BACKGROUND: Although immune checkpoint inhibitors (ICIs) represent a substantial breakthrough in cancer treatment, it is crucial to acknowledge that their efficacy is limited to a subset of patients. The heterogeneity and stemness of cancer render its response to immunotherapy variable, warranting the identification of robust biomarkers for evaluation. METHODS: Publicly available Ovarian Cancer (OV) single-cell RNA (scRNA) sequence dataset was collected and analyzed to elucidate the intrinsic driver gene of OV cancer cells. Through genome-scale CRISPR screening of RNA sequencing data from Project Achilles, essential genes specific to OV were identified. A novel cancer stem cell index (CSCI) was developed and validated using multiple advanced algorithms and large-scale datasets, as well as corresponding clinical features, including 14 OV transcriptomic datasets, 7 pan-cancer ICI transcriptomic cohorts and one melanoma scRNA dataset derived from PD-1 treated patients. RESULTS: Chromosomal 20q gain, 8q gain, and 5q loss have been identified as ovarian cancer-specific driving variations. By analyzing large-scale datasets of ovarian cancer transcriptomics, including scRNA and CRISPR cell line datasets, we have identified a gene set that influences tumor intrinsic drivers and stemness properties. We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. When applied to PD1/PD-L1 ICI transcriptomic cohorts, CSCI consistently and accurately predicts tumor progression and immunotherapy benefits, with a mean AUC greater than 0.8. Notably, compared to previously established signatures, CSCI demonstrates better predictive performance across multiple ovarian cancer datasets. Intriguingly, we discovered that amplification of CSE1L enhances the stemness of tumor-initiating cells, facilitates angiogenesis, and the formation of ovarian cancer, which can serve as a potential therapeutic target. Finally, experiments validated that CSE1L promotes progression, migration, and proliferation of ovarian cancer. CONCLUSIONS: Our study has uncovered a robust correlation between variations in cancer intrinsic drivers and stemness, as well as resistance to immunotherapy. This finding provides valuable insights for potential strategies to overcome immune resistance by targeting genes associated with stemness.
Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census.
多组学分析和实验揭示了卵巢癌中癌症内在驱动因素、干细胞特性和免疫疗法之间的联系,并在泛癌普查中得到了验证
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作者:Li Yilin, Chen Cen, Ji Xiaoyu, Jiang Ningxiao, Wang Fei, Gao Xiangqian, Chen Weiwei, Tang Qiang, Li Yan, Zhang Shinan, Qin Gaofeng, Xu Yingjiang, Wang Yanlin, Kong Lingwen, Han Lei, Mei Jie
| 期刊: | Frontiers in Immunology | 影响因子: | 5.900 |
| 时间: | 2025 | 起止号: | 2025 May 8; 16:1549656 |
| doi: | 10.3389/fimmu.2025.1549656 | 研究方向: | 发育与干细胞、细胞生物学 |
| 疾病类型: | 卵巢癌 | ||
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