in half of the cases, indicating a role in tumorigenesis, and these deletions may serve as a prognostic marker.

Chromosomal Instability in Cell-Free DNA as a Highly Specific Biomarker for Detection of Ovarian Cancer in Women with Adnexal Masses

Purpose: Chromosomal instability is a hallmark of ovarian cancer. Here, we explore copy-number alteration (CNA) profiling in cell-free DNA as a potential biomarker to detect malignancy in patients presenting with an adnexal mass.Experimental Design: We prospectively enrolled 68 patients with an adnexal mass, of which 57 were diagnosed with invasive or borderline carcinoma and 11 with benign disease. Cell-free DNA was extracted from plasma and analyzed by low-coverage whole-genome sequencing.Results: Patterns of chromosomal instability were detectable in cell-free DNA using 44 healthy individuals as a reference. Profiles were representative of those observed in matching tumor tissue and contained CNAs enriched in two large datasets of high-grade serous ovarian cancer (HGSOC). Quantitative measures of chromosomal instability, referred to as genome-wide z-scores, were significantly higher in patients with ovarian carcinoma than in healthy individuals or patients with benign disease. Cell-free DNA testing improved malignancy detection (AUC 0.89) over serum CA-125 (AUC 0.78) or the risk of malignancy index (RMI, AUC 0.81). AUC values of cell-free DNA testing even further increased for HGSOC patients specifically (AUC 0.94). At a specificity of 99.6%, a theoretical threshold required for ovarian cancer screening, sensitivity of cell-free DNA testing was 2- to 5-fold higher compared with CA-125 and RMI testing.Conclusions: This is the first study evaluating the potential of cell-free DNA for the diagnosis of primary ovarian cancer using chromosomal instability as a read-out. We present a promising method to increase specificity of presurgical prediction of malignancy in patients with adnexal masses. Clin Cancer Res; 23(9); 2223-31. ©2016 AACR.

Diagnosis of Ovarian Carcinoma Histotype Based on Limited Sampling: A Prospective Study Comparing Cytology, Frozen Section, and Core Biopsies to Full Pathologic Examination

Growing insights into the biological features and molecular underpinnings of ovarian cancer has prompted a shift toward histotype-specific treatments and clinical trials. As a result, the preoperative diagnosis of ovarian carcinomas based on small tissue sampling is rapidly gaining importance. The data on the accuracy of ovarian carcinoma histotype-specific diagnosis based on small tissue samples, however, remains very limited in the literature. Herein, we describe a prospective series of 30 ovarian tumors diagnosed using cytology, frozen section, core needle biopsy, and immunohistochemistry (p53, p16, WT1, HNF-1β, ARID1A, TFF3, vimentin, and PR). The accuracy of histotype diagnosis using each of these modalities was 52%, 81%, 85%, and 84% respectively, using the final pathology report as the reference standard. The accuracy of histotype diagnosis using the Calculator for Ovarian Subtype Prediction (COSP), which evaluates immunohistochemical stains independent of histopathologic features, was 85%. Diagnostic accuracy varied across histotype and was lowest for endometrioid carcinoma across all diagnostic modalities (54%). High-grade serous carcinomas were the most overdiagnosed on core needle biopsy (accounting for 45% of misdiagnoses) and clear cell carcinomas the most overdiagnosed on frozen section (accounting for 36% of misdiagnoses). On core needle biopsy, 2/30 (7%) cases had a higher grade lesion missed due to sampling limitations. In this study, we identify several challenges in the diagnosis of ovarian tumors based on limited tissue sampling. Recognition of these scenarios can help improve diagnostic accuracy as we move forward with histotype-specific therapeutic strategies.

Ovarian cancer treatment: The end of empiricism?

The diagnosis, investigation, and management of ovarian cancer are in a state of flux-balancing ever rapid advances in our understanding of its biology with 3 decades of clinical trials. Clinical trials that started with empirically driven selections have evolved in an evidence-informed manner to gradually improve outcome. Has this improved understanding of the biology and associated calls to action led to appropriate changes in therapy? In this review, the authors discuss incorporating emerging data on biology, combinations, dose, and scheduling of new and existing agents with patient preferences in the management of women with ovarian cancer.

New strategies in ovarian cancer: translating the molecular complexity of ovarian cancer into treatment advances

An improved understanding of the genomics of ovarian cancer and the separation of ovarian cancer into histologically and molecularly defined subgroups have affected drug development and clinical trial design in ovarian cancer. Active therapies that have been tested in ovarian cancer include agents that inhibit angiogenesis and poly (ADP-ribose) polymerase inhibitors (PARPi). However, no FDA drug approvals for ovarian cancer have been granted since 2006, and overall survival improvements have been difficult to achieve with new agents. The genomic complexity of ovarian cancer and modest single-agent activity of many biologic agents in this disease have led to testing of biologic agent combinations. In this article, we review recent advances in the understanding of the molecular diversity of ovarian cancer as well as emerging therapeutic strategies such as new agents and biologic combinations that attempt to target multiple aberrant pathways in this cancer.

A clinically applicable molecular-based classification for endometrial cancers

BACKGROUND

Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.

METHODS

Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.

RESULTS

Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.

CONCLUSIONS

Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

The clinical characteristics and outcomes of cases with pure ovarian clear cell, mixed type and high-grade serous adenocarcinoma

PURPOSE

This study aimed to compare the clinical characteristics and outcomes of the cases with pure ovarian clear cell adenocarcinoma (OCCC), mixed type (clear plus serous or clear plus endometrioid or serous plus clear plus endometrioid) ovarian adenocarcinoma (MOC) and high-grade serous ovarian adenocarcinoma (HGSOC).

METHODS

A retrospective comparison was conducted in 32 cases with pure OCCC, 23 cases with MOC and 28 cases with HGSOC followed between January 1999 and October 2011. Clinico-pathologic characteristics including histopathologic subtypes, age, stage, presence of ascites and/or peritoneal carcinomatosis, endometriosis and optimal cytoreduction, and also survival rates were compared in these three groups.

RESULTS

The cases with pure OCCC were younger than the cases with MOC and HGSOC (p = 0.004). The median pre-operative CA-125 level was lower in the pure OCCC than in MOC and HGSOC (p = 0.006) (p = 0.001, p = <0.001, respectively). Bilaterality and peritoneal carcinomatosis were more frequently seen in the HGSOC group (p = 0.001, p < 0.001, respectively). The majority of the cases (65 %) had stage I or II disease in the pure OCCC group, but most of the cases in the HGSOC group had advanced stage disease (p < 0.001). Endometriosis was found in 16 cases (16/55, 29 %) in the OCCC group. No significant difference was detected with regard to the median survival rate among three groups (p = 0.517), while the stage of disease was found to be the only important factor for survival (p = 0.002).

CONCLUSION

Pure OCCC, MOC and HGSOC represent distinct clinical characteristics. Clinical characteristics of MOC are more similar to those of HGSOC.

Mutational status of KRAS, NRAS, and BRAF in primary clear cell ovarian carcinoma

Ovarian clear cell carcinoma (OCCC) is a subtype of epithelial ovarian cancer with characteristic biological features and aggressive clinical behavior. OCCCs show a pattern of gene mutations different from other type I ovarian malignancies, notably a higher frequency of PIK3CA mutations. In low grade serous ovarian cancer, KRAS and BRAF mutations are frequent, but little data are available on the mutational status of these genes in OCCCs. To clarify this issue, we designed a clinicopathological study with the aim to establish the incidence of KRAS, NRAS, and BRAF hot spot mutations in OCCC. Between December 2006 and June 2012, 22 patients with a proven diagnosis of OCCC were admitted to our Institutions. In all cases, final diagnosis was established according to FIGO and WHO criteria. All women received complete surgical staging. The PyroMark Q24 system (Qiagen GmbH, Hilden, Germany) was used for pyrosequencing analysis of KRAS, NRAS, and BRAF hot spot regions on 2.5-μm sections of formalin-fixed paraffin-embedded tissue from primary OCCC. Pyrosequencing analysis of KRAS, NRAS, and BRAF hot spot regions revealed the presence of mutations only at codon 12 in exon 2 of KRAS in 3 of 22 (14 %) cases. We found no mutations in the hot spot regions of NRAF (exons 2, 3, 4) or BRAF (exon 15). The median age of women with a KRAS mutated OCCC was 74 years. These OCCC were unilateral FIGO stage IA lesions in two cases associated with foci of endometriosis. We conclude that in 14 % of OCCCs, a KRAS mutation occurs in codon 2 exon 2. NRAS and BRAF mutations were not found.