Discovery and Development of a TGFβ3/IL-13 Plasma Risk Score for Preoperative Discrimination of Benign and Malignant Ovarian Adnexal Masses
Background/Objectives: Differentiating between benign and malignant ovarian adnexal masses before surgery is a significant diagnostic challenge. This study examined a wide range of circulating plasma molecules (immune and inflammatory) to identify potential markers to classify tumors as benign or malignant. The goal was to develop a proof-of-concept tool for preoperative risk stratification. Methods: Twenty-three plasma molecules were evaluated in women with benign lesions (n = 68) and women with malignant ovarian tumors (n = 25). To evaluate the behavior of each marker in a normal population, women without adnexal pathology were also included (n = 11). The results were compared using the Kruskal–Wallis test with Dunn post hoc pairwise comparisons, the Benjamini–Hochberg correction for multiple comparisons, and ROC analysis. TGF-β isoforms and CA125 were measured in the complete cohort (n = 104), while the remaining molecules were assessed in a reduced cohort (n = 51). Two classification approaches were developed using TGF-β3 and IL-13: a sequential two-step algorithm and an ordinal logistic regression model. Apparent performance was corrected for optimism using Harrell’s bootstrap procedure. Results: Ten molecules reached statistical significance. Among the significant molecules, TGF-β3 identified ovarian lesions regardless of malignant status (AUC = 0.983), while IL-13 showed perfect malignancy-specific separation from benign cases (AUC = 1.000). Their combination in an ordinal logistic regression model produced three non-overlapping diagnostic strata across all three groups, significantly outperforming CA125, HE4, and ROMA at the malignancy-separation boundary (DeLong p < 0.05) in our exploratory cohort. Conclusions: TGF-β3 and IL-13 represent a biologically complementary marker pair whose combined ordinal regression model shows promising performance and warrants prospective validation in larger, multicenter independent cohorts as a preoperative risk-stratification tool for ovarian adnexal masses.
Authors
- Alejandro Bravo‐Cuéllar (ORCID: https://orcid.org/0000-0002-2945-4503)
- Alejandro Bravo‐Hernández (ORCID: https://orcid.org/0000-0001-7512-8162)
- Luis Felipe Jave‐Suárez (ORCID: https://orcid.org/0000-0001-6209-5031)
- Marı́a Martha Villaseñor-Garcı́a (ORCID: https://orcid.org/0000-0002-9280-7893)
- Georgina Hernández‐Flores (ORCID: https://orcid.org/0000-0002-4861-0065)
- Sarah Naomi Guevara-Hernández
- Adriana Aguilar‐Lemarroy (ORCID: https://orcid.org/0000-0001-9288-4824)
- Pablo Cesar Ortiz‐Lazareno (ORCID: https://orcid.org/0000-0001-9045-7052)
- Stéphanie López (ORCID: https://orcid.org/0009-0004-4610-5489)
- Raquel Villegas-Pacheco
- Jesús García-Gómez (ORCID: https://orcid.org/0009-0004-5610-4041)
- Johanna Lizeth Sáenz-Santibañez
Institutions
- Mexican Social Security Institute (MX)
- Universidad de Guadalajara (MX)
- Universidad Autónoma de Nayarit (MX)
- Hospital Universitario Dr José Eleuterio Gonzalez (MX)
Publication Details
- Journal
- Diagnostics
- Published
- 2026-07-28
- DOI
- https://doi.org/10.3390/diagnostics16152365
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00