Exploration of Extracellular Vesicle Long Non-Coding RNAs in Serum of Patients with Cervical Cancer.

INTRODUCTION: Cervical cancer (CC) is the fourth most common cancer type and a leading cause of cancer-related deaths in women worldwide. Its underlying molecular mechanisms are unclear. Cancer cell-derived extracellular vesicles (EVs) are involved in cancer development and progression by delivering regulatory factors, including microRNAs and long non-coding RNAs (lncRNAs). METHODS: Here, we identified the EV lncRNA expression profiles associated with different developmental stages of CC using next-generation sequencing. EVs from the serum of patients with stages I-III CC and healthy donors were characterized using EV marker immunoblotting and transmission electron microscopy. RESULTS: The EV concentration increases with progression of the disease. Most particles had a 100-250-nm diameter, and their sizes were similar in all groups. We identified many lncRNAs that were uniquely and differentially expressed (DE) in patients with different stages of CC. The pathway analysis results indicated that the upregulated DE EV lncRNAs abundant in stages I and II were associated with cell proliferation and inflammation and cancer progression pathways, respectively. LINC00941, LINC01910, LINC02454, and DSG2-AS1 were highly expressed, suggesting poor overall survival of CC patients. Interestingly, DSG2-AS1 was associated with the human papillomavirus infection pathway through AKT3, DLG1, and COL6A2 genes. CONCLUSION: This is the first study that reports the levels of EVs and their lncRNA contents change during cancer development, demonstrating the existence of a unique vesicle-mediated cell-to-cell communication network underlying cancer progression.

Proteomic profiling of urinary extracellular vesicles differentiates breast cancer patients from healthy women.

Urinary extracellular vesicles (uEVs) reflect the biological conditions of the producing cells. The protein profiling of uEVs allow us to better understand cancer progression in several cancers such as bladder cancer, prostate cancer and kidney cancer but has not been reported in breast cancer. We have, herein, aimed at quantifying the concentration and at generating the proteomic profile of uEVs in patients with breast cancer (BC) as compared to that of healthy controls (CT). Urine samples were collected from 29 CT and 47 patients with BC. uEVs were isolated by using differential ultracentrifugation, and were then characterized by Western blotting and transmission electron microscopy. Moreover, a nanoparticle tracking analysis was used in order to measure the concentration and the size distribution of urine particles and uEVs. The proteomic profiling of the uEVs was facilitated through LC-MS/MS. The uEV concentration was not significantly different between the assessed groups. The undertaken proteomic analysis revealed 15,473 and 11,278 proteins in the BC patients' group and the CT group, respectively. Furthermore, a heat map analysis revealed a differential protein expression, while a principal component analysis highlighted two clusters. The volcano plot indicated 259 differentially expressed proteins (DEPs; 155 up- and 104 down-regulated proteins) in patients with BC compared with CT. The up-regulated proteins from BC-derived uEVs were enriched in pathways related to cancer progression (i.e., cell proliferation, cell survival, cell cycle, cell migration, carbohydrate metabolism, and angiogenesis). Moreover, we verified the expression of the upregulated DEPs using UALCAN for web-based validation. Remarkably, the results indicated that 6 of 155 up-regulated proteins (POSTN, ATAD2, BCAS4, GSK3ß, HK1, and Ki-67) were overexpressed in BC compared with normal samples. Since these six proteins often act as markers of cell proliferation and progression, they may be potential biomarkers for BC screening and diagnosis. However, this requires validation in larger cohorts.

Integrated bioinformatic analysis of potential biomarkers of poor prognosis in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease associated with late-stage diagnosis and high metastatic rates. However, a gene signature for reliable TNBC biomarkers is not available yet. We aimed to identify potential key genes and their association with poor prognosis in TNBC through integrated bioinformatics. Methods: Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in TNBC vs. non-TNBC and TNBC vs. normal tissues were analyzed. Overlapping upregulated and downregulated DEGs were selected as inputs for Gene Ontology and pathway enrichment analyses using Metascape. Then, UALCAN and Kaplan-Meier plotter were employed to analyze the prognostic values of all overlapping DEGs. Results: We identified 21 upregulated and 24 downregulated overlapping DEGs in TNBC vs. non-TNBC and TNBC vs. normal breast tissue. The upregulated overlapping DEGs were mainly enriched in various pathways including chromosome segregation, cell cycle phase transition, and cell division, whereas overlapping DEGs were significantly downregulated in pathways, such as multicellular organismal homeostasis, tissue homeostasis, and negative regulation of cell population proliferation. Key genes were identified by association with poor overall survival (OS). Our results showed that high expression of CENPW and HORMAD1 was associated with poor OS of TNBC patients. Conversely, the low expression of PIP, APOD, and ZNF703 indicated worse OS. Conclusions: We identified key genes (CENPW, HORMAD1, APOD, PIP, and ZNF703) associated with poor OS. Thus, these genes might serve as candidate prognostic markers for TNBC.

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

Triple negative breast cancer (TNBC) lacks well-defined molecular targets and is highly heterogenous, making treatment challenging. Using gene expression analysis, TNBC has been classified into four different subtypes: basal-like immune-activated (BLIA), basal-like immune-suppressed (BLIS), mesenchymal (MES), and luminal androgen receptor (LAR). However, there is currently no standardized method for classifying TNBC subtypes. We attempted to define a gene signature for each subtype, and to develop a classification method based on machine learning (ML) for TNBC subtyping. In these experiments, gene expression microarray data for TNBC patients were downloaded from the Gene Expression Omnibus database. Differentially expressed genes unique to 198 known TNBC cases were identified and selected as a training gene set to train in seven different classification models. We produced a training set consisting of 719 DEGs selected from uniquely expressed genes of all four subtypes. The highest average accuracy of classification of the BLIA, BLIS, MES, and LAR subtypes was achieved by the SVM algorithm (accuracy 95-98.8%; AUC 0.99-1.00). For model validation, we used 334 samples of unknown TNBC subtypes, of which 97 (29.04%), 73 (21.86%), 39 (11.68%) and 59 (17.66%) were predicted to be BLIA, BLIS, MES, and LAR, respectively. However, 66 TNBC samples (19.76%) could not be assigned to any subtype. These samples contained only three upregulated genes (EN1, PROM1, and CCL2). Each TNBC subtype had a unique gene expression pattern, which was confirmed by identification of DEGs and pathway analysis. These results indicated that our training gene set was suitable for development of classification models, and that the SVM algorithm could classify TNBC into four unique subtypes. Accurate and consistent classification of the TNBC subtypes is essential for personalized treatment and prognosis of TNBC.

The Anticancer Effects of FDI-6, a FOXM1 Inhibitor, on Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) presents an important clinical challenge, as it does not respond to endocrine therapies or other available targeting agents. FOXM1, an oncogenic transcriptional factor, has reported to be upregulated and associated with poor clinical outcomes in TNBC patients. In this study, we investigated the anti-cancer effects of FDI-6, a FOXM1 inhibitor, as well as its molecular mechanisms, in TNBC cells. Two TNBC cell lines, MDA-MB-231 and HS578T, were used in this study. The anti-cancer activities of FDI-6 were evaluated using various 2D cell culture assays, including Sulforhodamine B (SRB), wound healing, and transwell invasion assays together with 3D spheroid assays, mimicking real tumour structural properties. After treatment with FDI-6, the TNBC cells displayed a significant inhibition in cell proliferation, migration, and invasion. Increased apoptosis was also observed in the treated cells. In addition, we found that FDI-6 lead to the downregulation of FOXM1 and its key oncogenic targets, including CyclinB1, Snail, and Slug. Interestingly, we also found that the FDI-6/Doxorubicin combination significantly enhanced the cytotoxicity and apoptotic properties, suggesting that FDI-6 might improve chemotherapy treatment efficacy and reduce unwanted side effects. Altogether, FDI-6 exhibited promising anti-tumour activities and could be developed as a newly effective treatment for TNBC.

Anti-breast cancer potential of frullanolide from Grangea maderaspatana plant by inducing apoptosis.

Breast cancer is the leading cause of female mortality worldwide. Although there are several modern treatments for breast cancer, there is a high rate of recurrence for the majority of treatments; therefore, the search for effective anticancer agents continues. The present study aimed to investigate the anti-breast cancer potential of frullanolide, a compound which is isolated and purified from the Grangea maderaspatana plant, for selected human breast cancer cell lines (MCF-7, MDA-MB-468 and MDA-MB-231). The MTT assay was used to assess cytotoxic activity in breast cancer cell lines of treatment with frullanolide at 1.25, 2.5, 5.0, 10.0 and 20.0 µg/ml. Additionally, the apoptotic induction ability of frullanolide at various concentrations [0.5×, 1× and 2× half maximal inhibitory concentration (IC50)] was investigated by flow cytometry and western blot analysis. Frullanolide exhibited strong anti-breast cancer activity against MDA-MB-468 (IC50, 8.04±2.69 µg/ml) and weak cytotoxicity against the MCF-7 (IC50, 10.74±0.86 µg/ml) and MDA-MB-231 (IC50, 12.36±0.31 µg/ml) cell lines. The IC50 of frullanolide was high in the human normal epithelial breast cell line (MCF-12A) and mouse fibroblast cell line (L-929). Density plot diagrams revealed that frullanolide induced apoptosis in MCF-7, MDA-MB-468 and MDA-MB-231 cells. Notably, a plausible anticancer mechanism was elucidated via cellular apoptosis by p53-independence in the treated MCF-7 cell line and p53-dependence in the treated MDA-MB-468 and MDA-MB-231 cell lines. In conclusion, the present study demonstrated that frullanolide may exert anticancer activity on breast cancer cell lines by inducing apoptosis. Frullanolide offers a possible novel approach to breast cancer therapy.

The role of WT1 isoforms in vasculogenic mimicry and metastatic potential of human triple negative breast cancer cells.

Triple negative breast cancer (TNBC) is highly aggressive and has a few therapeutic treatments, so new targeted therapy and biomarkers are required to provide alternative choices for treating TNBC patients. Recent studies showed that vasculogenic mimicry (VM), the formation of blood channels by aggressive cancer cells that mimic endothelial cells, is a factor contributing to poor prognosis in TNBC. Wilms' tumor 1 (WT1) gene has been found to be highly expressed in TNBC, and has 4 major distinct isoforms; isoform A (-17AA/-KTS; -/-), isoform B (+17AA/-KTS; +/-), isoform C (-17AA/+KTS; -/+) and isoform D (+17AA/+KTS; +/+). The involvement of each WT1 isoform in TNBC progression remains largely unclear. In this study, WT1 isoform-overexpressing cell sublines were established from a TNBC cell line, MDA-MB-231, by stable transfection, and the aggressive behavior of the cell sublines were evaluated. Only the WT1 isoform B- and isoform C-overexpressing cell sublines showed the significant increase in VM forming capability compared to the parental cell line and other isoform cell sublines. qRT-PCR was used to explore the change in expression level of two VM-related genes, EphA2 and VE-cadherin. All WT1 isoform cell sublines showed up-regulation of EphA2 but the levels detected in the isoform B- and isoform C-cell sublines were higher than those observed in other cell sublines. In contrast, significant up-regulation of VE-cadherin was found only in isoform A- and isoform D-cell sublines. Isoform B- and isoform C-cell sublines showed higher rates of cell migration compared to those of other cell sublines, as determined by both wound healing and Transwell assays. Gelatin zymography revealed increased MMP-9 enzyme production in isoform D-cell subline compared to the parental cell line, but this change was not observed in other cell sublines. Western blot analysis showed significantly increased expression of ß-catenin in isoform B- and isoform C-cell sublines, compared to parental cell line and other isoform cell sublines. In conclusion, our findings demonstrate that WT1 isoforms play different roles in modulating the VM-forming capacity and metastatic potential of TNBC cells.