Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening

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.

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Publication Details

Journal
Scientific Reports
Published
2026-03-03
DOI
https://doi.org/10.1038/s41598-026-36534-x
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening

Ziyi Qiu, Xiaodong Li, Xiao Ma, Tong Wang et al.
Scientific Reports
CRISPR and Genetic Engineering
article

Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening

Ziyi Qiu, Xiaodong Li, Xiao Ma, Tong Wang, Binglin Lv, J. Jiang, Rui Sun, Yao Liu, Lei Cheng, Shourong Wang, Xiaochen Ren
article en

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.

Scientific ReportsVol. 16(1)
Qingdao University (CN), Shandong University (CN), Yuhuangding Hospital (CN), Shandong Provincial Hospital (CN), Affiliated Hospital of Qingdao University (CN), Qilu Hospital of Shandong University (CN), Shandong First Medical University (CN)
China Postdoctoral Science Foundation
Good health and well-being
Openalex Percentile: Top 35%
CRISPR and Genetic Engineering
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