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.

An intra-tumoral niche maintains and differentiates stem-like CD8 T cells.

Tumour-infiltrating lymphocytes are associated with a survival benefit in several tumour types and with the response to immunotherapy1-8. However, the reason some tumours have high CD8 T cell infiltration while others do not remains unclear. Here we investigate the requirements for maintaining a CD8 T cell response against human cancer. We find that CD8 T cells within tumours consist of distinct populations of terminally differentiated and stem-like cells. On proliferation, stem-like CD8 T cells give rise to more terminally differentiated, effector-molecule-expressing daughter cells. For many T cells to infiltrate the tumour, it is critical that this effector differentiation process occur. In addition, we show that these stem-like T cells reside in dense antigen-presenting-cell niches within the tumour, and that tumours that fail to form these structures are not extensively infiltrated by T cells. Patients with progressive disease lack these immune niches, suggesting that niche breakdown may be a key mechanism of immune escape.

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.

Comparison of approaches to transcriptomic analysis in multi-sampled tumors.

Intratumoral heterogeneity is a well-documented feature of human cancers and is associated with outcome and treatment resistance. However, a heterogeneous tumor transcriptome contributes an unknown level of variability to analyses of differentially expressed genes (DEGs) that may contribute to phenotypes of interest, including treatment response. Although current clinical practice and the vast majority of research studies use a single sample from each patient, decreasing costs of sequencing technologies and computing power have made repeated-measures analyses increasingly economical. Repeatedly sampling the same tumor increases the statistical power of DEG analysis, which is indispensable toward downstream analysis and also increases one's understanding of within-tumor variance, which may affect conclusions. Here, we compared five different methods for analyzing gene expression profiles derived from repeated sampling of human prostate tumors in two separate cohorts of patients. We also benchmarked the sensitivity of generalized linear models to linear mixed models for identifying DEGs contributing to relevant prostate cancer pathways based on a ground-truth model.

Prostate-Specific Membrane Antigen Is a Biomarker for Residual Disease following Neoadjuvant Intense Androgen Deprivation Therapy in Prostate Cancer.

PURPOSE: Neoadjuvant intense androgen deprivation therapy (iADT) can exert a wide range of histological responses, which in turn are reflected in the final prostatectomy specimen. Accurate identification and measurement of residual tumor volumes are critical for tracking and stratifying patient outcomes. MATERIALS AND METHODS: The goal of this current study was to evaluate the ability of antibodies against prostate-specific membrane antigen (PSMA) to specifically detect residual tumor in a cohort of 35 patients treated with iADT plus enzalutamide for 6 months prior to radical prostatectomy. RESULTS: Residual carcinoma was detected in 31 patients, and PSMA reacted positively with tumor in all cases. PSMA staining was 96% sensitive for tumor, with approximately 82% of benign regions showing no reactivity. By contrast, PSMA positively reacted with 72% of benign regions in a control cohort of 37 untreated cases, resulting in 28% specificity for tumor. PSMA further identified highly dedifferentiated prostate carcinomas including tumors with evidence of neuroendocrine differentiation. CONCLUSIONS: We propose that anti-PSMA immunostaining be a standardized marker for identifying residual cancer in the setting of iADT.

Are localized prostate cancer biomarkers useful in the clinical practice?

Prostate cancer presents itself in a heterogeneous way with both aggressive and indolent forms. Despite the controversy surrounding its use, prostate-specific antigen screening ultimately leads to a greater number of diagnosed patients. One of the biggest challenges in clinical practice is to select the right patients for biopsy and, among diagnosed patients, to differentiate tumors with an indolent course from those with an unfavorable prognosis, in order to determine the best therapeutic decision for each case, avoiding unnecessary interventions. Currently, several types of biomarkers are available for clinical use in patients with prostate cancer, which include blood-based (prostate-specific antigen, Prostate Health Index®, 4K score®); urine sample-based (PCA3, SelectMDx®, ExoDx Prostate IntelliScore®); and biopsy, transurethral resection, or radical prostatectomy tissue-based (ConfirmMDx®, Oncotype®, Prolaris®, Decipher®). The aim of this review is to provide an overview of the current state of evidence and to highlight recent advances in the evaluation and diagnosis of prostate cancer, with emphasis on biomarkers related to diagnosis and to prognostic evaluation of localized prostate cancer.

Mutation Profiling Indicates High Grade Prostatic Intraepithelial Neoplasia as Distant Precursors of Adjacent Invasive Prostatic Adenocarcinoma.

INTRODUCTION: High Grade Prostatic Intraepithelial Neoplasia (HGPIN) is the putative precursor lesion to prostatic adenocarcinoma (PCa), but the precise relationship between HGPIN and PCa remains unclear. METHODS: We performed a molecular case study in which we studied mutation profiles of six tumor-associated HGPIN lesions in a single case of TMPRSS2:ERG fusion positive Gleason score 7 PCa that we had previously mapped for somatic mutations in adjacent Gleason patterns 3 and 4 foci, using microdissection and targeted deep-sequencing. RESULTS: A total of 32 tumor-specific mutated sites were successfully amplified and sequenced, including 25 truncal mutations and 7 mutations that were specific to either the Gleason pattern 3 or pattern 4 foci. All six HGPIN foci shared the same tumor-specific TMPRSS2:ERG fusion breakpoint, establishing that they were all clonally related to the adjacent invasive tumor. Among the 32 gene targets mutated in the invasive tumor, only mutation of the OR2AP1 gene, a truncal mutation, was found in a single focus of HGPIN. The remaining gene targets that were successfully sequenced were wild-type in all other HGPIN foci. DISCUSSION: This study demonstrates the feasibility of targeted mutation profiling of HGPIN lesions, which will be important to understand PCa tumorigenesis. The results in this case, showing a remarkable absence of truncal mutations in HGPIN lesions bearing the tumor-specific ERG fusion, indicate HGPIN lesions may be relatively stable genetically and argue against a stepwise clonal evolution model of HGPIN to PCa. Prostate 76:1227-1236, 2016. © 2016 Wiley Periodicals, Inc.

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.

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.

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.

Radiogenomic profiling of prostate tumors prior to external beam radiotherapy converges on a transcriptomic signature of TGF-ß activity driving tumor recurrence.

Background: Patients with localized prostate cancer have historically been assigned to clinical risk groups based on local disease extent, serum prostate specific antigen (PSA), and tumor grade. Clinical risk grouping is used to determine the intensity of treatment with external beam radiotherapy (EBRT) and androgen deprivation therapy (ADT), yet a substantial proportion of patients with intermediate and high risk localized prostate cancer will develop biochemical recurrence (BCR) and require salvage therapy. Prospective identification of patients destined to experience BCR would allow treatment intensification or selection of alternative therapeutic strategies. Methods: Twenty-nine individuals with intermediate or high risk prostate cancer were prospectively recruited to a clinical trial designed to profile the molecular and imaging features of prostate cancer in patients undergoing EBRT and ADT. Whole transcriptome cDNA microarray and whole exome sequencing were performed on pretreatment targeted biopsy of prostate tumors (n=60). All patients underwent pretreatment and 6-month post EBRT multiparametric MRI (mpMRI), and were followed with serial PSA to assess presence or absence of BCR. Genes differentially expressed in the tumor of patients with and without BCR were investigated using pathways analysis tools and were similarly explored in alternative datasets. Differential gene expression and predicted pathway activation were evaluated in relation to tumor response on mpMRI and tumor genomic profile. A novel TGF-ß gene signature was developed in the discovery dataset and applied to a validation dataset. Findings: Baseline MRI lesion volume and PTEN/TP53 status in prostate tumor biopsies correlated with the activation state of TGF-ß signaling measured using pathway analysis. All three measures correlated with the risk of BCR after definitive RT. A prostate cancer-specific TGF-ß signature discriminated between patients that experienced BCR vs. those that did not. The signature retained prognostic utility in an independent cohort. Interpretation: TGF-ß activity is a dominant feature of intermediate-to-unfavorable risk prostate tumors prone to biochemical failure after EBRT with ADT. TGF-ß activity may serve as a prognostic biomarker independent of existing risk factors and clinical decision-making criteria. Funding: This research was supported by the Prostate Cancer Foundation, the Department of Defense Congressionally Directed Medical Research Program, National Cancer Institute, and the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

Tumor-derived biomarkers predict efficacy of B7H3 antibody-drug conjugate treatment in metastatic prostate cancer models.

Antibody-drug conjugates (ADCs) are a promising targeted cancer therapy; however, patient selection based solely on target antigen expression without consideration for cytotoxic payload vulnerabilities has plateaued clinical benefits. Biomarkers to capture patients who might benefit from specific ADCs have not been systematically determined for any cancer. We present a comprehensive therapeutic and biomarker analysis of a B7H3-ADC with pyrrolobenzodiazepine(PBD) payload in 26 treatment-resistant, metastatic prostate cancer (mPC) models. B7H3 is a tumor-specific surface protein widely expressed in mPC, and PBD is a DNA cross-linking agent. B7H3 expression was necessary but not sufficient for B7H3-PBD-ADC responsiveness. RB1 deficiency and/or replication stress, characteristics of poor prognosis, and conferred sensitivity were associated with complete tumor regression in both neuroendocrine (NEPC) and androgen receptor positive (ARPC) prostate cancer models, even with low B7H3 levels. Non-ARPC models, which are currently lacking efficacious treatment, demonstrated the highest replication stress and were most sensitive to treatment. In RB1 WT ARPC tumors, SLFN11 expression or select DNA repair mutations in SLFN11 nonexpressors governed response. Importantly, WT TP53 predicted nonresponsiveness (7 of 8 models). Overall, biomarker-focused selection of models led to high efficacy of in vivo treatment. These data enable a paradigm shift to biomarker-driven trial designs for maximizing clinical benefit of ADC therapies.

Immune niches in brain metastases contain TCF1+ stem-like T cells, are associated with disease control and are modulated by preoperative SRS.

The CD8+ T-cell response is prognostic for survival outcomes in several tumor types. However, whether this extends to tumors in the brain, an organ with barriers to T cell entry, remains unclear. Here, we analyzed immune infiltration in 67 brain metastasis (BrM) and found high frequencies of PD1+ TCF1+ stem-like CD8+ T-cells and TCF1- effector-like cells. Importantly, the stem-like cells aggregate with antigen presenting cells in immune niches, and niches were prognostic for local disease control. Standard of care for BrM is resection followed by stereotactic radiosurgery (SRS), so to determine SRS's impact on the BrM immune response, we examined 76 BrM treated with pre-operative SRS (pSRS). pSRS acutely reduced CD8+ T cells at 3 days. However, CD8+ T cells rebounded by day 6, driven by increased frequency of effector-like cells. This suggests that the immune response in BrM can be regenerated rapidly, likely by the local TCF1+ stem-like population.

Prediction of cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values. DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Our key contribution is showing that ENLIGHT-DeepPT successfully predicts true responders in five independent patients' cohorts involving four different treatments spanning six cancer types with an overall odds ratio of 2.44, increasing the baseline response rate by 43.47% among predicted responders, without the need for any treatment data for training. Furthermore, its prediction accuracy on these datasets is comparable to a supervised approach predicting the response directly from the images, which needs to be trained and tested on the same cohort. ENLIGHT-DeepPT future application could provide clinicians with rapid treatment recommendations to an array of different therapies and importantly, may contribute to advancing precision oncology in developing countries.

Unpacking circulating tumor DNA lends insight into prostate cancer biology and the clonal dynamics of metastasis.

Prostate cancer (PCa) frequently metastasizes to bone, and analyses of DNA from bone biopsies are exceptionally challenging. A recent report in Nature demonstrates that whole-genome sequencing (WGS) of circulating tumor DNA (ctDNA) from patients with metastatic PCa can inform on the subclonal composition of metastatic disease and infer patterns of gene expression.

Autocrine Canonical Wnt Signaling Primes Noncanonical Signaling through ROR1 in Metastatic Castration-Resistant Prostate Cancer.

Wnt signaling driven by genomic alterations in genes including APC and CTNNB, which encodes ß-catenin, have been implicated in prostate cancer development and progression to metastatic castration-resistant prostate cancer (mCRPC). However, nongenomic drivers and downstream effectors of Wnt signaling in prostate cancer and the therapeutic potential of targeting this pathway in prostate cancer have not been fully established. Here we analyzed Wnt/ß-catenin signaling in prostate cancer and identified effectors distinct from those found in other tissues, including aryl hydrocarbon receptor and RUNX1, which are linked to stem cell maintenance, and ROR1, a noncanonical Wnt5a coreceptor. Wnt/ß-catenin signaling-mediated increases in ROR1 enhanced noncanonical responses to Wnt5a. Regarding upstream drivers, APC genomic loss, but not its epigenetic downregulation commonly observed in prostate cancer, was strongly associated with Wnt/ß-catenin pathway activation in clinical samples. Tumor cell upregulation of the Wnt transporter Wntless (WLS) was strongly associated with Wnt/ß-catenin pathway activity in primary prostate cancer but also associated with both canonical and noncanonical Wnt signaling in mCRPC. IHC confirmed tumor cell WLS expression in primary prostate cancer and mCRPC, and patient-derived prostate cancer xenografts expressing WLS were responsive to treatment with Wnt synthesis inhibitor ETC-1922159. These findings reveal that Wnt/ß-catenin signaling in prostate cancer drives stem cell maintenance and invasion and primes for noncanonical Wnt signaling through ROR1. They further show that autocrine Wnt production is a nongenomic driver of canonical and noncanonical Wnt signaling in prostate cancer, which can be targeted with Wnt synthesis inhibitors to suppress tumor growth. SIGNIFICANCE: This work provides fundamental insights into Wnt signaling and prostate cancer cell biology and indicates that a subset of prostate cancer driven by autocrine Wnt signaling is sensitive to Wnt synthesis inhibitors.

Progression of prostate cancer reprograms MYC-mediated lipid metabolism via lysine methyltransferase 2A.

BACKGROUND: The activities of MYC, the androgen receptor, and its associated pioneer factors demonstrate substantial reprogramming between early and advanced prostate cancer. Although previous studies have shown a shift in cellular metabolic requirements associated with prostate cancer progression, the epigenetic regulation of these processes is incompletely described. Here, we have integrated chromatin immunoprecipitation sequencing (ChIP-seq) and whole-transcriptome sequencing to identify novel regulators of metabolism in advanced prostate tumors characterized by elevated MYC activity. RESULTS: Using ChIP-seq against MYC, HOXB13, and AR in LNCaP cells, we observed redistribution of co-bound sites suggestive of differential KMT2A activity as a function of MYC expression. In a cohort of 177 laser-capture microdissected foci of prostate tumors, KMT2A expression was positively correlated with MYC activity, AR activity, and HOXB13 expression, but decreased with tumor grade severity. However, KMT2A expression was negatively correlated with these factors in 25 LuCaP patient-derived xenograft models of advanced prostate cancer and 99 laser-capture microdissected foci of metastatic castration-resistant prostate cancer. Stratified by KMT2A expression, ChIP-seq against AR and HOXB13 in 15 LuCaP patient-derived xenografts showed an inverse association with sites involving genes implicated in lipid metabolism, including the arachidonic acid metabolic enzyme PLA2G4F. LuCaP patient-derived xenograft models grown as organoids recapitulated the inverse association between KMT2A expression and fluorine-18 labeled arachidonic acid uptake in vitro. CONCLUSIONS: Our study demonstrates that the epigenetic activity of transcription factor oncogenes exhibits a shift during prostate cancer progression with distinctive phenotypic effects on metabolism. These epigenetically driven changes in lipid metabolism may serve as novel targets for the development of novel imaging agents and therapeutics.

Clinical outcome following checkpoint therapy in renal cell carcinoma is associated with a burst of activated CD8 T cells in blood.

PURPOSE: Checkpoint therapy is now the cornerstone of treatment for patients with renal cell carcinoma (RCC) with advanced disease, but biomarkers are lacking to predict which patients will benefit. This study proposes potential immunological biomarkers that could developed for predicting therapeutic response in patients with RCC. METHODS: Using flow cytometry, RNA sequencing, and T-cell receptor (TCR) sequencing, we investigated changes in T cells in the peripheral blood of patients with advanced RCC after receiving immunotherapy. We used immunofluorescence (IF) imaging and flow cytometry to investigate how intratumoral T cells in patients' tumors (resected months/years prior to receiving checkpoint therapy) predicted patient outcomes after immunotherapy. RESULTS: We found that a small proportion of CD4 and CD8 T cells in the blood activate following checkpoint therapy, expressing the proliferation marker Ki67 and activation markers HLA-DR and CD38. Patients who had the highest increase in these HLA-DR +CD38+CD8 T cells after treatment had the best antitumor immune response and experienced clinical benefit. Using RNA sequencing, we found that while these cells expanded in most patients, their phenotype did not drastically change during treatment. However, when we analyzed the TCR repertoire of these HLA-DR +CD38+CD8+T cells, we found that only patients who clinically benefitted had a burst of new clonotypes enter this pool of activated cells. Finally, we found that abundant T cells in the untreated tumors predicted clinical benefit to checkpoint therapy on disease progression. CONCLUSIONS: Together, these data suggest that having a strong pre-existing immune response and immediate peripheral T-cell activation after checkpoint therapy is a predictor of clinical benefit in patients with RCC.

Defining cellular population dynamics at single-cell resolution during prostate cancer progression.

Advanced prostate malignancies are a leading cause of cancer-related deaths in men, in large part due to our incomplete understanding of cellular drivers of disease progression. We investigate prostate cancer cell dynamics at single-cell resolution from disease onset to the development of androgen independence in an in vivo murine model. We observe an expansion of a castration-resistant intermediate luminal cell type that correlates with treatment resistance and poor prognosis in human patients. Moreover, transformed epithelial cells and associated fibroblasts create a microenvironment conducive to pro-tumorigenic immune infiltration, which is partially androgen responsive. Androgen-independent prostate cancer leads to significant diversification of intermediate luminal cell populations characterized by a range of androgen signaling activity, which is inversely correlated with proliferation and mRNA translation. Accordingly, distinct epithelial populations are exquisitely sensitive to translation inhibition, which leads to epithelial cell death, loss of pro-tumorigenic signaling, and decreased tumor heterogeneity. Our findings reveal a complex tumor environment largely dominated by castration-resistant luminal cells and immunosuppressive infiltrates.