ArticleScientific reports2026
Construction and initial validation of key gene network for progesterone resistance in endometrial cancer based on genome-wide CRISPR screening.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.