Genomic Heterogeneity Within Individual Prostate Cancer Foci Impacts Predictive Biomarkers of Targeted Therapy

Advancing Prostate Cancer Care: Treatment Approaches to Precision Medicine, Biomarker Innovations, and Equitable Access

Genetic testing and molecular imaging have great promise in the accurate diagnosis and treatment of #prostate #cancer, but only if they can be developed and implemented to achieve equitable benefit for all men.

Prostate cancer: Molecular aspects, consequences, and opportunities of the multifocal nature

Prostate cancer is unique compared to other major cancers due to the presence of multiple primary malignant foci in the majority of patients at the time of diagnosis. Each malignant focus has distinct somatic mutations and gene expression patterns, which represents a challenge for the development of prognostic tests for localized prostate cancer. Additionally, the molecular heterogeneity of advanced prostate cancer has important implications for management, particularly for patients with metastatic and locally recurrent cancer. Studies have shown that prostate cancers with mutations in DNA damage response genes are more sensitive to drugs inhibiting the poly ADP-ribose polymerase (PARP) enzyme. However, testing for such mutations should consider both spatial and temporal heterogeneity. Here, we summarize studies where multiregional genomics and transcriptomics analyses have been performed for primary prostate cancer. We further discuss the vast interfocal heterogeneity and how prognostic biomarkers and a molecular definition of the index tumor should be developed. The concept of focal treatments in prostate cancer has been evolving as a demand from patients and clinicians and is one example where there is a need for defining an index tumor. Here, biomarkers must have proven value for individual malignant foci. The potential discovery and implementation of biomarkers that are agnostic to heterogeneity are also explored as an alternative to multisample testing. Thus, deciding upon whole-organ treatment, such as radical prostatectomy, should depend on information from biomarkers which are informative for the whole organ.

Optimizing anti-androgen treatment use among men with pathologic lymph-node positive prostate cancer treated with radical prostatectomy: the importance of postoperative PSA kinetics

BACKGROUND

Optimal postsurgical management of prostate cancer (PCa) patients with nodal metastasis at the time of radical prostatectomy remains unclear. We sought to examine the role of postoperative PSA kinetics and pathologic tumor characteristics in guiding additional hormonal therapy use in pN1 men.

METHODS

In total, 297 pN1 PCa patients treated with radical prostatectomy and ePLND between 2002 and 2018 were identified within our prospectively maintained institutional cancer data-registry. Following surgery, these patients were managed with either immediate androgen deprivation therapy (iADT) or observation with deferred ADT (dADT). The former was defined as ADT given within ≤6 months of surgery and the latter as >6 months. The primary outcome was metastasis. Regression-tree analysis was used to stratify patients into novel risk-groups based on post-prostatectomy tumor characteristics and PSA kinetics and the corresponding metastasis risk. Multivariable Cox regression analyses tested the impact of iADT versus observation ± dADT on metastasis, cancer-specific mortality, and overall mortality within each risk-group separately.

RESULTS

The median follow-up was 6.1 years (IQR 3.2-9.0). Regression-tree analysis stratified patients into 3 novel risk-groups (Harrell's C-index 0.79) based on PSA-nadir and time to biochemical failure: group 1 (low-risk) included patients with time to biochemical recurrence >6 months (n = 115), while groups 2 and 3 included patients with biochemical failure within ≤6 months with a postoperative PSA-nadir <1.05 ng/mL (group 2 [intermediate-risk], n = 125) or ≥1.05 ng/mL (group 3 [high-risk], n = 57), respectively. No other patient or tumor characteristics were significant for risk stratification. Within each risk-group, the 10-year metastasis-free survival rates with iADT versus observation ± dADT use were: group 1, 100% versus 95.4% (Log-rank p = 0.738), group 2, 80.6% versus 53.5% (Log-rank p = 0.016), and group 3, 41.5% versus 0% (Log-rank p = 0.015), respectively. Adjusted Cox regression analyses confirmed the benefit of iADT utilization in reducing metastasis in group 2 (p = 0.029) and group 3 (p = 0.008) patients, with no benefit for group 1 patients (p = 0.918). Similar results were noted for cancer-specific and overall mortality.

CONCLUSIONS

Following radical prostatectomy, early postoperative PSA kinetics may provide valuable information for guiding the timing of ADT initiation-this may reduce over- and undertreatment of pN1 PCa men.

Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine

BACKGROUND

Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question.

METHODS

We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

RESULTS

In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases.

CONCLUSIONS

PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Standard deviation of CT radiomic features among malignancies in each individual: prognostic ability in lung cancer patients

PURPOSE

It was reported that individual heterogeneity among malignancies (IHAM) might correlate well to the prognosis of lung cancer; however, seldom radiomic study is on this field. Standard deviation (SD) in statistics could scale average amount of variability of a variable; therefore, we used SD of CT feature (FeatureSD) among primary tumor and malignant lymph nodes (LNs) in an individual to represent IHAM, and its prognostic ability was explored.

METHODS

The enrolled patients who had accepted PET/CT scans were selected from our previous study (ClinicalTrials.gov, NCT03648151). The patients had primary tumor and at least one LN, and standardized uptake value of LN higher than 2.0 and 2.5 were enrolled as the cohort 1 (n = 94) and 2 (n = 88), respectively. FeatureSD from the combined or thin-section CT were calculated among primary tumor and malignant LNs in each patient, and were separately selected by the survival XGBoost method. Finally, their prognostic ability was compared to the significant patient characteristics identified by the Cox regression.

RESULTS

In the univariate and multi-variate Cox analysis, surgery, target therapy, and TNM stage were significantly against OS in the both cohorts. In the survival XGBoost analysis of the thin-section CT dataset, none FeatureSD could be repeatably ranked on the top list of the both cohorts. For the combined CT dataset, only one FeatureSD ranked in the top three of both cohorts, but the three significant factors in the Cox regression were not even on the list. Both in the cohort 1 and 2, C-index of the model composed of the three factors could be improved by integrating the continuous FeatureSD; furthermore, that of each factor was obviously lower than FeatureSD.

CONCLUSION

Standard deviation of CT features among malignant foci within an individual was a powerful prognostic factor in vivo for lung cancer patients.

Prognostic Role of DNA Damage Response Genes Mutations and their Association With the Sensitivity of Olaparib in Prostate Cancer Patients

Objective

Evidence shows that gene mutation is a significant proportion of genetic factors associated with prostate cancer. The DNA damage response (DDR) is a signal cascade network that aims to maintain genomic integrity in cells. This comprehensive study was performed to determine the link between different DNA damage response gene mutations and prostate cancer.

Materials and methods

A systematic literature search was performed using PubMed, Web of Science, and Embase. Papers published up to February 1, 2022 were retrieved. The DDR gene mutations associated with prostate cancer were identified by referring to relevant research and review articles. Data of prostate cancer patients from multiple PCa cohorts were obtained from cBioPortal. The OR or HR and 95% CIs were calculated using both fixed-effects models (FEMs) and random-effects models (REMs).

Results

Seventy-four studies were included in this research, and the frequency of 13 DDR genes was examined. Through the analysis of 33 articles that focused on the risk estimates of DDR genes between normal people and PCa patients, DDR genes were found to be more common in prostate cancer patients (OR = 3.6293 95% CI [2.4992; 5.2705]). Also, patients in the mutated group had a worse OS and DFS outcome than those in the unmutated group (P < .05). Of the 13 DDR genes, the frequency of 9 DDR genes in prostate cancer was less than 1%, and despite differences in race, BRCA2 was the potential gene with the highest frequency (REM Frequency = .0400, 95% CI .0324 - .0541). The findings suggest that mutations in genes such as ATR, BLM, and MLH1 in PCa patients may increase the sensitivity of Olaparib, a PARP inhibitor.

Conclusion

These results demonstrate that mutation in any DDR pathway results in a poor prognosis for PCa patients. Furthermore, mutations in ATR, BLM, and MLH1 or the expression of POLR2L, PMS1, FANCE, and other genes significantly influence Olaparib sensitivity, which may be underlying therapeutic targets in the future.

Copy number variations: A novel molecular marker for papillary thyroid cancer

Background

We aimed to screen tumor-associated functional genes on a large scale through copy number variation (CNV) analysis of papillary thyroid cancer (PTC).

Methods

We analyzed 74 tissue samples from 41 patients with thyroid nodules. The samples were subjected to whole-genome resequencing and then analyzed by the ‘WISECONDOR’ method. Potential chromosome CNV regions were identified between the different sample groups.

Results

Of the 74 samples from 41 patients, 28 were PTC tissue samples, 29 were para-carcinoma tissue samples, 13 were benign tumor tissue samples and 4 were para-benign tumor tissue samples. According to our findings, PTC can be identified by CNVs at the corresponding positions on chromosomes 5, 7, 8, 10, and 17. For carcinoma tissue, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and area under the curve (AUC) of the test method were 100%, 66.7%, 87.5%, 100.0%, 90.0% and 0.83 (95% confidence interval [CI], 0.67–1.00) and for para-carcinoma tissue, these values were 96.6%, 75.0%, 96.6%, 75.0%, 93.9% and 0.86 (95% CI, 0.60–1.00).

Conclusion

CNV analysis assays involving high-volume sequencing analysis can increase the identification of PTC, potentially avoiding errors caused by position deflection in sampling.

1.

Thyroid nodules can be identified by CNVs at the corresponding positions on chromosomes 5, 7, 8, 10, and 17.

2.

The identification rate of PTC can be greatly increased through high-volume CNV sequencing analysis.

Androgen receptor mutations for precision medicine in prostate cancer

Hormonal therapies including androgen deprivation therapy and androgen receptor (AR) pathway inhibitors such as abiraterone and enzalutamide have been widely used to treat advanced prostate cancer. However, treatment resistance emerges after hormonal manipulation in most prostate cancers, and it is attributable to a number of mechanisms, including AR amplification and overexpression, AR mutations, the expression of constitutively active AR variants, intra-tumor androgen synthesis, and promiscuous AR activation by other factors. Although various AR mutations have been reported in prostate cancer, specific AR mutations (L702H, W742L/C, H875Y, F877L, and T878A/S) were frequently identified after treatment resistance emerged. Intriguingly, these hot spot mutations were also revealed to change the binding affinity of ligands including steroids and antiandrogens and potentially result in altered responses to AR pathway inhibitors. Currently, precision medicine utilizing genetic and genomic data to choose suitable treatment for the patient is becoming to play an increasingly important role in clinical practice for prostate cancer management. Since clinical data between AR mutations and the efficacy of AR pathway inhibitors are accumulating, monitoring the AR mutation status is a promising approach for providing precision medicine in prostate cancer, which would be implemented through the development of clinically available testing modalities for AR mutations using liquid biopsy. However, there are few reviews on clinical significance of AR hot spot mutations in prostate cancer. Then, this review summarized the clinical landscape of AR mutations and discussed their potential implication for clinical utilization.

A Novel Artificial Intelligence-Powered Method for Prediction of Early Recurrence of Prostate Cancer After Prostatectomy and Cancer Drivers

PURPOSE

To develop a novel artificial intelligence (AI)-powered method for the prediction of prostate cancer (PCa) early recurrence and identification of driver regions in PCa of all Gleason Grade Group (GGG).

MATERIALS AND METHODS

Deep convolutional neural networks were used to develop the AI model. The AI model was trained on The Cancer Genome Atlas Prostatic Adenocarcinoma (TCGA-PRAD) whole slide images (WSI) and data set (n = 243) to predict 3-year biochemical recurrence after radical prostatectomy (RP) and was subsequently validated on WSI from patients with PCa (n = 173) from the University of Wisconsin-Madison.

RESULTS

Our AI-powered platform can extract visual and subvisual morphologic features from WSI to identify driver regions predictive of early recurrence of PCa (regions of interest [ROIs]) after RP. The ROIs were ranked with AI-morphometric scores, which were prognostic for 3-year biochemical recurrence (area under the curve [AUC], 0.78), which is significantly better than the GGG overall (AUC, 0.62). The AI-morphometric scores also showed high accuracy in the prediction of recurrence for low- or intermediate-risk PCa-AUC, 0.76, 0.84, and 0.81 for GGG1, GGG2, and GGG3, respectively. These patients could benefit the most from timely adjuvant therapy after RP. The predictive value of the high-scored ROIs was validated by known PCa biomarkers studied. With this focused biomarker analysis, a potentially new STING pathway-related PCa biomarker-TMEM173-was identified.

CONCLUSION

Our study introduces a novel approach for identifying patients with PCa at risk for early recurrence regardless of their GGG status and for identifying cancer drivers for focused evolution-aware novel biomarker discovery.

Genomic and phenotypic heterogeneity in prostate cancer

From a clinical, morphological and molecular perspective, prostate cancer is a heterogeneous disease. Primary prostate cancers are often multifocal, having topographically and morphologically distinct tumour foci. Sequencing studies have revealed that individual tumour foci can arise as clonally distinct lesions with no shared driver gene alterations. This finding demonstrates that multiple genomically and phenotypically distinct primary prostate cancers can be present in an individual patient. Lethal metastatic prostate cancer seems to arise from a single clone in the primary tumour but can exhibit subclonal heterogeneity at the genomic, epigenetic and phenotypic levels. Collectively, this complex heterogeneous constellation of molecular alterations poses obstacles for the diagnosis and treatment of prostate cancer. However, advances in our understanding of intra-tumoural heterogeneity and the development of novel technologies will allow us to navigate these challenges, refine approaches for translational research and ultimately improve patient care.

Tumor ablation due to inhomogeneous anisotropic diffusion in generic three-dimensional topologies

In recent decades computer-aided technologies have become prevalent in medicine, however, cancer drugs are often only tested on in vitro cell lines from biopsies. We derive a full three-dimensional model of inhomogeneous -anisotropic diffusion in a tumor region coupled to a binary population model, which simulates in vivo scenarios faster than traditional cell-line tests. The diffusion tensors are acquired using diffusion tensor magnetic resonance imaging from a patient diagnosed with glioblastoma multiform. Then we numerically simulate the full model with finite element methods and produce drug concentration heat maps, apoptosis hotspots, and dose-response curves. Finally, predictions are made about optimal injection locations and volumes, which are presented in a form that can be employed by doctors and oncologists.

Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer

Localized prostate tumors show remarkably diverse clinical courses, with some being cured by local therapy alone, while others rapidly relapse and have a lethal course despite precision surgery or radiotherapy. Many genomic biomarkers have been developed to predict this clinical behavior, but these are confounded by the extreme spatial heterogeneity of prostate tumors: most are multifocal and harbor multiple subclonal populations. To quantify the influence of spatial heterogeneity on genomic prognostic biomarkers, we developed a case-control high-risk cohort (n = 42) using a prospective registry, risk matched by clinicopathologic prognostic indices. Half of the cohort had early biochemical recurrence (BCR; ie, ≤18 mo), while half remained without evidence of disease for at least 48 mo after radical prostatectomy. We then genomically profiled multiple tumor foci per patient, analyzing 119 total specimens. These data allowed us to validate three published genomic prognostic biomarkers and quantify their sensitivity to tumor spatial heterogeneity. Remarkably, all three biomarkers robustly predicted early BCR, and all three were robust to spatiogenomic variability. These data suggest that DNA-based genomic biomarkers can overcome intratumoral heterogeneity: single biopsies may be sufficient to estimate the risk of early BCR after radical treatment in patients with high-risk disease. PATIENT SUMMARY: We investigated whether heterogeneity between tumor regions within the prostate affects the accuracy of DNA-based biomarkers predicting early relapse after prostatectomy. We observed persistent accuracy in predicting disease relapse, suggesting that spatial heterogeneity may not hinder biomarker performance.

Intratumoral heterogeneity and genetic characteristics of prostate cancer

Prostate cancer is a heterogeneous disease and optimum gene targeting treatment is often impermissible. We aim to determine the intratumoral genomic heterogeneity of prostate cancer and explore candidate genes for targeted therapy. Exome sequencing was performed on 37 samples from 16 patients with prostate cancer. Somatic variant analysis, copy number variant (CNV) analysis, clonal evolution analysis and variant spectrum analysis were used to study the intratumoral genomic heterogeneity and genetic characteristics of metastatic prostate cancer. Our study confirmed the high intratumoral genetic heterogeneity of prostate cancer in many aspects, including number of shared variants, tumor mutation burden (TMB), variant genes, CNV burden, weighted genome instability index (wGII), CNV profiles, clonal evolutionary process, variant spectrum and mutational signatures. Moreover, we identified several common genetic characteristics of prostate cancer. Alterations of DNA damage repair genes, RTK/RAS pathway associated gene RASGRF1 and autophagy gene EPG5 may be involved in tumorigenesis in prostate cancer. CNV burden and DNA damage repair (DDR) genes may be associated with metastasis of prostate cancer.

Cellular and Molecular Mechanisms Underlying Prostate Cancer Development: Therapeutic Implications

Prostate cancer is the most frequent nonskin cancer and second most common cause of cancer-related deaths in man. Prostate cancer is a clinically heterogeneous disease with many patients exhibiting an aggressive disease with progression, metastasis, and other patients showing an indolent disease with low tendency to progression. Three stages of development of human prostate tumors have been identified: intraepithelial neoplasia, adenocarcinoma androgen-dependent, and adenocarcinoma androgen-independent or castration-resistant. Advances in molecular technologies have provided a very rapid progress in our understanding of the genomic events responsible for the initial development and progression of prostate cancer. These studies have shown that prostate cancer genome displays a relatively low mutation rate compared with other cancers and few chromosomal loss or gains. The ensemble of these molecular studies has led to suggest the existence of two main molecular groups of prostate cancers: one characterized by the presence of ERG rearrangements (~50% of prostate cancers harbor recurrent gene fusions involving ETS transcription factors, fusing the 5' untranslated region of the androgen-regulated gene TMPRSS2 to nearly the coding sequence of the ETS family transcription factor ERG) and features of chemoplexy (complex gene rearrangements developing from a coordinated and simultaneous molecular event), and a second one characterized by the absence of ERG rearrangements and by the frequent mutations in the E3 ubiquitin ligase adapter SPOP and/or deletion of CDH1, a chromatin remodeling factor, and interchromosomal rearrangements and SPOP mutations are early events during prostate cancer development. During disease progression, genomic and epigenomic abnormalities accrued and converged on prostate cancer pathways, leading to a highly heterogeneous transcriptomic landscape, characterized by a hyperactive androgen receptor signaling axis.

Spatial distribution of biopsy cores and the detection of intra-lesion pathologic heterogeneity

Objectives:

The objective of this study was to determine if spatial distribution of multiparametric magnetic resonance imaging–transrectal ultrasound (mpMRI-TRUS) fusion biopsy cores to the index lesion reveals trends in the detection of intra-lesion Gleason heterogeneity and a more optimal prostate biopsy strategy.

Methods:

Index lesion was the lesion with longest diameter on T2-weighted (T2W)-MRI. In cohort 1, fusion biopsy cores biopsies were taken in areas in the center of the target as well as 1 cm laterally on each side. For cohort 2, targeted biopsies were taken from the center of the lesion only. Heterogeneity was defined as difference in maximum Gleason score obtained from fusion cores in the center of the index lesion versus cores obtained from the periphery (cohort 1), or any difference in maximum Gleason score obtained from fusion cores targeted to the index lesion (cohort 2) compared with systematic 12 cores TRUS biopsy.

Results:

Ninety-nine consecutive patients (35 and 64 in cohorts 1 and 2, respectively) with median age (SD) and prostate-specific antigen (PSA) of 66.9 (±5.9) and 9.7 (±8.2) respectively, were included. Age, PSA, Prostate Imaging Reporting and Data System (PI-RADS) score, and preoperative MRI lesion size were not significantly different between cohorts. Gleason heterogeneity was observed at a significantly higher rate in cohort 1 versus cohort 2 (58% versus 24%; p = 0.041). In cohort 1, cores obtained from the center of the lesion had higher Gleason score than cores obtained from the periphery of the targeted lesion in 57% of cases.

Conclusions:

We demonstrate that there is observable tumor heterogeneity in biopsy specimens, and that increased number of cores, as well as cores focused on the center and periphery of the largest lesion in the prostate, provide more comprehensive diagnostic information about the patient’s clinical risk category than taking nonspecific cores targeted within the tumor.

Genomic Evaluation of Multiparametric Magnetic Resonance Imaging-visible and -nonvisible Lesions in Clinically Localised Prostate Cancer

BACKGROUND

The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification.

OBJECTIVE

To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease.

DESIGN, SETTING, AND PARTICIPANTS

Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa.

INTERVENTION

Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients.

OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS

Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication.

RESULTS AND LIMITATIONS

A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up.

CONCLUSIONS

Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied.

PATIENT SUMMARY

Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed.

Tumor cell heterogeneity and resistance; report from the 2018 Coffey-Holden Prostate Cancer Academy Meeting

INTRODUCTION

The 2018 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, "Tumor Cell Heterogeneity and Resistance," was held in Los Angeles, California from June 21 to 24, 2018.

METHODS

The CHPCA Meeting is a unique, discussion-oriented scientific conference convened annually by the Prostate Cancer Foundation (PCF), which focuses on the most critical topics in need of further study to advance the treatment of lethal prostate cancer. The 6th Annual CHPCA Meeting was attended by 70 investigators and concentrated on prostate cancer heterogeneity and treatment resistance.

RESULTS

The meeting focused on topics including: recognition of tumor heterogeneity, molecular drivers of heterogeneity, the role of the tumor microenvironment, the role of heterogeneity in disease progression, metastasis and treatment resistance, clinical trials designed to target resistance and tumor heterogeneity, and immunotherapeutic approaches to target and overcome tumor heterogeneity.

DISCUSSION

This review article summarizes the presentations and discussions from the 2018 CHPCA Meeting in order to share this knowledge with the scientific community and encourage new studies that will lead to improved treatments and outcomes for men with prostate cancer.

Activity of durvalumab plus olaparib in metastatic castration-resistant prostate cancer in men with and without DNA damage repair mutations

Background

Checkpoint inhibitors have not been effective for prostate cancer as single agents. Durvalumab is a human IgG1-K monoclonal antibody that targets programmed death ligand 1 and is approved by the U.S. Food and Drug Administration for locally advanced or metastatic urothelial cancer and locally advanced, unresectable stage 3 non-small cell lung cancer. Olaparib, a poly (ADP-ribose) polymerase inhibitor, has demonstrated an improvement in median progression-free survival (PFS) in select patients with metastatic castration-resistant prostate cancer (mCRPC). Data from other trials suggest there may be improved activity in men with DNA damage repair (DDR) mutations treated with checkpoint inhibitors. This trial evaluated durvalumab and olaparib in patients with mCRPC with and without somatic or germline DDR mutations.

Methods

Eligible patients had received prior enzalutamide and/or abiraterone. Patients received durvalumab 1500 mg i.v. every 28 days and olaparib 300 mg tablets p.o. every 12 h until disease progression or unacceptable toxicity. All patients had biopsies of metastatic lesions with an evaluation for both germline and somatic mutations.

Results

Seventeen patients received durvalumab and olaparib. Nausea was the only nonhematologic grade 3 or 4 toxicity occurring in > 1 patient (2/17). No patients were taken off trial for toxicity. Median radiographic progression-free survival (rPFS) for all patients is 16.1 months (95% CI: 4.5–16.1 months) with a 12-month rPFS of 51.5% (95% CI: 25.7–72.3%). Activity is seen in patients with alterations in DDR genes, with a median rPFS of 16.1 months (95% CI: 7.8–18.1 months). Nine of 17 (53%) patients had a radiographic and/or PSA response. Patients with fewer peripheral myeloid-derived suppressor cells and with alterations in DDR genes were more likely to respond. Early changes in circulating tumor cell counts and in both innate and adaptive immune characteristics were associated with response.

Conclusions

Durvalumab plus olaparib has acceptable toxicity, and the combination demonstrates efficacy, particularly in men with DDR abnormalities.

Trial registration

ClinicalTrials.gov identifier: NCT02484404.

Electronic supplementary material

The online version of this article (10.1186/s40425-018-0463-2) contains supplementary material, which is available to authorized users.