Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring1. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

Multiregion sampling of de novo metastatic prostate cancer reveals complex polyclonality and augments clinical genotyping.

De novo metastatic prostate cancer is highly aggressive, but the paucity of routinely collected tissue has hindered genomic stratification and precision oncology. Here, we leveraged a rare study of surgical intervention in 43 de novo metastatic prostate cancers to assess somatic genotypes across 607 synchronous primary and metastatic tissue regions plus circulating tumor DNA. Intra-prostate heterogeneity was pervasive and impacted clinically relevant genes, resulting in discordant genotypes between select primary restricted regions and synchronous metastases. Additional complexity was driven by polyclonal metastatic seeding from phylogenetically related primary populations. When simulating clinical practice relying on a single tissue region, genomic heterogeneity plus variable tumor fraction across samples caused inaccurate genotyping of dominant disease; however, pooling extracted DNA from multiple biopsy cores before sequencing can rescue misassigned somatic genotypes. Our results define the relationship between synchronous treatment-sensitive primary and metastatic lesions in men with de novo metastatic prostate cancer and provide a framework for implementing genomics-guided patient management.

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer.

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes.

Specific classes of DNA damage repair (DDR) defect can drive sensitivity to emerging therapies for metastatic prostate cancer. However, biomarker approaches based on DDR gene sequencing do not accurately predict DDR deficiency or treatment benefit. Somatic alteration signatures may identify DDR deficiency but historically require whole-genome sequencing of tumour tissue. We assembled whole-exome sequencing data for 155 high ctDNA fraction plasma cell-free DNA and matched leukocyte DNA samples from patients with metastatic prostate or bladder cancer. Labels for DDR gene alterations were established using deep targeted sequencing. Per sample mutation and copy number features were used to train XGBoost ensemble models. Naive somatic features and trinucleotide signatures were associated with specific DDR gene alterations but insufficient to resolve each class. Conversely, XGBoost-derived models showed strong performance including an area under the curve of 0.99, 0.99 and 1.00 for identifying BRCA2, CDK12, and mismatch repair deficiency in metastatic prostate cancer. Our machine learning approach re-classified several samples exhibiting genomic features inconsistent with original labels, identified a metastatic bladder cancer sample with a homozygous BRCA2 copy loss, and outperformed an existing exome-based classifier for BRCA2 deficiency. We present DARC Sign (DnA Repair Classification SIGNatures); a public machine learning tool leveraging clinically-practical liquid biopsy specimens for simultaneously identifying multiple types of metastatic prostate cancer DDR deficiencies. We posit that it will be useful for understanding differential responses to DDR-directed therapies in ongoing clinical trials and may ultimately enable prospective identification of prostate cancers with phenotypic evidence of DDR deficiency.

Genomic Features of Lung-Recurrent Hormone-Sensitive Prostate Cancer.

PURPOSE: Pulmonary involvement is rare in metastatic hormone-sensitive prostate cancer (mHSPC) that recurs after treatment for localized disease. Guidelines recommend intensive systemic therapy, similar to patients with liver metastases, but some lung-recurrent mHSPC may have good outcomes. Genomic features of lung metastases may clarify disease aggression, but are poorly understood since lung biopsy is rarely performed. We present a comparative assessment of genomic drivers and heterogeneity in metachronous prostate tumors and lung metastases. METHODS: We leveraged a prospective functional imaging study of 208 biochemically recurrent prostate cancers to identify 10 patients with lung-recurrent mHSPC. Histologic diagnosis was attained via thoracic surgery or fine-needle lung biopsy. We retrieved clinical data and performed multiregion sampling of primary tumors and metastases. Targeted and/or whole-exome sequencing was applied to 46 primary and 32 metastatic foci. RESULTS: Unusually for mHSPC, all patients remained alive despite a median follow-up of 11.5 years. Several patients experienced long-term freedom from systemic treatment. The genomic landscape of lung-recurrent mHSPC was typical of curable prostate cancer with frequent PTEN, SPOP, and chromosome 8p alterations, and there were no deleterious TP53 and DNA damage repair gene mutations that characterize aggressive prostate cancer. Despite a long median time to recurrence (76.8 months), copy number alterations and clonal mutations were highly conserved between metastatic and primary foci, consistent with intrapatient homogeneity and limited genomic evolution. CONCLUSION: In this retrospective hypothesis-generating study, we observed indolent genomic etiology in selected lung-recurrent mHSPC, cautioning against grouping these patients together with liver or bone-predominant mHSPC. Although our data do not generalize to all patients with lung metastases, the results encourage prospective efforts to stratify lung-recurrent mHSPC by genomic features.

BRCA2, ATM, and CDK12 Defects Differentially Shape Prostate Tumor Driver Genomics and Clinical Aggression.

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.

Identification of Hypermutation and Defective Mismatch Repair in ctDNA from Metastatic Prostate Cancer.

PURPOSE: DNA mismatch repair defects (MMRd) and tumor hypermutation are rare and under-characterized in metastatic prostate cancer (mPC). Furthermore, because hypermutated MMRd prostate cancers can respond to immune checkpoint inhibitors, there is an urgent need for practical detection tools. EXPERIMENTAL DESIGN: We analyzed plasma cell-free DNA-targeted sequencing data from 433 patients with mPC with circulating tumor DNA (ctDNA) purity ≥2%. Samples with somatic hypermutation were subjected to 185 × whole-exome sequencing and capture of mismatch repair gene introns. Archival tissue was analyzed with targeted sequencing and IHC. RESULTS: Sixteen patients (3.7%) had somatic hypermutation with MMRd etiology, evidenced by deleterious alterations in MSH2, MSH6, or MLH1, microsatellite instability, and characteristic trinucleotide signatures. ctDNA was concordant with mismatch repair protein IHC and DNA sequencing of tumor tissue. Tumor suppressors such as PTEN, RB1, and TP53 were inactivated by mutation rather than copy-number loss. Hotspot mutations in oncogenes such as AKT1, PIK3CA, and CTNNB1 were common, and the androgen receptor (AR)-ligand binding domain was mutated in 9 of 16 patients. We observed high intrapatient clonal diversity, evidenced by subclonal driver mutations and shifts in mutation allele frequency over time. Patients with hypermutation and MMRd etiology in ctDNA had a poor response to AR inhibition and inferior survival compared with a control cohort. CONCLUSIONS: Hypermutated MMRd mPC is associated with oncogene activation and subclonal diversity, which may contribute to a clinically aggressive disposition in selected patients. In patients with detectable ctDNA, cell-free DNA sequencing is a practical tool to prioritize this subtype for immunotherapy.See related commentary by Schweizer and Yu, p. 981.

Activating AKT1 and PIK3CA Mutations in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: Activating mutations in AKT1 and PIK3CA are undercharacterised in metastatic castration-resistant prostate cancer (mCRPC), but are linked to activation of phosphatidylinositol 3-kinase (PI3K) signalling and sensitivity to pathway inhibitors in other cancers. OBJECTIVE: To determine the prevalence, genomic context, and clinical associations of AKT1/PIK3CA activating mutations in mCRPC. DESIGN, SETTING, AND PARTICIPANTS: We analysed targeted cell-free DNA (cfDNA) sequencing data from 599 metastatic prostate cancer patients with circulating tumour DNA (ctDNA) content above 2%. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: In patients with AKT1/PIK3CA mutations, cfDNA was subjected to PTEN intron sequencing and matched diagnostic tumour tissue was analysed when possible. RESULTS AND LIMITATIONS: Of the patients, 6.0% (36/599) harboured somatic clonal activating mutation(s) in AKT1 or PIK3CA. Mutant allele-specific imbalance was common. Clonal mutations in mCRPC ctDNA were typically detected in pretreatment primary tissue and were consistent across serial ctDNA collections. AKT1/PIK3CA-mutant mCRPC had fewer androgen receptor (AR) gene copies than AKT1/PIK3CA wild-type mCRPC (median 4.7 vs 10.3, p = 0.003). AKT1 mutations were mutually exclusive with PTEN alterations. Patients with and without AKT1/PIK3CA mutations showed similar clinical outcomes with standard of care treatments. A heavily pretreated mCRPC patient with an AKT1 mutation experienced a 50% decline in prostate-specific antigen with Akt inhibitor (ipatasertib) monotherapy. Ipatasertib also had a marked antitumour effect in a patient-derived xenograft harbouring an AKT1 mutation. Limitations include the inability to assess AKT1/PIK3CA correlatives in ctDNA-negative patients. CONCLUSIONS: AKT1/PIK3CA activating mutations are relatively common and delineate a distinct mCRPC molecular subtype with low-level AR copy gain. Clonal prevalence and evidence of mutant allele selection propose PI3K pathway dependency in selected patients. The use of cfDNA screening enables prospective clinical trials to test PI3K pathway inhibitors in this population. PATIENT SUMMARY: Of advanced prostate cancer cases, 6% have activating mutations in the genes AKT1 or PIK3CA. These mutations can be identified using a blood test and may help select patients suitable for clinical trials of phosphatidylinositol 3-kinase inhibitors.