Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies.

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)--a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis (TMA) on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated, but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer (SCLC) subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to novel antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.

Convergent evolution of BRCA2 reversion mutations under therapeutic pressure by PARP inhibition and platinum chemotherapy.

Reversion mutations that restore wild-type function of the BRCA gene have been described as a key mechanism of resistance to Poly(ADP-ribose) polymerase (PARP) inhibitor therapy in BRCA-associated cancers. Here, we report a case of a patient with metastatic castration-resistant prostate cancer (mCRPC) with a germline BRCA2 mutation who developed acquired resistance to PARP inhibition. Extensive genomic interrogation of cell-free DNA (cfDNA) and tissue at baseline, post-progression, and postmortem revealed ten unique BRCA2 reversion mutations across ten sites. While several of the reversion mutations were private to a specific site, nine out of ten tumors contained at least one mutation, suggesting a powerful clonal selection for reversion mutations in the presence of therapeutic pressure by PARP inhibition. Variable cfDNA shed was seen across tumor sites, emphasizing a potential shortcoming of cfDNA monitoring for PARPi resistance. This report provides a genomic portrait of the temporal and spatial heterogeneity of prostate cancer under the selective pressure of a PARP inhibition and exposes limitations in the current strategies for detection of reversion mutations.

Evaluating Immune-Related Adverse Events Using PRO-CTCAE in a Phase II Study of Ipilimumab for Hormone-Sensitive Prostate Cancer.

Introduction: Use of the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) during chemotherapy is associated with decreased hospitalization rates, improved quality of life, and longer survival. Limited data exist on the benefit of this symptom assessment tool for monitoring immune-related adverse events (irAEs). Methods: We incorporated irAE-related items from the National Cancer Institute's (NCI) PRO-CTCAE in a trial evaluating ipilimumab in combination with androgen deprivation therapy in 16 patients with hormone-sensitive prostate cancer. For comparison, NCI's CTCAE version 4.0 was used by clinicians. Results: IrAE-related PRO-CTCAE surveys and matched CTCAEs (184 pairs) reporting abdominal pain, diarrhea, fatigue, anorexia, nausea, vomiting, rash, and pruritus were collected at each treatment administration and during follow-up. Fatigue, diarrhea, rash, and pruritus were the symptoms most frequently reported by both patients and clinicians. Agreement was lowest for pruritus (κ = 0.10) and highest for rash (κ = 0.64). IrAEs were more commonly reported and of higher grade with PRO-CTCAE scores compared with CTCAE grades. Conclusion: PRO-CTCAEs focused on irAEs capture the patient's immunotherapy experience while complementing the clinician's toxicity assessment measures. Further study is needed to assess PRO-CTCAE's utility in identifying and managing irAEs.

The Radiolabeling of [161Tb]-PSMA-617 by a Novel Radiolabeling Method and Preclinical Evaluation by In Vitro/In Vivo Methods.

Background: Prostate cancer (PC) is the most common type of cancer in elderly men, with a positive correlation with age. As resistance to treatment has developed, particularly in the progressive stage of the disease and in the presence of microfocal multiple bone metastases, new generation radionuclide therapies have emerged. Recently, [161Tb], a radiolanthanide introduced for treating micrometastatic foci, has shown great promise for treating prostate cancer. Results: In this study, Terbium-161 [161Tb]Tb was radiolabeled with prostate-specific membrane antigen (PSMA)-617 ([161Tb]-PSMA-617) and the therapeutic efficacy of the radiolabeled compound investigated in vitro and in vivo. [161Tb]-PSMA-617 was found to have a radiochemical yield of 97.99 ± 2.01% and was hydrophilic. [161Tb]-PSMA-617 was also shown to have good stability, with a radiochemical yield of over 95% up to 72 hours. In vitro, [161Tb]-PSMA-617 showed a cytotoxic effect on LNCaP cells but not on PC-3 cells. In vivo, scintigraphy imaging visualized the accumulation of [161Tb]-PSMA-617 in the prostate, kidneys, and bladder. Conclusions: The results suggest that [161Tb]-PSMA-617 can be an effective radiolabeled agent for the treatment of PSMA positive foci in prostate cancer.

Clinical Impact of a Rapid Genetic Testing Model for Advanced Prostate Cancer Patients.

PURPOSE: Genetic testing may alter clinical management for individuals with metastatic prostate cancer by identifying additional therapies. Traditional counseling models are unlikely to enable time-sensitive therapeutic decision-making. This study aimed to determine the feasibility and clinical impact of an alternative hereditary genetic testing model. MATERIALS AND METHODS: As part of a multicenter, single-arm prospective trial, individuals with advanced prostate cancer were referred by their oncologist for testing of 14 genes associated with hereditary prostate cancer. Pretest education (brochure and video) was provided in the oncology clinic. Questionnaires assessing participant satisfaction with both pretest education and decision to undergo genetic testing were collected. A genetic counselor contacted participants by phone to obtain family history and discuss results. Medical records were queried to determine whether a change in clinical management was discussed. RESULTS: Of 501 participants consented to germline analysis, 51 (10.2%) had at least 1 pathogenic/likely pathogenic variant. Change in treatment was discussed with 22/48 (45.8%) of eligible participants who tested positive. Feasibility of this model was assessed by participant satisfaction and turnaround time. Average±SD satisfaction with the pretest education (15.5±2.2, 4-20 scale) and with the decision to undergo genetic testing (17.1±2.9, 4-20 scale) were both high. Results were returned 20 days (median) after sample collection. CONCLUSIONS: Oncologist-initiated germline genetic testing in collaboration with a genetic counselor is a feasible approach to testing advanced prostate cancer patients with impactful clinical actionability. The testing model and educational material serve as resources to clinicians treating prostate cancer patients.

Gene-based Confirmatory Germline Testing Following Tumor-only Sequencing of Prostate Cancer.

BACKGROUND: Tumor-only genomic profiling is an important tool in therapeutic management of men with prostate cancer. Since clinically actionable germline variants may be reflected in tumor profiling, it is critical to identify which variants have a higher risk of being germline in origin to better counsel patients and prioritize genetic testing. OBJECTIVE: To determine when variants found on tumor-only sequencing of prostate cancers should prompt confirmatory germline testing. DESIGN, SETTING, AND PARTICIPANTS: Men with prostate cancer who underwent both tumor and germline sequencing at Memorial Sloan Kettering Cancer Center from January 1, 2015 to January 31, 2020 were evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Tumor and germline profiles were analyzed for pathogenic and likely pathogenic ("pathogenic") variants in 60 moderate- or high-penetrance genes associated with cancer predisposition. The germline probability (germline/germline + somatic) of a variant was calculated for each gene. Clinical and pathologic factors were analyzed as potential modifiers of germline probability. RESULTS AND LIMITATIONS: Of the 1883 patients identified, 1084 (58%) had a somatic or germline pathogenic variant in one of 60 cancer susceptibility genes, and of them, 240 (22%) had at least one germline variant. Overall, the most frequent variants were in TP53, PTEN, APC, BRCA2, RB1, ATM, and CHEK2. Variants in TP53, PTEN, or RB1 were identified in 746 (40%) patients and were exclusively somatic. Variants with the highest germline probabilities were in PALB2 (69%), MITF (62%), HOXB13 (60%), CHEK2 (55%), BRCA1 (55%), and BRCA2 (47%), and the overall germline probability of a variant in any DNA damage repair gene was 40%. Limitations were that most of the men included in the cohort had metastatic disease, and different thresholds for pathogenicity exist for somatic and germline variants. CONCLUSIONS: Of patients with pathogenic variants found on prostate tumor sequencing, 22% had clinically actionable germline variants, for which the germline probabilities varied widely by gene. Our results provide an evidenced-based clinical framework to prioritize referral to genetic counseling following tumor-only sequencing. PATIENT SUMMARY: Patients with advanced prostate cancer are recommended to have germline genetic testing. Genetic sequencing of a patient's prostate tumor may also identify certain gene variants that are inherited. We found that patients who had variants in certain genes, such as ones that function in DNA damage repair, identified in their prostate tumor sequencing, had a high risk for having an inherited cancer syndrome.

Analysis of BRCA2 Copy Number Loss and Genomic Instability in Circulating Tumor Cells from Patients with Metastatic Castration-resistant Prostate Cancer.

BACKGROUND: BRCA2 alterations predict for a response to poly-ADP-ribose polymerase inhibition in metastatic castration-resistant prostate cancer (mCRPC). However, detection is hindered by insufficient tumor tissue and low sensitivity of cell-free DNA for detecting copy number loss. OBJECTIVE: To evaluate the BRCA2 loss detection using single-cell, shallow whole-genome sequencing (sWGS) of circulating tumor cells (CTCs) in patients with mCRPC. DESIGN, SETTING, AND PARTICIPANTS: We analyzed CTC samples collected concurrently with tumor biopsies intended for clinical sequencing in patients with progressing mCRPC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Differences in proportions were evaluated using the chi-square test. Correlations between assays were analyzed in linear regression models. Associations between alterations and genomic instability were assessed on the single-cell level using mixed-effect negative binomial models. RESULTS AND LIMITATIONS: We identified 138 patients with concurrent CTC and biopsy samples. CTC sWGS generated copy number profiles in a similar proportion of patients to biopsy samples (83% vs 78%, p = 0.23), but was more effective than bone biopsies (79% vs 50%; p = 0.009). CTC sWGS detected BRCA2 loss in more patients than tissue at the ≥1 (42% vs 16%; p < 0.001) and ≥2 (27% vs 16%; p = 0.028) CTC thresholds. The overall prevalence of BRCA2 loss was not increased in CTCs using sample-level composite z scores (p = 0.4), but was significantly increased compared with a lower-than-expected prevalence in bone samples (21% vs 3%, p = 0.014). Positive/negative predictive values for CTC BRCA2 loss were 89%/96% using the ≥1 CTC threshold and 67%/92% using the composite z score. CTC BRCA2 loss was associated with higher genomic instability in univariate (1.4-fold large-scale transition difference, 95% confidence interval [CI]: 1.2-1.6; p < 0.001) and multivariable analysis (1.4-fold difference, 95% CI: 1.2-1.6; p < 0.001). CONCLUSIONS: Copy number profiles can reliably be generated using CTC sWGS, which detected a majority of tissue-confirmed BRCA2 loss and "CTC-only" losses. BRCA2 losses were supported by increases in genomic instability. PATIENT SUMMARY: Current testing strategies have limitations in their ability to detect BRCA2 loss, a relatively common alteration in prostate cancer that is used to identify patients who may benefit from targeted therapy. In this paper, we evaluated whether we could detect BRCA2 loss in individual tumor cells isolated from patient blood samples and found this method to be suitable for further analysis.

A clinical-grade liquid biomarker detects neuroendocrine differentiation in prostate cancer.

BackgroundNeuroendocrine prostate cancer (NEPC) is an aggressive subtype, the presence of which changes the prognosis and management of metastatic prostate cancer.MethodsWe performed analytical validation of a Circulating Tumor Cell (CTC) multiplex RNA qPCR assay to identify the limit of quantification (LOQ) in cell lines, synthetic cDNA, and patient samples. We next profiled 116 longitudinal samples from a prospectively collected institutional cohort of 17 patients with metastatic prostate cancer (7 NEPC, 10 adenocarcinoma) as well as 265 samples from 139 patients enrolled in 3 adenocarcinoma phase II trials of androgen receptor signaling inhibitors (ARSIs). We assessed a NEPC liquid biomarker via the presence of neuroendocrine markers and the absence of androgen receptor (AR) target genes.ResultsUsing the analytical validation LOQ, liquid biomarker NEPC detection in the longitudinal cohort had a per-sample sensitivity of 51.35% and a specificity of 91.14%. However, when we incorporated the serial information from multiple liquid biopsies per patient, a unique aspect of this study, the per-patient predictions were 100% accurate, with a receiver-operating-curve (ROC) AUC of 1. In the adenocarcinoma ARSI trials, the presence of neuroendocrine markers, even while AR target gene expression was retained, was a strong negative prognostic factor.ConclusionOur analytically validated CTC biomarker can detect NEPC with high diagnostic accuracy when leveraging serial samples that are only feasible using liquid biopsies. Patients with expression of NE genes while retaining AR-target gene expression may indicate the transition to neuroendocrine differentiation, with clinical characteristics consistent with this phenotype.FundingNIH (DP2 OD030734, 1UH2CA260389, R01CA247479, and P30 CA014520), Department of Defense (PC190039 and PC200334), and Prostate Cancer Foundation (Movember Foundation - PCF Challenge Award).

Evaluation of an Integrated Spectroscopy and Classification Platform for Point-of-Care Core Needle Biopsy Assessment: Performance Characteristics from Ex Vivo Renal Mass Biopsies.

PURPOSE: To evaluate a transmission optical spectroscopy instrument for rapid ex vivo assessment of core needle cancer biopsies (CNBs) at the point of care. MATERIALS AND METHODS: CNBs from surgically resected renal tumors and nontumor regions were scanned on their sampling trays with a custom spectroscopy instrument. After extracting principal spectral components, machine learning was used to train logistic regression, support vector machines, and random decision forest (RF) classifiers on 80% of randomized and stratified data. The algorithms were evaluated on the remaining 20% of the data set held out during training. Binary classification (tumor/nontumor) was performed based on a decision threshold. Multinomial classification was also performed to differentiate between the subtypes of renal cell carcinoma (RCC) and account for potential confounding effects from fat, blood, and necrotic tissue. Classifiers were compared based on sensitivity, specificity, and positive predictive value (PPV) relative to a histopathologic standard. RESULTS: A total of 545 CNBs from 102 patients were analyzed, yielding 5,583 spectra after outlier exclusion. At the individual spectra level, the best performing algorithm was RF with sensitivities of 96% and 92% and specificities of 90% and 89%, for the binary and multiclass analyses, respectively. At the full CNB level, RF algorithm also showed the highest sensitivity and specificity (93% and 91%, respectively). For RCC subtypes, the highest sensitivity and PPV were attained for clear cell (93.5%) and chromophobe (98.2%) subtypes, respectively. CONCLUSIONS: Ex vivo spectroscopy imaging paired with machine learning can accurately characterize renal mass CNB at the time of tissue acquisition.

The Impact of PIK3R1 Mutations and Insulin-PI3K-Glycolytic Pathway Regulation in Prostate Cancer.

PURPOSE: Oncogenic alterations of the PI3K/AKT pathway occur in >40% of patients with metastatic castration-resistant prostate cancer, predominantly via PTEN loss. The significance of other PI3K pathway components in prostate cancer is largely unknown. EXPERIMENTAL DESIGN: Patients in this study underwent tumor sequencing using the MSK-IMPACT clinical assay to capture single-nucleotide variants, insertions, and deletions; copy-number alterations; and structural rearrangements, or were profiled through The Cancer Genome Atlas. The association between PIK3R1 alteration/expression and survival was evaluated using univariable and multivariable Cox proportional-hazards regression models. We used the siRNA-based knockdown of PIK3R1 for functional studies. FDG-PET/CT examinations were performed with a hybrid positron emission tomography (PET)/CT scanner for some prostate cancer patients in the MSK-IMPACT cohort. RESULTS: Analyzing 1,417 human prostate cancers, we found a significant enrichment of PIK3R1 alterations in metastatic cancers compared with primary cancers. PIK3R1 alterations or reduced mRNA expression tended to be associated with worse clinical outcomes in prostate cancer, particularly in primary disease, as well as in breast, gastric, and several other cancers. In prostate cancer cell lines, PIK3R1 knockdown resulted in increased cell proliferation and AKT activity, including insulin-stimulated AKT activity. In cell lines and organoids, PIK3R1 loss/mutation was associated with increased sensitivity to AKT inhibitors. PIK3R1-altered patient prostate tumors had increased uptake of the glucose analogue 18F-fluorodeoxyglucose in PET imaging, suggesting increased glycolysis. CONCLUSIONS: Our findings describe a novel genomic feature in metastatic prostate cancer and suggest that PIK3R1 alteration may be a key event for insulin-PI3K-glycolytic pathway regulation in prostate cancer.

Statin and metformin use and outcomes in patients with castration-resistant prostate cancer treated with enzalutamide: A meta-analysis of AFFIRM, PREVAIL and PROSPER.

BACKGROUND: Statins and metformin are commonly prescribed for patients, including those with prostate cancer. Preclinical and epidemiologic studies of each agent have suggested anti-cancer properties. METHODS: Patient data from three randomised, double-blind, placebo-controlled, phase III studies evaluating enzalutamide (AFFIRM, PREVAIL and PROSPER) in patients with castration-resistant prostate cancer were included in this analysis. This post hoc, retrospective study examined the association of statin and metformin on radiographic progression-free survival (rPFS), metastasis-free survival (MFS), toxicity and overall survival (OS). After adjusting for available clinical prognostic variables, multivariate analyses were performed on pooled data from AFFIRM and PREVAIL, all three trials pooled, and each trial individually, to assess differential efficacy in these end-points associated with the baseline use of these medications. RESULTS: In the multivariate analysis of the individual trials, OS and rPFS/MFS were not significantly influenced by statin or metformin use in AFFIRM or PROSPER. However, in PREVAIL, OS was significantly influenced by statin (hazard ratio [HR] 0.72; 95% confidence interval [CI] 0.59-0.89) and rPFS was significantly influenced by metformin (HR, 0.48; 95% CI 0.34-0.70). In pooled analyses, improved OS was significantly associated with statin use but not metformin use for AFFIRM+PREVAIL trials (HR 0.83; 95% CI 0.72-0.96) and AFFIRM+PREVAIL+PROSPER (HR 0.75; 95% CI 0.66-0.85). CONCLUSIONS: The association between statin or metformin use and rPFS, MFS and OS was inconsistent across three trials. Analyses of all three trials pooled and AFFIRM+PREVAIL pooled revealed that statin but not metformin use was significantly associated with a reduced risk of death in enzalutamide-treated patients. Additional prospective, controlled studies are warranted. CLINICAL TRIAL REGISTRATION: AFFIRM (NCT00974311), PREVAIL (NCT01212991) and PROSPER (NCT02003924).

Clinical annotations for prostate cancer research: Defining data elements, creating a reproducible analytical pipeline, and assessing data quality.

BACKGROUND: Routine clinical data from clinical charts are indispensable for retrospective and prospective observational studies and clinical trials. Their reproducibility is often not assessed. We developed a prostate cancer-specific database for clinical annotations and evaluated data reproducibility. METHODS: For men with prostate cancer who had clinical-grade paired tumor-normal sequencing at a comprehensive cancer center, we performed team-based retrospective data collection from the electronic medical record using a defined source hierarchy. We developed an open-source R package for data processing. With blinded repeat annotation by a reference medical oncologist, we assessed data completeness, reproducibility of team-based annotations, and impact of measurement error on bias in survival analyses. RESULTS: Data elements on demographics, diagnosis and staging, disease state at the time of procuring a genomically characterized sample, and clinical outcomes were piloted and then abstracted for 2261 patients (with 2631 samples). Completeness of data elements was generally high. Comparing to the repeat annotation by a medical oncologist blinded to the database (100 patients/samples), reproducibility of annotations was high; T stage, metastasis date, and presence and date of castration resistance had lower reproducibility. Impact of measurement error on estimates for strong prognostic factors was modest. CONCLUSIONS: With a prostate cancer-specific data dictionary and quality control measures, manual clinical annotations by a multidisciplinary team can be scalable and reproducible. The data dictionary and the R package for reproducible data processing are freely available to increase data quality and efficiency in clinical prostate cancer research.

Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets.

In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR) dependence leads to clinically aggressive tumors with few therapeutic options. We used ATAC-seq (assay for transposase-accessible chromatin sequencing), RNA-seq, and DNA sequencing to investigate 22 organoids, six patient-derived xenografts, and 12 cell lines. We identified the well-characterized AR-dependent and neuroendocrine subtypes, as well as two AR-negative/low groups: a Wnt-dependent subtype, and a stem cell-like (SCL) subtype driven by activator protein-1 (AP-1) transcription factors. We used transcriptomic signatures to classify 366 patients, which showed that SCL is the second most common subtype of CRPC after AR-dependent. Our data suggest that AP-1 interacts with the YAP/TAZ and TEAD proteins to maintain subtype-specific chromatin accessibility and transcriptomic landscapes in this group. Together, this molecular classification reveals drug targets and can potentially guide therapeutic decisions.

Effects of metformin and statins on outcomes in men with castration-resistant metastatic prostate cancer: Secondary analysis of COU-AA-301 and COU-AA-302.

BACKGROUND: The associations of metformin and statins with overall survival (OS) and prostate specific antigen response rate (PSA-RR) in trials in metastatic castration-resistant prostate cancer remain unclear. OBJECTIVE: To determine whether metformin or statins ± abiraterone acetate plus prednisone/prednisolone (AAP) influence OS and PSA-RR. DESIGN, SETTING AND PARTICIPANT: COU-AA-301 and COU-AA-302 patients were stratified by metformin and statin use. Cox proportional hazards models were used to estimate hazards ratio (HR) stratified by concomitant medications, and a random effects model was used to pool HR. We compared PSA-RR using Chi χ2 test. RESULTS: In COU-AA-301-AAP, metformin was associated with improved PSA-RR (41.1% versus 28.6%) but not prolonged OS. In COU-AA-301-placebo-P, there was no association between metformin and prolonged OS or PSA-RR. In COU-AA-302-AAP, metformin was associated with prolonged OS (adjHR 0.69, 95% CI 0.48-0.98) and improved PSA-RR (72.7% versus 60.0%). In COU-AA-302-P, metformin was associated with prolonged OS (adjHR 0.66, 95% CI 0.47-0.93). In pooled analysis, OS was prolonged among those treated with metformin (pooled HR 0.77, 95% CI 0.62-0.95).In COU-AA-301-AAP, statins were associated with an improved OS (adjHR 0.76, 95% CI 0.62-0.93), while there was no difference in COU-AA-301-P. There was no association with statins and OS in either COU-AA-302 groups. When pooling HR, OS was prolonged among those treated with statins (pooled HR 0.78, 95% CI 0.68-0.88). CONCLUSION: Within the limitations of post-hoc sub-analyses, metformin and statins are associated with a prolonged OS and increased PSA-RR, particularly in combination with AAP.

Optimizing the future: how mathematical models inform treatment schedules for cancer.

For decades, mathematical models have influenced how we schedule chemotherapeutics. More recently, mathematical models have leveraged lessons from ecology, evolution, and game theory to advance predictions of optimal treatment schedules, often in a personalized medicine manner. We discuss both established and emerging therapeutic strategies that deviate from canonical standard-of-care regimens, and how mathematical models have contributed to the design of such schedules. We first examine scheduling options for single therapies and review the advantages and disadvantages of various treatment plans. We then consider the challenge of scheduling multiple therapies, and review the mathematical and clinical support for various conflicting treatment schedules. Finally, we propose how a consilience of mathematical and clinical knowledge can best determine the optimal treatment schedules for patients.

Automated Bone Scan Index to Optimize Prostate Cancer Working Group Radiographic Progression Criteria for Men With Metastatic Castration-Resistant Prostate Cancer.

INTRODUCTION: Radiographic progression-free survival (rPFS) by Prostate Cancer Working Group (PCWG) criteria is a radiographic endpoint. The automated bone scan index (aBSI) quantifies osseous disease burden on bone scintigraphy as a percentage of total skeletal weight. Using the aBSI, we sought to quantify increase in tumor burden represented by PCWG progression criteria, and to determine the interval increase that best associates with overall survival (OS). PATIENT AND METHODS: Retrospective analysis of trials using androgen receptor axis-targeted drugs for metastatic castration resistant prostate cancer patients (mCRPC). aBSI increase in bone disease was assessed from baseline scan to time-to-progression (per PCWG criteria). Threshold for time to aBSI increase were explored and the association between each time-to-threshold and OS was computed. RESULTS: A total of 169 mCPRC patients had bone scans available for aBSI analysis. Of these, 90 (53%) had progression in bone meeting PCWG criteria. Total aBSI increase in patients meeting PCWG criteria was 1.22 (interquartile range [IQR]: 0.65-2.49), with a median relative increase of 109% (IQR: 40%-377%). Median aBSI at baseline was 3.1 (IQR: 1.3-7.1). The best association between OS and time-to-progression occurred with an absolute increase in aBSI equal to 0.6 (Kendall's tau 0.52). CONCLUSION: An absolute increase of 0.6 or more in aBSI from the first follow-up scan results in the highest association with OS in patients with mCRPC. The rPFS by PCWG, identified progression at nearly twice this tumor burden, suggesting that aBSI may be used to further develop the PCWG criteria without degrading its association with OS.

Optimal Strategy and Benefit of Pulsed Therapy Depend On Tumor Heterogeneity and Aggressiveness at Time of Treatment Initiation.

Therapeutic resistance is a fundamental obstacle in cancer treatment. Tumors that initially respond to treatment may have a preexisting resistant subclone or acquire resistance during treatment, making relapse theoretically inevitable. Here, we investigate treatment strategies that may delay relapse using mathematical modeling. We find that for a single-drug therapy, pulse treatment-short, elevated doses followed by a complete break from treatment-delays relapse compared with continuous treatment with the same total dose over a length of time. For tumors treated with more than one drug, continuous combination treatment is only sometimes better than sequential treatment, while pulsed combination treatment or simply alternating between the two therapies at defined intervals delays relapse the longest. These results are independent of the fitness cost or benefit of resistance, and are robust to noise. Machine-learning analysis of simulations shows that the initial tumor response and heterogeneity at the start of treatment suffice to determine the benefit of pulsed or alternating treatment strategies over continuous treatment. Analysis of eight tumor burden trajectories of breast cancer patients treated at Memorial Sloan Kettering Cancer Center shows the model can predict time to resistance using initial responses to treatment and estimated preexisting resistant populations. The model calculated that pulse treatment would delay relapse in all eight cases. Overall, our results support that pulsed treatments optimized by mathematical models could delay therapeutic resistance.