Fucoidan is a natural derived compound found in different species of brown algae and in some animals, that has gained attention for its anticancer properties. However, the exact mechanism of action is currently unknown. Therefore, this review will address fucoidans structure, the bioavailability, and all known different pathways affected by fucoidan, in order to formulate fucoidans structure and activity in relation to its anti-cancer mechanisms. The general bioactivity of fucoidan is difficult to establish due to factors like species-related structural diversity, growth conditions, and the extraction method. The main pathways influenced by fucoidan are the PI3K/AKT, the MAPK pathway, and the caspase pathway. PTEN seems to be important in the fucoidan-mediated effect on the AKT pathway. Furthermore, the interaction with VEGF, BMP, TGF-β, and estrogen receptors are discussed. Also, fucoidan as an adjunct seems to have beneficial effects, for both the enhanced effectiveness of chemotherapy and reduced toxicity in healthy cells. In conclusion, the multipotent character of fucoidan is promising in future anti-cancer treatment. However, there is a need for more specified studies of the structure–activity relationship of fucoidan from the most promising seaweed species.

Myeloid-derived suppressor cells (MDSCs) expansion is a hallmark of cancer. Three major MDSC subsets defined as monocytic (M)-MDSCs, polymorphonuclear (PMN)-MDSCs and early stage (e)MDSCs can be revealed in human diseases. However, the clinical relevance and immunosupressive pattern of these cells in epithelial ovarian cancer (EOC) are unknown. Therefore, we performed a comprehensive analysis of each MDSC subset and immunosupressive factors in the peripheral blood (PB), peritoneal fluid (PF), and the tumor tissue (TT) samples from EOC and integrated this data with the patients' clinicopathological characteristic. MDSCs were analyzed using multicolor flow cytometry. Immunosuppressive factors analysis was performed with ELISA and qRT-PCR. The level of M-MDSCs in the PB/PF/TT of EOC was significantly higher than in healthy donors (HD); frequency of PMN-MDSCs was significantly greater in the TT than in the PB/PF and HD; while the level of eMDSCs was greater in the PB compared with the PF and HD. Elevated abundance of tumor-infiltrating M-MDSCs was associated with advanced stage and high grade of EOC. An analysis of immunosuppressive pattern showed significantly increased blood-circulating ARG/IDO/IL-10-expressing M- and PMN-MDSCs in the EOC patients compared with HD and differences in the accumulation of these subsets in the three tumor immune microenvironments (TIME). This accumulation was positively correlated with levels of TGF-β and ARG1 in the plasma and PF. Low level of blood-circulating and tumor-infiltrating M-MDSCs, but neither PMN-MDSCs nor eMDSCs was strongly associated with prolonged survival in ovarian cancer patients. Our results highlight M-MDSCs as the subset with potential the highest clinical significance.

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.

The aim of the study was to assess the activity of fucoidan on the uterine sarcomas (MES-SA and ESS-1) and carcinosarcoma cell lines (SK-UT-1 and SK-UT-1B) and its toxicity on the human skin fibroblasts (HSF). Two uterine sarcomas and two carcinosarcoma cell lines were examined, as a control HSF were used. Cell viability was assessed with MTT test, apoptosis with caspase-3 activity and cell cycle by assessment of DNA synthesis. Fucoidan significantly decreases cell viability in SK-UT-1, SK-UT-1B, and ESS-1 cell lines, such effect was not observed in MES-SA. Fucoidan was not substantially affecting proliferation among normal cells. The tested agent induced apoptosis in all cell cultures used in the experiment. Fucoidan affects cell cycle of all tested cell lines except MES-SA by increasing percentage of cells in G0/sub-G1/G1 phase. Fucoidan do not only affect proliferation but induces apoptosis in selected uterine sarcoma and carcinosarcoma cell lines, so it has potential to be used as cytotoxic agent. Fucoidan seems to be promising anti-cancer agent for endometrial stromal sarcoma and carcinosarcoma.

Progress in cancer treatment made by the beginning of the 21st century has shifted the paradigm from one-size-fits-all to tailor-made treatment. The popular vision, to study solid tumors through the relatively noninvasive sampling of blood, is one of the most thrilling and rapidly advancing fields in global cancer diagnostics. From this perspective, immune-cell analysis in cancer could play a pivotal role in oncology practice. This approach is driven both by rapid technological developments, including the analysis of circulating myeloid-derived suppressor cells (cMDSCs), and by the increasing application of (immune) therapies, the success or failure of which may depend on effective and timely measurements of relevant biomarkers. Although the implementation of these powerful noninvasive diagnostic capabilities in guiding precision cancer treatment is poised to change the ways in which we select and monitor cancer therapy, challenges remain. Here, we discuss the challenges associated with the analysis and clinical aspects of cMDSCs and assess whether the problems in implementing tumor-evolution monitoring as a global tool in personalized oncology can be overcome.