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[Preprint]. 2025 Jun 4:2025.05.19.654935.
doi: 10.1101/2025.05.19.654935.

Isoform-Specific Gene Regulation by Progesterone Receptors Drives Divergent Phenotypes in Breast Cancer Cells

Noelle E Gillis  1 , Thu H Truong  1   2 , Caroline H Diep  1 , Angela Spartz  1 , Julie H Ostrander  1   3 , Carol A Lange  1   3
Affiliations

Isoform-Specific Gene Regulation by Progesterone Receptors Drives Divergent Phenotypes in Breast Cancer Cells

Noelle E Gillis et al. bioRxiv. .

Abstract

Exposure to progesterone is a recognized risk factor for breast cancer, and PGR polymorphisms are associated with various malignancies. Two progesterone receptor (PR) isoforms, full length PR-B and truncated PR-A, are expressed from the PGR gene in breast tissue and play crucial roles in normal physiology and breast cancer progression. An imbalance in the expression ratio of these isoforms, favoring increased levels of PR-A, is common in breast cancer and is associated with resistance to tamoxifen in luminal A-type tumors. Notably, PRs have recently been implicated in promoting endocrine resistance and driving the expansion of cancer stem-like cell (CSC) populations. Despite this insight, the isoform-specific molecular and epigenetic mechanisms underlying PR action in estrogen receptor positive (ER+) breast cancers remain understudied. Phenotypic studies of T47D cell lines that express exclusively PR-A or PR-B showed that PR isoforms regulate divergent cell fates. PR-B-expressing cells have a higher proliferation rate, while PR-A-expressing cells produce more mammospheres. We profiled progesterone-driven gene expression in cells grown in both adherent (2D) and mammosphere (3D) growth conditions and found differential gene regulation by PR-A and PR-B that is consistent with the observed divergent phenotypes. Only the PR-A-driven gene signature of ER+ breast cancer cells maintained as non-adherent mammospheres robustly predicted poor clinical outcome in the METABRIC data set. We then performed CUT&RUN to identify the genomic binding patterns unique to each PR isoform and their suite of target genes. Our findings indicate that PR-A acts as a regulator of the cell cycle, while PR-B plays a pivotal role in metabolism and intracellular signaling. Our genomic profiling of PRs in this model system has unveiled novel isoform-specific functions of PR. This work has shifted our prior understanding of the role of PRs in gene regulation, offering potential insights for therapeutic interventions in ER+ breast cancer.

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Conflict of interest statement

COMPETING INTEREST STATEMENT The authors have no competing interests.

Figures

Figure 1.
Figure 1.. PR-A and PR-B expressing cells exhibit divergent phenotypic characteristics in vitro.
A. Western blot shows protein expression of total PR and phosphorylated PR (p-PR) in T47D CO, PR-A, and PR-B expressing cell lines in 2D and 3D growth conditions. B. Cell growth over 72 hours was measured in T47D CO, PR-A, and PR-B expressing cell lines with and without 10 nM R5020 treatment (n =3). C. Quantification of colony formation in soft agar in T47D CO, PR-A, and PR-B expressing cell lines with and without 10 nM R5020 treatment (n = 3). D. Primary sphere counts of T47D CO, PR-A, and PR-B expressing cell lines with and without 10 nM R5020 in the media (n = 3). E. Secondary sphere counts of T47D CO, PR-A, and PR-B expressing cell lines with and without 10 nM R5020 in the media (n = 3).
Figure 2.
Figure 2.. PR-A and PR-B control discrete transcriptomes.
A. PCA Plot demonstrates that R5020 treatment and growth condition drive differential gene expression between RNA-seq samples. B. Clustered heatmap shows differential gene expression patterns in response to R5020 treatment when PR-A and PR-B expressing cells are grown in 2D and 3D conditions. All DEGs (log2Fold change > 1 or < −1; p.adjust < 0.05) C. Scatter plot shows that PR-A expressing cells have a larger response to R5020 treatment in 3D growth conditions. D. Scatter plot shows that PR-B expressing cells have a larger response to R5020 treatment in 2D growth conditions. E. Venn diagrams show the overlap between R5020-induced differentially expressed gene lists in PR-A and PR-B expressing cells.
Figure 3.
Figure 3.. PR-A and PR-B sustain diverse transcriptomic landscapes.
A. GSEA analysis dotplot shows that PR-A and PR-B regulate different pathways and cellular functions in 2D and 3D growth conditions. The top 8 enriched GO pathways are shown (FDR < 0.05). Dot color indicates normalized enrichment score (NES) for each gene set. Dot size indicates gene ratio for each gene set. B. GSEA enrichment plot demonstrates specific negative enrichment of cell cycle regulation, regulation of mitosis, and epithelial differentiation pathways within PR-A-regulated R50-induced DEGs in 3D growth conditions. C. GSEA enrichment plot demonstrates specific positive enrichment of cellular metabolic signaling, transmembrane signaling receptor activity, and MYC-driven proliferation within a PR-B-regulated R50-induced DEGs in 2D growth conditions. D. PR-A regulated gene signature is predictive of worse overall survival for patients in the METABRIC cohort. E. PR-B regulated gene signature is not predictive of better overall survival for patients in the METABRIC cohort.
Figure 4.
Figure 4.. PR-A and PR-B have distinct genomic binding patterns.
A. Venn diagrams represent peak overlap analysis for PR-A and PR-B in response to R5020 treatment. B. Density plots show limited overlap in CUT&RUN signal between PR-A occupied binding sites and PR-B occupied binding sites. C. PCA plot demonstrates that PR isoform is the main driver of differential binding patterns between CUT&RUN samples. Each data point represents one biological replicate (n = 3 per treatment group). D. Distribution of PR binding sites annotated to promoters, introns, exons, and intergenic regions. E. Homer motif analysis highlights the top transcription factor motifs enriched near PR-A binding sites. F. Homer motif analysis highlights the top transcription factor motifs enriched near PR-B binding sites. G. Average log2(FoldChange) of DEGs with 0,1, 2, 3 or >4 PR binding sites within 10kb of the TSS.
Figure 5.
Figure 5.. PR-A and PR-B drive differential growth patterns in MIND tumor xenograft models.
A. Diagram illustrates mammary intraductal injection technique. B. Bioluminescent imaging of MIND xenograft tumors from injection of PR-A- and PR-B-expressing cells after 1, 7,14, and 28 days of growth (4 of 8 total mice per group shown). C. Quantification of PR-A and PR-B tumor growth over 60 days with bioluminescent imaging plotted as total proton flux over time. D. Quantification of circulating tumor cells (CTCs) per 100 μl blood recovered from mice injected with PR-A- or PR-B-expressing cells (n = 4). E. Representative images of H&E and Ki67 staining in PR-A and PR-B tumors. F. Quantification of total Ki67 staining in PR-A and PR-B expressing tumors (n =3).
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