Preoperative discrimination of tumour stage in clear cell carcinoma of the ovary using computed tomography and magnetic resonance imaging

Exploration and prognostic analysis of two types of high-risk ovarian cancers: clear cell vs. serous carcinoma: a population-based study

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare pathological histotype in ovarian cancer, while the survival rate of advanced OCCC (Stage III-IV) is substantially lower than that of the advanced serous ovarian cancer (OSC), which is the most common histotype. The goal of this study was to identify high-risk OCCC by comparing OSC and OCCC, with investigating potential risk and prognosis markers.

METHODS

Patients diagnosed with ovarian cancer from 2009 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) Program. Logistic and Cox regression models were used to identify risk and prognostic factors in high-risk OCCC patients. Cancer-specific survival (CSS) and overall survival (OS) were assessed using Kaplan-Meier curves. Furthermore, Cox analysis was employed to build a nomogram model. The performance evaluation results were displayed using the C-index, calibration plots, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Immunohistochemically approach was used to identify the expression of the novel target (GPC3).

RESULTS

In the Cox analysis for advanced OCCC, age (45-65 years), tumor numbers (total number of in situ/malignant tumors for patient), T3-stage, bilateral tumors, and liver metastases could be defined as prognostic variables. Nomogram showed good predictive power and clinical practicality. Compared with OSC, liver metastases had a stronger impact on the prognosis of patients with OCCC. T3-stage, positive distant lymph nodes metastases, and lung metastases were risk factors for developing liver metastases. Chemotherapy was an independent prognostic factor for patient with advanced OCCC, but had no effect on CSS in patients with liver metastases (p = 0.0656), while surgery was significantly related with better CSS in these patients (p < 0.0001) (p = 0.0041). GPC3 expression was detected in all tissue sections, and GPC3 staining was predominantly found in the cytoplasm and membranes.

CONCLUSION

Advanced OCCC and OCCC with liver metastases are two types of high-risk OCCC. The constructed nomogram exhibited a satisfactory survival prediction for patients with advanced OCCC. GPC3 immunohistochemistry is expected to accumulate preclinical evidence to support the inclusion of GPC3 in OCCC targeted therapy.

A preoperative nomogram incorporating CT to predict the probability of ovarian clear cell carcinoma

OBJECTIVES

To evaluate clinical, laboratory, and radiological variables from preoperative contrast-enhanced computed tomography (CECT) for their ability to distinguish ovarian clear cell carcinoma (OCCC) from non-OCCC and to develop a nomogram to preoperatively predict the probability of OCCC.

METHODS

This IRB-approved, retrospective study included consecutive patients who underwent surgery for an ovarian tumor from 1/1/2000 to 12/31/2016 and CECT of the abdomen and pelvis ≤90 days before primary debulking surgery. Using a standardized form, two experienced oncologic radiologists independently analyzed imaging features and provided a subjective 5-point impression of the probability of the histological diagnosis. Nomogram models incorporating clinical, laboratory, and radiological features were created to predict histological diagnosis of OCCC over non-OCCC.

RESULTS

The final analysis included 533 patients with surgically confirmed OCCC (n = 61) and non-OCCC (n = 472); history of endometriosis was more often found in patients with OCCC (20% versus 3.6%; p < 0.001), while CA-125 was significantly higher in patients with non-OCCC (351 ng/mL versus 70 ng/mL; p < 0.001). A nomogram model incorporating clinical (age, history of endometriosis and adenomyosis), laboratory (CA-125) and imaging findings (peritoneal implant distribution, morphology, laterality, and diameter of ovarian lesion and of the largest solid component) had an AUC of 0.9 (95% CI: 0.847, 0.949), which was comparable to the AUCs of the experienced radiologists' subjective impressions [0.8 (95% CI: 0.822, 0.891) and 0.9 (95% CI: 0.865, 0.936)].

CONCLUSIONS

A presurgical nomogram model incorporating readily accessible clinical, laboratory, and CECT variables was a powerful predictor of OCCC, a subtype often requiring a distinctive treatment approach.

Clear cell carcinoma of the ovary: Epidemiology, pathological and biological features, treatment options and clinical outcomes

Clear cell carcinoma of the ovary is a rare and distinct histotype of epithelial ovarian carcinomas. Women diagnosed with clear cell carcinomas are usually younger and diagnosed at earlier stages than those with the most common high-grade serous histology. Endometriosis is considered a main risk factor for the development of clear cell carcinoma of the ovary, and it can be considered a precursor of of this tumor, as it is identified in more than 50% of patients with clear cell carcinoma. Different molecular pathways and alterations heve been identified in ovarian clear cell carcinoma, including the most common mutations of AT-rich interaction domain 1A [ARID1A] and phosphatidylinositol-4,5-bisphosphate 3-kinase [PIK3] catalytic subunit alpha [PIK3CA]. The prognosis of patients at early stage is favorable, while patients with advanced or recurrent disease experience a poor oncologic outcomes. Despite a lower rate of responses due to an intrinsic chemoresistance, the treatment strategy for advanced disease resembles the treatment of high-grade serous carcinoma, which includes aggressive cytoreductive surgery and platinum-based chemotherapy. For this reason, the role of adjuvant chemotherapy in patients with stage I disease undergoing complete surgical staging is still under debate. Alternative treatments, including biological agents that target different pathways constitute the most promising treatment strategies, and well-designed, collaborative international trials should be designed in order to improve the oncologic outcomes and the quality of life of patients with this aggressive disease.

Assessing CT imaging features combined with CEA and CA125 levels to identify endometriosis-associated ovarian cancer

PURPOSE

To improve the diagnosis and identification of ovarian clear cell carcinoma (CCC) and ovarian endometrioid carcinoma (EC), we evaluated CT imaging findings and cut-off values for CEA and CA125.

METHODS

The CT features and tumour markers (tumour size, location, morphology, composition, number of cysts, growth pattern of the mural nodules, mural nodule HWR, enhancement of the mural nodules, ascites, complications, CEA level, CA125 level) of 55 tumours in 52 patients with CCC, confirmed by surgery and pathology at the Yunnan Cancer Hospital from January 1, 2012 to December 30, 2018, were compared with those of 41 tumours in 36 patients with EC. All patients had a long history of endometriosis. Statistical analysis was performed using t test, chi-square test, Mann-Whitney U test, univariate analysis, multivariate logistic regression analysis and receiver-operating characteristic (ROC) curves.

RESULTS

CCC and EC presented as large oval or irregular mixed cystic-solid masses in the pelvic region, with moderately delayed enhancement of the solid components. There was a statistically significant difference between the number of cysts, the growth pattern of the mural nodules, the presence/absence of ascites, and the levels of CEA and CA125 (P < 0.05). Most CCCs had unilocular cysts, mural nodules that were polypoid structures, and no ascites (46/55, 33/55, 42/55); most ECs had multilocular cysts and broad-based nodular structures and were ascites positive (28/41, 31/41, 21/41). The CEA positive rate was lower in the CCC group than in the EC group (2/52, 3.8% versus 11/36, 30.6%, P < 0.05), and the CA125 positive rate was high in both the CCC and EC groups (44/52, 84.6% versus EC = 35/36, 97.2%, P = 0.118). The ROC curves revealed that when the values of CEA and CA125 were higher than the cut-off values (CEA = 3.270 µg/L, CA125 = 589.400 kU/L), the diagnostic efficiency of CEA was 0.723, and the diagnostic specificity of CEA was as high as 0.903.

CONCLUSIONS

The number of cysts, growth pattern of the mural nodules, presence/absence of ascites, and levels of CEA and CA125 were useful factors for distinguishing CCC from EC; the best cut-off values of CEA and CA125 for distinguishing CCC from EC were 3.270 and 589.40, respectively. These findings may be helpful for correctly diagnosing and identifying CCC and EC.