Adrian Ishkanian

Purpose: To investigate the relationships between circulating tumor cells (CTCs), free circulating DNA (fcDNA) and biochemical response in prostate cancer patients treated primarily versus salvage radiotherapy (RT). Methods and Materials: Blood was collected prospectively from patients, enrolled in two institutional Phase II trials for primary and salvage RT. Three blood samples were collected at: (i) prior to treatment [RT or androgen deprivation therapy (ADT)], (ii) last week of RT, and (iii) three months post-RT. CTCs were quantified in 31 samples from 12 primary patients and 30 samples from 12 salvage patients; fcDNA were analyzed in 11 primary (28 samples) and 5 (9 samples) salvage patients. CTCs were visualized by immunofluorescence after microfilter capture and fcDNA was quantified using real-time Polymerase chain reaction (PCR). CTCs and fcDNA were correlated with early biochemical response by subdividing patients into early favorable and unfavorable response at 3 months after RT. Results: For those treated primarily, there was a direct correlation with CTC counts and prostate specific antigen (PSA) pre-RT that changed to a reciprocal relationship 3 months post-RT. CTCs increased significantly (p=0.03) at 3 months after primary RT in the biochemical favorable patients, while no significant association was observed for fcDNA. Correspondingly, post-RT fcDNA levels were inversely related to CTC counts. In salvage patients, the number of CTCs was related to pre-RT PSA, but it was not correlated to RT response. In post-RT series, a significant direct correlation was observed between CTCs and PSA. Conclusion: Our preliminary studies suggest that RT affects CTC counts, which are thus associated with prostate cancer biochemical response. A larger cohort with longer follow-up will be needed to establish the association with more recognized treatment endpoints.

Radiotherapy can elicit systemic immune control of local tumors and distant nonirradiated tumor lesions, known as the abscopal effect. Although this effect is enhanced using checkpoint blockade or costimulatory antibodies, objective responses remain suboptimal. As radiotherapy can induce secretion of VEGF and other stress products in the tumor microenvironment, we hypothesized that targeting immunomodulatory drugs to such products will not only reduce toxicity but also broaden the scope of tumor-targeted immunotherapy. Using an oligonucleotide aptamer platform, we show that radiation-induced VEGF-targeted 4-1BB costimulation potentiated both local tumor control and abscopal responses with equal or greater efficiency than 4-1BB, CTLA-4, or PD1 antibodies alone. Although 4-1BB and CTLA-4 antibodies elicited organ-wide inflammatory responses and tissue damage, VEGF-targeted 4-1BB costimulation produced no observable toxicity. These findings suggest that radiation-induced tumor-targeted immunotherapy can improve the therapeutic index and extend the reach of immunomodulatory agents. Cancer Res; 77(6); 1310–21. ©2017 AACR.

8 Background: A number of biomarkers related to cell cycle, angiogenesis or apoptosis have been found to be associated with patient outcome in tissue samples from men treated with first line radiation therapy in RTOG clinical trials using immunohistochemical staining and analysis. In a prior study, four biomarkers (Ki-67, MDM2, p16 and Cox-2) and clinical covariates were included in a model of distant metastasis (DM; Pollack et al, Clin Cancer Res, 2014 [epub ahead of print]) risk. The current study tested the hypothesis that these genes are prognostic for DM in men treated primarily with total prostatectomy using RNA expression profiling. Methods: RNA fromprostatectomy samples from Cleveland Clinic (CC, n=182); Mayo Clinic (MC)-I (n = 545) and II (n=235); Memorial Sloan Kettering Cancer Center (MSKCC, n=131); Erasmus Medical Center (EMC, n=48) and Thomas Jefferson University (TJU, n=130) were profiled using 1.4 million RNA features. A Cox proportional hazards model was built on the MC-I training set to combine the 4 biomarkers into a prognostic risk score (4BMSig). 4BMSig was subsequently evaluated for its prognostic significance separately and in combination with clinical risk factors (biopsy Gleason Score, cT-category and Preop-PSA) for DM. Results: 4BMSig was found to discriminate DM patients significantly for the MC-II (AUC = 0.66, p < 0.001), CCF (AUC = 0.68, p < 0.001), and MSKCC (AUC = 0.71, p = 0.04) datasets, and achieved borderline significance for EMC (AUC = 0.70, p = 0.06). 4BMSig did not discriminate DM in the TJU dataset (only 10 DM events). Pooled multivariable analysis (n = 726) with clinical covariates revealed that 4BMSig is a strong independent prognostic covariate for DM (p < 0.001) and prostate cancer specific mortality (p = 0.005). Conclusions: The four genes identified previously as being associated with DM in radiotherapy patients were incorporated herein into 4BMSig, which was found to have potential as a pretreatment prognostic DM risk assessment tool for men treated with prostatectomy. Further validation would consist of testing 4BMSig from RNA in diagnostic tissue from prostate cancer patients prior to prostatectomy.

39 Background: Health-related quality of life (HRQoL) outcomes are important in treatment selection for prostate cancer. The Expanded Prostate Cancer Index Composite (EPIC) is a validated and widely-utilized HRQoL survey which accounts for newer radiotherapeutic, surgical, and hormonal treatment methods. We present a meta-analysis of patient reported HRQoL outcomes collected with EPIC and compare HRQoL trends with radiation therapy, surgery, or active surveillance as primary treatment. Methods: The PubMed database was systematically searched for all studies which presented data directly derived from the use of EPIC on patients with prostate cancer prior to 07/09/2014. All eligible studies were selected for either inclusion and analysis or exclusion based on pre-determined criteria. The data from included studies was compiled and a simulation-based estimation method using Approximate Bayesian Computation was performed to obtain missing standard deviation estimate. A longitudinal meta-analysis was conducted to estimate EPIC-profiles for each component using Bayesian p-spline method. Results: Over 4,000 studies were searched, 152 were deemed eligible, and 39 were included. The calculated mean summary score estimates are shown in the attached table. Conclusions: In the urinary domain, radical prostatectomy (RP) has lower acute scores than active surveillance (AS) or radiation therapy (RT) without long-term difference. In the bowel domain, RT has lower scores than AS or RP acutely and long-term. In the sexual domain, RT and RP have lower acute scores than AS. RP has lower scores than RT without long-term difference. In the hormonal domain, little difference was noted between modalities. [Table: see text]

25 Background: Current methods for prostate cancer risk stratification are often insufficient to accurately predict outcome after definitive therapy. As tumor multi-focality and genetic heterogeneity can lead to diagnostic prostate biopsy sampling bias, we hypothesize that quantitative imaging with multiparametric (MP)-MRI will more accurately direct targeted biopsies to index lesions associated with highest risk clinical and genomic features, and improve accuracy of current risk classification systems. Methods: Regionally distinct prostate habitats were delineated on MP-MRI (T2w, perfusion and diffusion imaging). Directed biopsies were performed on 17 habitats from 6 patients using MRI-ultrasound fusion. Biopsy location was characterized with 51 radiographic features (including intensity, volume, perfusion, and diffusion paramters). Transcriptome-wide analysis of 1.4 million RNA probes was performed on RNA from each habitat. Genomics features with insignificant expression values ( 0.7). Furthermore, genomic features were found to be significantly enriched for prostate cancer related pathways (p < 0.05), representing a potential biologically meaningful link between imaging and genomic data. Conclusions: MP-MRI-targeted diagnostic biopsies can potentially improve risk classification by directing pathological and genomic analysis to highest risk index lesions. This is the first demonstration of a link between quantitative imaging features (radiomics) with genomic features in MRI-directed prostate biopsies.