Lymphocyte and macrophage infiltration in omental metastases indicates poor prognosis in advance stage epithelial ovarian cancer

LncRNA IL21-AS1 facilitates tumour progression by enhancing CD24-induced phagocytosis inhibition and tumorigenesis in ovarian cancer

CD24 is overexpressed in various tumours and considered a regulator of cell migration, invasion, and proliferation. Recent studies have found that CD24 on ovarian cancer (OC) and triple-negative breast cancer cells interacts with the inhibitory receptor sialic-acid-binding Ig-like lectin 10 (Siglec-10) on tumour-associated macrophages (TAMs) to inhibit phagocytosis by macrophages. Because of its multiple roles in regulating the immune response and tumorigenesis, CD24 is a very promising therapeutic target. However, the regulatory mechanism of CD24 in OC remains unclear. Here, we found that the long noncoding RNA (lncRNA) IL21-AS1, which was upregulated in OC, inhibited macrophage-mediated phagocytosis and promoted OC cell proliferation and apoptosis inhibition. More importantly, after IL21-AS1 knockdown, a significant survival advantage was observed in mice engrafted with tumours. Mechanistically, we identified IL21-AS1 as a hypoxia-induced lncRNA. Moreover, IL21-AS1 increased HIF1α-induced CD24 expression under hypoxic conditions. In parallel, we found that IL21-AS1 acted as a competing endogenous RNA (ceRNA) for miR-561-5p to regulate CD24 expression. Finally, IL21-AS1 increased CD24 expression in OC and facilitated OC progression. Our findings provide a molecular basis for the regulation of CD24, thus highlighting a potential strategy for targeted treatment of OC.

Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review)

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.

High Tumor-Infiltrating Lymphocyte Count Is Associated with Distinct Gene Expression Profile and Longer Patient Survival in Advanced Ovarian Cancer

Cancer-related immunity plays a significant role in the outcome of ovarian cancer, but the exact mechanisms are not fully explored. A retrospective, real-life observational study was conducted including 57 advanced ovarian cancer patients. Immunohistochemistry for CD4+, CD8+, and CD45+ was used for assessing tumor-infiltrating immune cells. Furthermore, an immune-related gene expression assay was performed on 12-10 samples from patients with less than and more than 1-year overall survival (OS), respectively. A higher number of CD4+ (p = 0.0028) and CD45+ (p = 0.0221) immune cells within the tumor microenvironment were associated with longer OS of patients. In a multivariate setting, higher CD4+ T cell infiltration predicted longer OS (p = 0.0392). Twenty-three differentially expressed genes-involved in antigen presentation, costimulatory signaling, matrix remodeling, metastasis formation, and myeloid cell activity-were found when comparing the prognostic groups. It was found that tumor-infiltrating immune cell counts are associated with peculiar gene expression patterns and bear prognostic information in ovarian cancer. SOX11 expression emerged and was validated as a predictive marker for OS.

Targeting tumor-associated macrophages for successful immunotherapy of ovarian carcinoma

Epithelial ovarian cancer (EOC) is among the top five causes of cancer-related death in women, largely reflecting early, prediagnosis dissemination of malignant cells to the peritoneum. Despite improvements in medical therapies, particularly with the implementation of novel drugs targeting homologous recombination deficiency, the survival rates of patients with EOC remain low. Unlike other neoplasms, EOC remains relatively insensitive to immune checkpoint inhibitors, which is correlated with a tumor microenvironment (TME) characterized by poor infiltration by immune cells and active immunosuppression dominated by immune components with tumor-promoting properties, especially tumor-associated macrophages (TAMs). In recent years, TAMs have attracted interest as potential therapeutic targets by seeking to reverse the immunosuppression in the TME and enhance the clinical efficacy of immunotherapy. Here, we review the key biological features of TAMs that affect tumor progression and their relevance as potential targets for treating EOC. We especially focus on the therapies that might modulate the recruitment, polarization, survival, and functional properties of TAMs in the TME of EOC that can be harnessed to develop superior combinatorial regimens with immunotherapy for the clinical care of patients with EOC.