Background/Objectives: Endometriosis (END) is a painful gynecological condition. Clinical examination, imaging, and laparoscopy can provide a definitive diagnosis of END. Nonetheless, non-invasive biomarkers could help enhance and streamline the diagnostic process. Micro-RNAs (miRNAs), a family of small non-coding RNAs, could serve as useful non-invasive biomarkers for END. The aim of this study was to perform serum miRNA profiling in a retrospective cohort of women to identify miRNAs that are differentially expressed in END compared to control patients. Methods: RNA was isolated from serum samples of 67 END patients and 60 control women. The expression profile of a 754-miRNA panel was studied with RT-qPCR performed on a QuantStudio 12K Flex with the TaqMan OpenArray miRNA panel. A Censored Regression Model was used for miRNA differential expression analysis. Several gene-enrichment algorithms were employed to identify pathways related to the target genes of differentially expressed miRNAs. Results: One hundred and thirty miRNAs were detected in at least 75% of samples from either the END or the control group. Sixteen miRNAs were significantly modulated between the END and control groups. Enrichment analysis identified targets significantly overrepresented in numerous pathways involved in biological processes related to END, including inflammation, angiogenesis, cellular invasion, cell-cycle/cell proliferation, and estrogen and progesterone hormonal signaling. Conclusions: Our study indicates that differentially expressed miRNAs between END patients and controls can be identified through liquid biopsy. Our findings also suggest a potential role for serum miRNAs in the pathophysiology of END, warranting further investigations for their use as non-invasive biomarkers.

STUDY QUESTION: Can a serum miRNA signature serve as a potential diagnostic biomarker for endometriosis (END)? SUMMARY ANSWER: A miRNA-based diagnostic model demonstrated an accuracy of 65.8% in distinguishing END patients from control subjects (CTR), demonstrating good sensitivity but limited specificity. WHAT IS KNOWN ALREADY: Existing research has examined the potential utility of circulating miRNAs as biomarkers for END diagnosis, revealing their differential expression between women with END and CTR. Nevertheless, the findings remain conflicting, and at present, neither a single miRNA nor a panel of them has yet been established as a reliable diagnostic test in clinical practice for the management of END. STUDY DESIGN, SIZE, DURATION: We previously reported different miRNA expression patterns in serum samples from 67 END patients and 60 CTR by high-throughput RT-qPCR. In this multicenter study, a total of 364 patients with pathology-confirmed diagnosis of END or a benign non-END gynecological condition were retrospectively selected from a biobank or prospectively enrolled. The aims of the present study were to analyze, in the entire cohort of patients, a set of 23 potential diagnostic miRNAs via RT-qPCR and to create models capable of diagnosing END through cross-validated machine learning algorithms. PARTICIPANTS/MATERIALS, SETTING, METHODS: Total RNA was extracted from serum samples collected before surgical treatment and miRNAs were evaluated by RT-qPCR. Diagnostic models were developed using both the Random Forest and Logistic Regression algorithms. The performance assessment of the various models was derived from internal validation, using repeated cross-validation. MAIN RESULTS AND THE ROLE OF CHANCE: The most effective diagnostic model was constructed with 11 miRNAs: miR-140-3p, miR-181a-5p, miR-192-5p, miR-22-3p, miR-29a-3p, miR-30b-5p, miR-338-3p, miR-340-5p, miR-342-3p, miR-486-5p, and miR-652-3p. The diagnostic efficacy of the model was defined by an AUC of 70.4%, a sensitivity of 75.6%, a specificity of 53.5%, and an accuracy of 65.8%. The model that used six miRNAs (miR-192-5p, miR-30b-5p, miR-335-5p, miR-338-3p, miR-486-5p, miR-652-3p) was the best at identifying deep infiltrating endometriosis compared to the control group, with an AUC of 80.4% and an accuracy of 75.9%. A lower accuracy was achieved by the model differentiating ovarian endometrioma (OMA) from CTR (AUC = 65.8%; accuracy = 62.4%). LARGE SCALE DATA: miRNA expression profiles have been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession numbers GSE279435. LIMITATIONS, REASONS FOR CAUTION: Despite the internal cross-validation, the models still need to be tested on larger cohorts of prospectively enrolled patients across several centers to enhance their accuracy and robustness. This testing will also facilitate monitoring the model in a real-world setting, potentially integrating the miRNA-based model with other diagnostic tools, such as ultrasound. WIDER IMPLICATIONS OF THE FINDINGS: If proven effective in larger cohorts, this model could serve as a tool for the diagnosis of END, thereby enhancing early identification and clinical care of this disease. Moreover, given its low false negative rate, the miRNA-based model may be useful as a screening tool to help identify patients who are likely to have END but warrant further evaluation to confirm END diagnosis. STUDY FUNDING/COMPETING INTEREST(S): This research was financed by the Italian Ministry of Health, grant number “LOMBARDIA ENDO-2021-12371946”, project title: FREEDOM TRIAL, and the Italian Ministry of Research (PRIN project n. 2022SYXEHJ to SC). The authors disclose no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Pathogenic mutations in BRCA1/2 are associated with improved survival in high-grade serous ovarian carcinoma, but the prognostic impact of specific mutations remains unclear. The primary aim of this study was to evaluate the role of different locations, types, and functions of BRCA1/2 mutations on survival in patients with high-grade serous ovarian carcinoma. This study included a total of 174 patients with advanced-stage high-grade serous ovarian cancer, 74 women with BRCA1/2 mutations, and 100 wild-type controls. Mutations were categorized based on gene (BRCA1 vs BRCA2), location (inside exon 11 vs outside; functional domains), type (frameshift, nonsense, missense), and function (truncated protein vs amino acid change). Poly (adenosine diphosphate-ribose) polymerase inhibitor exposure was defined as receipt of maintenance therapy in first or subsequent lines. Survival outcomes were analyzed using univariate and multi-variate models. In multi-variate analysis, adjusted for residual tumor and International Federation of Gynecology and Obstetrics stage, mutations in BRCA2 RAD51-BD (hazard ratio 0.03, P=.001) and in BRCA1 DNA-binding domain (hazard ratio 0.23, p =.008) were associated with the most favorable prognosis compared to wild type. In contrast, BRCA1 BRCT or RING domain mutations showed survival outcomes similar to wild type. Frameshift (hazard ratio 0.17, p <.001) and nonsense mutations (hazard ratio 0.4, p =.016) were associated with improved survival compared to wild type, whereas missense variants were not. In patients not receiving poly (adenosine diphosphate-ribose) polymerase inhibitors, the presence of a BRCA2 or BRCA1 mutation was an independent marker of improved overall survival (hazard ratio 0.09, p <.001 and hazard ratio 0.37, p =.006, respectively), while the presence of residual tumor (>0) and International Federation of Gynecology and Obstetrics stage IV were associated with worse prognosis (hazard ratio 3.07, p =.001; hazard ratio 1.93, p =.031, respectively). In the poly (adenosine diphosphate-ribose) polymerase inhibitor-treated group, only BRCA2 mutations remained significantly associated with improved overall survival (hazard ratio 0.12, p =.043). The prognostic value of BRCA1/2 mutations in high-grade serous ovarian carcinoma may depend on their specific location and type. If validated in larger cohorts, our findings could influence patient stratification and should be considered in future clinical trial design.

Background/Objectives: Despite advances in targeted therapies, a substantial proportion of high-risk endometrial carcinomas (EC) do not respond to treatment and have a poor prognosis. The identification of prognostic and predictive biomarkers to improve patient stratification is therefore a clinical priority. L1 cell adhesion molecule (L1CAM) is a promising biomarker in EC; however, its soluble circulating form (sL1CAM) has been poorly investigated. This study aimed to evaluate the prognostic and predictive significance of sL1CAM in high-risk ECs. Methods: High-risk EC patients, treated with surgery and platinum-based adjuvant chemotherapy, were retrospectively enrolled. sL1CAM levels were quantified in 72 preoperative serum samples by enzyme-linked immunosorbent assay (ELISA). Results: High sL1CAM levels were associated with advanced age and non-endometrioid histology. Across the entire patient cohort, higher sL1CAM concentrations significantly correlated with worse prognosis in terms of DSS and PFS in univariate (DSS: HR = 2.22, p = 0.028; PFS: HR = 1.21, p = 0.041) and multivariate (DSS: HR = 2.13, p = 0.041; PFS: HR = 1.93, p = 0.048) analyses. Stratification by histological type revealed a significant prognostic association only in the endometrioid subgroup, both in univariate and multivariate analyses. Moreover, in this subgroup, elevated sL1CAM levels were associated with shorter time to recurrence after chemotherapy, both in univariate (PFI: HR = 2.69, p = 0.027) and multivariate (PFI: HR = 2.97, p = 0.017) analysis, and significantly predicted relapse within 6 months (OR = 7.83, p = 0.027). Conclusions: sL1CAM is associated with poor prognosis in high-risk EC and seems to be associated with platinum response in endometrioid tumors. These findings support its potential role as a biomarker to improve risk stratification, warranting validation in larger, prospective studies.