Uterine leiomyosarcoma (uLMS) is a type of malignant soft-tissue tumor, which is developed from myometrium in the female reproductive system. This disease is difficult to be distinguished from benign uterine leiomyoma in the early stages, but it progresses aggressively and relentlessly. Hence, uLMS has a dismal prognosis and high rates of both misdiagnosis and missed diagnosis. Unfortunately, current studies of uLMS pathogenesis and disease biology are inadequate. uLMS disease models are also very limited, hindering the development of effective therapeutics. In this review, we focus on the pathological molecular biology of uLMS, and systematically review the molecular genetic features, epigenetic variants, experimental models, and clinical research progress of uLMS. We further discuss the development direction and potential needs of uLMS in the fields of tumor evolution, tumor microenvironment, and tumor therapy, with the aim of providing a better understanding of the pathobiological mechanism of uLMS and providing a reference for the development of potential diagnostic and therapeutic strategies.
子宫平滑肌肉瘤(uterine leiomyosarcoma，uLMS)是一种发生在女性生殖系统子宫肌层的恶性软组织肿瘤，漏诊误诊率高、侵袭性强、预后差。uLMS的发生机制尚未明确，疾病生物学研究相对滞后，实验模型和治疗手段也较为有限。本文重点关注了uLMS的病理分子生物学，系统梳理了uLMS的分子遗传学特征、表观遗传学变异、实验模型以及临床研究进展，同时还探讨了uLMS在肿瘤演进、肿瘤微环境、肿瘤治疗等生物学研究领域的发展方向和潜在需求，以期更好地理解uLMS的病理生物学机制并为开发潜在诊疗策略提供参考。.

BACKGROUND: Leiomyosarcoma is a tumor that can develop in any organ that contains smooth muscles. Although leiomyosarcoma is common, its epididymal localization is quite rare.
METHODS: A 79-year-old male Chinese Han patient presented with mild pain in the right groin and scrotum for 3 years concomitant with right scrotal swelling. Ultrasonography and magnetic resonance imaging of the scrotum showed a irregular and heterogeneous mass that was extratesticular. Right high orchiectomy was performed, and pathological examination of the resected specimen confirmed the diagnosis of leiomyosarcoma of the epididymis with surgical margins clear of tumor.
CONCLUSIONS: Epididymal leiomyosarcoma is rare and difficult to diagnose preoperatively. The final diagnosis of epididymal leiomyosarcoma requires histologic examination. Resection must be extensive and complete. The effect of chemotherapy and radiation on the epididymal leiomyosarcoma remains unclear. Recurrence is common, so follow-up is necessary.

BACKGROUND: Uterine sarcoma is a rare and heterogeneous gynecological malignancy characterized by aggressive progression and poor prognosis. The current study aimed to investigate the relationship between clinicopathological characteristics and the prognosis of uterine sarcoma in Chinese patients.
METHODS: In this single-center retrospective study, we reviewed the medical records of 75 patients with histologically verified uterine sarcoma treated at the First Affiliated Hospital of Xi\'an Jiaotong University between 2011 and 2020. Information on clinical characteristics, treatments, pathology and survival was collected. Progression-free survival (PFS) and overall survival (OS) were visualized in Kaplan-Meier curves. Prognostic factors were identified using the log-rank test for univariate analysis and Cox-proportional hazards regression models for multivariate analysis.
RESULTS: The histopathological types included 36 endometrial stromal sarcomas (ESS,48%), 33 leiomyosarcomas (LMS,44%) and 6 adenosarcomas (8%). The mean age at diagnosis was 50.2 ± 10.7 years. Stage I and low-grade accounted for the majority. There were 26 recurrences and 25 deaths at the last follow-up. The mean PFS and OS were 89.41 (95% CI: 76.07-102.75) and 94.03 (95% CI: 81.67-106.38) months, respectively. Univariate analysis showed that > 50 years, post-menopause, advanced stage, ≥ 1/2 myometrial invasion, lymphovascular space invasion and high grade were associated with shorter survival (P < 0.05). Color Doppler flow imaging positive signals were associated with shorter PFS in the LMS group (P = 0.046). The ESS group had longer PFS than that of the LMS group (99.56 vs. 76.05 months, P = 0.043). The multivariate analysis showed that post-menopause and advanced stage were independent risk factors of both PFS and OS in the total cohort and LMS group. In the ESS group, diagnosis age > 50 years and high-grade were independent risk factors of PFS, while high-grade and lymphovascular space invasion were independent risk factors of OS.
CONCLUSIONS: In Chinese patients with uterine sarcoma, post-menopause and advanced stage were associated with a significantly poorer prognosis. The prognosis of ESS was better than that of LMS. Color Doppler flow imaging positive signals of the tumor helped to identify LMS, which needs to be further tested in a larger sample in the future.

UNASSIGNED: The aim of this study was to investigate the risk factors of postmenopausal special uterine leiomyoma pathological types or leiomyosarcoma and to develop a nomogram for clinical risk assessment, ultimately to reduce unnecessary surgical interventions and corresponding economic expenses.
UNASSIGNED: A total of 707 patients with complete information were enrolled from 1 August 2012 to 1 August 2022. Univariate and multivariate logistic regression models were used to analyse the association between variables and special uterine leiomyoma pathological types or leiomyosarcoma in postmenopausal patients. A nomogram for special uterine leiomyoma pathological types or leiomyosarcoma in postmenopausal patients was developed and validated by bootstrap resampling. The calibration curve was used to assess the accuracy of the model and receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were compared with the clinical experience model.
UNASSIGNED: The increasing trend after menopause, the diameter of the largest uterine fibroid, serum carcinoembryonic antigen 125 concentration, Serum neutrophil to lymphocyte ratio, and Serum phosphorus ion concentration were independent risk factors for special uterine leiomyoma pathological types or leiomyosarcoma in postmenopausal patients. We developed a user-friendly nomogram which showed good diagnostic performance (AUC=0.724). The model was consistent and the calibration curve of our cohort was close to the ideal diagonal line. DCA indicated that the model has potential value for clinical application. Furthermore, our model was superior to the previous clinical experience model in terms of ROC and DCA.
UNASSIGNED: We have developed a prediction nomogram for special uterine leiomyoma pathological types or leiomyosarcoma in postmenopausal patients. This nomogram could serve as an important warning signal and evaluation method for special uterine leiomyoma pathological types or leiomyosarcoma in postmenopausal patients.

The incidence of leiomyosarcoma (LMS) is about 4-5/100,000 individuals per year. LMSs occurring in the small bowel are even rarer, and their preoperative diagnosis is very difficult. We described two patients with pathologically confirmed small bowel LMS and analyzed their clinical and medical imaging features. Similar cases reported in English in Pubmed database over the past decade were reviewed and summarized. These tumors were categorized by the growth direction and relationship with the intestinal lumen into three types: intraluminal (n = 10), intermural (n = 3), and extraluminal (n = 7). Notably, among the three types of LMS, the intramural leiomyosarcoma stands out as a noteworthy subtype. Emerging evidence suggests that smaller tumor size (< 5 cm) and the intraluminal type may serve as favorable prognostic indicators, while the extraluminal type is associated with relatively poor prognosis. Furthermore, the integration of imaging features with CA125 and LDH biomarkers holds promise for potential diagnostic value in LMS.

Uterine leiomyomas (ULM) are the most common benign tumors of the female genitalia, while uterine leiomyosarcomas (ULMS) are rare. The sarcoma is diffuse growth, prone to hematogenous metastasis, and has a poor prognosis. Due to their similar clinical symptoms and morphological features, it is sometimes difficult to distinguish them, and the final diagnosis depends on histological diagnosis. Misdiagnosis of ULM as ULMS will lead to more invasive and extensive surgery when it is not needed, while misdiagnosis of ULMS as ULM may lead to delayed treatment and poor prognosis. This review searched and studied the published articles on ULM and ULMS, and summarized the potential markers for the differential diagnosis of ULMS. These markers will facilitate differential diagnosis and personalized treatment, providing timely diagnosis and potentially better prognosis for patients.

BACKGROUND: Primary thyroid leiomyosarcoma is an extremely rare soft tissue sarcoma, characterized by high malignancy and poor prognosis. Currently, only 13 cases of primary thyroid leiomyosarcoma have been described in the medical literature (limited to English).
METHODS: A 76-year-old female presented with a giant neck mass. Physical examination revealed a large, firm mass in the left thyroid gland. No symptoms such as hoarseness or dysphagia were noted at the time of presentation. The patient underwent unilateral thyroidectomy and cervical lymph node dissection.
UNASSIGNED: Pathologic findings revealed a low-grade sarcoma with spindle-shaped tumor cells in an interwoven, sheet-like distribution. Immunohistochemistry showed positivity for desmin, SMMHC, STAT6, CK19, and Galectin3, but negativity for S-100, MyoD1, CD34, CK (AE1/AE3), CD117, and CD56. The findings were consistent with thyroid leiomyosarcoma.
CONCLUSIONS: The treatment of primary thyroid LMS presents challenges due to its atypical symptoms and high malignance, highlighting the imperative for further exploration of therapeutic strategies to improve the outcomes.

暂无摘要。

OBJECTIVE: To investigate the clinicopathological characteristics and prognosis of patients with primary sarcoma of the uterine cervix.
METHODS: We identified all patients with primary cervical sarcomas treated at our institution from 2002 to 2020 and analyzed the clinicopathological characteristics and prognosis.
RESULTS: 34 patients were identified, 7 (20.6%) patients had leiomyosarcoma, 6 (17.6%) had carcinosarcoma, 5 (14.7%) had Ewing sarcoma, 4 (11.8%) had rhabdomyosarcoma, 4 (11.8%) had undifferentiated sarcoma, 2 (5.9%) had adenosarcoma, 2 (5.9%) had endometrial stromal sarcoma, 1 (2.9%) had dermatofibrosarcoma protuberans, 1 (2.9%) had alveolar soft tissue sarcoma and 2 (5.9%) had sarcoma not otherwise specified. The median age of the whole patients was 43.5 years (range, 13-63). The median age of patients with Ewing sarcoma or rhabdomyosarcoma was 22 years (range, 13-39) and 17 years (range, 13-36 years), respectively. The distribution by stage was: stage I in 21 (61.8%) patients, stage II in 4 (11.8%), stage III in 6 (17.6%) and stage IV in 3 (8.8%). Overall, 30 patients (88.2%) received surgical treatment. The median follow-up was 33.3 months (range 3.6-187.3 months). 11 patients died within 2 years after diagnosis, most of them were patients with carcinosarcoma or undifferentiated sarcoma (45.5%, 5/11). In the entire cohort, 2- and 5-year OS were 67.2% and 56.9%, respectively. 5-year OS was 25.0% for undifferentiated sarcoma, 50.0% for rhabdomyosarcoma, 50.0% for carcinosarcoma, 53.3% for Ewing sarcoma, 57.1% for leiomyosarcoma.
CONCLUSIONS: Cervical sarcomas are rare neoplasms with multiple histological subtypes and follow an aggressive course. Prognosis may be associated with tumor histology and stage.

BACKGROUND: Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection.
METHODS: A total of 179 patients who had undergone surgery for the treatment of histologically confirmed RLS were retrospectively recruited from two tertiary sarcoma centers. Semantic segmentation features derived from a convolutional neural network deep learning model as well as conventional hand-crafted radiomics features were extracted from preoperative three-phase CECT images to quantify the sarcoma phenotypes. A conventional radiomics signature (RS) and a deep learning radiomics signature (DLRS) that incorporated hand-crafted radiomics and deep learning features were developed to predict the risk of MDM. Additionally, a deep learning radiomics nomogram (DLRN) was established to evaluate the incremental prognostic significance of the DLRS in combination with clinico-radiological predictors.
RESULTS: The comparison of the area under the curve (AUC) values in the external validation set, as determined by the DeLong test, demonstrated that the integrated DLRN, DLRS, and RS models all exhibited superior predictive performance compared with that of the clinical model (AUC 0.786 [95% confidence interval 0.649-0.923] vs. 0.822 [0.692-0.952] vs. 0.733 [0.573-0.892] vs. 0.511 [0.359-0.662]; both P < 0.05). The decision curve analyses graphically indicated that utilizing the DLRN for risk stratification provided greater net benefits than those achieved using the DLRS, RS and clinical models. Good alignment with the calibration curve indicated that the DLRN also exhibited good performance.
CONCLUSIONS: The novel CECT-based DLRN developed in this study demonstrated promising performance in the preoperative prediction of the risk of MDM following curative resection in patients with RLS. The DLRN, which outperformed the other three models, could provide valuable information for predicting surgical efficacy and tailoring individualized treatment plans in this patient population.
BACKGROUND: Not applicable.