Molecular stratification can improve the management of advanced cancers, but requires relevant tumor samples. Metastatic urothelial carcinoma (mUC) is poised to benefit given a recent expansion of treatment options and its high genomic heterogeneity. We profile minimally-invasive plasma circulating tumor DNA (ctDNA) samples from 104 mUC patients, and compare to same-patient tumor tissue obtained during invasive surgery. Patient ctDNA abundance is independently prognostic for overall survival in patients initiating first-line systemic therapy. Importantly, ctDNA analysis reproduces the somatic driver genome as described from tissue-based cohorts. Furthermore, mutation concordance between ctDNA and matched tumor tissue is 83.4%, enabling benchmarking of proposed clinical biomarkers. While 90% of mutations are identified across serial ctDNA samples, concordance for serial tumor tissue is significantly lower. Overall, our exploratory analysis demonstrates that genomic profiling of ctDNA in mUC is reliable and practical, and mitigates against disease undersampling inherent to studying archival primary tumor foci. We urge the incorporation of cell-free DNA profiling into molecularly-guided clinical trials for mUC.
Purpose: Cross-resistance renders multiple lines of androgen receptor (AR) signaling inhibitors increasingly futile in metastatic castration-resistant prostate cancer (mCRPC). We sought to determine acquired genomic contributors to cross-resistance.Experimental Design: We collected 458 serial plasma cell-free DNA samples at baseline and progression timepoints from 202 patients with mCRPC receiving sequential AR signaling inhibitors (abiraterone and enzalutamide) in a randomized phase II clinical trial (NCT02125357). We utilized deep targeted and whole-exome sequencing to compare baseline and posttreatment somatic genomic profiles in circulating tumor DNA (ctDNA).Results: Patient ctDNA abundance was correlated across plasma collections and independently prognostic for sequential therapy response and overall survival. Most driver alterations in established prostate cancer genes were consistently detected in ctDNA over time. However, shifts in somatic populations after treatment were identified in 53% of patients, particularly after strong treatment responses. Treatment-associated changes converged upon the AR gene, with an average 50% increase in AR copy number, changes in AR mutation frequencies, and a 2.5-fold increase in the proportion of patients carrying AR ligand binding domain truncating rearrangements.Conclusions: Our data show that the dominant AR genotype continues to evolve during sequential lines of AR inhibition and drives acquired resistance in patients with mCRPC.
Purpose: DNA damage repair (DDR) defects are common across cancer types and can indicate therapeutic vulnerability. Optimal exploitation of DDR defects in prostate cancer requires new diagnostic strategies and a better understanding of associated clinical genomic features. Experimental Design: We performed targeted sequencing of 1,615 plasma cell-free DNA samples from 879 patients with metastatic prostate cancer. Depth-based copy-number calls and heterozygous SNP imbalance were leveraged to expose DDR-mutant allelic configuration and categorize mechanisms of biallelic loss. We used split-read structural variation analysis to characterize tumor suppressor rearrangements. Patient-matched archival primary tissue was analyzed identically. Results: BRCA2, ATM, and CDK12 were the most frequently disrupted DDR genes in circulating tumor DNA (ctDNA), collectively mutated in 15% of evaluable cases. Biallelic gene disruption via second somatic alteration or mutant allele–specific imbalance was identified in 79% of patients. A further 2% exhibited homozygous BRCA2 deletions. Tumor suppressors TP53, RB1, and PTEN were controlled via disruptive chromosomal rearrangements in BRCA2-defective samples, but via oncogene amplification in context of CDK12 defects. TP53 mutations were rare in cases with ATM defects. DDR mutations were re-detected across 94% of serial ctDNA samples and in all available archival primary tissues, indicating they arose prior to metastatic progression. Loss of BRCA2 and CDK12, but not ATM, was associated with poor clinical outcomes. Conclusions: BRCA2, ATM, and CDK12 defects are each linked to distinct prostate cancer driver genomics and aggression. The consistency of DDR status in longitudinal samples and resolution of allelic status underscores the potential for ctDNA as a diagnostic tool.
Cell phenotype underlies prostate cancer presentation and treatment resistance and can be regulated by epigenomic features. However, the osteotropic tendency of prostate cancer limits access to metastatic tissue, meaning most prior insights into prostate cancer chromatin biology are from preclinical models that do not fully represent disease complexity. Noninvasive chromatin immunoprecipitation of histones in plasma cell–free DNA (cfDNA) in humans may enable the capture of disparate prostate cancer phenotypes. In this study, we analyzed activating promoter- and enhancer-associated H3K4me2 from cfDNA in metastatic prostate cancer enriched for divergent patterns of metastasis and diverse clinical presentation. H3K4me2 density across prostate cancer genes, accessible chromatin, and lineage-defining transcription factor–binding sites correlated strongly with ctDNA fraction—demonstrating capture of prostate cancer–specific biology and informing the development of a statistical framework to adjust for ctDNA fraction. Chromatin hallmarks mirrored synchronously measured clinicogenomic features: bone- versus liver-predominant disease, serum PSA, biopsy-confirmed histopathologic subtype, and RB1 deletions convergently indicated phenotype segregation along an axis of differential androgen receptor activity and neuroendocrine identity. Detection of lineage switching after sequential progression on systemic therapy in select patients indicates potential use for individualized resistance monitoring. Epigenomic footprints of metastasis-induced normal tissue destruction were evident in bulk cfDNA from two patients. Finally, a public epigenomic resource was generated using a distinct chromatin marker that has not been widely investigated in prostate cancer. These results provide insights into the adaptive molecular landscape of aggressive prostate cancer and endorse plasma cfDNA chromatin profiling as a biomarker source and biological discovery tool. Significance: Plasma cell–free chromatin immunoprecipitation sequencing enables phenotypic dissection of lethal prostate cancer and is a practical tool for biomarker discovery while overcoming prior limitations of access to relevant tissue and reliance on model systems.
Clinical genomic testing of patient germline, tumor tissue, or plasma cell-free DNA can enable a personalized approach to cancer management and treatment. In prostate cancer (PCa), broad genotyping tests are now widely used to identify germline and/or somatic alterations in BRCA2 and other DNA damage repair genes. Alterations in these genes can confer cancer sensitivity to poly (ADP-ribose) polymerase inhibitors, are linked with poor prognosis, and can have potential hereditary cancer implications for family members. However, there is huge variability in genomic tests and reporting standards, meaning that for successful implementation of testing in clinical practice, end users must carefully select the most appropriate test for a given patient and critically interpret the results. In this white paper, we outline key pre- and post-test considerations for choosing a genomic test and evaluating reported variants, specifically for patients with advanced PCa. Test choice must be based on clinical context and disease state, availability and suitability of tumor tissue, and the genes and regions that are covered by the test. We describe strategies to recognize false positives or negatives in test results, including frameworks to assess low tumor fraction, subclonal alterations, clonal hematopoiesis, and pathogenic versus nonpathogenic variants. We assume that improved understanding among health care professionals and researchers of the nuances associated with genomic testing will ultimately lead to optimal patient care and clinical decision making.