Journal: Nature
Article Title: Anti-progestin therapy targets hallmarks of breast cancer risk
doi: 10.1038/s41586-025-09684-7
Figure Lengend Snippet: a , Real-time PCR gene expression of TNFSF11 , KIT and SOX9 in breast tissue microstructures from women at increased cancer risk, cultured in ‘soft’ and ‘stiff’ hydrogels. Data are shown as mean fold change ± s.d., with individual points. n = 6 breast samples. b , KIT and SOX9 protein in breast microstructures (sample 1989N) cultured in soft (S) and stiff (ST) hydrogels, treated with UA (2 nM) or onapristone (ON; 100 nM). Densitometry normalized to β-actin is shown above the bands. n = 3 breast samples. c , MFE after culture in soft and stiff hydrogels with UA (2 nM) or ON (100 nM). Data are shown as mean fold change ± s.d., with individual points. n = 6 breast samples. d , Collagen coherency was assessed in peri-lobular regions (three lobules per sample) with representative PSR-stained sections shown at baseline and post-treatment. The ellipse indicates fibre alignment: examples of aligned (baseline) and non-aligned (post-treatment) collagen are shown in the insets. The graph shows mean collagen coherency for n = 22 paired samples. Scale bars, 100 μm. e , Reduced modulus of peri-lobular regions at baseline (B) and post-treatment (PT) measured by AFM indentation. At least three 100 μm 2 regions per sample were measured as shown in the representative images. n = 4 tissue pairs. Scale bars, 100 μm. f , MRI annotation in ITK-snap: black denotes the background, opaque red indicates fatty tissue, and bright red shows the fibroglandular tissue. The FGV percentage was calculated by dividing the number of fibroglandular pixels by the total number of fibroglandular and fat pixels across slices. n = 12 paired MRI scans. Scale bars, 1 cm. g , Percentage of Ki67 + cells before treatment and post-treatment stratified by mammographic density. Participants were grouped using Volpara density grades to approximate BI-RADS categories (A/B denotes low MD, n = 6 tissue pairs; C/D indicates high MD, n = 17 tissue pairs). h , Heatmap of whole-tissue RNA-seq showing the differentially expressed genes between high MD (BI-RADS C/D; dark grey) and low MD (BI-RADS A/B; light grey) breast tissue at baseline ( n = 9; FC > 3, P < 0.05). VST, variance-stabilizing transformation. i , Illustration shows that progesterone paracrine signalling regulates luminal progenitor/LASP (SOX9 + ) cells and fibroblasts, driving ECM remodelling and stiffness. Stiffness amplifies PR signalling, establishing a feedback loop. Anti-progestins disrupt this by inhibiting luminal cell-derived ligands (for example, WNT5A), lowering fibroblast collagen (for example, COL6A3), decreasing stiffness and reducing luminal progenitor/LASP cells. Boxplot centre lines represent median values and box bounds indicate the 25th and 75th percentiles ( d – g ), with connecting lines between paired data points ( d , f , g ) or whiskers denoting minimum and maximum values ( e ). P values were calculated with two-sided Wilcoxon matched-pairs test ( a , c , d , f , g ) or two-sided Student’s t -test ( e ).
Article Snippet: The antibodies used included α-smooth muscle actin (clone 1A4, 141Pr), E-cadherin (clone 24E10, 158Gd), Ki67 (clone B56, 168Er) and collagen I (polyclonal, 169Tm) from Standard BioTools (201508, Maxpar Human Immuno-oncology IMC panel kit), as well as fibronectin (polyclonal, 149Sm; ab23750, Abcam), collagen VI (polyclonal, 160Gd; ab6588, Abcam) and SOX9 (clone EPR14335 , 147Sm; 3147022D, Standard BioTools).
Techniques: Real-time Polymerase Chain Reaction, Gene Expression, Cell Culture, Staining, RNA Sequencing, Transformation Assay, Derivative Assay