Xiang Zhou

Dual Targeting of Mutant p53 and SNRPD2 via Engineered Exosomes Modulates Alternative Splicing to Suppress Ovarian Cancer

ABSTRACT Mutation of the tumor suppressor gene TP53 promotes ovarian cancer progression and therapeutic resistance. Whether mutant p53 (mtp53) regulates alternative splicing and how this regulation can be exploited for cancer therapy remain unclear. Here, small nuclear ribonucleoprotein D2 polypeptide (SNRPD2) as a binding partner of mtp53 is identified. SNRPD2 is highly expressed in ovarian cancer and associated with an unfavorable prognosis. The overexpression of SNRPD2 promotes, whereas its depletion inhibits, the growth and migration of ovarian cancer cells. Mechanistically, mtp53 cooperates with SNRPD2 to facilitate the assembly of the Sm/SMN protein complex, an essential component of the spliceosome, modulating alternative splicing of pre‐mRNAs. Specifically, the co‐depletion of mtp53 and SNRPD2 reduces the level of OTUD3 oncogenic transcripts while increasing its tumor suppressor counterparts through an exon‐skipping event. Moreover, therapeutic engineered exosomes are developed with their surfaces decorated with iRGD and their interiors loaded with siRNAs targeting mtp53 and SNRPD2. These exosomes effectively suppress the growth of ovarian cancer cells and enhance their sensitivity to chemotherapy in vivo. Collectively, this study uncovers that mtp53 and SNRPD2 cooperatively regulate alternative splicing to drive ovarian cancer progression, and co‐targeting these two molecules via engineered exosomes represents a potential therapeutic strategy for ovarian cancer.

YY1-induced USP43 drives ferroptosis suppression by FASN stabilization and subsequent activation of SLC7A11 in ovarian cancer

Abstract The ubiquitin-specific protease (USP) family is a major member of the deubiquitinating enzyme family that plays important and diverse roles in multiple tumors. The roles and mechanisms of action of USP family members in ovarian cancer are not well understood. This study aimed to screen all the USP family members and explored the specific function of USP43 in ovarian cancer. The expression levels of USP family members in ovarian cancer were screened using bioinformatics analysis, and the specific function of USP43 was explored through in vitro and in vivo experiments. Functional assays, including cell viability, ferroptosis, and tumor xenograft models, were employed. In short, USP43 drives the ferroptosis suppression by activating the expression of SLC7A11 through FASN-HIF1α pathway. USP43 is an important prognostic factor for ovarian cancer, with its overexpression promoting ovarian cancer progression and its knockdown inhibiting it. Mechanistically, USP43, which is transcriptionally activated by YY1, stabilizes FASN through deubiquitination, and FASN activates SLC7A11 expression by stabilizing HIF1α. Furthermore, the combination of cisplatin and the SLC7A11 inhibitor HG106 significantly inhibits the growth of ovarian tumors. Thus, targeting the USP43-FASN-HIF1α-SLC7A11 axis can inhibit ferroptosis and promote platinum sensitivity in ovarian cancer.

CKAP4 and mutant p53 cooperatively abrogate cell cycle checkpoint to induce genotoxic resistance in ovarian cancer

Single‐cell transcriptomes reveal heterogeneity of high‐grade serous ovarian carcinoma

AbstractBackgroundHigh‐grade serous ovarian carcinoma (HGSOC) is the most common and aggressive histotype of epithelial ovarian cancer. The heterogeneity and molecular basis of this disease remain incompletely understood.MethodsTo address this question, we have performed a single‐cell transcriptomics analysis of matched primary and metastatic HGSOC samples.ResultsA total of 13 571 cells are categorized into six distinct cell types, including epithelial cells, fibroblast cells, T cells, B cells, macrophages, and endothelial cells. A subset of aggressive epithelial cells with hyperproliferative and drug‐resistant potentials is identified. Several new markers that are highly expressed in epithelial cells are characterized, and their roles in ovarian cancer cell growth and migration are further confirmed. Dysregulation of multiple signaling pathways, including the translational machinery, is associated with ovarian cancer metastasis through the trajectory analysis. Moreover, single‐cell regulatory network inference and clustering (SCENIC) analysis reveals the gene regulatory networks and suggests the JUN signaling pathway as a potential therapeutic target for treatment of ovarian cancer, which is validated using the JUN/AP‐1 inhibitor T‐5224. Finally, our study depicts the epithelial‐fibroblast cell communication atlas and identifies several important receptor‐ligand complexes in ovarian cancer development.ConclusionsThis study uncovers new molecular features and the potential therapeutic target of HGSOC, which would advance the understanding and treatment of the disease.

SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies

AbstractSpatial transcriptomic studies are becoming increasingly common and large, posing important statistical and computational challenges for many analytic tasks. Here, we present SPARK-X, a non-parametric method for rapid and effective detection of spatially expressed genes in large spatial transcriptomic studies. SPARK-X not only produces effective type I error control and high power but also brings orders of magnitude computational savings. We apply SPARK-X to analyze three large datasets, one of which is only analyzable by SPARK-X. In these data, SPARK-X identifies many spatially expressed genes including those that are spatially expressed within the same cell type, revealing new biological insights.