Primary leiomyosarcoma of the uterine cervix: report of 4 cases, systematic review, and meta-analysis

Sarcoma of the uterine cervix: experience of a single center

OBJECTIVES

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.

CONCLUSION

Cervical sarcomas are rare neoplasms with multiple histological subtypes and follow an aggressive course. Prognosis may be associated with tumor histology and stage.

Preoperative Differentiation of Uterine Leiomyomas and Leiomyosarcomas: Current Possibilities and Future Directions

The distinguishing of uterine leiomyosarcomas (ULMS) and uterine leiomyomas (ULM) before the operation and histopathological evaluation of tissue is one of the current challenges for clinicians and researchers. Recently, a few new and innovative methods have been developed. However, researchers are trying to create different scales analyzing available parameters and to combine them with imaging methods with the aim of ULMs and ULM preoperative differentiation ULMs and ULM. Moreover, it has been observed that the technology, meaning machine learning models and artificial intelligence (AI), is entering the world of medicine, including gynecology. Therefore, we can predict the diagnosis not only through symptoms, laboratory tests or imaging methods, but also, we can base it on AI. What is the best option to differentiate ULM and ULMS preoperatively? In our review, we focus on the possible methods to diagnose uterine lesions effectively, including clinical signs and symptoms, laboratory tests, imaging methods, molecular aspects, available scales, and AI. In addition, considering costs and availability, we list the most promising methods to be implemented and investigated on a larger scale.

TIM-3 as a Prognostic Marker and a Potential Immunotherapy Target in Human Malignant Tumors: A Meta-Analysis and Bioinformatics Validation

Background

As a novel immune checkpoint molecular, T-cell immunoglobulin mucin 3 (TIM-3) is emerging as a therapeutic target for cancer immunotherapy. However, the predictive role of TIM-3 in cancer remains largely undetermined. This study was designed to investigate the role of TIM-3 in cancer.

Methods

Publications were searched using multiple databases. The hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. To further confirm the prognostic effect of TIM-3, The Cancer Genome Atlas (TCGA) data were applied. Functional analysis of TIM-3 was also investigated.

Results

28 studies with 7284 patients with malignant tumors were identified. Based on multivariate Cox regression analysis, TIM-3 was an independent prognostic indicator for poor overall survival (OS) (HR= 1.54, 95% CI = 1.19-1.98, P = 0.001). However, TIM-3 was not correlated with cancer-specific survival and disease-free survival (DFS). Particularly, TIM-3 showed a worse prognosis in non-small cell lung carcinoma and gastric cancer; but it showed a favorable prognosis in breast cancer. Functional analysis showed that TIM-3 was closely correlated with immune responses such as T-cell activation and natural killer cell-mediated cytotoxicity. Moreover, TIM-3 expression was found to be related to worse OS in 9491 TCGA patients (HR = 1.2, P < 0.001), but was not associated with DFS.

Conclusions

TIM-3 was an independent prognostic factor. Meanwhile, TIM-3 played a crucial role in tumor immune responses. This supports TIM-3 as a promising target for cancer immunotherapy.