Evaluation of the potential of ultrasound-mediated drug delivery for the treatment of ovarian cancer through preclinical studies

The predictive value of nomogram for adnexal cystic-solid masses based on O-RADS US, clinical and laboratory indicators

BACKGROUND

Ovarian cancer remains a leading cause of death among women, largely due to its asymptomatic early stages and high mortality when diagnosed late. Early detection significantly improves survival rates, and the Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) is currently the most commonly used method, but has limitations in specificity and accuracy. While O-RADS US has standardized reporting, its sensitivity can lead to the misdiagnosis of benign masses as malignant, resulting in overtreatment. This study aimed to construct a nomogram model based on the O-RADS US and clinical and laboratory indicators to predict the malignancy risk of adnexal cystic-solid masses.

METHODS

This retrospective study collected data from patients with adnexal cystic-solid masses who underwent ultrasonography and were pathologically confirmed between January 2021 and December 2023 at the First Affiliated Hospital of Shenzhen University. They were categorized into benign and malignant groups according to pathological findings. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select the most relevant predictors of ovarian cancer. A nomogram model was constructed, and its diagnostic performance was calculated. We bootstrapped the data 500 times to perform internal verification, drew a calibration curve to verify the prediction ability, and performed a decision curve analysis to assess clinical usefulness.

RESULTS

A total of 399 patients with adnexal cystic-solid masses were included in this study: 327 in the benign group and 72 in the malignant group. Five predictors associated with the risk of malignancy of adnexal cystic-solid masses were selected using LASSO regression: O-RADS, acoustic shadowing, postmenopausal status, CA125, and HE4. The area under the curve, sensitivity, specificity, accuracy, positive and negative predictive values of the nomogram were 0.909, 83.3%, 82.9%, 83.0%, 51.7%, and 95.8%, respectively. The calibration curve of the nomogram showed good consistency between the predicted and actual probabilities, and the decision curve showed good clinical usefulness.

CONCLUSION

The nomogram model based on O-RADS US and clinical and laboratory indicators can be used to predict the risk of malignancy in adnexal cystic-solid masses, with high predictive performance, good calibration, and clinical usefulness.

Immunotherapy and the ovarian cancer microenvironment: Exploring potential strategies for enhanced treatment efficacy

Despite progress in cancer immunotherapy, ovarian cancer (OC) prognosis continues to be disappointing. Recent studies have shed light on how not just tumour cells, but also the complex tumour microenvironment, contribute to this unfavourable outcome of OC immunotherapy. The complexities of the immune microenvironment categorize OC as a 'cold tumour'. Nonetheless, understanding the precise mechanisms through which the microenvironment influences the effectiveness of OC immunotherapy remains an ongoing scientific endeavour. This review primarily aims to dissect the inherent characteristics and behaviours of diverse cells within the immune microenvironment, along with an exploration into its reprogramming and metabolic changes. It is expected that these insights will elucidate the operational dynamics of the immune microenvironment in OC and lay a theoretical groundwork for improving the efficacy of immunotherapy in OC management.

METTL3/YTHDF1 m6A axis promotes tumorigenesis by enhancing DDR2 expression in ovarian cancer

Ovarian cancer has the highest mortality among all gynecological malignancies. Therefore, it is urgent to determine the molecular mechanism of ovarian cancer progression. As the most prevalent modification of messenger RNA (mRNA), N6-Methyladenosine (m6A) modification is recognized as a key regulatory role in the progression of various tumors. However, the specific role of m6A and its related regulatory pathways in ovarian cancer (OV) remains unclear. In this study, we demonstrated that the METTL3/YTHDF1 m6A axis plays an important role in the progression of ovarian cancer. Depletion of METTL3/YTHDF1 impaired cancer proliferation and metastasis in vitro and in vivo. Mechanistically, The METTL3/YTHDF1 m6A axis directly binds to the mRNA of DDR2, thereby promoting the expression levels of the tumor promoter DDR2 and thus contributing to the progression of ovarian cancer. Collectively, our findings on the METTL3/YTHDF1/DDR2 m6A axis provide the insight into the underlying mechanism of ovarian carcinogenesis and highlight potential therapeutic targets for cancer treatment.