Stem cell dynamics and cellular heterogeneity across lineage subtypes of castrate-resistant prostate cancer.

To resist lineage-dependent therapies such as androgen receptor inhibition, prostate luminal epithelial adenocarcinoma cells often adopt a stem-like state resulting in lineage plasticity and phenotypic heterogeneity. Castrate-resistant prostate adenocarcinoma can transition to neuroendocrine (NE) and occasionally to amphicrine, co-expressed luminal and NE, phenotypes. We developed castrate-resistant prostate cancer (CRPC) patient-derived organoid models that preserve heterogeneity of the originating tumor, including an amphicrine model displaying a range of luminal and NE phenotypes. To gain biological insight and to identify potential treatment targets within heterogeneous tumor cell populations, we assessed the lineage hierarchy and molecular characteristics of various CRPC tumor subpopulations. Transcriptionally similar stem/progenitor (St/Pr) cells were identified for all lineage populations. Lineage tracing in amphicrine CRPC showed that heterogeneity originated from distinct subclones of infrequent St/Pr cells that produced mainly quiescent differentiated amphicrine progeny. By contrast, adenocarcinoma CRPC progeny originated from St/Pr cells and self-renewing differentiated luminal cells. Neuroendocrine prostate cancer (NEPC) was composed almost exclusively of self-renewing St/Pr cells. Amphicrine subpopulations were enriched for secretory luminal, mesenchymal, and enzalutamide treatment persistent signatures that characterize clinical progression. Finally, the amphicrine St/Pr subpopulation was specifically depleted with an AURKA inhibitor, which blocked tumor growth. These data illuminate distinct stem cell (SC) characteristics for subtype-specific CRPC in addition to demonstrating a context for targeting differentiation-competent prostate SCs.

Reproducible preclinical models of androgen receptor driven human prostate cancer bone metastasis.

BACKGROUND: Preclinical models recapitulating the metastatic phenotypes are essential for developing the next-generation therapies for metastatic prostate cancer (mPC). We aimed to establish a cohort of clinically relevant mPC models, particularly androgen receptor positive (AR+) bone metastasis models, from LuCaP patient-derived xenografts (PDX) that reflect the heterogeneity and complexity of mPC. METHODS: PDX tumors were dissociated into single cells, modified to express luciferase, and were inoculated into NSG mice via intracardiac injection. The progression of metastases was monitored by bioluminescent imaging. Histological phenotypes of metastases were characterized by immunohistochemistry and immunofluorescence staining. Castration responses were further investigated in two AR-positive models. RESULTS: Our PDX-derived metastasis (PDM) model collection comprises three AR+ adenocarcinomas (ARPC) and one AR- neuroendocrine carcinoma (NEPC). All ARPC models developed bone metastases with either an osteoblastic, osteolytic, or mixed phenotype, while the NEPC model mainly developed brain metastasis. Different mechanisms of castration resistance were observed in two AR+ PDM models with distinct genotypes, such as combined loss of TP53 and RB1 in one model and expression of AR splice variant 7 (AR-V7) expression in another model. Intriguingly, the castration-resistant tumors displayed inter- and intra-tumor as well as organ-specific heterogeneity in lineage specification. CONCLUSION: Genetically diverse PDM models provide a clinically relevant system for biomarker identification and personalized medicine in metastatic castration-resistant prostate cancer.

Increased chromatin accessibility mediated by nuclear factor I drives transition to androgen receptor splice variant dependence in castration-resistant prostate cancer.

Androgen receptor (AR) splice variants, of which ARv7 is the most common, are increased in prostate cancer (PC) that develops resistance to androgen signaling inhibitor drugs, but the extent to which these variants drive AR activity, and whether they have novel functions or dependencies, remain to be determined. We generated a subline of VCaP PC cells (VCaP16) that is resistant to the AR inhibitor enzalutamide (ENZ) and found that AR activity was independent of the full-length AR (ARfl), despite its continued high-level expression, and was instead driven by ARv7. The ARv7 cistrome and transcriptome in VCaP16 cells mirrored that of the ARfl in VCaP cells, although ARv7 chromatin binding was weaker, and strong ARv7 binding sites correlated with higher affinity ARfl binding sites across multiple models and clinical samples. Notably, although ARv7 expression in VCaP cells increased rapidly in response to ENZ, there was a long lag before it gained chromatin binding and transcriptional activity. This lag was associated with an increase in chromatin accessibility, with the AR and nuclear factor I (NFI) motifs being most enriched at these more accessible sites. Moreover, the transcriptional effects of combined NFIB and NFIX knockdown versus ARv7 knockdown were highly correlated. These findings indicate that ARv7 can drive the AR program, but that its activity is dependent on adaptations that increase chromatin accessibility to enhance its intrinsically weak chromatin binding.

FASN Gene Methylation is Associated with Fatty Acid Synthase Expression and Clinical-genomic Features of Prostate Cancer.

Fatty acid synthase (FASN) catalyzes the synthesis of long-chain saturated fatty acids and is overexpressed during prostatic tumorigenesis, where it is the therapeutic target in several ongoing trials. However, the mechanism of FASN upregulation in prostate cancer remains unclear. Here, we examine FASN gene CpG methylation pattern by InfiniumEPIC profiling and whole-genome bisulfite sequencing across multiple racially diverse primary and metastatic prostate cancer cohorts, comparing with FASN protein expression as measured by digitally quantified IHC assay and reverse phase protein array analysis or FASN gene expression. We demonstrate that the FASN gene body is hypomethylated and overexpressed in primary prostate tumors compared with benign tissue, and FASN gene methylation is significantly inversely correlated with FASN protein or gene expression in both primary and metastatic prostate cancer. Primary prostate tumors with ERG gene rearrangement have increased FASN expression and we find evidence of FASN hypomethylation in this context. FASN expression is also significantly increased in prostate tumors from carriers of the germline HOXB13 G84E mutation compared with matched controls, consistent with a report that HOXB13 may contribute to epigenetic regulation of FASN in vitro. However, in contrast to previous studies, we find no significant association of FASN expression or methylation with self-identified race in models that include ERG status across two independent primary tumor cohorts. Taken together, these data support a potential epigenetic mechanism for FASN regulation in the prostate which may be relevant for selecting patients responsive to FASN inhibitors. SIGNIFICANCE: Here, we leverage multiple independent primary and metastatic prostate cancer cohorts to demonstrate that FASN gene body methylation is highly inversely correlated with FASN gene and protein expression. This finding may shed light on epigenetic mechanisms of FASN regulation in prostate cancer and provides a potentially useful biomarker for selecting patients in future trials of FASN inhibitors.

Localized high-risk prostate cancer harbors an androgen receptor low subpopulation susceptible to HER2 inhibition.

Patients diagnosed with localized high-risk prostate cancer have higher rates of recurrence, and the introduction of neoadjuvant intensive hormonal therapies seeks to treat occult micrometastatic disease by their addition to definitive treatment. Sufficient profiling of baseline disease has remained a challenge in enabling the in-depth assessment of phenotypes associated with exceptional vs. poor pathologic responses after treatment. In this study, we report comprehensive and integrative gene expression profiling of 37 locally advanced prostate tumors prior to six months of androgen deprivation therapy (ADT) plus the androgen receptor (AR) inhibitor enzalutamide prior to radical prostatectomy. A robust transcriptional program associated with HER2 activity was positively associated with poor outcome and opposed AR activity, even after adjusting for common genomic alterations in prostate cancer including PTEN loss and expression of the TMPRSS2:ERG fusion. Patients experiencing exceptional pathologic responses demonstrated lower levels of HER2 and phospho-HER2 by immunohistochemistry of biopsy tissues. The inverse correlation of AR and HER2 activity was found to be a universal feature of all aggressive prostate tumors, validated by transcriptional profiling an external cohort of 121 patients and immunostaining of tumors from 84 additional patients. Importantly, the AR activity-low, HER2 activity-high cells that resist ADT are a pre-existing subset of cells that can be targeted by HER2 inhibition alone or in combination with enzalutamide. In summary, we show that prostate tumors adopt an AR activity-low prior to antiandrogen exposure that can be exploited by treatment with HER2 inhibitors.

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren's Disease.

Sjögren's Disease (SjD) is a systemic autoimmune disease without a clear etiology or effective therapy. Utilizing unbiased single-cell and spatial transcriptomics to analyze human minor salivary glands in health and disease we developed a comprehensive understanding of the cellular landscape of healthy salivary glands and how that landscape changes in SjD patients. We identified novel seromucous acinar cell types and identified a population of PRR4+CST3+WFDC2- seromucous acinar cells that are particularly targeted in SjD. Notably, GZMK+CD8 T cells, enriched in SjD, exhibited a cytotoxic phenotype and were physically associated with immune-engaged epithelial cells in disease. These findings shed light on the immune response's impact on transitioning acinar cells with high levels of secretion and explain the loss of this specific cell population in SjD. This study explores the complex interplay of varied cell types in the salivary glands and their role in the pathology of Sjögren's Disease.