Genomic alterations in metastatic prostate cancer remain incompletely characterized. Here we analyse 493 prostate cancer cases from the TCGA database and perform whole-genome plasma sequencing on 95 ...plasma samples derived from 43 patients with metastatic prostate cancer. From these samples, we identify established driver aberrations in a cancer-related gene in nearly all cases (97.7%), including driver gene fusions (TMPRSS2:ERG), driver focal deletions (PTEN, RYBP and SHQ1) and driver amplifications (AR and MYC). In serial plasma analyses, we observe changes in focal amplifications in 40% of cases. The mean time interval between new amplifications was 26.4 weeks (range: 5-52 weeks), suggesting that they represent rapid adaptations to selection pressure. An increase in neuron-specific enolase is accompanied by clonal pattern changes in the tumour genome, most consistent with subclonal diversification of the tumour. Our findings suggest a high plasticity of prostate cancer genomes with newly occurring focal amplifications as a driving force in progression.
The benefit of alpelisib in hormone-receptor-positive (HR+) metastatic breast cancer patients provided clinical evidence for the increasing importance of PIK3CA testing. We performed a comparison of ...liquid biopsy and tissue-based detection of PIK3CA mutations.
PIK3CA hotspot mutation analysis using a high-resolution SiMSen-Seq assay was performed in plasma from 93/99 eligible patients with HR+/HER2- breast cancer. Additionally, mFAST-SeqS was used to estimate the tumour fractions in plasma samples. In 72/93 patients, matched tissue was available and analysed using a customised Ion Torrent panel.
PIK3CA mutations were detected in 48.6% of tissue samples and 47.3% of plasma samples, with identical PIK3CA mutation detected in 24/72 (33.3%) patients both in tissue and plasma. In 10 (13.9%) patients, mutations were only found in plasma, and in 6 (8.3%) patients, PIK3CA mutations found in tissue were not detectable in ctDNA. In 49/93 plasma samples without detectable PIK3CA mutations, 22 (44.9%) samples had elevated tumour fractions, implying true negative results.
SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted approach for detecting ctDNA fractions may confirm a negative PIK3CA result and enhance the performance of the SiMSen-Seq test.
The putative cannabinoid receptor GPR55 has been shown to play a tumor‐promoting role in various cancers, and is involved in many physiological and pathological processes of the gastrointestinal (GI) ...tract. While the cannabinoid receptor 1 (CB1) has been reported to suppress intestinal tumor growth, the role of GPR55 in the development of GI cancers is unclear. We, therefore, aimed at elucidating the role of GPR55 in colorectal cancer (CRC), the third most common cancer worldwide. Using azoxymethane (AOM)‐ and dextran sulfate sodium (DSS)‐driven CRC mouse models, we found that GPR55 plays a tumor‐promoting role that involves alterations of leukocyte populations, i.e. myeloid‐derived suppressor cells and T lymphocytes, within the tumor tissues. Concomitantly, expression levels of COX‐2 and STAT3 were reduced in tumor tissue of GPR55 knockout mice, indicating reduced presence of tumor‐promoting factors. By employing the experimental CRC models to CB1 knockout and CB1/GPR55 double knockout mice, we can further show that GPR55 plays an opposing role to CB1. We report that GPR55 and CB1 mRNA expression are differentially regulated in the experimental models and in a cohort of 86 CRC patients. Epigenetic methylation of CNR1 and GPR55 was also differentially regulated in human CRC tissue compared to control samples. Collectively, our data suggest that GPR55 and CB1 play differential roles in colon carcinogenesis where the former seems to act as oncogene and the latter as tumor suppressor.
What's new?
The cannabinoid receptor GPR55 may boost colon tumor growth, new results show. Earlier work has established the receptor's role in various cancers, but this study is the first to investigate its relationship to colorectal cancer. These authors observed that mice lacking GPR55 had a much lighter tumor burden than wild type mice, as well as lower levels of COX‐2 and STAT3, both of which help drive tumor growth. Knocking out GPR55 also bumped the infiltration of CD4+ and CD8+ T cells in the tumor microenvironment, suggesting that GPR55 aids cancer by arranging a friendlier leukocyte population around the tumor.
With longitudinal untargeted assessment of circulating tumor DNA in metastatic HR+ breast cancer patients during CDK4/6 treatment and joint model analyses, we demonstrated that tumor fraction ...trajectories rather than single time point measurements provide important dynamic information on developing disease progression. The joint model can also use the trajectories for providing dynamic predictions for the individual patient.
Despite improved clinical outcomes, intrinsic or acquired resistance to CDK4/6 inhibitor treatment has limited the success of this treatment in HR+HER2− metastatic breast cancer patients. Biomarkers are urgently needed, and longitudinal biomarker measurements may harbor more dynamic predictive and prognostic information compared to single time point measurements. The aim of this study was to explore the longitudinal evolution of circulating tumor fractions within cell‐free DNA assessed by an untargeted sequencing approach during CDK4/6 therapy and to quantify the potential association between longitudinal z‐score measurements and clinical outcome by using joint models. Forty‐nine HR+HER2− metastatic breast cancer patients were enrolled, and z‐score levels were measured at baseline and during 132 follow‐up visits (median number of measurements per patient = 3, 25th–75th percentile: 3–5, range: 1–8). We observed higher baseline z‐score levels (estimated difference 0.57, 95% CI: 0.147–0.983, P‐value = 0.008) and a constant increase of z‐score levels over follow‐up time (overall P‐value for difference in log z‐score over time = 0.024) in patients who developed progressive disease. Importantly, the joint model revealed that elevated z‐score trajectories were significantly associated with higher progression risk (HR of log z‐score at any time of follow‐up = 3.3, 95% CI, 1.44–7.55, P = 0.005). In contrast, single z‐score measurement at CDK4/6 inhibitor treatment start did not predict risk of progression. In this prospective study, we demonstrate proof‐of‐concept that longitudinal z‐score trajectories rather than single time point measurements may harbor important dynamic information on the development of disease progression in HR+HER2− breast cancer patients undergoing CDK4/6 inhibitor treatment.
Despite achieving complete remission after intensive therapy, most patients with cytogenetically normal (CN) AML relapse due to the persistence of submicroscopic residual disease. In this pilot ...study, we hypothesized that detection of leukemia‐specific mutations following consolidation treatment using a targeted parallel sequencing approach predicts relapse. We included 34 AML patients of whom diagnostic material and remission bone marrow slides after at least one cycle of consolidation were available. Isolated DNA was screened for mutations in 19 genes using an Ion Torrent sequencing platform. Furthermore, the variant allelic frequency of distinct mutations was validated by digital PCR and sequencing using a barcoding approach. Twenty‐seven out of 34 patients could be analyzed for mutation clearance. We identified 68 somatic mutations at diagnosis (median, 3 mutations per patient; range 1‐5) and 22 of these were still detected in 16 patients after consolidation therapy with a reliable sensitivity of 0.5% (median, 1 mutation; range 0‐3). The most frequent noncleared mutations were found in DNMT3A. However, as persistence of these mutations has recently been shown to be without any impact on relapse risk, we performed survival and relapse risk analysis excluding DNMT3A mutations. Importantly, persistence of non‐DNMT3A mutations was associated with a higher risk of AML relapse (7/8 pts versus 6/19 pts; P = .013) and with a shorter relapse‐free survival (333 days vs. not reached; log‐rank P = .0219). Detection of residual disease by routine targeted parallel sequencing proved feasible and effective as persistence of somatic mutations other than DNMT3A were prognostic for relapse in CN AML.
We addressed a significant unknown feature of circulating tumor DNA (ctDNA), i.e., how ctDNA levels change during chemotherapy, by serially monitoring ctDNA in patients with colorectal cancer during ...the 48-h application of FOLFOX. Surprisingly, we did not observe a spike in ctDNA as a sign of a responsive tumor, but instead ctDNA levels initially decreased and remained low in patients with stable disease or partial response. Our observations reveal further insights into cell destruction during chemotherapy with important implications for the management of patients.
ObjectivePrecision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation ...of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).MethodsIn order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.ResultsEach platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.ConclusionsTreatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.
In psychology, linear discriminant analysis (LDA) is the method of choice for two‐group classification tasks based on questionnaire data. In this study, we present a comparison of LDA with several ...supervised learning algorithms. In particular, we examine to what extent the predictive performance of LDA relies on the multivariate normality assumption. As nonparametric alternatives, the linear support vector machine (SVM), classification and regression tree (CART), random forest (RF), probabilistic neural network (PNN), and the ensemble k conditional nearest neighbor (EkCNN) algorithms are applied. Predictive performance is determined using measures of overall performance, discrimination, and calibration, and is compared in two reference data sets as well as in a simulation study. The reference data are Likert‐type data, and comprise 5 and 10 predictor variables, respectively. Simulations are based on the reference data and are done for a balanced and an unbalanced scenario in each case. In order to compare the algorithms' performance, data are simulated from multivariate distributions with differing degrees of nonnormality. Results differ depending on the specific performance measure. The main finding is that LDA is always outperformed by RF in the bimodal data with respect to overall performance. Discriminative ability of the RF algorithm is often higher compared to LDA, but its model calibration is usually worse. Still LDA mostly ranges second in cases it is outperformed by another algorithm, or the differences are only marginal. In consequence, we still recommend LDA for this type of application.
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