Landscape of prostate-specific membrane antigen heterogeneity and regulation in AR-positive and AR-negative metastatic prostate cancer

Abstract

Tumor expression of prostate-specific membrane antigen (PSMA) is lost in 15-20% of men with castration-resistant prostate cancer (CRPC), yet the underlying mechanisms remain poorly defined. In androgen receptor (AR)-positive CRPC, we observed lower PSMA expression in liver lesions versus other sites, suggesting a role of the microenvironment in modulating PSMA. PSMA suppression was associated with promoter histone 3 lysine 27 methylation and higher levels of neutral amino acid transporters, correlating with ¹⁸F-fluciclovine uptake on positron emission tomography imaging. While PSMA is regulated by AR, we identified a subset of AR-negative CRPC with high PSMA. HOXB13 and AR co-occupancy at the PSMA enhancer and knockout models point to HOXB13 as an upstream regulator of PSMA in AR-positive and AR-negative prostate cancer. These data demonstrate how PSMA expression is differentially regulated across metastatic lesions and in the context of the AR, which may inform selection for PSMA-targeted therapies and development of complementary biomarkers.

Extended Data Fig. 1 |. PSMA (FOLH1) gene expression is mostly correlated with AR and NEPC markers except in liver metastatic tumors with no NE features.

a, Heatmaps of the expression levels of PSMA gene (FOLH1), AR-markers and NE markers in metastatic CRPC samples from the International SU2C/PCF Dream Team dataset. b, Expression of PSA gene (KLK3) and sites of metastases in the International SU2C/PCF Dream Team CRPC dataset. c, AR score (left) and NEPC score (right) liver (n = 39), lymph node (n = 115) and bone (n = 73) metastatic CRPC samples in the International SU2C/PCF Dream Team dataset. The size of data points is proportional with the level of KLK3 gene expression in each sample. The lines and squares inside each box are the median and mean, respectively. The upper box border represents the 75^th quartile, lower box border represents the 25^th quartile and whiskers represent outliers by using the 1.5 interquartile range rule. In b, the data were analyzed by one-way ANOVA followed by Tukey’s multiple comparison tests.

Extended Data Fig. 2 |. PSMA heterogeneity in CRPC can be independent from AR score.

a, PSMA protein expression by IHC displaying heterogeneity in metastatic tumors from liver obtained at autopsy in two patients with CRPC. b, Evaluation of AR and NEPC markers in metastatic liver tumors of Mouse A01 (from Fig. 1g). c, Images of spontaneous metastatic tumors following orthotopic injection of 22Rv1 cell line in Mouse Model A02. Purple arrow points to a metastatic tumor in liver. d, Evaluation of AR and PSMA protein expression by IHC in Mouse A02. e, Western blot analyses of PSMA, AR and NKX3–1 protein levels in Mouse A02. The experiment in e was repeated 2 times with N = 2 independently collected samples with similar results. f, Representative images of spontaneous metastatic tumors in Mouse Model A03. g, Evaluation of AR and PSMA by IHC in Mouse A03. h, AR-score in primary and metastatic tissues of orthotopic 22Rv1 mouse models. LNCaP used as a reference. i, Heatmaps of the expression levels of PSMA gene (FOLH1), AR-markers and NE markers in primary and metastatic tissues of orthotopic 22Rv1 mouse models. j, Principal Component Analysis (PCA) identified global similarity patterns in N = 3 primary prostate tumors, N = 3 metastatic tumors from lymph nodes, and N = 6 PSMA-high metastatic tumors in liver. In b, d and g, IHC experiments were performed once using proper positive and negative controls.

Extended Data Fig. 3 |. Single-cell transcriptome analysis of the 22Rv1-WT cell line and 22Rv1 liver metastasis.

a, Uniform Manifold Approximation and Projection (UMAP) reduced dimension plots shows 22Rv1-WT consists of different clusters. The majority of 22Rv1 liver metastasis cells grouped as a single cluster, albeit this scRNA analysis was limited due to the number of viable cells of the sequenced liver metastasis (n = 197 cells) compared with 22Rv1-WT cell line (n = 3467 cells). b, Single-cell RNA expression of FOLH1, AR, HOXB13, LAT1 and NE markers over the UMAP representation of the map. The expression of LAT1 in Cluster 3 shows PSMA-low subpopulation of 22Rv1-WT cells are not LAT1 positive. This observation implies there is a heterogeneity within the PSMA-low cell populations. c, Unsupervised clusters were annotated as three clusters with distinct FOLH1 levels. d, Expression of FOLH1 in identified clusters. e, Stacked barplot displaying percentage of each cluster in 22Rv1-WT and 22Rv1 liver metastasis. Notably, only 10.9% of 22Rv1-WT belong to PSMA-low Cluster 3. However, more than 58% of 22Rv1 liver metastasis are within Cluster 3. In d, the data were analyzed by one-way ANOVA followed by Šídák’s multiple comparison tests. In a-c, data presented is based on data from a single experiment.

Extended Data Fig. 4 |. Estimation of clinically relevant FOLH1-positive regulators during progression from benign prostate to NEPC.

a, PSMA protein levels in prostate cancer models annotated by their FOLH1 mRNA expression levels obtained by RNA-seq. Since 22Rv1 xenograft tumors with RNA expression of 31.3 RPKM are pathologically considered as PSMA-positive xenografts and they are radiologically detectable with moderate PSMA PET uptake, we defined samples with FOLH1 expression levels more than 50 RPKM as FOLH1-high tumors and samples with FOLH1 expression levels less than 5 RPKM as FOLH1-low tumors. The column chart show mean ± s.e.m for N = 3 independently collected samples. b, Expression of FOLH1 during progression of prostate cancer toward NEPC. The incidence of FOLH1-high was at its maximum among primary prostate cancer samples. On the other hand, FOLH1-low was at its maximum among NEPC samples. c, A differential expression (DGE) performed on each cohort to determine which genes are expressed at FOLH1-high tumors. d, Short (1 kb), mid-range (10 kb) and long-range (100 kb) influence scores were calculated using Cistrome DB. e, Schematic of generation of Venn diagram of overlapping differentially expressed genes in FOLH1-high cohorts with the estimated FOLH1 regulator to predict clinically relevant FOLH1-positive regulators.

Extended Data Fig. 5 |. Estimation of FOLH1-positive regulators among CRPC tumors with and without neuroendocrine (NE) features.

a, Heat map of the expression levels of PSMA gene (FOLH1), AR-markers, NE markers and projected PSMA regulators in metastatic CRPC samples from the International SU2C/PCF Dream Team dataset (N = 224 tumors) a, Expression levels of FOLH1 in prostate tissue during progression from benign to NEPC. b, Volcano plot of DGE analysis in FOLH1-high vs. FOLH1-low among CRPC tumors with and without NE features. c, Venn diagrams illustrate the overlap of differentially expressed genes in FOLH1-high cohorts, with FOLH1 potential transcription factors estimated by Cistrome DB.

Extended Data Fig. 6 |. HOXB13 is a positive regulator of PSMA (FOLH1).

a, Overexpression of WT-HOXB13 in LNCaP-shHOXB13 cells rescues FOLH1 expression while overexpression of G84E mutant-HOXB13 cannot rescue suppression of FOLH1. Data from GEO accession GSE153585. b, Significant reduction in FOLH1 expression in LN95 (left) and 22Rv1 (right). Data from GEO accession GSE99378¹⁵. The boxes represent experimental replicates and samples with same treatment are labeled with same color. c, Bar charts of the expression levels of AR (top) and HOXB13 (bottom) in prostate tumors during progression from benign to NEPC. The bar colors represent FOLH1 levels in each sample. d, AR (top) and HOXB13 (bottom) ChIP-seq intensity in representative CRPC samples from GEO accession GSE130408.

Extended Data Fig. 7 |. Gene expression of PSMA (FOLH1) in preclinical models and corresponding chromatin accessibility of its promoter and upstream enhancer are highly correlated.

a, Heat map of ATAC-seq intensity among prostate cancer models at the FOLH1 gene annotated with FOLH1 expression in each sample. Pearson correlation between the intensity of ATAC-seq peak and the expression of FOLH1 at promoter (b), close to upstream enhancer (c) and on upstream enhancer (d-e). Data from GEO accession GSE199190. In b-e, the scatter plots show the intensity of ATAC-seq peak (y axis) and the expression of FOLH1 (x axis) for N = 18 preclinical prostate cancer models.

Extended Data Fig. 8 |. Elevation of LAT1 and ASCT2 gene expression in NEPC and low PSMA CRPC.

a, Tissue sections of CRPC and NEPC models stained with LAT1 and 4F2hc antibodies. Scale bar: 200 μm b, Western blot analyses of PSMA, LAT1 and ASCT2 protein levels of models. c, Tissue sections of NEPC model WCM1078 stained with ASCT2 antibody. Scale bar: 100 μm d, Evaluation of the expression of ASCT2 (SLC1A5) gene in Beltran dataset for N = 34 CRPC tumors and N = 15 NEPC tumors. The lines and squares inside each box are the median and mean, respectively. The upper box border represents the 75^th quartile, lower box border represents the 25^th quartile and whiskers represent the outlier by using the 1.5 interquartile range rule. e, Schematic illustration of anatomic sites of samples and expression levels of PSMA, LAT1 and ASCT2 in each sample. The representative images are shown for N = 3 (a-c) independently collected samples.

Extended Data Fig. 9 |. Proposed model of PSMA regulation in prostate cancer.

PSMA (FOLH1) expression is activated in prostate cancer via binding of both AR and its cofactor HOXB13 to the PSMA enhancer. Even in the absence of AR expression, a subset of AR-negative tumors will still express PSMA due to HOXB13 binding of the PSMA enhancer. CRPC tumors may suppress or lose PSMA expression either due to loss of AR/HOXB13 binding of the PSMA promotor and/ or methylation of the PSMA promotor.

Fig. 1 |. Suppression of PSMA in prostate cancer liver metastases.

a, Expression of PSMA gene (FOLH1) and sites of metastasis in the International SU2C/PCF Dream Team CRPC dataset. b, AR score (left) and NEPC score (right) among liver (n = 39 tumors), lymph node (n = 115 tumors) and bone (n = 73 tumors) metastatic CRPC in the SU2C/PCF dataset. The size of data points is proportional to the level of PSMA gene expression in each sample. The lines and squares inside each box are the median and mean, respectively. The upper box border represents the 75th quartile, lower box border represents the 25th quartile and whiskers represent the outlier by using the 1.5 interquartile range rule. c, IHC showing PSMA protein expression of tumor tissues obtained at autopsy in a patient with CRPC with concurrent primary prostate and liver metastasis (case report). H&E, hematoxylin and eosin. d, Schematic of the development of the liver-derived metastatic 22Rv1 model. e, Representative images of spontaneous metastatic tumors following orthotopic injection of 22Rv1 cell lines to the left anterior prostate lobe of a castrated mouse (left) and spontaneous metastatic tumors in a second-generation liver-derived 22Rv1 orthotopic tumor model. Green arrow points to primary prostate tumor. Orange, yellow, gray and blue colored arrows indicate four metastatic tumors (i–iv) in liver. *refers to the 1st generation orthotopic model and **refers to the 2nd generation liver-derived orthotopic model. f, Western blot analyses of PSMA, AR and HOXB13 protein levels in the first-generation 22Rv1 orthotopic model (left), second-generation liver-derived orthotopic model (center) and 22Rv1 cell line models (right). g, Tissue sections from primary tumor and liver metastases of subcutaneous 22Rv1 model stained with PSMA (left) and AR (right) antibodies. Scale bar, 200 μm. h, ⁶⁸Ga-PSMA-11 PET–CT images of 22Rv1-WT and 22Rv1-LMD tumors in an athymic nude male mouse bearing subcutaneous tumor xenografted on the left shoulder (1 h after injection). ID, injected dose. In a, data were analyzed by one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison tests. In e–g, the representative blots and IHCs are shown for n = 2 independently collected samples. In h, representative images are shown for n = 3 mice models.

Fig. 2 |. Intra-tumoral heterogeneity of PSMA in liver lesions.

a, Representative image of the formed tumors following orthotopic injection of PSMA-positive 22Rv1 cell line to prostate and liver of mice (left) and H&E staining of tumor tissues (right). b, Western blot analyses of PSMA in 22Rv1 tumors following orthotopic injection to prostate in comparison with liver. c, PSMA and AR IHC and H&E staining in primary and liver metastases of prostate orthotopic 22Rv1 model in comparison to liver orthotopic 22Rv1 model. Scale bars, 200 μm d, PSMA IHC signal intensity in metastases of orthotopic 22Rv1 models, including primary prostate tumor (n = 9), liver metastatic tumors (n = 21) and liver orthotopic tumors (n = 9). The line inside each box is the median, upper box border represents the 75th quartile, lower box border represents the 25th quartile and whiskers represent the range. e, Expression levels of FOLH1 by DSP of three patients with CRPC from the UW Rapid Autopsy Program. f, Heat map of DSP expression levels of PSMA gene (FOLH1), AR markers and NE markers in patients with CRPC from the UW dataset (n = 169 tumors). g, DSP expression levels of FOLH1 among samples from liver metastases versus lymph node metastases. The data were analyzed by either Student’s t-test (g) or one-way ANOVA followed by Tukey’s multiple comparison test (d). Representative blots are shown for n = 2 independently collected samples (b) or n = 3 mice (a,c).

Fig. 3 |. Investigation of the PSMA cistrome across prostate cancer progression identifies a PSMA-positive subset of AR-negative NEPC tumors.

a, Expression levels of FOLH1 in prostate tumors during progression from benign to NEPC. RPKM, reads per kilobase of transcript per million reads mapped; PCa, prostate cancer. b, Venn diagrams illustrate the overlap of differentially expressed genes in FOLH1-high cohorts, with FOLH1 potential TFs estimated by Cistrome DB. The four defined n values on the figure correspond to both a and b. c, Heat map of expression levels of PSMA gene (FOLH1), AR markers, NE markers and potential PSMA regulators in PCa models. AdPC, prostate adenocarcinoma. d, Western blot analyses of PSMA, adenocarcinoma (Adeno) markers, NEPC markers and HOXB13 protein levels. e, Tissue sections of different models stained with PSMA, AR and HOXB13 antibodies. f, Western blot analyses of PSMA and HOXB13 in the second-generation liver-derived orthotopic model (left) and 22Rv1 cell lines (right). g, Representative bright field photos of 22Rv1-WT (top) and 22Rv1-LMD (bottom) cell lines. h, Representative immunocytochemistry imaging of 22Rv1-WT (top) and 22Rv1-LMD (bottom) cell lines stained with 4,6-diamidino-2-phenylindole (DAPI) (blue), anti-PSMA (green) and anti-HOXB13 (red). i, Representative immunofluorescence imaging of NEPC and CRPC models stained with DAPI (blue), anti-PSMA (green) and anti-AR (red). j, ⁶⁸Ga-PSMA-11 PET–CT images of athymic nude male mouse bearing subcutaneous tumor xenografted on the left shoulder (1 h after injection). Representative transverse planar image is shown. Representative images are shown for n = 2 independently collected samples (c–i) or n = 3 mice (j).

Fig. 4 |. HOXB13 binds to intronic and upstream enhancers of PSMA gene and regulates its expression.

a, Expression of FOLH1 following KD of HOXB13. b, Western blot of HOXB13, PSMA and AR after treatment with siHOXB13 or siControl. c, Peak calls HOXB13 ChIP depicted with green bars at the vicinity of AR (left) and FOLH1 (right) (Gene Expression Omnibus (GEO) GSE96652 (ref. 17)). d, PSMA in control (sgControl) and two independent HOXB13-KO (sgHOXB13) models. e, Schematic of subcutaneous (top) and orthotopic (bottom) tumor models of 22Rv1-WT and HOXB13-KO cell lines. f, Western blot of PSMA and HOXB13 protein in orthotopic primary tumor models. g, Western blot of PSMA and HOXB13 protein before and after overexpression of HOXB13. h, Heat map of HOXB13 ChIP peak intensity at intronic (left) and upstream (right) enhancers of FOLH1 among healthy (n = 15 samples), localized PCa (n = 13 tumors) and CRPC (n = 15 tumors) samples from GSE130408 (ref. 33). i, HOXB13 ChIP intensity intronic (blue arrow) and upstream (purple arow) enhancers of FOLH1 gene shown at three representative healthy (green), localized PCa (blue) and CRPC (brown) samples (top). H3K27Ac-HiChIP loops in LNCaP cell line from Giambartolomei et al. (bottom). Loops from merged data of five replicates. j, ChIP–qPCR for HOXB13 chromatin binding at upstream enhancer of FOLH1. k, Comparison of subcutaneous tumor growth of sgControl and sgHOXB13 (Wilcoxon matched-pairs test). l, Weight of primary tumor following orthotopic injection of 22Rv1 (sgControl (n = 6 tumors) and sgHOXB13 (n = 4 tumors)) after 60 d. m, Representative images of spontaneous metastasis tumors following orthotopic injection of sgControl (left) and sgHOXB13 (right) 22Rv1 cell lines to prostate (yellow arrows indicate metastatic tumors). n, Heat map of metastatic tumor incidence and prostate tumor weight in orthotopic models. o, IHC of tissue sections of orthotopic 22Rv1 models. Representative blots are shown for n = 2 (b,d,g,f) independently collected samples or n = 4 mice (n,o). Column charts show mean ± s.e.m. (t-test) for n = 3 independently collected samples (a,j,l).

Fig. 5 |. PSMA suppression is associated with H3K27ac and H3K27me at FOLH1 gene locus.

a, Snapshots of H3K27ac ChIP-seq intensity at FOLH1 loci in association with FOLH1 expression levels in NEPC organoid models and 22Rv1 cell line. b, FOLH1 expression levels in LuCaP CRPC PDX models c, Snapshots for HOXB13 (blue), AR (green) and H3K27ac (purple) ChIP-seq in LuCaP CRPC PDX models with a heterogeneous FOLH1 expression level from GEO accession GSE130408 (ref. 33) (mean ± s.d.). d, Overview of FOLH1 expression levels in 22Rv1 models and the selected samples for H3K27ac ChIP sequencing. e, Snapshots of H3K27ac ChIP-seq intensity at FOLH1, AR and HOXB13 loci in association with FOLH1 expression levels in metastatic 22Rv1 models. f, Overview of rapid autopsies and H3K27ac and H3K27me ChIP sequencing of selected tumors from the WCM study cohort and schematic illustration of anatomic sites of samples and the expression levels of PSMA in each sample. h, Snapshots of H3K27ac ChIP-seq intensity and f, H3K27ac ChIP-seq intensity at FOLH1, HOXB13 and luminal and NE markers loci in association with FOLH1 expression levels. Genomic coordinates are indicated below.

Fig. 6 |

¹⁸F-fluciclovine PET delineates PSMA-suppressed CRPC and NEPC tumors. a, Volcano plot of DGE analysis in 22Rv1-WT versus 22Rv1-LMD. b, Tissue sections of primary and metastatic 22Rv1 model stained with PSMA, AR, HOXB13, LAT1 and 4F2hc antibodies. c, Western blot analyses of PSMA, AR, HOXB13, LAT1 and 4F2hc protein levels in 22Rv1 models. d, H3K27ac ChIP-seq intensity at FOLH1 and LAT1 loci in association with FOLH1 expression levels. e, GO enrichment analysis results for Molecular Functions (left) and Biological Process (right). Bar plot for the log₁₀ of the P value of each term. Pathways related to amino acid uptake are highlighted in purple color. f, Heat map of the expression levels of PSMA gene (FOLH1), luminal, NE markers and identified amino acid uptake genes from GO analysis. TPM, transcripts per million. g, ¹⁸F-fluciclovine PET–CT images of an athymic nude male mouse bearing subcutaneous 22Rv1-WT (left) and 22Rv1-LMD (right) tumor xenografted on the right shoulder (1 h after injection). h, Representative images of subcutaneous 22Rv1 tumors (left) and maximum intensity projection of their ¹⁸F-fluciclovine PET–CT images. i, Evaluation of the expression of PSMA (FOLH1) and LAT1 (SLC7A5) genes and their association with NEPC features in the International SU2C/PCF Dream Team (top) and Beltran (bottom) datasets. j, PET–CT images of ¹⁸F-fluciclovine (top) and ¹⁸F-rh-PSMA (bottom) in athymic nude male mice bearing subcutaneous WCM154, WCM1078, WCM1262, WCM12 and 22Rv1 tumors xenografted on the right shoulder (1 h after injection). k, SUV_max and SUV_mean of imaged models in association with PSMA (FOLH1) and LAT1 (SLC7A5) gene expression in 22Rv1-LMD (n = 2 mice), WCM154 (n = 3 mice), WCM1078 (n = 3 mice), WCM1262 (n = 2 mice), WCM12 (n = 2 mice) and 22Rv1-WT (n = 2 mice) xenograft models (mean ± s.e.m.). In a–c, representative images are shown for n = 3 independently collected samples.