Yi Zhang

Chemoresistance Evolution in Ovarian Cancer Delineated by Single-Cell RNA Sequencing

High-grade serous ovarian cancer (HGSOC) is an aggressive gynecological malignancy characterized by intraperitoneal spread and chemotherapy resistance. Chemotherapies have demonstrated limited effectiveness in HGSOC, underscoring the urgent need to evaluate how the tumor microenvironment (TME) was reshaped by chemotherapy in different sites of tumor foci. In this study, we performed single-cell transcriptomic analysis to explore the TME in samples obtained from various sites of tumor foci, with or without the history of Neoadjuvant chemotherapy (NACT). We discovered that chemotherapy reshaped the tumor immune microenvironment, evident through the reduction in human leukocyte antigen (HLA) diversity and the increase in PDCD1/CD274 in CD8_ANXA1, LAMP3+ dendritic cell (DC_LAMP3), and EREG+ monocytes (mono_EREG). Moreover, cancer.cell.2, cancer-associated C3+ fibroblasts (CAF_C3), and Fibrocyte_CD34, which are prone to accumulate in the metastatic site and post-NACT group, harbored poor clinical outcome, reflected in the immune exclusion and tumor progression signaling. Cell–cell communication identified a stronger interaction between cancer.cell.2 and CAF_C3, as well as Fibrocyte_CD34, in post-NACT samples, indicating that chemotherapy reshapes pre-existing cell clusters in a site-dependent manner. Our findings suggest that chemotherapy and sites of foci were critical for the transcriptional reprogramming of pre-existed cell clusters. Our study offers a single-cell phenotype data substrate from which to develop a personalized combination of chemotherapy and immunotherapy.

Therapeutic potential of miRNAs in placental extracellular vesicles in ovarian and endometrial cancer

There is a cross-link between the placenta and cancer development, as the placenta is grown as a highly invasive tumour-like organ. However, placental development is strictly controlled. Although the underlying mechanism of this control is largely unknown, it is now well-recognised that extracellular vesicles (EVs) released from the placenta play an important role in controlling placenta proliferation and invasion, as placental EVs have shown their effect on regulating maternal adaptation. Better understanding the tumour-like mechanism of the placenta could help to develop a therapeutic potential in cancers. In this study, by RNA sequencing of placental EVs, 20 highly expressed microRNAs (miRNAs) in placental EVs were selected and analysed for their functions on ovarian and endometrial cancer. There were up to seven enriched miRNAs, including miRNA-199a-3p, miRNA-143-3p, and miRNA-519a-5p in placental EVs showing effects on the inhibition of ovarian and endometrial cancer cell proliferation and migration, and promotion of cancer cell death, reported in the literature. Most of these miRNAs have been reported to be downregulated in ovarian and endometrial cancer. Transfection of ovarian and endometrial cancer cells with mimics of miRNA-199a-3p, miRNA-143-3p, and miRNA-519a-5p significantly reduced the cell viability. Our findings could provide strategies for using these naturally occurring miRNAs to develop a novel method to treat ovarian and endometrial cancer in the future.

Targeting of Tumoral NAC1 Mitigates Myeloid-Derived Suppressor Cell–Mediated Immunosuppression and Potentiates Anti–PD-1 Therapy in Ovarian Cancer

Abstract Epithelial ovarian cancer is the most common type of ovarian cancer with a low rate of response to immunotherapy such as immune checkpoint blockade therapy. In this study, we report that nucleus accumbens–associated protein 1 (NAC1), a putative driver of epithelial ovarian cancer, has a critical role in immune evasion. We showed in murine ovarian cancer models that depleting or inhibiting tumoral NAC1 reduced the recruitment and immunosuppressive function of myeloid-derived suppressor cells (MDSC) in the tumor microenvironment, led to significant increases of cytotoxic tumor-infiltrating CD8+ T cells, and promoted antitumor immunity and suppressed tumor progression. We further showed that tumoral NAC1 directly enhanced the transcription of CXCL16 by binding to CXCR6, thereby promoting MDSC recruitment to the tumor. Moreover, lipid C20:1T produced by NAC1-expressing tumor cells fueled oxidative metabolism of MDSCs and promoted their immune-suppressive function. We also showed that NIC3, a small-molecule inhibitor of NAC1, was able to sensitize mice bearing NAC1-expressing ovarian tumors to anti–PD-1 therapy. Our study reveals a critical role for NAC1 in controlling tumor infiltration of MDSCs and in modulating the efficacy of immune checkpoint blockade therapy. Thus, targeting of NAC1 may be exploited to sensitize ovarian cancer to immunotherapy.

Vitamin D receptor (VDR) variants are risk factors for ovarian cancer: a meta-analysis and trial sequential analysis

The importance of Vitamin D in ovarian cancer (OC) has been well documented, and lower levels have been associated with susceptibility to OC. Vitamin D exerts its effect through the vitamin D receptor (VDR). Common genetic variants in the VDR gene (

Lung Adenocarcinoma with Metachronous Ovarian Metastasis: a long survival case report

Abstract Background Lung adenocarcinoma which invades ovaries is very rare. However, with the increase of long-survival female lung cancer, more patients will suffer ovarian metastasis. On grounds of the paucity of reported cases, the clinicopathological features and treatment strategies remain unknown. Case presentation This patient was stage IV lung adenocarcinoma at first diagnosis. Following multiple-line systemic treatments, she experienced extensive pelvic metastasis. After debulking surgery and reevaluation about the drive genes, she was administered by targeted therapy. Up to now, the patient has shown no evidence of progression for 8 years after the initial diagnosis of primary lung cancer and 46 months after her ovarian metastasis. Conclusion The comprehensive treatment modality for the bilateral ovarian metastasis is effective in clinical course.

Chemerin promotes proliferation and migration of ovarian cancer cells by upregulating expression of PD-L1

Ovarian cancer is the third-most-common malignant reproductive tumor in women. According to the American Cancer Society, it has the highest mortality rate of gynecological tumors. The five-year survival rate was only 29% during the period from 1975 to 2008 (Reid et al., 2017). In recent decades, the five-year survival rate of ovarian cancer has remained around 30% despite continuous improvements in surgery, chemotherapy, radiotherapy, and other therapeutic methods. However, because of the particularity of the volume and location of ovarian tissue, the early symptoms of ovarian cancer are hidden, and there is a lack of highly sensitive and specific screening methods. Most patients have advanced metastasis, including abdominal metastasis, when they are diagnosed (Reid et al., 2017). Therefore, exploring the mechanism of ovarian cancer metastasis and finding early preventive measures are key to improving the survival rate and reducing mortality caused by ovarian cancer.

LDAI-ISPS: LncRNA–Disease Associations Inference Based on Integrated Space Projection Scores

Long non-coding RNAs (long ncRNAs, lncRNAs) of all kinds have been implicated in a range of cell developmental processes and diseases, while they are not translated into proteins. Inferring diseases associated lncRNAs by computational methods can be helpful to understand the pathogenesis of diseases, but those current computational methods still have not achieved remarkable predictive performance: such as the inaccurate construction of similarity networks and inadequate numbers of known lncRNA–disease associations. In this research, we proposed a lncRNA–disease associations inference based on integrated space projection scores (LDAI-ISPS) composed of the following key steps: changing the Boolean network of known lncRNA–disease associations into the weighted networks via combining all the global information (e.g., disease semantic similarities, lncRNA functional similarities, and known lncRNA–disease associations); obtaining the space projection scores via vector projections of the weighted networks to form the final prediction scores without biases. The leave-one-out cross validation (LOOCV) results showed that, compared with other methods, LDAI-ISPS had a higher accuracy with area-under-the-curve (AUC) value of 0.9154 for inferring diseases, with AUC value of 0.8865 for inferring new lncRNAs (whose associations related to diseases are unknown), with AUC value of 0.7518 for inferring isolated diseases (whose associations related to lncRNAs are unknown). A case study also confirmed the predictive performance of LDAI-ISPS as a helper for traditional biological experiments in inferring the potential LncRNA–disease associations and isolated diseases.