A Transcriptomics-Based Computational Drug Repositioning Pipeline Identifies Simvastatin And Primaquine As Novel Therapeutics For Endometriosis Pain

Abstract

Introduction and methods: Endometriosis has limited treatment options, prompting the search for novel therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline to analyze public bulk transcriptomic data and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model. Building on this, we now evaluate two additional candidates, simvastatin (a cholesterol-lowering drug) and primaquine (an antimalarial), based on strong gene expression reversal scores and favorable safety profiles. Using a validated rat model of endometriosis and pain, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential.

Results: Of 299 drugs identified computationally, simvastatin and primaquine ranked highly for reversing gene expression signatures associated with endometriosis. In vivo validation using a rat model of endometriosis demonstrated that both drugs significantly reduced vaginal hyperalgesia, a surrogate marker of endometriosis-associated pain. RNA-seq of uteri and lesions confirmed reversal of disease-associated gene expression signatures following treatment.

Conclusion: Simvastatin and primaquine attenuated pain behaviors and reversed endometriosis-related gene expression changes in an animal model. These findings highlight their potential as repurposed therapeutics for endometriosis-related pain and support the effectiveness of computational drug repositioning strategies in identifying new treatment strategies.

Keywords: bioinformatics; drug repositioning; endometriosis; therapeutics; transcriptomics.

Figure 1.. Study overview and disease signature reversal by primaquine and simvastatin.

(A) Overview of the study that identified therapeutic candidates through a transcriptomics-based computational drug repositioning pipeline and then validated drug candidates in a rat model of endometriosis. Bulk RNA-sequencing was conducted of the uterus and endometriosis lesions from the rats, and differentially expressed genes and enriched pathways were analyzed. (B,C) Heatmap showing (B) primaquine and (C) simvastatin drug signature vs. unstratified and stratified endometriosis disease signatures.

Figure 2.. Endometriosis pain-associated escape behaviors in a rat model.

(A) Female Sprague Dawley rats (n=18) were trained over 4 weeks to perform an escape response to terminate a noxious vaginal stimulus (water-filled balloon). Vaginal nociception was assessed as % escape response to varying balloon volumes in 1-hour sessions, 3 times/week, over 24 weeks. Each session included 8 volumes (0.01–0.90 mL), each tested 3 times in randomized, blinded order. Responses to all 3 trials of a volume were counted as 100% response. Nociception was measured at Baseline (8 weeks), after endometriosis induction (Post-Endo, 8 weeks), and during a 4-week treatment period. (B) Animal model median escape response (%) with interquartile range (IQR; error bars)(y-axis) for each delivered volume (0.01, 0.15,0.30, 0.40, 0.55, 0.70, 0.80, and 0.90 mL)(x-axis) during the baseline, post-endo surgery, and post-treatment periods for the 6 animal study groups; Control No endo Surgery; Vehicle; Ibuprofen; Fenoprofen; Primaquine; and Simvastatin. (Note: Control No endo Surgery, Ibuprofen, and Fenoprofen escape responses results are from previous work.)

Figure 3.

Strip and Violin plots with Medians and Significance Bars of Escape Responses to vaginal balloon distention at volumes of 0.01, 0.15, 0.30, 0.40, 0.55, 0.70, 0.80, and 0.90 mL for at baseline (Baseline), post-endometriosis (Post-Endo), and post-treatment (Post-Treatment) periods in a rat endometriosis model comparing 6 animal study groups — Control No Surgery (“CNS”), Vehicle (“VEH”), Ibuprofen (“IBU”), Fenoprofen (“FEN”), Primaquine (“PRIMA”), Simvastatin (“SIMVA”). Mann-Whitney test; Bonferonni adjusted p-values from Mann-Whitney U comparisons of groups. (Note: CNS, FEN, and IBU escape responses results are from previous work.) p-value annotation legend: ns: 5.00e-02 < p <= 1.00e+00 *: 1.00e-02 < p <= 5.00e-02 **: 1.00e-03 < p <= 1.00e-02 ***: 1.00e-04 < p <= 1.00e-03 ****: p <= 1.00e-04

Figure 4.. RNA-Seq analysis of treated animals.

Principal component analysis (PCA) of all animal study samples, with each dot representing a sample, colored (A) by treatment group or (B) by sample source. (C) Heatmap of disease-associated and treatment-associated gene signatures (Left: vehicle-treated uterus samples. Middle: drug-treated uterus samples. Right: lesion samples). Red indicates up-regulated genes and blue indicates downregulated genes. (D) Pearson correlation analysis between disease-induced (“U.Endo”) and drug-induced gene expression changes. Red indicates positive correlations and blue indicates negative correlations. (E) Gene Set Enrichment Analysis (GSEA) of KEGG pathways in disease and drug-treated groups. Red indicates up-regulated pathways and blue indicates downregulated pathways.

Figure 5.. Correlation with human data.

(A) Venn Diagram, (B) Heatmap, and (C) Network analysis to identify pathways associated with the 55 differentially expressed genes (DEGs) that overlap between our human and rat transcriptomics analysis, and their networks.