基于全基因组CRISPR筛选的子宫内膜癌孕激素耐药关键基因网络的构建与初步验证
Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening.
摘要(中文译文)
子宫内膜癌是女性生殖系统常见的恶性肿瘤，其发病率不断上升且呈年轻化趋势。激素治疗是保留生育功能的首选方案，也可用于晚期和复发病例。然而，相当数量的患者对孕激素治疗反应不佳。我们采用CRISPR/Cas9技术在Ishikawa细胞系中构建了全面的人类基因组文库。随后暴露于甲羟孕酮并进行高通量测序，利用基于模型的基因组范围CRISPR-Cas9敲除分析（MAGeCK）的稳健秩聚合（RRA）和最大似然估计（MLE）算法进行差异基因表达和富集分析。采用迭代数据交集方法，利用孕激素耐药细胞系的测序数据，鉴定与孕激素耐药相关的关键基因。通过Cell Counting Kit-8（CCK-8）实验和凋亡检测，在先前建立的孕激素耐药细胞模型中对排名前10的基因进行了功能验证。在异种移植小鼠模型中对孕激素耐药基因NNMT和孕激素敏感基因SOX17进行了体内验证。所构建的文库质量高，符合测序标准。采用RRA和MLE算法，我们分别鉴定了332个和829个负选择基因，以及3438个和5098个正选择基因。富集分析涉及DNA和RNA合成、代谢及相关过程的通路。经过多次数据交集，我们共鉴定出5个促进孕激素耐药的基因和20个抑制耐药的基因，功能实验证实了它们的作用。采用CRISPR/Cas9技术能够构建相对可靠的子宫内膜癌孕激素耐药关键基因网络。涉及DNA和RNA合成、代谢及相关机制的过程似乎显著影响子宫内膜癌的孕激素敏感性。
Abstract
Endometrial carcinoma, a prevailing malignancy of the female reproductive system, exhibits escalating incidence and a trend towards early onset. Hormone therapy serves as a primary choice for fertility preservation and is also considered for advanced and recurrent cases. However, a considerable number of patients fail to respond favorably to progestin treatments. We employed CRISPR/Cas9 technology to establish a comprehensive human genome library in the Ishikawa cell line. Subsequent exposure to medroxyprogesterone was followed by high-throughput sequencing, and differential gene expression and enrichment analyses were conducted using Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) Robust Rank Aggregation (RRA) and MAGeCK Maximum-Likelihood Estimation (MLE) algorithms. An iterative data intersection approach was employed, utilizing sequenced data from progestin-resistant cell lines, to identify pivotal genes associated with progestin resistance. The top 10 identified genes were functionally validated in our previously established progestin-resistant cell model through Cell Counting Kit-8 (CCK-8) assays and apoptosis detection. The progestin-resistant gene NNMT and the progestin-sensitive gene SOX17 were validated in vivo in xenograft mouse models. The constructed library exhibited high quality, meeting sequencing standards. Employing RRA and MLE algorithms, we identified 332 and 829 negative selection genes, as well as 3438 and 5098 positive selection genes. Enrichment analysis implicated pathways linked to DNA and RNA synthesis, metabolism, and related processes. After multiple data intersections, we identified a total of 5 genes promoting progestin resistance and 20 genes inhibiting resistance, with functional experiments confirming their roles. Employing CRISPR/Cas9 technology enables the construction of a relatively reliable network of pivotal genes associated with progestin resistance in endometrial carcinoma. Processes involving DNA and RNA synthesis, metabolism, and related mechanisms appear to significantly impact the progestin sensitivity of endometrial carcinoma.
如何引用
AMA
Xinyue Li, Shourong Wang, Ziyi Qiu, Rui Sun, Tong Wang, Xiaochen Ren, et al. Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening.. Scientific reports. 2026; doi:10.1038/s41598-026-36534-x.
APA
Xinyue Li, Shourong Wang, Ziyi Qiu, Rui Sun, Tong Wang, Xiaochen Ren, et al (2026). Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening.. Scientific reports. https://doi.org/10.1038/s41598-026-36534-x
GB/T 7714
Xinyue Li, Shourong Wang, Ziyi Qiu, Rui Sun, Tong Wang, Xiaochen Ren, et al. Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening.[J]. Scientific reports, 2026 doi:10.1038/s41598-026-36534-x.
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