Epigenomic integrity and cell identity is disrupted in Brca1/Trp53-deficient mammary glands

To map cell state transitions in the mammary gland prior to tumor formation, we performed a time-series analysis on virgin Blg-Cre+/–  Trp53fl/flBrca1fl/fl (CreP) female mice, combining transcriptomics via single-cell RNA sequencing (scRNA-seq) with single-cell epigenomic profiling (snCUT&Tag)(Fig. 1a). CreP mice developed mammary tumors at a median age of 5.4 months (Extended Data Supplementary Fig. 1a). Early abnormalities were observed starting at 3 months, characterized by abnormal gland structures and carcinoma in situ (CIS), with irregular nuclei and disrupted duct organization (Fig. 1a). By 5 months, CreP mice displayed multiple CIS, which were not detectable before dissection. To enhance our chances of detecting tumor initiation events, we especially focused on tumor-free CreP mice from a litter in which at least one other mouse already had a tumor (n = 3 animals), as we reasoned that these mice would be on the verge of developing tumors. We included mammary gland tissue from control mice that did not express the Cre-recombinase (Blg-Cre–/– Trp53fl/fl Brca1fl/fl; CreN), as well as tumors from CreP mice (Fig. 1a and Supplementary Table 1). To increase the likelihood of identifying rare phenotypic states, we enriched part of the collected samples for the epithelial fraction (Supplementary Table 1; see Methods).

Fig. 1

Transcriptomic and epigenomic profiling reveals non-genetic loss of cell identity in pre-tumoral Brca1/Trp53 deficient mammary glands. a Top: representative immuno-histochemistry for normal, pre-tumoral and tumor tissues, scale bars correspond to 20 µm. Bottom: Cre-recombinase–positive (CreP) or –negative (CreN) state in normal, pre-tumoral and tumor bearing mice, showing the number of samples used for scRNA-seq and snH3K4me1 profiling. For each sample, the number of slices within the circle/square corresponds to the number of mice used. For tumor-free mammary glands from CreP mice, color codes represent the age of the mouse. b Left: UMAP representation of scRNA-seq datasets for CreP epithelial cells. Cells are colored according to the sample of origin. Right: UMAP representation of scRNA-seq datasets for CreP epithelial cells; cells are colored according to the cluster of origin. Clusters are classified into states according to the sample of origin of cells, whereby tumor states correspond to clusters originating from tumor samples only; pre-tumoral states, from pre-tumoral CreP mice; and normal-like states, from both CreN and CreP mice. c Density plots representing the distribution of single cells according to their sample of origin grouped by genotype and presence or not of a tumor in the mouse, as in (a). d Focus on epithelial cells in normal-like states in CreP mice. Cells in normal-like state were grouped into 3 categories depending on the age of their mouse-of-origin. Ternary plots represent cell populations along three axes representing basal, luminal progenitor (LP) and luminal hormone-sensing (H–S) cells. Signatures (extreme poles) were established based on the top marker genes of each cell population in CreN animals. e UMAP representation of single nuclei H3K4me1 profiles of epithelial cells from CreN and CreP mice with and without tumors. Nuclei are colored according to their cell type. Right: representative snapshots of pseudo-bulk snH3K4me1 profiles for each cell type for the Krt5 and Elf5 genes. f Density UMAP plot representing the distribution of CreN and pre-tumoral CreP cells, similar as in (e). g Scatterplot representing the epigenomic basal and luminal progenitor scores for CreN and pre-tumoral CreP cells. Basal and LP epigenomic signatures were defined based on CreN basal and LP epigenomic profiles

For the scRNA-seq dataset, we collected 43,084 cells from 20 mice, including 23,129 epithelial cells (19,342 from CreP mice, and 3,787 cells from CreN mice) (Fig. 1b and Extended Data Supplementary Fig. 1b). To identify distinct cell states, we first performed unsupervised graph-based clustering (Fig. 1b) and then annotated cell clusters based on the level of expression of physiological markers and their samples of origin (Extended Data Supplementary Fig. 1c,d and Supplementary Table 2), whereby cluster was named if > 50% of cells in it belonged to a single sample (e.g. the T1a cluster has > 50% cells from tumor T1; Extended Data Supplementary Fig. 1e). We then grouped clusters into three states according to their distribution within CreN, CreP and tumor-bearing mice (Fig. 1b,c): (i)"normal-like"states corresponding to clusters in tumor-free CreN and CreP mice, (ii) tumor states, found only in tumors, and (iii) pre-tumoral states, corresponding to clusters found in tumor-free CreP mice and tumors but not in control CreN mice. We identified a series of normal-like states corresponding to well-known mammary gland cell populations: basal cells (Krt5) and clusters of luminal cells (Krt8), including luminal hormone-sensing (H–S) cells (Prlr), luminal progenitor (LP) cells (Aldh1a3) and secretory alveolar-differentiated (Avd) cells (Csn2) (Extended Data Supplementary Fig. 1c,d). Of particular interest, secretory Avd cells were abnormally enriched in CreP virgin mice at all time points, consistent with previous reports of deregulated luminal progenitor differentiation in Brca1/Trp53-mediated tumorigenesis [13].

To distinguish the earliest non-genetic defects occurring in Brca1/Trp53 deficient mammary glands, we first studied normal-like states using both transcriptomics and epigenomic information. Building on previous work identifying LP differentiation defects [13], we quantified and monitored the cell lineage integrity of epithelial cells over time, based on our detailed mapping of tumorigenesis in CreP mice, from 2.7 to 5.4 months. We measured lineage integrity based on coordinates of cells within a ternary plot, whereby each pole represented a reference epithelial cell type—basal, LP or luminal H–S—based on marker genes from CreN mice. At three months, basal cells from CreP mice were segregated near each pole, while LP and H–S cells displayed a continuum between LP and H–S poles, reflecting physiological differentiation from LP to H–S lineage (Fig. 1d). In contrast, starting from 5 months, basal, LP and Avd CreP cells accumulated in the center of the plot, with a continuum of expression profiles from basal to LP reference cell states (Fig. 1d).

To elucidate the non-genetic determinants of this loss of cell lineage integrity, we analysed single-cell epigenomic features of CreP mammary glands using H3K4me1 profiling (Fig. 1a). H3K4me1 accumulates at primed and activated enhancers and promoters [14, 15], offering insights on cell state encoding beyond gene transcription. We adapted snCUT&Tag [16] to mammary glands, achieving a median coverage of 890 unique fragments per nucleus (n = 7,045 nuclei; Extended Data Supplementary Fig. 2a,b). We then in silico sorted cells based on their H3K4me1 enrichment at marker genes (Extended Data Supplementary Fig. 2c–d and Fig. 1e). Hierarchical clustering showed that tumor cells have an epigenome closely related to that of LP cells (Extended Data Supplementary Fig. 1 d), in line with LP cells being the cell of origin of these tumors. It also demonstrated that tumor cells "keep track" of their cell of origin through epigenomic features, even in a highly genomically-rearranged setting. Next, we compared epigenomic profiles of epithelial cells in CreP and CreN mice (Fig. 1f,g). CreP LP cells exhibited a broader range of epigenomic states than CreN LP cells, illustrated by a broader spread of cells over a 2D space (Fig. 1f). To determine whether this variability was associated with the loss of cell lineage integrity that we observed between LP and basal cells, we projected single-cell epigenomic profiles into a 2D plot, with poles representing the reference epigenomes of LP and basal cells obtained from CreN cells (Fig. 1g). Similar to gene expression patterns, we observed a continuum of epigenomic profiles from LP to H–S cells, testifying to a physiological differentiation route in CreN cells. Further, we observed highly disordered epigenomic landscapes for CreP LP cells, with 27% (75 th quantile) of cells occupying intermediary states between basal and LP epigenomes (Fig. 1g).

Altogether, normal-like luminal progenitor cells deficient for Trp53 and Brca1 classified as normal-like cells based on their expression of physiological markers (Fig. 1b, Extended Data Supplementary Fig. 1 d), yet they displayed a drastic epigenomic disorder, potentially leading to the loss of cell lineage integrity observed here and by others [17].

Detection of a rare, epigenetically-primed pre-tumoral cell state

Next, we focused on the three pre-tumoral states we detected. Among these, one is sample specific, while two are multi-sample (Extended Data Supplementary Fig. 1e). Using the PAGA algorithm, we quantified cluster connectivity [18] and found that one of these pre-tumoral states served as a hub linking epithelial sub-clusters, with tumor cell states only accessible via this intermediate state (Fig. 2a). This cell state was found in multiple samples (Shannon index d = 0.70; Fig. 2a) and is composed primarily of cells from tumor-free CreP mice (75%), and to a lesser extent, from tumor samples (25%). We designed this cluster as "pre-tumoral" because tumor states were only reachable through this intermediate transcriptional state (Fig. 2a). Importantly, cells in the pre-tumoral state were overall very rare (0.9% of epithelial cells) yet detectable in 3-month-old CreP mice (0.4%); the fraction of these cells increased with age (1.8% at 5 months). In terms of cell identity, cells in a pre-tumoral state displayed a significant down-regulation of genes characteristic of the luminal compartments, as compared to LP and Avd cells (e.g. Krt8, Krt18, Krt19 and Csn2) (Fig. 2b, Extended Data Supplementary Fig. 1c and Supplementary Table 3). This result indicates that the loss of identity observed in some CreP LPs by 5 months becomes further exacerbated in the pre-tumoral state (Fig. 1d). Notably, while CreP LPs did not yet express pre-tumoral genes (Fig. 2c, e.g. Col9a1, Tnnt2 or Serpine2), we observed H3K4me1 enrichment at these loci within the LP compartment (Fig. 2d), suggesting an epigenetic priming of pre-tumoral genes in Brca1/Trp53-deficient LP cells.

Fig. 2

Identification of a primed pre-tumoral state in vivo. a Partition-based graph abstraction (PAGA) representation of scRNA-seq datasets, with cells from normal-like, pre-tumoral and tumor clusters. Nodes refer to clusters, and edge thickness is proportional to the transcriptional similarity between clusters. The sample of origin for the three pre-tumoral clusters is indicated, with the multi-sample pre-tumoral cluster (derived from multiple pre-tumoral mammary glands) highlighted with a light green background. b Volcano plot representing the log2 expression fold-change and log10 adjusted p-value comparing cells in pre-tumoral state and LP cells. c Violin representation of log10-normalized expression level of pre-tumoral marker genes Serpine2 and Tnnt2. *** corresponds to adjusted p-value < 10–3. d Snapshots of pseudobulk snH3 K4 me1 profiles for the Serpine2, Tnnt2 and Olfml3 genes in epithelial cells and tumor cells

To understand whether the pre-tumoral state originated from the expansion of isolated clones or was reached independently by multiple luminal cells, we evaluated the clonality of cells in the pre-tumoral state using inferred copy-number variation (CNV) profiles derived from scRNA-seq data, analyzed with inferCNV [19] (Extended Data Supplementary Fig. 3; see Methods). First, to understand when genomic alterations began accumulating in mammary glands of CreP mice, we quantified the percentage of genome with inferred CNVs in each cell as compared to reference basal cells. Both the proportion of cells with high CNV content and the average amount of CNV per cell increased with age (Extended Data Supplementary Fig. 3a). Notably, we detected cells with high CNV content as early as 3 months, prior to any observable tumor. This indicates that luminal cells can tolerate significant CNV accumulation without immediate tumor initiation. Luminal progenitors, in particular, exhibited the highest CNV burden, comparable to that observed in pre-tumoral and tumor cells (Extended Data Supplementary Supplementary Fig. 3b,c). Using consensus clustering to group inferred single-cell genomic profiles, we found that the LP compartment is multi-clonal, with a lack of stable partitioning into distinct clones and low pairwise correlation scores, while tumors appeared oligo-clonal, with only a few genetic sub-clones (Extended Data Supplementary Fig. 3 d,e). Notably, part of the pre-tumoral cell population (39%) was multi-clonal, suggesting that multiple luminal cells can switch to the pre-tumoral state. These findings suggest that non-genetic mechanisms can drive the transition of luminal progenitors to the pre-tumoral state.

Altogether, thanks to the profiling of multiple animals nearing tumor initiation, we identified a continuum of cell states shared across several individuals. Luminal cells transition from an aberrant luminal state with compromised epigenetic and lineage integrity to a rare pre-tumoral state, demarked by a more pronounced loss of luminal identity, among other features. This pre-tumoral state serves as an intermediate stage before progressing to fully developed tumor cell states.

Cells in a pre-tumoral state display signs of cell cycle defects and undergo partial EMT

We then explored biological functions of cells in a pre-tumoral state. We first studied which biological pathways characterized the transition from luminal to the pre-tumoral state (Fig. 3a) by comparing pathway activity between cells from LP, Avd and pre-tumoral clusters. We identified that several hallmarks of cancer cells [20] were activated—namely, Myc signaling, the cell cycle (E2F target gene signature), the epithelial-to-mesenchymal transition (EMT) and angiogenesis—while the apoptosis pathway was repressed. These transcriptional signatures endorsed the pre-tumoral nature of this transition state.

Fig. 3

Cell cycle defect and partial EMT in pre-tumoral state. a Barplot representation of the top hallmark pathways activated in pre-tumoral cells (in green) or LP/Avd (in gray); x-axis represents –log10 adjusted p-value. b Stack violin plot representation of expression of genes involved in EMT in epithelial clusters. ***p-value < 0.001, from Wilcoxon rank test comparing pre-tumoral cluster to LP/Avd clusters. c Pseudo-colored multiplex IHC staining for keratin 8 (red), keratin 5 (green), E-cadherin (magenta) and the mesenchymal markers N-cadherin (cyan) and vimentin (yellow). Scale bar, 50 µm. d Dot plot representation of the top 30 candidate TFs of the pre-tumoral expression program. TF ranks (x-axis) and scores (y-axis) were calculated using ChEA3. e Immunofluorescence staining for keratin 8 (red) and EMT-TF Snail (yellow) for CreN (control) or CreP mice and tumors. Scale bar, 50 µm. f Stack violin plot representation of the top markers of pre-tumoral cluster involved in the cell cycle regulation. ***p-value < 0.001, Wilcoxon rank test comparing pre-tumoral cluster to LP/Avd clusters. g Left: pseudo-colored multiplex IHC staining for identity markers keratin 5 (green) and keratin 8 (red), together with senescent marker p16 (cyan) and EMT markers E-cadherin (magenta) and vimentin (yellow). Scale bar, 50 µm. Right: Sunburst plot representation of the multiplex IHC staining for p16 + and p16– luminal cells from glands from 5-month-old CreP mice. Number of analyzed cells and mice are indicated

To further understand what role the EMT plays in these cells, we investigated the marker genes of the pre-tumoral state. The Vim, Fn1 and Sparc genes were significantly up-regulated in cells in a pre-tumoral state (Fig. 3b and Supplementary Table 3), indicative of changes in cytoskeleton and extracellular matrix. Cdh1/E-cadherin and several claudin genes (Cldn4, -3 and -1) (Supplementary Table 3) were downregulated, indicative of the dissolution of adherens and tight junctions. Pre-tumoral state cells still expressed epithelial keratins, albeit to a lower level than their LP counterparts (Extended Data Supplementary Fig. 1c), suggesting that they reside in an intermediary epithelial and mesenchymal state [21]. We validated these findings using multiplex immunohistochemistry (IHC). We detected luminal cells in CreP mammary glands that expressed both vimentin and E-cadherin (n = 314 double positive cells, out of 2,079 luminal cells; P = 3.1e- 5 compared to CreN glands, Fisher’s extract test; Fig. 3c).

Predicting the transcription factors (TF) that potentially drive the transcriptomic changes from the luminal to the pre-tumoral state, we observed FOX family members among the top candidates as well as a series of EMT-associated TFs: Prrx1 and Prrx2 [22, 23], recently discovered to be EMT inducers, and the canonical EMT-associated TFs (Twist1, Twist2, Snail and Snail2) (Fig. 3d). To validate our finding that the EMT-associated TFs were expressed prior to tumor formation, we stained formalin-fixed, paraffin-embedded (FFPE) sections from mice at different ages for the EMT-related TFs Twist1 and Snail using immunofluorescence. In CreP mice, we detected luminal cells that expressed Snail prior to tumor formation, and the proportion of these cells increased with age; in turn, we found that Twist1 and Zeb1 were only expressed in full-grown tumors (Fig. 3e and Extended Data Supplementary Fig. 4a-c). These results are similar to previous findings of Snail expression leading up to tumor formation in mice [24]. We show here that EMT is one link of a series of state switches that occurs prior to tumor initiation.

We next focused on the top marker of the pre-tumoral state, Cdkn2a/p16 (Fig. 2b and Supplementary Table 3), which is a marker for cell cycle arrest and senescence [25,26,27,28]. We first tested for p16-positive cells in CreP tumor-free mammary gland and assessed the cell cycle status of these cells. Using both immunofluorescence and multiplex IHC, we showed that cells expressing p16 are specific to CreP mice and are mostly luminal cells (Extended Data Supplementary Fig. 5a-d). These cells were detectable starting at 3 months of age and displayed an increased fraction of Ki67 staining, as compared to luminal CreN cells, with mouse aging (Extended Data Supplementary Fig. 5e). Thus, luminal cells can activate p16 prior to tumor initiation and can apparently bypass the cell cycle arrest normally imposed by p16. Notably, other cell cycle related genes that together promote G1 to S transition—Cdk1, Cdk4 and Ccnd1— were overexpressed in cells in a pre-tumoral state (Fig. 3f and Supplementary Table 3). The overactivation of these genes could help cells bypass a p16 overexpression–induced cell cycle arrest [29].

Next, we looked for traces of a present or past senescence-like phenomenon in CreP mammary glands. At the transcriptional level, the pre-tumoral state was significantly enriched for a senescence-related signature (Fridman_Senescence [30], adjusted P < 0.01) (Supplementary Table 3). In addition, cells in pre-tumoral state express the pro-senescence secreted factors, Igfbp4 and Igfbp7 (Supplementary Table 3), which can trigger senescence in neighboring cells [31]. We also screened CreP tissues for markers of senescence associated to p16 upregulation [18], including the presence of senescence-associated heterochromatin foci (SAHF) and senescence-associated-B-galactosidase (SABgal). We saw no SABgal staining within CreP mammary glands or tumor sections (Extended Data Supplementary Fig. 5 h); however, by immunofluorescence, we observed SAHF-like structures in tumor-free CreP glands, starting in 3-month-old mice (Extended Data Supplementary Fig. 5f,g). These results suggest that, in addition to p16 activation, cells in a pre-tumoral state might have undergone a senescent-like phenomenon.

To spatially resolve the cell cycle and EMT associated changes in the mammary gland, we stained for epithelial (E-cadherin) and mesenchymal (N-cadherin, vimentin) markers as well as for p16, with multiplex IHC. p16 expression was significantly associated with the expression of vimentin in CreP mammary glands: both E-cadherin and vimentin were expressed in 43% of p16-positive luminal cells but only in 17% of p16-negative luminal cells (P = 3.3e- 6, Fisher’s exact test; Fig. 3g). These results indicate that alterations of cell cycle and a partial EMT can co-occur in luminal cells prior to tumor formation.

Features of pre-tumoral cell state are detected in early-stage breast cancers and in mammary glands of BRCA1m carriers

To first determine whether the pre-tumoral state is present in human tissues, we interrogated two large breast tumor cohorts [19, 32,33,34] and analysed the expression patterns of pre-tumoral genes, first focusing on the top marker of the pre-tumoral state, CDKN2A/p16. We found that CDKN2A was specifically over-expressed in almost all basal-like tumors (Fig. 4a). These findings mirrored our observations for Cdkn2a/p16 expression in mice (which was detectable prior to tumor initiation and maintained in tumor cells), suggesting that CDKN2A activation might be an early event in basal-like tumorigenesis. Next, we studied the expression pattern of the full pre-tumoral signature, defined as the top overexpressed genes in pre-tumoral cells versus LP and Avd cells (n = 50 human orthologs) (Supplementary Table 4). In the two cohorts, the pre-tumoral signature was significantly more expressed in basal-like tumors than in other tumors (Fig. 4b and Extended Data Fig. 6a). In addition, the signature was more expressed in low-stage than high-stage basal-like tumors and was associated with a longer disease-free survival (Fig. 4c,d and Extended Data Supplementary Fig. 6b,c). These results suggest that tumors with a pre-tumoral like expression program might be closer to an early-stage disease.

Fig. 4

Features of the pre-tumoral state are detected in human low grade basal-like tumors and BRCA1-deficient mammary glands. a Boxplot of the log10 normalized expression level of CDKN2A in the Pan Cancer breast dataset according to the tumor subtype, ***p-value < 0.001 from Wilcoxon rank test comparing CDNK2A expression score of basal tumors vs other samples. b Boxplot representation of the scores for the pre-tumoral signature according to the tumor subtype, ***p-value < 0.001 from Wilcoxon rank test comparing pre-tumoral score of basal tumors vs other samples. c Box plot representation of the scores for pre-tumoral signature according to the stage of the tumor, * p-value < 0.05 from Wilcoxon rank test comparing pre-tumoral score of stage I vs stage II/III tumors. d Kaplan–Meier disease-free survival curve for basal-like tumors, according to expression score of the human-derived pre-tumoral signature in the Pan Cancer breast dataset. e-f UMAP representation of the MERFISH datasets of 4 BRCA1m ± juxta-tumor human biopsies clustered by sample of origin (e) or cell identity (f). g Left: Merscope visualizer screenshots of two juxta-tumor breast BRCA1m human samples, analyzed using a custom 140 gene-panel (Supplementary Table 6). Scale bar, 1 mm. Middle: 2D spatial visualization of single cells from each experiment. Cells were labeled according to their corresponding cell type annotation. Right: 2D spatial visualization of the kernel-density score estimation of the co-expression of the top highly spatially variable pre-tumoral genes (CCND1, VIM, IGFBP4, AQP5) and the LP marker ELF5 positive cells. For a-c, *p-value < 0.05, ***p-value < 0.001, n.s: not significant, Wilcoxon's test comparing basal-like to each other breast cancer subtype or stage 1 to stage 2–3 cancers

We next asked whether the pre-tumoral state can be detected in normal-like glands in humans near tumor initiation, by analysing mammary epithelium from women with BRCA1 germline deficiency. We reasoned that informative samples would be those where the epithelium had been exposed to the same intrinsic—here, BRCA1 deficiency—and extrinsic stresses as cells that already have initiated a tumor. This unique scenario, corresponding to juxta-tumoral tissue, enhances the likelihood of detecting pre-malignant molecular abnormalities. We used the spatial transcriptomics MERFISH [35] approach to probe the expression of genes of the pre-tumoral signature (Supplementary Tables 5 and 6), together with 20 marker genes to call cell identities in four juxta-tumoral tissues of BRCA1 m carriers (n = 49,970 cells; Extended Data Supplementary Fig. 6 d). We identified across four patients 20,021 epithelial cells, among which 11,263 LP cells. We detected the co-activation of several pre-tumoral genes – CCND1, VIM, AQP5 & IGFBP4— in patches of LP cells (Fig. 4e, Extended Supplementary Fig. 6e-f). Such observations mirror our findings in the mouse model, where pre-tumoral luminal cells acquire mesenchymal (Vim), senescence-related (Igfbp4) and aberrant cell cycle (Ccnd1) features. This analysis demonstrates that a fraction of LP cells displays a pre-tumoral signature in the tissues of BRCA1 m carriers that already had a tumor.

Luminal cells in pre-tumoral state activate immunosuppressive and FGF signaling

We then explored the way cells in pre-tumoral state communicate with one another and with other cell types from their microenvironment. To do so, we leveraged all cell types in our mouse scRNA-seq datasets and inferred cell–cell communication pathways using the CellChat algorithm [36] applied on all cells of CreP tumor-free mice (n = 8,855 cells; Fig. 5a). Pre-tumoral cells shared inward communication pathways with both LP and basal cells, expression genes coding for receptors for Notch, Kit and Epha signaling (Extended Data Supplementary Fig. 7a). Looking at the outward communications, we identified that pre-tumoral epithelial cells were predicted to send different signals than normal-like epithelial cells (Extended Data Supplementary Fig. 7b). Strikingly, pre-tumoral cells activated two signaling axes —MIF and SPP1— that were also found in tumor cells. Both pathways involved the emission of ligands from tumor cells to communicate with macrophages that bear the Cd44 receptor (Extended Data Supplementary Fig. 7c,d). The Spp1:Cd44 signaling axis has been previously reported to act as an immune checkpoint, inducing immune tolerance in tumors [13, 37, 38]. Pre-tumoral cells could thus be using such a signaling axis to evade immune surveillance during tumor initiation.

Fig. 5

Activation of FGF signaling pathway prior to tumor formation. a UMAP representation of all cells from CreP scRNA-seq datasets. b Circos plot representation of Fgfr1/Fgf8 communication between pre-tumoral cells and other cells. c Stack violin plot representation of log10 normalized expression values of top Fgf and Fgfr genes predicted to contribute to the FGF signaling between pre-tumoral cells and other cells. *** adjusted p-value < 0.001, n.s, non-significant for Wilcoxon rank test comparing expression scores in LP and pre-tumoral cells. d Immunofluorescence staining for keratin 8 (magenta), Krt5 (cyan) and pFGFR (yellow) of wild-type and BRCA1m prophylactic, juxta-tumoral and invasive carcinoma human samples. Scale bar, 100 µm. e Biplot illustrating the intensity of pFGFR staining per cell, together with the expression level of the luminal marker keratin 8 and the basal marker keratin 5

Cells in pre-tumoral state also transiently activated fibroblast growth factor (FGF) signaling (Fig. 5b and Extended Data Supplementary Fig. 7b,c) for autocrine and paracrine communication with epithelial cells and fibroblasts (Fig. 5b and Extended Data Supplementary Fig. 7 d). This signaling is not predicted to occur in tumor cells. Pre-tumoral cells displayed an over-expression of the receptor Fgfr1 as compared to LP cells (Fig. 5c) and were the only cells expressing the Fgf8 ligand. Expression of the ligand is lost in tumor cells, suggesting that the activation of the FGF signaling is transient and potentially necessary for early phases of transformation, but not for maintenance of tumor growth.

To assess the relevance of these findings in human tissues, we analysed the activation of the FGF signaling in human mammary glands. For this, we performed immunofluorescence staining for the activated phosphorylated form of all four isoforms of FGF receptors (pFGFR) in FFPE samples from n = 20 individuals (Supplementary Table 7). Samples included 8 healthy mammary glands from patients that never had a tumor (n = 4 BRCA1wt and n = 4 BRCA1m ‘prophylactic’), as well as normal-like mammary glands from BRCA1m carriers with a tumor (n = 9 BRCA1m juxta-tumoral) and tumors from BRCA1m carriers (n = 3, Fig. 5d). pFGFR levels were significantly elevated in specific regions of normal-like mammary glands of BRCA1 m carriers with and without a tumor, as compared to mammary glands of BRCA1wt individuals (Extended Data Supplementary Fig. 7e). Cells with high levels of pFGFR were specific to the luminal compartment (Fig. 5e). We did not detect high levels of pFGFR in any cells in the three tumors we studied, suggesting that activation of FGF signaling is not a prerequisite for tumor growth. These results show that FGF signaling is over-activated in BRCA1m tissues. Further studies will be needed to understand whether the number of FGF-high cells is associated to the timing of occurrence of tumors in BRCA1m carriers.