Pre-operative stereotactic radiosurgery and peri-operative dexamethasone for resectable brain metastases: a two-arm pilot study evaluating clinical outcomes and immunological correlates.

Enhancing the efficacy of immunotherapy in brain metastases (BrM) requires an improved understanding of the immune composition of BrM and how this is affected by radiation and dexamethasone. Our two-arm pilot study (NCT04895592) allocated 26 patients with BrM to either low (Arm A) or high (Arm B) dose peri-operative dexamethasone followed by pre-operative stereotactic radiosurgery (pSRS) and resection (n= 13 per arm). The primary endpoint, a safety analysis at 4 months, was met. The secondary clinical endpoints of overall survival, distant brain failure, leptomeningeal disease and local recurrence at 12-months were 66%, 37.3%, 6%, and 0% respectively and were not significantly different between arms (p= 0.7739, p= 0.3884, p= 0.3469). Immunological data from two large retrospective BrM datasets and confirmed by correlates from both arms of this pSRS prospective trial revealed that BrM CD8 T cells were composed of predominantly PD1+ TCF1+ stem-like and PD1+ TCF1-TIM3+ effector-like cells. Clustering of TCF1+ CD8 T cells with antigen presenting cells in immune niches was prognostic for local control, even without pSRS. Following pSRS, CD8 T cell and immune niche density were transiently reduced compared to untreated BrM, followed by a rebound 6+ days post pSRS with an increased frequency of TCF1- effector-like cells. In sum, pSRS is safe and therapeutically beneficial, and these data provide a framework for how pSRS may be leveraged to maximize intracranial CD8 T cell responses.

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.

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.

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.

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.

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.

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.

Assessment of Androgen Receptor Splice Variant-7 as a Biomarker of Clinical Response in Castration-Sensitive Prostate Cancer.

PURPOSE: Therapies targeting the androgen receptor (AR) have improved the outcome for patients with castration-sensitive prostate cancer (CSPC). Expression of the constitutively active AR splice variant-7 (AR-V7) has shown clinical utility as a predictive biomarker of AR-targeted therapy resistance in castration-resistant prostate cancer (CRPC), but its importance in CSPC remains understudied. EXPERIMENTAL DESIGN: We assessed different approaches to quantify AR-V7 mRNA and protein in prostate cancer cell lines, patient-derived xenograft (PDX) models, publicly available cohorts, and independent institutional clinical cohorts, to identify reliable approaches for detecting AR-V7 mRNA and protein and its association with clinical outcome. RESULTS: In CSPC and CRPC cohorts, AR-V7 mRNA was much less abundant when detected using reads across splice boundaries than when considering isoform-specific exonic reads. The RM7 AR-V7 antibody had increased sensitivity and specificity for AR-V7 protein detection by immunohistochemistry (IHC) in CRPC cohorts but rarely identified AR-V7 protein reactivity in CSPC cohorts, when compared with the EPR15656 AR-V7 antibody. Using multiple CRPC PDX models, we demonstrated that AR-V7 expression was exquisitely sensitive to hormonal manipulation. In CSPC institutional cohorts, AR-V7 protein quantification by either assay was associated neither with time to development of castration resistance nor with overall survival, and intense neoadjuvant androgen-deprivation therapy did not lead to significant AR-V7 mRNA or staining following treatment. Neither pre- nor posttreatment AR-V7 levels were associated with volumes of residual disease after therapy. CONCLUSIONS: This study demonstrates that further analytical validation and clinical qualification are required before AR-V7 can be considered for clinical use in CSPC as a predictive biomarker.

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.

Modeling Androgen Deprivation Therapy-Induced Prostate Cancer Dormancy and Its Clinical Implications.

Treatment-induced tumor dormancy is a state in cancer progression where residual disease is present but remains asymptomatic. Dormant cancer cells are treatment-resistant and responsible for cancer recurrence and metastasis. Prostate cancer treated with androgen-deprivation therapy (ADT) often enters a dormant state. ADT-induced prostate cancer dormancy remains poorly understood due to the challenge in acquiring clinical dormant prostate cancer cells and the lack of representative models. In this study, we aimed to develop clinically relevant models for studying ADT-induced prostate cancer dormancy. Dormant prostate cancer models were established by castrating mice bearing patient-derived xenografts (PDX) of hormonal naïve or sensitive prostate cancer. Dormancy status and tumor relapse were monitored and evaluated. Paired pre- and postcastration (dormant) PDX tissues were subjected to morphologic and transcriptome profiling analyses. As a result, we established eleven ADT-induced dormant prostate cancer models that closely mimicked the clinical courses of ADT-treated prostate cancer. We identified two ADT-induced dormancy subtypes that differed in morphology, gene expression, and relapse rates. We discovered transcriptomic differences in precastration PDXs that predisposed the dormancy response to ADT. We further developed a dormancy subtype-based, predisposed gene signature that was significantly associated with ADT response in hormonal naïve prostate cancer and clinical outcome in castration-resistant prostate cancer treated with ADT or androgen-receptor pathway inhibitors. IMPLICATIONS: We have established highly clinically relevant PDXs of ADT-induced dormant prostate cancer and identified two dormancy subtypes, leading to the development of a novel predicative gene signature that allows robust risk stratification of patients with prostate cancer to ADT or androgen-receptor pathway inhibitors.

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.

A Subset of Localized Prostate Cancer Displays an Immunogenic Phenotype Associated with Losses of Key Tumor Suppressor Genes.

PURPOSE: A subset of primary prostate cancer expresses programmed death-ligand 1 (PD-L1), but whether they have a unique tumor immune microenvironment or genomic features is unclear. EXPERIMENTAL DESIGN: We selected PD-L1-positive high-grade and/or high-risk primary prostate cancer, characterized tumor-infiltrating lymphocytes with multiplex immunofluorescence, and identified genomic alterations in immunogenic and nonimmunogenic tumor foci. RESULTS: One quarter of aggressive localized prostate cancer cases (29/115) had tumor PD-L1 expression more than 5%. This correlated with increased density of CD8+ T cells, a large fraction coexpressing PD-1, versus absent PD-1 expression on sparse CD8 T cells in unselected cases. Most CD8+PD-1+ cells did not express terminal exhaustion markers (TIM3 or LAG3), while a subset expressed TCF1. Consistent with these CD8+PD-1+TCF1+ cells being progenitors, they were found in antigen-presenting cell niches in close proximity to MHC-II+ cells. CD8 T-cell density in immunogenic prostate cancer and renal cell carcinoma (RCC) was nearly identical. Shallow RB1 and BRCA2 losses, and deep deletions of CHD1, were prevalent, the latter being strongly associated with a dendritic cell gene set in The Cancer Genome Atlas. Tumor mutation burden was variable; neither high microsatellite instability nor CDK12 alterations were present. CONCLUSIONS: A subset of localized prostate cancer is immunogenic, manifested by PD-L1 expression and CD8+ T-cell content comparable with RCC. The CD8+ T cells include effector cells and exhausted progenitor cells, which may be expanded by immune checkpoint inhibitors (ICI). Genomic losses of RB1, BRCA2, and CHD1 may be drivers of this phenotype. These findings indicate that immunotherapies may be effective in biomarker-selected subpopulations of patients with localized prostate cancer.

EZH2 inhibition activates a dsRNA-STING-interferon stress axis that potentiates response to PD-1 checkpoint blockade in prostate cancer.

Prostate cancers are considered to be immunologically 'cold' tumors given the very few patients who respond to checkpoint inhibitor (CPI) therapy. Recently, enrichment of interferon-stimulated genes (ISGs) predicted a favorable response to CPI across various disease sites. The enhancer of zeste homolog-2 (EZH2) is overexpressed in prostate cancer and known to negatively regulate ISGs. In the present study, we demonstrate that EZH2 inhibition in prostate cancer models activates a double-stranded RNA-STING-ISG stress response upregulating genes involved in antigen presentation, Th1 chemokine signaling and interferon response, including programmed cell death protein 1 (PD-L1) that is dependent on STING activation. EZH2 inhibition substantially increased intratumoral trafficking of activated CD8+ T cells and increased M1 tumor-associated macrophages, overall reversing resistance to PD-1 CPI. Our study identifies EZH2 as a potent inhibitor of antitumor immunity and responsiveness to CPI. These data suggest EZH2 inhibition as a therapeutic direction to enhance prostate cancer response to PD-1 CPI.

Nascent Prostate Cancer Heterogeneity Drives Evolution and Resistance to Intense Hormonal Therapy.

BACKGROUND: Patients diagnosed with high risk localized prostate cancer have variable outcomes following surgery. Trials of intense neoadjuvant androgen deprivation therapy (NADT) have shown lower rates of recurrence among patients with minimal residual disease after treatment. The molecular features that distinguish exceptional responders from poor responders are not known. OBJECTIVE: To identify genomic and histologic features associated with treatment resistance at baseline. DESIGN, SETTING, AND PARTICIPANTS: Targeted biopsies were obtained from 37 men with intermediate- to high-risk prostate cancer before receiving 6 mo of ADT plus enzalutamide. Biopsy tissues were used for whole-exome sequencing and immunohistochemistry (IHC). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We assessed the relationship of molecular features with final pathologic response using a cutpoint of 0.05 cm3 for residual cancer burden to compare exceptional responders to incomplete and nonresponders. We assessed intratumoral heterogeneity at the tissue and genomic level, and compared the volume of residual disease to the Shannon diversity index for each tumor. We generated multivariate models of resistance based on three molecular features and one histologic feature, with and without multiparametric magnetic resonance imaging estimates of baseline tumor volume. RESULTS AND LIMITATIONS: Loss of chromosome 10q (containing PTEN) and alterations to TP53 were predictive of poor response, as were the expression of nuclear ERG on IHC and the presence of intraductal carcinoma of the prostate. Patients with incompletely and nonresponding tumors harbored greater tumor diversity as estimated via phylogenetic tree reconstruction from DNA sequencing and analysis of IHC staining. Our four-factor binary model (area under the receiver operating characteristic curve [AUC] 0.89) to predict poor response correlated with greater diversity in our cohort and a validation cohort of 57 Gleason score 8-10 prostate cancers from The Cancer Genome Atlas. When baseline tumor volume was added to the model, it distinguished poor response to NADT with an AUC of 0.98. Prospective use of this model requires further retrospective validation with biopsies from additional trials. CONCLUSIONS: A subset of prostate cancers exhibit greater histologic and genomic diversity at the time of diagnosis, and these localized tumors have greater fitness to resist therapy. PATIENT SUMMARY: Some prostate cancer tumors do not respond well to a hormonal treatment called androgen deprivation therapy (ADT). We used tumor volume and four other parameters to develop a model to identify tumors that will not respond well to ADT. Treatments other than ADT should be considered for these patients.

Sequential Prostate Magnetic Resonance Imaging in Newly Diagnosed High-risk Prostate Cancer Treated with Neoadjuvant Enzalutamide is Predictive of Therapeutic Response.

PURPOSE: For high-risk prostate cancer, standard treatment options include radical prostatectomy (RP) or radiotherapy plus androgen deprivation therapy (ADT). Despite definitive therapy, many patients will have disease recurrence. Imaging has the potential to better define characteristics of response and resistance. In this study, we evaluated prostate multiparametric MRI (mpMRI) before and after neoadjuvant enzalutamide plus ADT. PATIENTS AND METHODS: Men with localized intermediate- or high-risk prostate cancer underwent a baseline mpMRI and mpMRI-targeted biopsy followed by a second mpMRI after 6 months of enzalutamide and ADT prior to RP. Specimens were sectioned in the same plane as mpMRI using patient-specific 3D-printed molds to permit mpMRI-targeted biopsies to be compared with the same lesion from the RP. Specimens were analyzed for imaging and histologic correlates of response. RESULTS: Of 39 patients enrolled, 36 completed imaging and RP. Most patients (92%) had high-risk disease. Fifty-eight lesions were detected on baseline mpMRI, of which 40 (69%) remained measurable at 6-month follow-up imaging. Fifty-five of 59 lesions (93%) demonstrated >50% volume reduction on posttreatment mpMRI. Three of 59 lesions (5%) demonstrated growth in size at follow-up imaging, with two lesions increasing more than 3-fold in volume. On whole-mount pathology, 15 patients demonstrated minimal residual disease (MRD) of <0.05 cc or pathologic complete response. Low initial mpMRI relative tumor burden was most predictive of MRD on final pathology. CONCLUSIONS: Low relative lesion volume at baseline mpMRI was predictive of pathologic response. A subset of patients had limited response. Selection of patients based on these metrics may improve outcomes in high-risk disease.

Battling the two-headed dragon of prostate cancer targeted therapy.

Neoadjuvant intense androgen deprivation therapy for high-risk localized prostate cancer is an emerging but unproven treatment paradigm that is hoped to delay or prevent disease recurrence. We found that a patient enrolled in a clinical trial harbored two completely independent prostate cancers that responded differently to this therapy.