Prognostic and immunotherapeutic potential of regulatory T cell-associated signature in ovarian cancer.

Tumour-induced immunosuppressive microenvironments facilitate oncogenesis, with regulatory T cells (Tregs) serving as a crucial component. The significance of Treg-associated genes within the context of ovarian cancer (OC) remains elucidated insufficiently. Utilizing single-cell RNA sequencing (scRNA-Seq) for the identification of Treg-specific biomarkers, this investigation employed single-sample gene set enrichment analysis (ssGSEA) for the derivation of a Treg signature score. Weighted gene co-expression network analysis (WGCNA) facilitated the identification of Treg-correlated genes. Machine learning algorithms were employed to determine an optimal prognostic model, subsequently exploring disparities across risk strata in terms of survival outcomes, immunological infiltration, pathway activation and responsiveness to immunotherapy. Through WGCNA, a cohort of 365 Treg-associated genes was discerned, with 70 implicated in the prognostication of OC. A Tregs-associated signature (TAS), synthesized from random survival forest (RSF) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, exhibited robust predictive validity across both internal and external cohorts. Low TAS OC patients demonstrated superior survival outcomes, augmented by increased immunological cell infiltration, upregulated immune checkpoint expression, distinct pathway enrichment and differential response to immunotherapeutic interventions. The devised TAS proficiently prognosticates patient outcomes and delineates the immunological milieu within OC, offering a strategic instrument for the clinical stratification and selection of patients.

Integrative analysis from multi-center studies identifies a weighted gene co-expression network analysis-based Tregs signature in ovarian cancer.

Ovarian cancer (OC) is a malignancy associated with poor prognosis and has been linked to regulatory T cells (Tregs) in the immune microenvironment. Nevertheless, the association between Tregs-related genes (TRGs) and OC prognosis remains incompletely understood. The xCell algorithm was used to analyze Tregs scores across multiple cohorts. Weighted gene co-expression network analysis (WGCNA) was utilized to identify potential TRGs and molecular subtypes. Furthermore, we used nine machine learning algorithms to create risk models with prognostic indicators for patients. Reverse transcription-quantitative polymerase chain reaction and immunofluorescence staining were used to demonstrate the immunosuppressive ability of Tregs and the expression of key TRGs in clinical samples. Our study found that higher Tregs scores were significantly correlated with poorer overall survival. Recurrent patients exhibited increased Tregs infiltration and reduced CD8+ T cell. Moreover, molecular subtyping using seven key TRGs revealed that subtype B exhibited higher enrichment of multiple oncogenic pathways and had a worse prognosis. Notably, subtype B exhibited high Tregs levels, suggesting immune suppression. In addition, we validated machine learning-derived prognostic models across multiple platform cohorts to better distinguish patient survival and predict immunotherapy efficacy. Finally, the differential expression of key TRGs was validated using clinical samples. Our study provides novel insights into the role of Tregs in the immune microenvironment of OC. We identified potential therapeutic targets derived from Tregs (CD24, FHL2, GPM6A, HOXD8, NAP1L5, REN, and TOX3) for personalized treatment and created a machining learning-based prognostic model for OC patients, which could be useful in clinical practice.

REG3A promotes proliferation and DDP resistance of ovarian cancer cells by activating the PI3K/Akt signaling pathway.

This study explored the effect of Regenerating Islet-Derived 3-Alpha (REG3A) on ovarian cancer (OC) progression. REG3A expression was scrutinized in clinical tissues of 97 OC cases by quantitative real-time polymerase chain reaction (qRT-PCR). REG3A expression in OC cells and cisplatin (DDP) resistance OC cells was regulated by transfection. LY294002 (10 µM, inhibitor of the PI3K/Akt signaling pathway) was used to treat OC cells and DDP resistance OC cells. Cell counting kit-8 and methyl-thiazolyl-tetrazolium assays were applied for proliferation and DDP resistance detection. Flow cytometry was utilized for cell cycle and apoptosis analysis. The effect of REG3A on the OC cell in vivo growth was researched by establishing xenograft tumor model via using nude mice using nude mice. The expression of genes in clinical samples, cells and xenograft tumor tissues was investigated by qRT-PCR, Western blot and immunohistochemistry. As a result, REG3A was over-expressed in OC patients and cells, associating with dismal prognosis of patients. REG3A knockdown repressed proliferation, DDP resistance, induced cell cycle arrest and apoptosis of OC cells, and reduced the expression MDR-1, Cyclin D1, Cleaved caspase 3 proteins and the PI3K/Akt signaling pathway activity in OC cells. LY294002 treatment abrogated the promotion effect of REG3A on OC cell proliferation, apoptosis inhibition and DDP resistance. REG3A knockdown suppressed the in vivo growth of OC cells. Thus, REG3A promoted proliferation and DDP resistance of OC cells by activating the PI3K/Akt signaling pathway. REG3A might be a promising target for the clinical treatment of OC.

Hsa_circ_0063804 enhances ovarian cancer cells proliferation and resistance to cisplatin by targeting miR-1276/CLU axis.

PURPOSE: This article researched circ_0063804 effects on ovarian cancer (OC) development and resistance to cisplatin, aiming to provide a new target for OC therapy. METHODS: A total of 108 OC patients participated in this study. The circle structure of circ_0063804 was investigated using RNase R. Circ_0063804 expression in OC cells were up-regulated or down-regulated by transfection. Cell proliferation was assessed by cell counting kit-8 assay and colony formation assay. Flow cytometry was used to detect apoptosis. OC cells resistance to cisplatin was explored through MTT assay. Luciferase reporter assay was performed. qRT-PCR and Western blot was applied to research genes expression. Xenograft tumor experiment was conducted using nude mice. Ki67 expression in xenograft tumor was detected by immunohistochemistry. RESULTS: Circ_0063804 expression was up-regulated in OC patients and indicated poor prognosis (P < 0.05). Circ_0063804 had a stable circle structure. Circ_0063804 enhanced proliferation, resistance to cisplatin and reduced apoptosis of OC cells (P < 0.01). miR-1276 was down-regulated in OC patients and sponged by circ_0063804. CLU was directly inhibited by miR-1276 and up-regulated in OC patients. Circ_0063804 exacerbated malignant phenotype and resistance to cisplatin of OC cells in vitro by enhancing CLU expression via sponging miR-1276 (P < 0.01). Circ_0063804 silencing inhibited OC cells growth, resistance to cisplatin and Ki67 expression in vivo (P < 0.01). CONCLUSION: Circ_0063804 promoted OC cells proliferation and resistance to cisplatin by enhancing CLU expression via sponging miR-1276.

Polyphyllin E Inhibits Proliferation, Migration and Invasion of Ovarian Cancer Cells by Down-Regulating the AKT/NF-κB Pathway.

Ovarian cancer has long been considered the second-highest cancer threat to women's reproductive system with high mortality. This is ascribed to the absence of highly efficient therapy and cancer metastasis. Accordingly, there is an urgent need for the development of new agents. Recently, Traditional Chinese medicine has gained extensive interest because of its safe use, validity, and distinct pharmacological effects. Polyphyllin E (PPE), as a major constituent in Rhizoma Paridis, is a promising cancer-fighting agent. However, the effect of PPE on ovarian cancers as well as associated latent mechanisms is still not completely understood. In this study, PPE was found to prohibit the proliferation of SK-OV-3 and OVCAR-3 ovarian cancer cells, causing marked cell death. Additionally, low-dose PPE could also inhibit motility and invasion of ovarian cancer cells. The mechanistic assessment revealed PPE-mediated matrix metalloproteinases, i.e., MMP2 and MMP9, inhibition via the AKT-nuclear factor kappa B (AKT/NF-κB) signaling pathway. Rescue experiments with transfection of AKT lentiviral particles remarkably reversed PPE inhibitory effects against ovarian cancer cells. In conclusion, PPE could inhibit proliferation of ovarian cancer cell migration and invasion by down-regulating the AKT/NF-κB pathway. Moreover, it has the potential to act as a novel agent for ovarian cancer treatment.