Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes

Diagnostic efficacy of combining diffusion-weighted magnetic resonance imaging with serum Mucin 1, Mucin 13, and Mucin 16 in distinguishing borderline from malignant epithelial ovarian tumors

AIMS

To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors.

METHODS

A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay.

RESULTS

Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670 ± 0.250) × 103 mm2/s, while MEOTs had a lower ADC mean of (1.332 ± 0.481) × 103 mm2/s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44 ng/mL vs. 7.77 ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%.

CONCLUSION

The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.

Deciphering cellular and molecular mechanism of MUC13 mucin involved in cancer cell plasticity and drug resistance

There has been a surge of interest in recent years in understanding the intricate mechanisms underlying cancer progression and treatment resistance. One molecule that has recently emerged in these mechanisms is MUC13 mucin, a transmembrane glycoprotein. Researchers have begun to unravel the molecular complexity of MUC13 and its impact on cancer biology. Studies have shown that MUC13 overexpression can disrupt normal cellular polarity, leading to the acquisition of malignant traits. Furthermore, MUC13 has been associated with increased cancer plasticity, allowing cells to undergo epithelial-mesenchymal transition (EMT) and metastasize. Notably, MUC13 has also been implicated in the development of chemoresistance, rendering cancer cells less responsive to traditional treatment options. Understanding the precise role of MUC13 in cellular plasticity, and chemoresistance could pave the way for the development of targeted therapies to combat cancer progression and enhance treatment efficacy.

Mucins and mucinous ovarian carcinoma: Development, differential diagnosis, and treatment

Mucinous ovarian carcinoma (MOC) is a rare histological type of epithelial ovarian cancer. It has poor response to conventional platinum-based chemotherapy regimens and PARPi-based maintenance treatment, resulting in short survival and poor prognosis in advanced-disease patients. MOC is characterized by mucus that is mainly composed of mucin in the cystic cavity. Our review discusses in detail the role of mucins in MOC. Mucins are correlated with MOC development. Furthermore, they are valuable in the differential diagnosis of primary and secondary ovarian mucinous tumors. Some types of mucins have been studied in the context of chemoresistance and targeted therapy for ovarian cancer. This review may provide a new direction for the diagnosis and treatment of advanced MOC.