Circulating Transcripts and Biomarkers in Uterine Tumors: Is There a Predictive Role?

Ultrasound features using MUSA terms and definitions in uterine sarcoma and leiomyoma: cohort study

OBJECTIVES

Timely and accurate preoperative diagnosis of uterine sarcoma will increase patient survival. The primary aim of this study was to describe the ultrasound features of uterine sarcoma compared with those of uterine leiomyoma based on the terms and definitions of the Morphological Uterus Sonographic Assessment (MUSA) group. A secondary aim was to assess the interobserver agreement for reporting on ultrasound features according to MUSA terminology.

METHODS

This was a retrospective cohort study of patients with uterine sarcoma or uterine leiomyoma treated in a single tertiary center during the periods 1997-2019 and 2016-2019, respectively. Demographic characteristics, presenting symptoms and surgical outcomes were extracted from patients' files. Ultrasound images were re-evaluated independently by two sonologists using MUSA terms and definitions. Descriptive statistics were calculated and interobserver agreement was assessed using Cohen's κ (with squared weights) or intraclass correlation coefficient, as appropriate.

RESULTS

A total of 107 patients were included, of whom 16 had a uterine sarcoma and 91 had a uterine leiomyoma. Abnormal uterine bleeding was the most frequent presenting symptom (69/107 (64%)). Compared with leiomyoma cases, patients with uterine sarcoma were older (median age, 65 (interquartile range (IQR), 60-70) years vs 48 (IQR, 43-52) years) and more likely to be postmenopausal (13/16 (81%) vs 15/91 (16%)). In the uterine sarcoma cohort, leiomyosarcoma was the most frequent histological type (6/16 (38%)), followed by adenosarcoma (4/16 (25%)). On ultrasound evaluation, according to Observers 1 and 2, the tumor border was irregular in most sarcomas (11/16 (69%) and 13/16 (81%) cases, respectively), but regular in most leiomyomas (65/91 (71%) and 82/91 (90%) cases, respectively). Lesion echogenicity was classified as non-uniform in 68/91 (75%) and 51/91 (56%) leiomyomas by Observers 1 and 2, respectively, and 15/16 (94%) uterine sarcomas by both observers. More than 60% of the uterine sarcomas showed acoustic shadows (11/16 (69%) and 10/16 (63%) cases by Observers 1 and 2, respectively), whereas calcifications were reported in a small minority (0/16 (0%) and 2/16 (13%) cases by Observers 1 and 2, respectively). In uterine sarcomas, intralesional vascularity was reported as moderate to abundant in 13/16 (81%) cases by Observer 1 and 15/16 (94%) cases by Observer 2, while circumferential vascularity was scored as moderate to abundant in 6/16 (38%) by both observers. Interobserver agreement for the presence of cystic areas, calcifications, acoustic shadow, central necrosis, color score (overall, intralesional and circumferential) and maximum diameter of the lesion was moderate. The agreement for shape of lesion, tumor border and echogenicity was fair.

CONCLUSIONS

A postmenopausal patient presenting with abnormal uterine bleeding and a new or growing mesenchymal mass with irregular tumor borders, moderate-to-abundant intralesional vascularity, cystic areas and an absence of calcifications on ultrasonography is at a higher risk of having a uterine sarcoma. Interobserver agreement for most MUSA terms and definitions is moderate. Future studies should validate the abovementioned clinical and ultrasound findings on uterine mesenchymal tumors in a prospective multicenter fashion. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Management of Uterine Fibroids and Sarcomas: The Palermo Position Paper

BACKGROUND

Uterine fibroids are benign monoclonal tumors originating from the smooth muscle cells of the myometrium, constituting the most prevalent pathology within the female genital tract. Uterine sarcomas, although rare, still represent a diagnostic challenge and should be managed in centers with adequate expertise in gynecological oncology.

OBJECTIVES

This article is aimed to summarize and discuss cutting-edge elements about the diagnosis and management of uterine fibroids and sarcomas.

METHODS

This paper is a report of the lectures presented in an expert meeting about uterine fibroids and sarcomas held in Palermo in February 2023.

OUTCOME

Overall, the combination of novel molecular pathways may help combine biomarkers and expert ultrasound for the differential diagnosis of uterine fibroids and sarcomas. On the one hand, molecular and cellular maps of uterine fibroids and matched myometrium may enhance our understanding of tumor development compared to histologic analysis and whole tissue transcriptomics, and support the development of minimally invasive treatment strategies; on the other hand, ultrasound imaging allows in most of the cases a proper mapping the fibroids and to differentiate between benign and malignant lesions, which need appropriate management.

CONCLUSIONS AND OUTLOOK

The choice of uterine fibroid management, including pharmacological approaches, surgical treatment, or other strategies, such as high-intensity focused ultrasound (HIFU), should be carefully considered, taking into account the characteristics of the patient and reproductive prognosis.

Advances in the Preoperative Identification of Uterine Sarcoma

Simple Summary

As a lethal malignant tumor, uterine sarcomas lack specific diagnostic criteria due to their similar presentation with uterine fibroids, clinicians are prone to make the wrong diagnosis or adopt incorrect treatment methods, which leads to rapid tumor progression and increased metastatic propensity. In recent years, with the improvement of medical level and awareness of uterine sarcoma, more and more studies have proposed new methods for preoperative differentiation of uterine sarcoma and uterine fibroids. This review outlines the up-to-date knowledge about preoperative differentiation of uterine sarcoma and uterine fibroids, including laboratory tests, imaging examinations, radiomics and machine learning-related methods, preoperative biopsy, integrated model and other relevant emerging technologies, and provides recommendations for future research.

Abstract

Uterine sarcomas are rare malignant tumors of the uterus with a high degree of malignancy. Their clinical manifestations, imaging examination findings, and laboratory test results overlap with those of uterine fibroids. No reliable diagnostic criteria can distinguish uterine sarcomas from other uterine tumors, and the final diagnosis is usually only made after surgery based on histopathological evaluation. Conservative or minimally invasive treatment of patients with uterine sarcomas misdiagnosed preoperatively as uterine fibroids will shorten patient survival. Herein, we will summarize recent advances in the preoperative diagnosis of uterine sarcomas, including epidemiology and clinical manifestations, laboratory tests, imaging examinations, radiomics and machine learning-related methods, preoperative biopsy, integrated model and other relevant emerging technologies.

Clinical Value and Molecular Function of Circulating MicroRNAs in Endometrial Cancer Regulation: A Systematic Review

This systematic review of literature highlights the different microRNAs circulating in the serum or plasma of endometrial cancer patients and their association with clinical and prognostic characteristics in endometrial cancer. This study also investigates the molecular functions of these circulating microRNAs. According to this systematic review, a total of 33 individual circulating miRs (-9, -15b, -20b-5p, -21, -27a, -29b, -30a-5p, -92a, -99a, -100, -135b, -141, -142-3p, -143-3p, -146a-5p, -150-5p, -151a-5p, -186, -195-5p, -199b, -200a, -203, -204, -205, -222, -223, -301b, -423-3p, -449, -484, -887-5p, -1228, and -1290) and 6 different panels of miRs (“miR-222/miR-223/miR-186/miR-204”, “miR-142-3p/miR-146a-5p/miR-151a-5p”, “miR-143-3p/miR-195-5p/miR-20b-5p/miR-204-5p/miR-423-3p/miR-484”, “mir-9/miR-1229”, “miR-9/miR-92a”, and “miR-99a/miR-199b”) had a significant expression variation in EC patients compared to healthy patients. Also, seven individual circulating miRs (-9, -21, -27a, -29b, -99a, -142-3p, and -449a) had a significant expression variation according to EC prognostic factors such as the histological type and grade, tumor size, FIGO stage, lymph node involvement, and survival rates. One panel of circulating miRs (“-200b/-200c/-203/-449a”) had a significant expression variation according to EC myometrial invasion. Further studies are needed to better understand their function and circulation.

Combining Clinicopathological Parameters and Molecular Indicators to Predict Lymph Node Metastasis in Endometrioid Type Endometrial Adenocarcinoma

Background

Lymph node metastasis (LNM) is a critical unfavorable prognostic factor in endometrial cancer (EC). At present, models involving molecular indicators that accurately predict LNM are still uncommon. We addressed this gap by developing nomograms to individualize the risk of LNM in EC and to identify a low-risk group for LNM.

Methods

In all, 776 patients who underwent comprehensive surgical staging with pelvic lymphadenectomy at the First Affiliated Hospital of Chongqing Medical University were divided into a training cohort (used for building the model) and a validation cohort (used for validating the model) according to a predefined ratio of 7:3. Logistics regression analysis was used in the training cohort to screen out predictors related to LNM, after which a nomogram was developed to predict LNM in patients with EC. A calibration curve and consistency index (C-index) were used to estimate the performance of the model. A receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of the risk probability of LNM predicted by the model proposed in this study. Then, the prediction performance of different models and their discrimination abilities for identifying low-risk patients were compared.

Result

LNM occurred in 87 and 42 patients in the training and validation cohorts, respectively. Multivariate logistic regression analysis showed that histological grade (P=0.022), myometrial invasion (P=0.002), lymphovascular space invasion (LVSI) (P=0.001), serum CA125 (P=0.008), Ki67 (P=0.012), estrogen receptor (ER) (0.009), and P53 (P=0.003) were associated with LNM; a nomogram was then successfully established on this basis. The internal and external calibration curves showed that the model fits well, and the C-index showed that the prediction accuracy of the model proposed in this study was better than that of the other models (the C-index of the training and validation cohorts was 0.90 and 0.91, respectively). The optimal threshold of the risk probability of LNM predicted by the model was 0.18. Based on this threshold, the model showed good discrimination for identifying low-risk patients.

Conclusion

Combining molecular indicators based on classical clinical parameters can predict LNM of patients with EC more accurately. The nomogram proposed in this study showed good discrimination for identifying low-risk patients with LNM.

Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer

Simple Summary

Endometrial cancer is the commonest cancer of the female genital tract and obesity is its main modifiable risk factor. Over 80% of endometrial cancers develop in the context of obesity-induced metabolic changes. This study focuses on the potential of plasma-based metabolites to enable the early detection of endometrial cancer in a cohort of women with body mass index (BMI) ≥ 30 kg/m². Specific lipid metabolites including phospholipids and sphingolipids (sphingomyelins) demonstrated good accuracy for the detection of endometrial cancer, especially when combined in a diagnostic model. This study advances our knowledge of the role of metabolomics in endometrial cancer and provides a basis for the minimally invasive screening of women with elevated BMI.

Abstract

Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥ 30 kg/m² and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m².