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Abstract Immune checkpoint inhibitors (ICI) improve overall survival in patients with metastatic urothelial cancer (mUC), but therapeutic success at the individual patient level varies significantly. Here we identify predictive markers of response, based on whole-genome DNA (n = 70) and RNA-sequencing (n = 41) of fresh metastatic biopsy samples, collected prior to treatment with pembrolizumab. We find that PD-L1 combined positivity score does not, whereas tumor mutational burden and APOBEC mutagenesis modestly predict response. In contrast, T cell-to-stroma enrichment (TSE) score, computed from gene expression signature data to capture the relative abundance of T cells and stromal cells, predicts response to immunotherapy with high accuracy. Patients with a positive and negative TSE score show progression free survival rates at 6 months of 67 and 0%, respectively. The abundance of T cells and stromal cells, as reflected by the TSE score is confirmed by immunofluorescence in tumor tissue, and its good performance in two independent ICI-treated cohorts of patients with mUC (IMvigor210) and muscle-invasive UC (ABACUS) validate the predictive power of the TSE score. In conclusion, the TSE score represents a clinically applicable metric that potentially supports the prospective selection of patients with mUC for ICI treatment.

Multiple prognostic biomarkers, including circulating tumour cell (CTC) counts, exist in metastatic castration‐resistant prostate cancer (mCRPC) patients, but none of them have been implemented into daily clinical care. The modified fast aneuploidy screening test‐sequencing system (mFast‐SeqS), which yields a genome‐wide aneuploidy score, is able to reflect the fraction of cell‐free tumour DNA (ctDNA) within cell‐free DNA (cfDNA) and may be a promising biomarker in mCRPC. In this study, we investigated the prognostic value of dichotomized aneuploidy scores (

AMG 256 is a bi-specific, heteroimmunoglobulin molecule with an anti-PD-1 antibody domain and a single IL-21 mutein domain on the C-terminus. Nonclinical studies in cynomolgus monkeys revealed that AMG 256 administration led to the development of immunogenicity-mediated responses and indicated that the IL-21 mutein domain of AMG 256 could enhance the anti-drug antibody response directed toward the monoclonal antibody domain. Anti-AMG 256 IgE were also observed in cynomolgus monkeys. A first-in-human (FIH) study in patients with advanced solid tumors was designed with these risks in mind. AMG 256 elicited ADA in 28 of 33 subjects (84.8%). However, ADA responses were only robust and exposure-impacting at the 2 lowest doses. At mid to high doses, ADA responses remained low magnitude and all subjects maintained exposure, despite most subjects developing ADA. Limited drug-specific IgE were also observed during the FIH study. ADA responses were not associated with any type of adverse event. The AMG 256 program represents a unique case where nonclinical studies informed on the risk of immunogenicity in humans, due to the IL-21-driven nature of the response.

Prostate cancer is known to have a variable response to androgen receptor signalling inhibitors. Here, the authors use machine learning to predict response to therapy from genomic, transcriptomic and clinical data.

Metastatic and locally-advanced neuroendocrine neoplasms (aNEN) display heterogeneous clinical and genetic characteristics. Here, the authors investigate the mutational landscape of 85 aNEN by whole genome sequencing and identify distinct subpopulations, tumour mutational burden patterns, drivers and actionable somatic alterations.

Abstract Here, we describe a novel approach for rapid discovery of a set of tumor-specific genomic structural variants (SVs), based on a combination of low coverage cancer genome sequencing using Oxford Nanopore with an SV calling and filtering pipeline. We applied the method to tumor samples of high-grade ovarian and prostate cancer patients and validated on average ten somatic SVs per patient with breakpoint-spanning PCR mini-amplicons. These SVs could be quantified in ctDNA samples of patients with metastatic prostate cancer using a digital PCR assay. The results suggest that SV dynamics correlate with and may improve existing treatment-response biomarkers such as PSA. https://github.com/UMCUGenetics/SHARC .

Molecular landscapes of metastatic colorectal cancers (mCRC) have often been restricted to coding regions or low numbers of patients. Here the authors present a whole-genome landscape of 429 mCRC patients, revealing the mutational impact of prior therapies and potential actionable targets.

Prostate cancer is the most dominant male malignancy worldwide. The clinical presentation of prostate cancer ranges from localized indolent to rapidly progressing lethal metastatic disease. Despite a decline in death rate over the past years, with the advent of early diagnosis and new treatment options, challenges remain towards the management of metastatic prostate cancer, particularly metastatic castration sensitive prostate cancer (mCSPC) and castration resistant prostate cancer (mCRPC). Current treatments involve a combination of chemotherapy with androgen deprivation therapy and/or androgen receptor signalling inhibitors. However, treatment outcomes are heterogeneous due to significant tumor heterogeneity indicating a need for better prognostic biomarkers to identify patients with poor outcomes. Liquid biopsy has opened a plethora of opportunities from early diagnosis to (personalized) therapeutic disease interventions. In this review, we first provide recent insights about (metastatic) prostate cancer and its current treatment landscape. We highlight recent studies involving various circulating biomarkers such as circulating tumor cells, genetic markers, circulating nucleic acids, extracellular vesicles, tumor-educated platelets, and the secretome from (circulating) tumor cells and tumor microenvironment in metastatic prostate cancer. The comprehensive array of biomarkers can provide a powerful approach to understanding the spectrum of prostate cancer disease and guide in developing improved and personalized treatments for patients.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Background: Biomarkers predicting treatment response may be used to stratify pancreatic ductal adenocarcinoma (PDAC) patients for therapy. The aim of this study was to identify circulating tumor DNA (ctDNA) mutations that associate with tumor progression during FOLFIRINOX chemotherapy, and overall survival (OS). Methods: Circulating cell-free DNA was analyzed with a 57 gene next-generation sequencing panel using plasma samples of 48 PDAC patients of all disease stages. Patients received FOLFIRINOX as initial treatment. Chemotherapy response was determined on CT scans as disease control ( n = 30) or progressive disease ( n = 18) within eight cycles of FOLFIRINOX, based on RECIST 1.1 criteria. Results: Detection of a TP53 ctDNA mutation before start of FOLFIRINOX [odds ratio (OR) 10.51, 95% confidence interval (CI) 1.40–79.14] and the presence of a homozygous TP53 Pro72Arg germline variant (OR 6.98, 95% CI 1.31–37.30) were predictors of early tumor progression during FOLFIRINOX in multivariable analysis. Five patients presented with the combination of a TP53 ctDNA mutation before start of FOLFIRINOX and the homozygous Pro72Arg variant. All five patients showed progression during FOLFIRINOX. The combination of the TP53 mutation and TP53 germline variant was associated with shorter survival (median OS 4.4 months, 95% CI 2.6–6.2 months) compared with patients without any TP53 alterations (median OS 13.0 months, 95% CI 8.6–17.4 months). Conclusion: The combination of a TP53 ctDNA mutation before start of FOLFIRINOX and a homozygous TP53 Pro72Arg variant is a promising biomarker, associated with early tumor progression during FOLFIRINOX and poor OS. The results of this exploratory study need to be validated in an independent cohort.

Abstract Background Patients with advanced cancer for whom standard systemic treatment is no longer available may be offered participation in early phase clinical trials. In the decision making process, both medical-technical information and patient values and preferences are important. Since patients report decisional conflict after deciding on participation in these trials, improving the decision making process is essential. We aim to develop and evaluate an Online Value Clarification Tool (OnVaCT) to assist patients in clarifying their values around this end-of-life decision. This improved sharing of values is hypothesized to support medical oncologists in tailoring their information to individual patients’ needs and, consequently, to support patients in taking decisions in line with their values and reduce decisional conflict. Methods In the first part, patients’ values and preferences and medical oncologists’ views hereupon will be explored in interviews and focus groups to build a first prototype OnVaCT using digital communication (serious gaming). Next, we will test feasibility during think aloud sessions, to deliver a ready-to-implement OnVaCT. In the second part, the OnVaCT, with accompanied training module, will be evaluated in a pre-test (12–18 months before implementation) post-test (12–18 months after implementation) study in three major Dutch cancer centres. We will include 276 patients (> 18 years) with advanced cancer for whom standard systemic therapy is no longer available, and who are referred for participation in early phase clinical trials. The first consultation will be recorded to analyse patient-physician communication regarding the discussion of patients’ values and the decision making process. Three weeks afterwards, decisional conflict will be measured. Discussion This project aims to support the discussion of patient values when considering participation in early phase clinical trials. By including patients before their first appointment with the medical oncologist and recording that consultation, we are able to link decisional conflict to the decision making process, e.g. the communication during consultation. The study faces challenges such as timely including patients within the short period between referral and first consultation. Furthermore, with new treatments being developed rapidly, molecular stratification may affect the patient populations included in the pre-test and post-test periods. Trial registration Netherlands Trial Registry number: NTR7551 (prospective; July 17, 2018).

Detecting genomic abnormalities in metastatic castration-resistant prostate cancer (mCRPC) may impact clinical treatment. Here, the authors present whole-genome sequencing of metastatic biopsies from 197 mCRPC patients, highlighting the landscape of microsatellite stability, homologous repair deficiency, and other genomic subgroups.

The emerging interest in circulating tumor DNA (ctDNA) analyses for clinical trials has necessitated the development of a high‐throughput method for fast, reproducible, and efficient isolation of ctDNA. Currently, the majority of ctDNA studies use the manual QIAamp (QA) platform to isolate DNA from blood. The purpose of this study was to compare two competing automated DNA isolation platforms [Maxwell (MX) and QIAsymphony (QS)] to the current ‘gold standard’ QA to facilitate high‐throughput processing of samples in prospective trials. We obtained blood samples from healthy blood donors and metastatic cancer patients for plasma isolation. Total cell‐free DNA (cfDNA) quantity was assessed by TERT quantitative PCR. Recovery efficiency was investigated by quantitative PCR analysis of spiked‐in synthetic plant DNA. In addition, a β‐actin fragmentation assay was performed to determine the amount of contamination by genomic DNA from lysed leukocytes. ctDNA quality was assessed by digital PCR for somatic variant detection. cfDNA quantity and recovery efficiency were lowest using the MX platform, whereas QA and QS showed a comparable performance. All platforms preferentially isolated small (136 bp) DNA fragments over large (420 and 2000 bp) DNA fragments. Detection of the number variant and wild‐type molecules was most comparable between QA and QS. However, there was no significant difference in variant allele frequency comparing QS and MX to QA. In summary, we show that the QS platform has comparable performance to QA, the ‘gold standard’, and outperformed the MX platform depending on the readout used. We conclude that the QS can replace the more laborious QA platform, especially when high‐throughput cfDNA isolation is needed.

BACKGROUND Continued androgen receptor (AR) signaling constitutes a key target for treatment in metastatic castration-resistant prostate cancer (CRPC). Studies have identified 11-ketotestosterone (11KT) as a potent AR agonist, but it is unknown if 11KT is present at physiologically relevant concentrations in patients with CRPC to drive AR activation. The goal of this study was to investigate the circulating steroid metabolome including all active androgens in patients with CRPC.METHODS Patients with metastatic CRPC (n = 29) starting a new line of systemic therapy were included. Sequential plasma samples were obtained for measurement of circulating steroid concentrations by multisteroid profiling employing liquid chromatography–tandem mass spectrometry. Metastatic tumor biopsy samples were obtained at baseline and subjected to RNA sequencing.RESULTS 11KT was the most abundant circulating active androgen in 97% of patients with CRPC (median 0.39 nmol/L, range: 0.03–2.39 nmol/L), constituting 60% (IQR 43%–79%) of the total active androgen (TA) pool. Treatment with glucocorticoids reduced 11KT by 84% (49%–89%) and testosterone by 68% (38%–79%). Circulating TA concentrations at baseline were associated with a distinct intratumor gene expression signature comprising AR-regulated genes.CONCLUSION The potent AR agonist 11KT is the predominant circulating active androgen in patients with CRPC and, therefore, one of the potential drivers of AR activation in CRPC. Assessment of androgen status should be extended to include 11KT, as current clinical approaches likely underestimate androgen abundance in patients with CRPC.TRIAL REGISTRATION Netherlands Trial Register: NL5625 (NTR5732).FUNDING Daniel den Hoed Foundation and Wellcome Trust (Investigator Award WT209492/Z/17/Z).

We and others have previously demonstrated that the acute release of progenitor cells in response to chemotherapy actually reduces the efficacy of the chemotherapy. Here, we take these data further and investigate the clinical relevance of circulating endothelial (progenitor) cells (CE(P)Cs) and modulatory cytokines in patients after chemotherapy with relation to progression-free and overall survival (PFS/OS). Patients treated with various chemotherapeutics were included. Blood sampling was performed at baseline, 4 hours, and 7 and 21 days after chemotherapy. The mononuclear cell fraction was analyzed for CE(P)C by FACS analysis. Plasma was analyzed for cytokines by ELISA or Luminex technique. CE(P)Cs were correlated with response and PFS/OS using Cox proportional hazard regression analysis. We measured CE(P)Cs and cytokines in 71 patients. Only patients treated with paclitaxel showed an immediate increase in endothelial progenitor cell 4 hours after start of treatment. These immediate changes did not correlate with response or survival. After 7 and 21 days of chemotherapy, a large and consistent increase in CE(P)C was found (P < .01), independent of the type of chemotherapy. Changes in CE(P)C levels at day 7 correlated with an increase in tumor volume after three cycles of chemotherapy and predicted PFS/OS, regardless of the tumor type or chemotherapy. These findings indicate that the late release of CE(P)C is a common phenomenon after chemotherapeutic treatment. The correlation with a clinical response and survival provides further support for the biologic relevance of these cells in patients' prognosis and stresses their possible use as a therapeutic target.

BackgroundMesenchymal Consensus Molecular Subtype 4 (CMS4) colon cancer is associated with poor prognosis and therapy resistance. In this proof-of-concept study, we assessed whether a rationally chosen drug could mitigate the distinguishing molecular features of primary CMS4 colon cancer.MethodsIn the ImPACCT trial, informed consent was obtained for molecular subtyping at initial diagnosis of colon cancer using a validated RT-qPCR CMS4-test on three biopsies per tumor (Phase-1, n=69 patients), and for neoadjuvant CMS4-targeting therapy with imatinib (Phase-2, n=5). Pre- and post-treatment tumor biopsies were analyzed by RNA-sequencing and immunohistochemistry. Imatinib-induced gene expression changes were associated with molecular subtypes and survival in an independent cohort of 3232 primary colon cancer.ResultsThe CMS4-test classified 52/172 biopsies as CMS4 (30%). Five patients consented to imatinib treatment prior to surgery, yielding 15 pre- and 15 post-treatment samples for molecular analysis. Imatinib treatment caused significant suppression of mesenchymal genes and upregulation of genes encoding epithelial junctions. The gene expression changes induced by imatinib were associated with improved survival and a shift from CMS4 to CMS2.ConclusionImatinib may have value as a CMS-switching drug in primary colon cancer and induces a gene expression program that is associated with improved survival.

During the last years, there has been a dramatic increase in the administrative and bureaucratic burden associated with clinical research, which has clearly had an impact on its overall efficiency and on the activity of clinical investigators and research teams. Indeed, the supervision of the adherence of clinical research to Good Clinical Practice (GCP) guidelines and legal regulations is of the utmost importance. Yet, while such regulations have remained largely unchanged during recent years, the number of administrative tasks and their complexity have grown markedly, as supported by the results of a survey performed among 940 clinical investigators that we report in this manuscript. Therefore, many investigators believe that it has become necessary to undertake a rigorous analysis of the causes and consequences of this issue, and to create a conduit to channel the advice from experienced investigators regarding clinical research procedures, in order to improve them. Based on these premises, ESMO has launched the ESMO Clinical Research Observatory (ECRO), a task force that will analyse different aspects of clinical research. ECRO will aim to provide the views of ESMO on clinical research procedures based on the feedback from clinical investigators, under complete adherence to the Declaration of Helsinki, the GCP guidelines and any other applicable legal regulations, while at the same time showing profound respect for all the stakeholders involved in clinical research. This manuscript provides the background and rationale for the creation of ECRO, its planned activity and an analysis of the current administrative burden in clinical research with recommendations to rationalise it. Indeed, we expect that this effort shall lead to a relevant improvement in the care of patients and in the development of clinical research.

Targeted Next Generation Sequencing (NGS) offers a way to implement testing of multiple genetic aberrations in diagnostic pathology practice, which is necessary for personalized cancer treatment. However, no standards regarding input material have been defined. This study therefore aimed to determine the effect of the type of input material (e.g. formalin fixed paraffin embedded (FFPE) versus fresh frozen (FF) tissue) on NGS derived results. Moreover, this study aimed to explore a standardized analysis pipeline to support consistent clinical decision-making.We used the Ion Torrent PGM sequencing platform in combination with the Ion AmpliSeq Cancer Hotspot Panel v2 to sequence frequently mutated regions in 50 cancer related genes, and validated the NGS detected variants in 250 FFPE samples using standard diagnostic assays. Next, 386 tumour samples were sequenced to explore the effect of input material on variant detection variables. For variant calling, Ion Torrent analysis software was supplemented with additional variant annotation and filtering.Both FFPE and FF tissue could be sequenced reliably with a sensitivity of 99.1%. Validation showed a 98.5% concordance between NGS and conventional sequencing techniques, where NGS provided both the advantage of low input DNA concentration and the detection of low-frequency variants. The reliability of mutation analysis could be further improved with manual inspection of sequence data.Targeted NGS can be reliably implemented in cancer diagnostics using both FFPE and FF tissue when using appropriate analysis settings, even with low input DNA.