Multiple distinct metastatic cell states are induced by epithelial-mesenchymal plasticity

Multiple distinct metastatic cell states are induced by epithelial-mesenchymal plasticity | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Multiple distinct metastatic cell states are induced by epithelial-mesenchymal plasticity View ORCID Profile Fahda Alsharief , View ORCID Profile Robert K. Suter , View ORCID Profile Apsra Nasir , View ORCID Profile Gray W. Pearson doi: https://doi.org/10.1101/2025.08.15.670583 Fahda Alsharief 1 Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University , Washington, DC 20057, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Fahda Alsharief Robert K. Suter 1 Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University , Washington, DC 20057, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robert K. Suter Apsra Nasir 1 Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University , Washington, DC 20057, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Apsra Nasir Gray W. Pearson 1 Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University , Washington, DC 20057, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Gray W. Pearson For correspondence: gp507{at}georgetown.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT Epithelial–mesenchymal plasticity (EMP) enables carcinoma cells to adopt phenotypes along a continuum between fully epithelial and fully mesenchymal states. In triple-negative breast cancer (TNBC), EMP has been implicated as a driver of metastasis, but the functional roles of specific EMP-associated states remain poorly defined. Here, we combined single-cell RNA sequencing with functional assays in the a genetically engineered mouse model of basal-like TNBC to determine how EMP contributes to phenotypic heterogeneity and metastatic progression. We identified a previously uncharacterized population of highly plastic tumor cells that had lost mammary lineage identity yet retained core epithelial features, including E-cadherin and EpCAM expression. These high-plasticity EpCAM-high (HP-Ehi) cells lacked canonical mesenchymal markers such as Vimentin, yet exhibited elevated heritable intrinsic plasticity, enabling transitions toward more mesenchymal-like EpCAM-low (Elo) states. Strikingly, both HP-Ehi and Elo populations independently initiated robust lung metastases and maintained the EMP phenotypes of their cells of origin throughout colonization. Together, these findings demonstrate that EMP generates multiple distinct heritable transcriptional states with high metastatic potential. INTRODUCTION The tumors of 15-20% of women diagnosed with breast cancer lack pathologically detectable estrogen receptor (ER), progesterone receptor (PR) and ErbB2 (HER2) expression ( 1 ). These patients are classified as having triple negative breast cancer (TNBC) ( 2 ). The outcomes for TNBC patients are worst among all classes of breast cancer patients ( 3 ). Notably, less than 11% of women diagnosed with metastatic TNBC survive an additional 5 years ( 4 ). Cellular plasticity underlies the ability of TNBC cells to metastasize and evade therapeutic interventions ( 5 , 6 ). TNBC cell plasticity is increased by the activation of epithelial-mesenchymal plasticity programs ( 7 ). EMP enhances TNBC invasion and metastatic dissemination ( 8 – 11 ). EMP also promotes TNBC resistance to treatment ( 12 ). However, while it is clear that EMP is detrimental to patient outcome, attempts to translate our understanding of EMP into clinically improved prognostic markers and treatments have not yet been successful ( 13 ). EMP describes a spectrum of reversible phenotypic changes in which epithelial tumor cells gradually lose polarity and cell–cell adhesion while acquiring mesenchymal traits such as motility and invasion. This process is governed by a conserved set of transcription factors—including SNAIL, SLUG, TWIST1, ZEB1, and ZEB2—that repress epithelial programs (e.g., E-cadherin/ CDH1) and activate mesenchymal genes (e.g., VIM, MMPs). EMP induced phenotypic conversion are transient and highly contextual ( 9 , 11 , 14 ). Notably, EMP is now recognized to generate a continuum of intermediate or “hybrid” states. These hybrids can co-express both epithelial and mesenchymal features and are functionally heterogeneous. The expression of Epitehlial Cell Adhesion Marker (EpCAM) is used as a surrogate for epithelial lineage identity. In the context of EMP induced phenotypic heterogeneity, EpCAM-high (Ehi) cells retain more epithelial characteristics, exhibit limited activation of mesenchymal genes, and express a restricted subset of EMP transcription factors ( 5 , 8 , 15 – 18 ). In contrast, EpCAM-low (Elo) hybrid cells show greater epithelial lineage infidelity, upregulate multiple EMP-TFs, remodel the extracellular matrix, and exhibit enhanced invasive collective and single cell invasive behavior ( 5 , 15 , 19 ). Much of what is known about the contribution of EMP to metastasis in TNBC comes from studies of Elo cells, which can differ in metastatic potential and, in some cases, revert toward more epithelial phenotypes ( 19 – 21 ). By comparison, the functional role of Ehi hybrids remains poorly defined. Notably, it is unclear whether Ehi cells can initiate metastasis directly or merely serve as intermediates en route to more mesenchymal states. To address this gap, we used the C3-TAg genetically engineered mouse model (GEMM) of TNBC, which recapitulates key features of the human disease ( 22 , 23 ). Combining single-cell RNA sequencing with functional assays, we investigated how EMP generates phenotypic heterogeneity. We identified a previously uncharacterized population of high plasticity (HP) Ehi cells that emerge during tumor progression. These HP-Ehi cells showed a loss of mammary identity while retaining the expression of epithelial lineage markers. Notably, the HP-Ehi cells exhibited an inconsistent and low-level of mesenchymal gene expression, indicating that this new state is a precursor to previously described hybrid states that are exemplified by co-expression of E-cadherin and Vimentin ( 24 ). Importantly, HP-Ehi cells displayed higher heritable intrinsic plasticity than Ehi cells from early hyperplasias. This intrinsic plasticity enabled HP-Ehi cells with the ability to transition into canonical hybrid states and more stable mesenchymal Elo states in response to extrinsic cues, suggesting that they serve as a reservoir for further EMP progression. Despite retaining epithelial identity, HP-Ehi cells were independently capable of initiating metastasis to the lung and liver. Moreover, the metastases formed by HP-Ehi and Elo cells were phenotypically distinct, differing in Vimentin expression and spatial architecture. These observations indicate that multiple EMP states can seed metastases, and that phenotypic diversity established in the primary tumor is maintained in distant lesions. MATERIALS AND METHODS Mice The C3-TAg [FVB-Tg(C3-1-TAg)cJeg/Jeg], PyMT [FVB/N-Tg(MMTV-PyVT)634Mul/J] and NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were purchased from The Jackson Laboratory (C3-TAg: 013591, PyMT: 002374 and NSG: 005557) and ( Supplementary file 1 ). Mice were housed, bred and euthanized in accordance with a protocol approved by the Institutional Animal Use and Care Committee at Georgetown University (IRB# 2017-0076) and in compliance with the NIH Guide for the Care and Use of Laboratory animals. Female mice were used for all experiments. Tumor organoid derivation The largest tumors from female C3-TAg and PyMT mice were minced and dissociated for up to 120 min at 37°C in a mixture of 1 mg/ml Collagenase (Worthington, LS004188), 20 U/ml DNase (Invitrogen, 18047-019), 5% Fetal Bovine Serum (FBS) (Peak Serum, PS-FB2), ITS (Lonza, 17-838Z), non-essential amino acids (Sigma, M7145) and 10 ng/ml FGF-2 (Peprotech, 100-18C) in DMEM/F-12 (Corning, 10-092-CV). Dissociated tumors were pelleted at 80 x g for 2 min and the supernatant was discarded. Tumor organoids were then rinsed up to 5 times in 5% FBS in DMEM/F-12 followed by filtering through a 250 µm tissue strainer. Organoids were then tested in invasion assays or to establish organoid lines and cell lines ( Supplementary file 1 ). Cell and organoid culture Cell and organoid lines were generated from C3-TAg tumors (Supplementary file 1) and tested for mycoplasma (Lonza, LT07-703) prior to use and the creation of frozen stocks. Cells and organoids were routinely used within 25 passages. Culture conditions for all cell and organoid lines are summarized in Supplementary file 1. Organoids were passaged at least once per week by dissociating tumor organoids into single cell suspensions with Dispase (Sigma, SCM133) and TryPLE (Gibco, 12605-010). The cell suspensions were plated at a density of 200,000-500,000 cells per well in a 24-well ultra-low adhesion plate (Sigma, CLS3474) to form multicellular aggregates for at least 16 h. The aggregates were then embedded in Matrigel (Corning, 354230) or Cultrex (Biotechne, 3533-005-02) and overlaid with Organoid Media ( Supplementary file 1 ) in 6-well ultra-low adhesion plates (Sigma, CLS3471). Orthotopic Tumor Models For orthotopic transplantation experiments, organoid cells were first cultured in Organoid media. To initiate orthotopic tumors 250,000 organoid cells were injected in the right 4 th fat pad of 8-12 weeks old female NSG mice. Mice were euthanized due to tumors reaching a maximum allowed diameter of 2 cm and tissue collection was performed 34 days post injection. Representative portions of primary tumors were fixed in formalin followed by paraffin embedding and sectioning by Histology and Tissue Shared Resource (HTSR) at Georgetown University. Organoid invasion Organoids in 30 µl of ECM were plated onto a 20 µl base layer of ECM in 8 well chamber slides (Falcon, 354108) and allowed to invade for 48 h unless otherwise indicated. The ECM was a mixture of 2.4 mg/ml rat tail collagen I (Corning, CB-40236) and 2 mg/ml of reconstituted basement membrane (Matrigel or Cultrex) unless otherwise indicated. Tumor organoids were analyzed in a base media of DMEM/F-12, ITS and FGF. Organoids were fixed and stained with Hoechst and Phalloidin. Images were acquired with a Zeiss LSM800 laser scanning confocal microscope using 10x/0.45 (Zeiss, 1 420640-9900-000) or 20x/0.8 (Zeiss, 1 420650-9902-000) objectives. To determine the area of invasion, an image mask for each organoid was generated using ImageJ (NIH) based on the Hoechst or Phalloidin signal. The total area of the invading cell nuclei was determined using the “Measure” function in ImageJ. Circularity was quantified using the “Analyze Particle” function. Immunofluorescence and immunoblotting Experiments and analysis were performed as described ( 25 ) using antibodies detailed in Supplementary file 1. Immunoblots were imaged using an Odyssey scanner (Licor, 9120). Immunofluorescence images were acquired using 10x/ 0.45 (Zeiss, 1 420640-9900-000) and 20x/0.8 (Zeiss, 1 420650-9902-000) objectives. For analysis of the relationship between Krt14 expression and invasion, organoids were classified as invasive if they had at least two protrusions with each protrusion having at least two cells invading outward from the center mass. Images were exported as TIFFs and analyzed with ImageJ. The freehand selection tool was used to define ROIs containing individual organoids for analysis. The Krt14 fluorescence for each organoid was then defined as the “Mean Gray Value”, as determined using the “Measure” function. To define Krt14 expression in cells leading invasion, >10 organoids stained with Phalloidin, Hoechst, Krt14 and Krt8 were analyzed. Seven Z slices at 10 µm intervals over a total span of 100 µm were acquired, and the leading cells of each protrusion were designated as Krt14 low or Krt14 high . Vimentin and E-cadherin expression were analyzed in 5 µm histology sections. Organoids in 8-well chamber slides (Falcon, 354108) were washed 3x with distilled water. After detaching the chamber walls from the slides, the organoid/ECM gels were gently picked up using a single edge blade (Personna, 94-120-71) and laid out on a strip of parafilm (Bemis, PM-999). The 8-well chamber walls were placed around the gels and 150-200 µl of hydroxyethyl agarose processing gel (Thermo Fisher, HG 4000-012) was poured into the well. After the hydroxyethyl agarose processing gel solidified, it was transferred into histosettes (Simport, M498-3) and stored in 70% EtOH until embedding in paraffin by the Georgetown Histology and Tissue Shared Resource. The 5 µm sections were deparaffinized and immunostained as described ( 5 ) to detect Vimentin and E-cadherin expression ( Table S1) . For individual organoids, Vimentin expression was defined as the “Mean Gray Value” using the “Measure” function in ImageJ. Using ImageJ, Vimentin expression was defined as the “Mean Gray Value” for individual organoids using the “Measure” function. For characterization of the trailblazer cell state, the cell leading a collectively invading group of cells was classified as a “trailblazer cell” while cells detached from the tumor organoid were classified as “single cells”. Each cell was assigned E-caderhin pos / Vimentin neg , E-Cadherin pos /Vimentin pos or E-Caderin neg / Vimentin pos status based on E-Cadherin and Vimentin expression. Immunohistochemistry Sample processing and staining was performed as described ( 25 ). Images were acquired using 10x/0.45 (Zeiss, 1 420640-9900-000) and 20x/0.8 (Zeiss, 1 420650-9902-000) objectives. The area of metastasis was determined by dividing the area of metastases in each lung section by the total area of lung tissue in the section. Zen Blue software was used to define image masks based on SV40 or Vimentin signal. The area of Vimentin was divided by the total area SV40 to determine the expression of Vimentin in metastatic lesions. Flow Cytometry Cells were dissociated with TrypLe (Gibco, 12605-010) into single cell suspensions, and then washed 2x with FACs buffer (PBS + 2% FBS). Cells were then incubated with anti-CD326 (EpCAM)-PE/Dazzle 594 (Biolegend, 118236) at 4°C for 30 minutes. After staining, cells were washed with FACs buffer 2x, and stained with Helix NP Blue (Biolegend, 425305) in order to exclude dead cells. Cells were then subjected to flow cytometry analysis using BD LSR Fortessa. Results were analyzed using FCSExpress 7 (De Novo Software). Single cell gene expression analysis Libraries were prepared with the Georgetown Genomics and Epigenomics Shared Resource using the Chromium Next GEM Single Cell Single Cell 3’ kit following the manufacturer’s protocol (10X Genomics). Targeted cell recovery was 5000 cells per sample. Libraries were sequenced by Novogene with the Hiseq PE150 platform at a depth of approximately 70 million paired-end 150 base pair reads per sample. Cell Ranger software was used for demultiplexing samples, barcode processing and alignment to the mouse reference genome (mm10). Cells were subjected to quality control and filtering based on per cell total RNA counts and mitochondrial transcript abundance ( 26 ). Uniform Manifold Approximation and Projection (UMAP) dimension reduction, clustering, peak calling was performed in R using Seurat ( 27 ). Clusters of non-tumor cells were determined based on gene expression using canonical lineage markers. Pseuodotime trajectory analysis and gene module derivation was performed with Monocle3 ( 28 ). Regulon analysis was perfomed using SCENIC ( 29 ). Statistical Methods Data was analyzed with Prism 9.0.2 (Graphpad). Data with a normal distribution, as determined by Shapiro-Wilk test, was analyzed by two tailed Student’s t-test. Data that did not pass a normality test were analyzed by Mann-Whitney U test or Kruskal Wallis test with Dunn’s Multiple comparison test. The specific statistical tests are indicated in the figure legends. Sample numbers are defined and indicated in the figure legends or on the figure panels. RESULTS Using scRNA-seq to define the cellular composition of C3-TAg tumors To investigate how epithelial-mesenchymal plasticity (EMP) contributes to phenotypic heterogeneity in triple-negative breast cancer (TNBC) progression, we analyzed mammary tumors from the C3( 1 )/SV40 T-antigen (C3-TAg) genetically engineered mouse model (GEMM) ( 22 , 30 ). Among available GEMMs, C3-TAg tumors most closely resemble human TNBC when compared across intrinsic breast cancer subtypes ( 23 ). To capture dynamic changes in cellular phenotypes during tumor development, we performed single-cell RNA sequencing (scRNA-seq) on normal mammary glandular epithelium, as well as 5 mm diameter and >15 mm diameter C3-TAg tumors ( Fig. 1A ). After quality control filtering based on mitochondrial transcript abundance and doublet exclusion, 2,561 high-quality cells were retained for downstream analysis ( Fig. 1B ). Cell types were annotated based on canonical lineage markers, transcriptional similarity to a reference mouse singlecell transcriptomic atlas ( 31 ), cell cycle status, and sample origin ( Fig. 1B-D , S1A-D ). Cells from 5 mm tumors expressed both basal and luminal keratins and most closely resembled mammary progenitor cells in the mouse cell atlas ( Fig. 1E-G ). While commonly classified as “basal-like” due to basal keratin expression, TNBC tumors in patients more closely resemble mammary progenitor cells ( 32 ). In contrast, cells from >15 mm tumors exhibited reduced similarity to mammary progenitors and increased transcriptional resemblance to mesenchymal stem cells (Fig. E-G). Subsets of >15 mm tumor cells also showed increased expression of the canonical mesenchymal marker Vimentin and transcription factors associated with EMP ( Fig. 1G ). These findings indicate that EMP-driven lineage plasticity contributes to the emergence of new cell identities as C3-TAg tumors progress. Download figure Open in new tab Figure 1. Using scRNA-seq to define the cellular composition of C3-TAg tumors. A. Graphical model showing the samples analyzed by scRNA-seq. B. UMAP showing cells from normal mammary gland, 5 mm and >15 mm tumors annotated by sample source. C. UMAP showing cells from normal mammary gland, 5 mm and >15 mm tumors annotated by cell type. D. UMAP showing the expression of cell lineage specific genes in cells from normal mammary gland, 5 mm and >15 mm tumors annotated by cell type. E. Heatmap showing the similarity of tumor cells to the indicated normal cell types. F. Quantification show a comparison of the similarity of 5 mm and >15 mm tumor cells to luminal progenitor, secretory alveolar and mesenchymal stem cells. G. UMAPs showing the expression of representative luminal progenitor, lactation, basal and EMT genes in 5 mm and >15 mm tumor cells. Defining transcriptional heterogeneity in C3-TAg tumor cell populations To assess how EMP contributes to transcriptional diversity, we performed unsupervised clustering of tumor cells ( Fig S2 ). Cells from >15 mm tumors were distributed across 7 of 8 transcriptional clusters than cells while cells from the 5 mm tumors were restricted to 3 clusters, suggesting increased heterogeneity with tumor progression ( Fig. 2A-B ). Notably, clusters 2, 3, 6, and 8 showed elevated expression of EMP-associated genes and reduced expression of mammary progenitor markers and cell-cell adhesion genes relative to other clusters ( Fig. 2C-E , S2 ). This pattern indicates that EMP-induced heterogeneity was widespread, not limited to a specific subpopulation. These findings are consistent with prior studies, including our own, demonstrating that rather than following a binary epithelial-to-mesenchymal switch, cells existed along a continuum of intermediate states. A hallmark of this EMP-induced heterogeneity is the emergence of hybrid states, in which cells simultaneously express both epithelial and mesenchymal markers ( 17 ). Indeed, cells in hybrid EMP states, as indicated by the co-expression of epithelial genes such as E-cadherin and EpCAM and mesenchymal genes, such as Vimentin and EMT transcription factors (Twist1, Zeb1 and Zeb2) were detected in the >15 mm tumor population. Notably, clusters showed distinct patterns of EMP gene expression. Cluster 8 included Slug expression and p63-associated signatures, while Clusters 3 and 6 represented more advanced EMP states with loss of epithelial identity and robust induction of Vimentin and different combinations of EMP-TFs and ECM genes ( Fig. 2C-E and S2). Consistent with these molecular features, organoids derived from >15 mm tumors were more invasive than those from 5 mm tumors ( Fig. 2F ). Thus, EMP promotes extensive transcriptional heterogeneity by generating a spectrum of intermediate and mesenchymal-like states, rather than a uniform phenotypic endpoint. Download figure Open in new tab Figure 2. Using scRNA-seq to define transcriptional heterogeneity in C3-TAg tumor cell populations. A. UMAP showing annotation of 5 mm and >15 mm tumor cells after clustering when controlling for the contribution of cell cycle genes and when just plotting tumor cells. B. UMAP showing Serurat clusters from 5 mm and >15 mm tumor cells. C. UMAPs showing the expression of canonical EMT genes and EMT transcription factors. D. UMAPs showing the expression of p63 induced EMT related genes. E. UMAPs showing the expression of canonical epithelial genes. F. Invasion of organoids derived from normal mammary gland, 5 mm and >15 mm tumors. Trajectory analysis reveals multiple EMP paths with distinct regulatory features To understand how these diverse transcriptional states relate to each other, we used Monocle3 to construct pseudotime trajectories ( 28 ). Pseudotime approximates the progression of transcriptional states but does not reflect real-time dynamics. To focus on EMP-associated transitions, canonical cell cycle genes were excluded. The observed transitions did not follow a single linear progression but instead revealed a branched bifurcation terminating in Clusters 3 and 6 ( Fig. 3A-C ). This contrasts with prior models based on cell lines and xenografts, which described EMP as a more linear or unidirectional process. The 2 trajectories shared features—including downregulation of epithelial identity genes and upregulation of the canonical EMP genes, like Vimentin ( Fig. 3D-E ). However there were also notable differences among genes associated with EMP. Twist1 and Zeb1 were enriched along trajectory 1, while Foxc2 was uniquely activated along trajectory 2 ( Fig. 3D-E ). These differences suggest that distinct regulatory mechanisms govern each EMP trajectory. Importantly, gene expression changes along pseudotime revealed that downregulation of mammary lineage gene expression preceded the robust induction of mesenchymal genes, which peaked at the end of the trajectories. This uncoupling challenges traditional EMP models in which mesenchymal traits appear first and suggests a more complex regulatory logic, where partial loss of epithelial identity sets the stage for subsequent mesenchymal transitions ( Fig. 3D-E ). To confirm this uncoupling of mammary identity we next used Monocle3 to group genes into co-expression modules and visualize how each trajectory activated distinct combinations of regulatory programs ( Fig. S3A and Table S2). Cells in both trajectories lost activity of modules related to the mammary lineage and epithelial identity, including apical junction and mammary-specific genes first in pseudotime ( Fig. S3B ). This loss of lineage identity was followed by an increased of modules associated with ECM remodeling and motility ( Fig. S3B ). These findings support a model in which EMP proceeds through multiple transcriptional paths with distinct regulators, and in which epithelial gene loss is an early and separable event from full mesenchymal conversion. Download figure Open in new tab Figure 3. Trajectory analysis reveals multiple EMP paths with distinct regulatory features. A. UMAP showing the pseudotime annotation of 5 mm and >15 mm tumor cells. Trajectories are indicated by colored lines. B. UMAP showing the tumor source annotation of 5 mm and >15 mm tumor cells. Trajectories are indicated by colored lines. C. UMAP showing the Seurat clusters of 5 mm and >15 mm tumor cells. Trajectories are indicated by colored lines. D. Trajectory 1 showing progression of cells through different states induced by EMP. E. Trajectory 2 showing progression of cells through different states induced by EMP. Plasticity is dynamic, directional, and heritable To test whether EMP states predicted invasive behavior, we isolated EpCAM-high (Ehi) and EpCAM-low (Elo) cells from >15 mm tumors using fluorescence-activated cell sorting (FACS). ( Fig. 4A ). To test whether EMP states are stable or reversible, we cultured Ehi and Elo cells as organoids and analyzed their phenotypes over four weeks ( S4A ). Ehi cells frequently transitioned to the Elo state, while Elo cells rarely reverted ( Fig. 4B ). Parental organoid cultures also showed enrichment of Elo cells over time ( Fig. 4B ). Unsorted primary tumor organoid cultures also showed an enrichment of Elo cells over time in all but one tumor analyzed ( Fig. 4C ). This directional bias towards Elo enrichment mirrored the pseudotime-inferred trajectory. These results suggest that the pseudotime trajectory observed in scRNA-seq reflects dynamic transitions between cell states during tumor progression, rather than the outgrowth of fixed clones. Notably, cells from early-stage hyperplasias exhibited the lowest frequency of Elo conversion ( Fig. 4D ). This suggested that the Ehi cells acquired an increased intrinsic plasticity as primary tumors evolved, However, this high plasticity was not essential for tumor initiation, as low plasticity hyperplasia-derived organoids initiated tumor growth with similar kinetics as high plasticity tumor-derived organoids ( Fig. S4B ). Thus, the high plasticity in the Ehi population was necessary for progression to Elo states is acquired during tumor development and heritable. To distinguish this step in tumor development, we term this state the high plasticity Ehi (HP-Ehi) state. Download figure Open in new tab Figure 4. Plasticity is dynamic, directional, and heritable. A. Graphical model showing how Ehi and Elo cells are isolated by FACS from tumor cell populations. B. FACS plots show the change in expression of EpCAM in organoids derived from Ehi and Elo cells. Graph shows that percentage of cells that converted from and Ehi to Elo state and Elo to Ehi state. C. FACS plots show the change in expression of EpCAM in unsorted tumor organoids over time. Graph shows that percentage of Elo cells in the organoids with the first 14 days and after 28 days in culture. D. FACS plots show the change in expression of EpCAM in unsorted hyperplasias and primary tumor organoids over time. Graph shows that percentage of Elo cells in the hyperplasias and primary tumor organoids after at least 14 days in culture. E. Invasion and Vimentin expression in organoids derived from hyperplasias and primary tumors. Graphs show quantification of invasion and Vimentin expression. ERK1/2 signaling in the HP-Ehi state that is necessary for conversion to highly mesenchymal Elo states To identify molecular regulators of plasticity in HP-Ehi cells, we returned to our pseudotime analysis and focused on gene modules activated during later stages of tumor progression—when HP-Ehi states were frequently observed—but prior to the induction of canonical EMP markers. Two modules were enriched for genes associated with EGFR-RAS-MEK1/2-ERK1/2 signaling ( Fig. 5A ). We had previously shown that EGFR pathway activity contributes to invasive behavior in C3-TAg tumors, prompting us to test whether this pathway also promotes plasticity ( 33 ). To further investigate transcriptional regulators downstream of ERK1/2, we applied the SCENIC algorithm and identified Hmga2 as a key transcriptional regulator selectively activated in HP-Ehi cells ( Fig. 5B , S5 ). Notably, Hmga2 expression was dependent on ERK1/2 signaling ( Fig. 5C ). Importantly, pharmacologic inhibition of ERK1/2 activation with trametinib reduced both Vimentin expression and invasion, confirming that ERK1/2 activity promotes plasticity ( Fig. 5D ). Together, these findings indicate that ERK1/2 activity induces a transcriptional program—including Hmga2—that increases cellular plasticity in HP-Ehi cells prior to the acquisition of a mesenchymal phenotype. These findings define an ERK1/2–Hmga2 axis that promotes cellular plasticity and heterogeneity independently of canonical EMP transcriptional outputs. Download figure Open in new tab Figure 5. ERK1/2 signaling in the HP-Ehi state that is necessary for conversion to highly mesenchymal Elo states. A. UMAP showing the activity of gene modules associated with ERK1/2 activation. Numbers indicate the gene modules in the heatmap shown in S3. B. UMAP showing the expression of ERK1/2 pathway genes. C. Graph shows the expression of HMGA2 in tumor organoids with different levels of ERK1/2 activity. D. Invasion and Vimentin expression in organoids grown in the absence or presence of the MEK1/2 inhibitor Trametinib. Graphs show quantification of invasion and Vimentin expression. Plasticity state influences metastatic phenotype We next examined how EMP states influence metastasis. Previous studies in triple-negative breast cancer (TNBC), squamous cell carcinoma (SCC), and pancreatic cancer have suggested that induction of Vimentin and a conversion to an Elo state enhances metastatic capability ( 19 , 20 , 34 , 35 ). To evaluate whether this association held in the C3-TAg model, we analyzed the relationship between the enrichment for the Elo state in primary tumors and the ability to establish metastatic colonies in the lung after intravenous injection. We found that C3-TAg tumors that were predominantly Ehi established metastases in the lung to the same extent is C3-TAg tumors that were predominantly composed of Elo cells ( Fig. 6A ). To further investigate how plasticity shapes metastatic behavior, we examined the phenotypes of the metastatic lesions themselves. It has been proposed that disseminated tumor cells must undergo a mesenchymal-to-epithelial transition (MET) to initiate colonization and outgrowth in secondary tissues ( 36 ). We therefore asked whether metastatic lesions uniformly adopt a more epithelial state, regardless of the EMP status of the metastasis initiating cells. To determine whether metastatic lesions converge on a shared EMP state, we assessed Vimentin expression in metastases derived from Ehi or Elo enriched tumors. The expression of Vimentin was widespread and substantially higher in the metastatic lesions initiated by Elo cells compared to the Ehi cells ( Fig. 6B ). These findings indicate that EMP states established in the primary tumor persist in metastases and do not converge on a single epithelial, hybrid or mesenchymal phenotype. Together, these findings demonstrate that EMP status does not determine the ability of C3-TAg tumor cells to initiate metastatic colonization. Rather, the EMP state present in the primary tumor is reflected in the phenotypic diversity of the resulting metastases, reinforcing the conclusion that epithelial-mesenchymal plasticity generates heritable heterogeneity that persists through the metastatic cascade. Download figure Open in new tab Figure 6. Plasticity state influences metastatic phenotype. A. Imaging and quantification of the area lung metastasis after tail vein injection. B. Imaging and quantification of the Vimentin expression in lung metastases after tail vein injection. DISCUSSION EMP generates heritable plasticity and phenotypic heterogeneity in TNBC EMP is frequently conceptualized as a linear progression in which epithelial tumor cells gradually lose epithelial features and acquire mesenchymal identity ( 37 ). Our findings in TNBC challenge this model, revealing that EMP instead involves an early, heritable loss of mammary lineage identity that precedes and enables divergent transcriptional transcriptional trajectories. Following the loss of mammary identity, tumor cells adopted distinct transcriptional trajectories. One trajectory aligned with canonical TGFβ-induced EMP, marked by progressive loss of epithelial genes and induction of mesenchymal markers such as Vimentin. A second trajectory involved activation of hypoxia and glycolysis-associated modules, suggesting distinct microenvironmental regulation. Notably, these EMP trajectories were not part of a linear continuum but represented parallel, modular routes of phenotypic conversion. Together, these findings reframe EMP as a branching and modular process that generates extensive transcriptional heterogeneity in TNBC. Multiple EMP states contribute to metastasis without convergence on a single phenotype Our study also reveals that metastasis in TNBC is not restricted to cells in advanced Elo EMP states. Both Ehi and Elo cells were independently capable of forming metastases in the lungs, demonstrating that canonical EMP program activation is not required for metastatic colonization. These results contrast with models in which metastatic potential is tightly coupled to Vimentin expression and a Elo phenotype ( 10 , 19 , 20 , 34 , 35 ). Metastatic lesions derived from Ehi and Elo cells remained phenotypically distinct, differing in Vimentin expression and spatial organization. These observations argue against the requirement for a MET during metastatic outgrowth and support a model in which the EMP state of the primary tumor is maintained in metastases. Thus, TNBC metastases can arise from multiple transcriptionally and phenotypically distinct subpopulations, and features of the EMP state present at the time of dissemination is preserved in distant sites. Implications for modeling TNBC and guiding therapy These findings challenge widely used preclinical models that overrepresent mesenchymal-like tumor cells and fail to capture the full diversity of EMP states observed in patient tumors ( 20 , 38 – 40 ). In contrast, the C3-TAg model used here faithfully recapitulates the phenotypic heterogeneity of TNBC. By defining metastasisinitiating populations beyond the Elo state, our results expand the repertoire of EMP programs with clinical relevance. From a therapeutic perspective, the potential presence of multiple metastasis-competent EMP states suggests that effective intervention will require strategies that target diverse tumor cell subpopulations. HP-Ehi cells may be more responsive to therapies targeting epithelial pathways or ERK1/2 signaling, while Elo states may be more sensitive to inhibition of ECM remodeling programs. Overall, our work underscores the need for EMP-informed therapeutic strategies that reflect the dynamic and modular nature of plasticity in TNBC. Conclusion This study defines a new model of epithelial-mesenchymal plasticity in TNBC in which early loss of mammary lineage identity enables multiple, heritable EMP trajectories. These distinct transcriptional states generate phenotypically diverse tumor subpopulations, including multiple metastasis-competent cell types. Rather than converging on a single metastatic phenotype, disseminated cells maintain their EMP identity, contributing to inter-metastatic heterogeneity and variable therapeutic vulnerabilities. These findings redefine how EMP drives metastasis and provide a framework for designing therapeutic approaches that reflect the full complexity of tumor cell plasticity in TNBC. DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST There are no potential conflicts of interest. AUTHORS’ CONTRIBUTIONS F. Alsharief: Conceptualization, investigation, writing-review and editing. R.K. Suter: Conceptualization, investigation writing-review and editing. A. Nasir: Conceptualization, investigation and editing. G.W. Pearson: Conceptualization, investigation, writing-review and editing, funding acquisition. FIGURE LEGENDS Download figure Open in new tab Figure S1. Related to Using scRNA-seq to define the cellular composition of C3-TAg tumors. A. UMAPs showing the cell cycle phase of cells from normal mammary gland, 5 mm and >15 mm tumors annotated by sample source. B. UMAP showing cell clusters from normal mammary gland, 5 mm and >15 mm tumors annotated by sample source. defined by Seurat. C. Dot plot showing the expression of marker genes in the indicated normal cell lineages. D. Heatmap showing the similarity of mammary epithelial and microenvironmental cells to the indicated normal cell types. Download figure Open in new tab Figure S2. Related to using scRNA-seq to define transcriptional heterogeneity in C3-TAg tumor cell populations. Heatmao of clustered 5 mm and >15 mm tumor cells showing the expression of genes that are differentially expressed between clusters. Download figure Open in new tab Figure S3. Related to trajectory analysis reveals multiple EMP paths with distinct regulatory features. A. Heatmap showing gene module activity in tumor cell clusters. B. UMAPs showing the activity. if the indicated gene modules in tumor cells. Download figure Open in new tab Figure S4. Related to plasticity is dynamic, directional, and heritable. Plot of tumor volume changes over time from tumors that were initiated by orthotopic injection of hyperplasia organoids and primary tumor organoids. Download figure Open in new tab Figure S5. Related to ERK1/2 signaling in the HP-Ehi state that is necessary for conversion to highly mesenchymal Elo states. Heatmap shows the activity of gene regulons regulated by the indicated transcription factors in different clusters, as determined by SCENIC analysis. ACKNOWLEDGEMENTS Work was supported by NIH R01CA218670, Georgetown Women and Wine (to G.W. Pearson), and NIH P30CA051008. Funder Information Declared National Cancer Institute , R01CA218670 , P30CA051008 REFERENCES 1. ↵ Li CI , Uribe DJ , Daling JR . Clinical characteristics of different histologic types of breast cancer . Br J Cancer 2005 ; 93 : 1046 – 52 OpenUrl CrossRef PubMed Web of Science 2. ↵ Dent R , Trudeau M , Pritchard KI , Hanna WM , Kahn HK , Sawka CA , et al. 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