Whole-genome mapping of APOBEC mutagenesis in metastatic urothelial carcinoma identifies driver hotspot mutations and a novel mutational signature

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) enzymes mutate specific DNA sequences and hairpin-loop structures, challenging the distinction between passenger and driver hotspot mutations. Here, we characterized 115 whole genomes of metastatic urothelial carcinoma (mUC) to identify APOBEC mutagenic hotspot drivers. APOBEC-associated mutations were detected in 92% of mUCs and were equally distributed across the genome, while APOBEC hotspot mutations (ApoHMs) were enriched in open chromatin. Hairpin loops were frequent targets of didymi (twins in Greek), two hotspot mutations characterized by the APOBEC SBS2 signature, in conjunction with an uncharacterized mutational context (Ap[C&gt;T]). Next, we developed a statistical framework that identified ApoHMs as drivers in coding and non-coding genomic regions of mUCs. Our results and statistical framework were validated in independent cohorts of 23 non-metastatic UCs and 3,744 samples of 17 metastatic cancers, identifying cancer-type-specific drivers. Our study highlights the role of APOBEC in cancer development and may contribute to developing novel targeted therapy options for APOBEC-driven cancers.</p

Whole-genome mapping of APOBEC mutagenesis in metastatic urothelial carcinoma identifies driver hotspot mutations and a novel mutational signature

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) enzymes mutate specific DNA sequences and hairpin-loop structures, challenging the distinction between passenger and driver hotspot mutations. Here, we characterized 115 whole genomes of metastatic urothelial carcinoma (mUC) to identify APOBEC mutagenic hotspot drivers. APOBEC-associated mutations were detected in 92% of mUCs and were equally distributed across the genome, while APOBEC hotspot mutations (ApoHMs) were enriched in open chromatin. Hairpin loops were frequent targets of didymi (twins in Greek), two hotspot mutations characterized by the APOBEC SBS2 signature, in conjunction with an uncharacterized mutational context (Ap[C&gt;T]). Next, we developed a statistical framework that identified ApoHMs as drivers in coding and non-coding genomic regions of mUCs. Our results and statistical framework were validated in independent cohorts of 23 non-metastatic UCs and 3,744 samples of 17 metastatic cancers, identifying cancer-type-specific drivers. Our study highlights the role of APOBEC in cancer development and may contribute to developing novel targeted therapy options for APOBEC-driven cancers.</p

Influence of enzalutamide on cabazitaxel pharmacokinetics: A Drug–Drug interaction study in metastatic castration-resistant prostate cancer (mCRPC) patients

Purpose: In ongoing clinical research on metastatic castration-resistant prostate cancer (mCRPC) treatment, the potential enhanced efficacy of the combination of taxanes with AR-targeted agents, that is, enzalutamide and abiraterone, is currently being explored. Because enzalutamide induces the CYP3A4 enzyme and taxanes are metabolized by this enzyme, a potential drug–drug interaction needs to be investigated. Experimental Design: Therefore, we performed a pharmacokinetic cross-over study in mCRPC patients who were scheduled for treatment with cabazitaxel Q3W (25 mg/m2). Patients were studied for three consecutive cabazitaxel cycles. Enzalutamide (160 mg once daily) was administered concomitantly after the first cabazitaxel cycle, during 6 weeks. Primary endpoint was the difference in mean area under the curve (AUC) between the first (cabazitaxel monotherapy) and third cabazitaxel cycle, when enzalutamide was added. Results: A potential clinically relevant 22% (95% CI, 9%–34%; P ¼ 0.005) reduction in cabazitaxel exposure was found with concomitant enzalutamide use. The geometric mean AUC0–24h of cabazitaxel was 181 ngh/mL (95% CI, 150–219 ngh/mL) in cycle 3 and 234 ngh/mL (95% CI, 209–261 ngh/mL) in cycle 1. This combination did not result in excessive toxicity, whereas PSA response was promising. Conclusions: We found a significant decrease in cabazitaxel exposure when combined with enzalutamide. In an era of clinical trials on combination strategies for mCRPC, it is important to be aware of clinically relevant drug–drug interactions. Because recent study results support the use of a lower standard cabazitaxel dose of 20 mg/m2, the clinical relevance of this interaction may be substantial, because the addition of enzalutamide may result in subtherapeutic cabazitaxel exposure

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

Continued Androgen Signalling Inhibition improves Cabazitaxel Efficacy in Prostate Cancer: Adding enzalutamide to cabazitaxel in hormone refractory PCa

Background:: The androgen receptor (AR) pathway is a key driver of neoplastic behaviour in the different stages of metastatic prostate cancer (mPCa). Targeting the AR therefore remains the cornerstone for mPCa treatment. We have previously reported that activation of AR signalling affects taxane chemo-sensitivity in preclinical models of castration resistant PCa (CRPC). Here, we explored the anti-tumour efficacy of the AR targeted inhibitor enzalutamide combined with cabazitaxel. Methods:: We used the AR positive CRPC model PC346C-DCC-K to assess the in vitro and in vivo activity of combining enzalutamide with cabazitaxel. Subsequent validation studies were performed using an enzalutamide resistant VCaP model. To investigate the impact of AR signalling on cabazitaxel activity we used quantitative live-cell imaging of tubulin stabilization and apoptosis related nuclear fragmentation. Findings:: Enzalutamide strongly amplified cabazitaxel anti-tumour activity in the patient-derived xenograft models PC346C-DCC-K (median time to humane endpoint 77 versus 48 days, P&lt;0.0001) and VCaP-Enza-B (median time to humane endpoint 80 versus 53 days, P&lt;0.001). Although enzalutamide treatment by itself was ineffective in reducing tumour growth, it significantly suppressed AR signalling in PC346C-DCC-K tumours as shown by AR target gene expression. The addition of enzalutamide enhanced cabazitaxel induced apoptosis as shown by live-cell imaging (P&lt;0.001). Interpretation:: Our study demonstrates that cabazitaxel efficacy can be improved by simultaneous blocking of AR signalling by enzalutamide, even if AR targeted treatment no longer affects tumour growth. These findings support clinical studies that combine AR targeted inhibitors with cabazitaxel in CRPC.</p

Comprehensive Molecular Characterization Reveals Genomic and Transcriptomic Subtypes of Metastatic Urothelial Carcinoma

Recent molecular characterization of primary urothelial carcinoma (UC) may guide future clinical decision-making. For metastatic UC (mUC), a comprehensive molecular characterization is still lacking. We analyzed whole-genome DNA and RNA sequencing data for fresh-frozen metastatic tumor biopsies from 116 mUC patients who were scheduled for palliative systemic treatment within the context of a clinical trial (NCT01855477 and NCT02925234). Hierarchical clustering for mutational signatures revealed two major genomic subtypes: GenS1 (67%), which was APOBEC-driven; and GenS2 (24%), which had a high fraction of de novo mutational signatures related to reactive oxygen species and is putatively clock-like. Significantly mutated genes (SMGs) did not differ between the genomic subtypes. Transcriptomic analysis revealed five mUC subtypes: luminal-a and luminal-b (40%), stroma-rich (24%), basal/squamous (23%), and a nonspecified subtype (12%). These subtypes differed regarding expression of key genes, SMGs, oncogenic pathway activity, and immune cell infiltration. We integrated the genomic and transcriptomic data to propose potential therapeutic options by transcriptomic subtype and for individual patients. This in-depth analysis of a large cohort of patients with mUC may serve as a reference for subtype-oriented and patient-specific research on the etiology of mUC and for novel drug development. Patient summary: We carried out an in-depth analysis of the molecular and genetic features of metastatic cancer involving the cells that line the urinary tract. We showed that this is a heterogeneous disease with different molecular subtypes and we identified possible targets for therapy for each subtype

Implementation of a multicenter biobanking collaboration for next-generation sequencing-based biomarker discovery based on fresh frozen pretreatment tumor tissue biopsies

__Background__ The discovery of novel biomarkers that predict treatment response in advanced cancer patients requires acquisition of high-quality tumor samples. As cancer evolves over time, tissue is ideally obtained before the start of each treatment. Preferably, samples are freshly frozen to allow analysis by next-generation DNA/RNA sequencing (NGS) but also for making other emerging systematic techniques such as proteomics and metabolomics possible. Here, we describe the first 469 image-guided biopsies collected in a large coll