BACKGROUND: This is a multicentre, single-arm, phase II study aimed at further exploring the activity of trabectedin as second-/further-line treatment in retroperitoneal leiomyosarcoma (LMS) and well-differentiated/dedifferentiated liposarcoma (LPS).
METHODS: The primary endpoint was the growth modulation index (GMI) defined as the ratio between PFS under trabectedin (PFS) and during previous chemotherapy treatment: time to progression (TTP-1). Secondary endpoints were objective response rate (ORR) and PFS. As per protocol, patients were considered responders if the GMI was >1.33, non-responders if <0.75 and neither if 0.76-1.32.
RESULTS: Overall 91 patients were assessable for the primary endpoint (32 patients with LMS and 59 patients with LPS): the median number of cycles received was 6.0 (Q1-Q3 3.0-12.0), and the main reason for treatment discontinuation was disease progression in 72% of patients. The median PFS was 6.0 months, while the median TTP1 was 7.5 months (8.1 and 6.4 months for LMS and LPS, respectively). Thirty-three patients [52%, 95% confidence interval (CI) 36% to 58%, P = 0.674, odds of response 1.1] had a GMI >1.33 (LMS 46%, 95% CI 26% to 67%, odds of response 0.85; LPS 56%, 95% CI 40% to 72%, odds of response 1.3). Overall, in LPS we observed 15/47 patients with a GMI <0.5 and 15/47 patients with a GMI >2. Among LMS patients, 9/26 had a GMI <0.5 and 10/26 had a GMI >2. Overall, ORR (complete response + partial response) was 16% (24% for LMS and 12% for LPS).
CONCLUSIONS: While the primary endpoint of the study was not met, we noticed a subgroup of patients with a markedly discrepant TTP with trabectedin in comparison to previous therapy (GMI <0.5 or >2, the latter including some patients with a long TTP with trabectedin). A mismatch between PFS and overall survival was observed, possibly due to the natural history of the two different histologies and the availability of further lines in LMS.

Most mesenchymal tumors found in the uterine corpus are benign tumors; however, uterine leiomyosarcoma is a malignant tumor with unknown risk factors that repeatedly recurs and metastasizes. In some cases, the histopathologic findings of uterine leiomyoma and uterine leiomyosarcoma are similar and surgical pathological diagnosis using excised tissue samples is difficult. It is necessary to analyze the risk factors for human uterine leiomyosarcoma and establish diagnostic biomarkers and treatments. Female mice deficient in the proteasome subunit low molecular mass peptide 2 (LMP2)/β1i develop uterine leiomyosarcoma spontaneously.
METHODS: Out of 334 patients with suspected uterine mesenchymal tumors, patients diagnosed with smooth muscle tumors of the uterus were selected from the pathological file. To investigate the expression status of biomarker candidate factors, immunohistochemical staining was performed with antibodies of biomarker candidate factors on thin-cut slides of human uterine leiomyosarcoma, uterine leiomyoma, and other uterine mesenchymal tumors.
CONCLUSIONS: In human uterine leiomyosarcoma, there was a loss of LMP2/β1i expression and enhanced cyclin E1 and Ki-67/MIB1 expression. In human uterine leiomyomas and normal uterine smooth muscle layers, enhanced LMP2/β1i expression and the disappearance of the expression of E1 and Ki-67/MIB1 were noted. The pattern of expression of each factor in other uterine mesenchymal tumors was different from that of uterine leiomyosarcoma.
CONCLUSIONS: LMP2/β1i, cyclin E1, and Ki-67/MIB1 may be candidate factors for biomarkers of human uterine leiomyosarcoma. Further large-cohort clinical trials should be conducted to establish treatments and diagnostics for uterine mesenchymal tumors.

(1) Background: Rare skin cancers include epithelial, neuroendocrine, and hematopoietic neoplasias as well as cutaneous sarcomas. Ultraviolet (UV) radiation and sunburns are important drivers for the incidence of certain cutaneous sarcomas; however, the pathogenetic role of UV light is less clear in rare skin cancers compared to keratinocyte cancer and melanoma. In this study, we compared the degree of actinic elastosis (AE) as a surrogate for lifetime UV exposure among selected rare skin cancers (atypical fibroxanthoma [AFX], pleomorphic dermal sarcoma [PDS], dermatofibrosarcoma protuberans [DFSP], Kaposi sarcoma [KS], Merkel cell carcinoma [MCC], and leiomyosarcoma [LMS]) while taking into account relevant clinical variables (age, sex, and body site). (2) Methods: We newly established a semi-quantitative score for the degree of AE ranging from 0 = none to 3 = total loss of elastic fibers (basophilic degeneration) and multiplied it by the perilesional vertical extent (depth), measured histometrically (tumor-associated elastosis grade (TEG)). We matched the TEG of n = 210 rare skin cancers from 210 patients with their clinical variables. (3) Results: TEG values were correlated with age and whether tumors arose on UV-exposed body sites. TEG values were significantly higher in AFX and PDS cases compared to all other analyzed rare skin cancer types. As expected, TEG values were low in DFSP and KS, while MCC cases exhibited intermediate TEG values. (4) Conclusions: High cumulative UV exposure is more strongly associated with AFX/PDS and MCC than with other rare skin cancers. These important results expand the available data associated with rare skin cancers while also offering insight into the value of differentiating among these tumor types based on their relationship with sun exposure, potentially informing preventative, diagnostic and/or therapeutic approaches.

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.

BACKGROUND: Up to half of patients with leiomyosarcoma (LMS) present with distant metastases, most commonly in the lungs. Despite guidelines around managing metachronous oligometastatic disease, limited evidence exists for synchronous isolated lung metastases (SILMs). Our histology-specific study describes management patterns and outcomes for patients with LMS and SILM across disease sites.
METHODS: We used the National Cancer Database to analyze patients with LMS of the retroperitoneum, extremity, trunk/chest/abdominal wall, and pelvis with SILM. Patients with extra-pulmonary metastases were excluded. We identified factors associated with primary tumor resection and receipt of metastasectomy. Outcomes included median, 1-year, and 5-year overall survival (OS) across treatment approaches using log-rank tests, Kaplan-Meier curves, and Cox proportional hazard models.
RESULTS: We identified 629 LMS patients with SILM from 2004 to 2017. Patients were more likely to have resection of their primary tumor or lung metastases if treated at an academic center compared to a community cancer center. Five year OS for patients undergoing both primary tumor resection and metastasectomy was 20.9% versus 9.2% for primary tumor resection alone, and 2.6% for nonsurgical patients. Median OS for all-comers was 15.5 mo. Community treatment site, comorbidity score, and larger primary tumors were associated with worse survival. Chemotherapy, primary resection, and curative intent surgery predicted improved survival on multivariate Cox regression.
CONCLUSIONS: An aggressive surgical approach to primary LMS with SILM was undertaken for select patients in our population and found to be associated with improved OS. This approach should be considered for suitable patients at high-volume centers.

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.

Introduction Uterine masses are commonly submitted for frozen section, to guide the surgeon, regarding the type and extent of the procedure during surgery. Despite the technical difficulties in processing, sectioning, and staining of frozen section samples, it remains a fairly reliable intraoperative tool. Aim This study aims to analyze the diverse spectrum of uterine masses sent for frozen sections for two years. In addition, it aims to analyze the histomorphology of the uterine masses sent for the frozen section and correlate it with that of the routine histopathological findings, thereby justifying the diagnostic value of the frozen section with this study. Furthermore, the study aims to classify the lesions into benign and malignant, quantify their frequency, and list the most common lesions seen in the uterine mass specimens sent for frozen section analysis. Methodology This retrospective descriptive study includes data from January 2021 to December 2022, retrieved from the archives of the Department of Pathology at Saveetha Medical College. This study includes a total of 76 cases, including all the uterine masses sent for frozen section analysis during the study period. Results Of the total of 76 cases received, 17 (22.4%) were malignant and 59 (77.6%) were benign. Of the malignant cases reported, the most common was endometrial carcinoma, and the least common entities encountered were carcinosarcoma and leiomyosarcoma. Of the benign cases, benign endometrial polyp was the most common endometrial lesion and leiomyoma with and without degeneration was the most common myometrial lesion encountered. Of the 50 cases of leiomyoma encountered, 16 had extensive degenerative changes. The most common degeneration seen in the fibroid was hyaline degeneration, and the least common was xanthogranulomatous degeneration. Conclusions The intraoperative frozen section analysis is a very important diagnostic tool, but we need to be aware of its limitations. The accuracy, sensitivity, and specificity rates were found to be high. Thus, frozen section diagnoses can be very valuable in the clinical management of uterine tumors. Careful gross examination, sampling from representative areas, and good communication between the pathologist and surgeon may help in avoiding its limitations.

HMGA1 is a structural epigenetic chromatin factor that has been associated with tumor progression and drug resistance. Here, we reported the prognostic/predictive value of HMGA1 for trabectedin in advanced soft-tissue sarcoma (STS) and the effect of inhibiting HMGA1 or the mTOR downstream pathway in trabectedin activity. The prognostic/predictive value of HMGA1 expression was assessed in a cohort of 301 STS patients at mRNA (n = 133) and protein level (n = 272), by HTG EdgeSeq transcriptomics and immunohistochemistry, respectively. The effect of HMGA1 silencing on trabectedin activity and gene expression profiling was measured in leiomyosarcoma cells. The effect of combining mTOR inhibitors with trabectedin was assessed on cell viability in vitro studies, whereas in vivo studies tested the activity of this combination. HMGA1 mRNA and protein expression were significantly associated with worse progression-free survival of trabectedin and worse overall survival in STS. HMGA1 silencing sensitized leiomyosarcoma cells for trabectedin treatment, reducing the spheroid area and increasing cell death. The downregulation of HGMA1 significantly decreased the enrichment of some specific gene sets, including the PI3K/AKT/mTOR pathway. The inhibition of mTOR, sensitized leiomyosarcoma cultures for trabectedin treatment, increasing cell death. In in vivo studies, the combination of rapamycin with trabectedin downregulated HMGA1 expression and stabilized tumor growth of 3-methylcholantrene-induced sarcoma-like models. HMGA1 is an adverse prognostic factor for trabectedin treatment in advanced STS. HMGA1 silencing increases trabectedin efficacy, in part by modulating the mTOR signaling pathway. Trabectedin plus mTOR inhibitors are active in preclinical models of sarcoma, downregulating HMGA1 expression levels and stabilizing tumor growth.

OBJECTIVE: This multicenter, single-arm, open-label, phase Ib study was designed to determine the recommended phase II dose (RP2D) and to evaluate the safety and preliminary efficacy of unesbulin plus dacarbazine (DTIC) in patients with advanced leiomyosarcoma (LMS).
METHODS: Adult subjects with locally advanced, unresectable or metastatic, relapsed or refractory LMS were treated with escalating doses of unesbulin orally twice per week in combination with DTIC 1,000 mg/m2 intravenously (IV) once every 21 days. The time-to-event continual reassessment method was used to determine the RP2D on the basis of dose-limiting toxicities (DLTs) assessed during the first two 21-day treatment cycles. All explored doses of unesbulin (200 mg up to 400 mg) were in combination with DTIC. An expansion cohort was enrolled to evaluate the safety and efficacy of unesbulin at the RP2D.
RESULTS: Unesbulin 300 mg administered orally twice per week in combination with DTIC 1,000 mg/m2 IV once every 21 days was identified as the RP2D. On the basis of data from 27 subjects who were deemed DLT-evaluable, toxicity was higher in the unesbulin 400 mg group, with three of four subjects (75%) experiencing DLTs versus one of four subjects (25%) in the 200 mg group and three of 19 subjects (15.8%) in the 300 mg group. The most commonly reported DLTs and treatment-related grade 3 and 4 adverse events were thrombocytopenia and neutropenia. At the RP2D, seven subjects who were efficacy evaluable achieved partial response for an objective response rate of 24.1%.
CONCLUSIONS: Unesbulin 300 mg twice per week plus DTIC 1,000 mg/m2 once every 21 days was identified as the RP2D, demonstrating a favorable benefit-risk profile in a heavily pretreated population of adults with advanced LMS.

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.