Weidong Fei

Nanotechnology-integrated ovarian cancer metastasis therapy: Insights from the metastatic mechanisms into administration routes and therapy strategies

Ovarian cancer is a kind of malignant tumour which locates in the pelvic cavity without typical clinical symptoms in the early stages. Most patients are diagnosed in the late stage while about 60 % of them have suffered from the cancer cells spreading in the abdominal cavity. The high recurrence rate and mortality seriously damage the reproductive needs and health of women. Although recent advances in therapeutic regimes and other adjuvant therapies improved the overall survival of ovarian cancer, overcoming metastasis has still been a challenge and is necessary for achieving cure of ovarian cancer. To present potential targets and new strategies for curbing the occurrence of ovarian metastasis and the treatment of ovarian cancer after metastasis, the first section of this paper explained the metastatic mechanisms of ovarian cancer comprehensively. Nanomedicine, not limited to drug delivery, offers opportunities for metastatic ovarian cancer therapy. The second section of this paper emphasized the advantages of various administration routes of nanodrugs in metastatic ovarian cancer therapy. Furthermore, the third section of this paper focused on advances in nanotechnology-integrated strategies for targeting metastatic ovarian cancer based on the metastatic mechanisms of ovarian cancer. Finally, the challenges and prospects of nanotherapeutics for ovarian cancer metastasis therapy were evaluated. In general, the greatest emphasis on using nanotechnology-based strategies provides avenues for improving metastatic ovarian cancer outcomes in the future.

Single-Cell RNA Sequencing Reveals the Tissue Architecture in Human High-Grade Serous Ovarian Cancer

Abstract Purpose: The heterogeneity of high-grade serous ovarian cancer (HGSOC) is not well studied, which severely hinders clinical treatment of HGSOC. Thus, it is necessary to characterize the heterogeneity of HGSOC within its tumor microenvironment (TME). Experimental Design: The tumors of 7 treatment-naïve patients with HGSOC at early or late stages and five age-matched nonmalignant ovarian samples were analyzed by deep single-cell RNA sequencing (scRNA-seq). Results: A total of 59,324 single cells obtained from HGSOC and nonmalignant ovarian tissues were sequenced by scRNA-seq. Among those cells, tumor cells were characterized by a set of epithelial-to-mesenchymal transition (EMT)-associated gene signatures, in which a combination of NOTCH1, SNAI2, TGFBR1, and WNT11 was further selected as a genetic panel to predict the poor outcomes of patients with HGSOC. Matrix cancer-associated fibroblasts (mCAF) expressing α-SMA, vimentin, COL3A, COL10A, and MMP11 were the dominant CAFs in HGSOC tumors and could induce EMT properties of ovarian cancer cells in the coculture system. Specific immune cell subsets such as C7-APOBEC3A M1 macrophages, CD8+ TRM, and TEX cells were preferentially enriched in early-stage tumors. In addition, an immune coinhibitory receptor TIGIT was highly expressed on CD8+ TEX cells and TIGIT blockade could significantly reduce ovarian cancer tumor growth in mouse models. Conclusions: Our transcriptomic results analyzed by scRNA-seq delineate an ecosystemic landscape of HGSOC at early or late stages with a focus on its heterogeneity with TME. The major applications of our findings are a four–EMT gene model for prediction of HGSOC patient outcomes, mCAFs’ capability of enhancing ovarian cancer cell invasion and potential therapeutic value of anti-TIGIT treatment.