Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic.
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ABSTRACT:
SUBMITTER: de Schaetzen van Brienen L
PROVIDER: S-EPMC8582433 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesTo perform a systematic review and network meta-analysis to compare the efficacy and safety of currently available treatments for the management of metastatic hormone-sensitive prostate cancer (mHSPC), as there has been a paradigm shift with the use of next-generation androgen receptor inhibitors (ARIs) and docetaxel.MethodsMultiple databases were searched for articles published before May 2020 according to the Preferred Reporting Items for Systematic Review and Meta-analysis extension statement for network meta-analysis. Studies comparing overall/progression-free survival (OS/PFS) and/or adverse events (AEs) in patients with mHSPC were eligible.ResultsNine studies (N = 9960) were selected, and formal network meta-analyses were conducted. Abiraterone (hazard ratio [HR] 0.83, 95% credible interval [CrI] 0.76-0.90), docetaxel (HR 0.90, 95% CrI 0.82-0.98), and enzalutamide (HR 0.85, 95% CrI 0.73-0.99) were associated with significantly better OS than androgen-deprivation therapy (ADT), and abiraterone emerged as the best option. Abiraterone (HR 0.71, 95% CrI 0.67-0.76), apalutamide (HR 0.73, 95% CrI 0.65-0.81), docetaxel (HR 0.84, 95% CrI 0.78-0.90), and enzalutamide (HR 0.67, 95% CrI 0.63-0.71) were associated with significantly better PFS than ADT, and enzalutamide emerged as the best option. Abiraterone (HR 0.85, 95% CrI 0.78-0.93), apalutamide (HR 0.87, 95% CrI 0.77-0.98), and enzalutamide (HR 0.80, 95% CrI 0.73-0.88) were significantly more effective than docetaxel. Regarding AEs, apalutamide was the likely best option among the three ARIs. In patients with low-volume mHSPC, enzalutamide was the best option in terms of OS and PFS.ConclusionsAll three ARIs are effective therapies for mHSPC; apalutamide was the best tolerated. All three seemed more effective than docetaxel. These findings may facilitate individualised treatment strategies and inform future comparative trials.
| S-EPMC9291853 | biostudies-literature
Project description:Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.
| S-EPMC4396364 | biostudies-literature
Project description:MotivationIdentification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes.ResultsWe have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or penta-nucleotide context substitutions observed in the cohort under study. Our method can identify known clusters and bona-fide cancer drivers across cohorts of tumor whole-exomes, outperforming the existing OncodriveCLUST algorithm and complementing other methods based on different signals of positive selection. Our results indicate that OncodriveCLUSTL can be applied to the analysis of non-coding genomic elements and non-human mutations data.Availability and implementationOncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6853674 | biostudies-literature
Project description:Androgen-ablation therapies, which are the standard treatment for metastatic prostate cancer, invariably lead to acquired resistance. Hence, a systematic identification of additional drivers may provide useful insights into the development of effective therapies. Numerous microRNAs that are critical for metastasis are dysregulated in metastatic prostate cancer, but the underlying molecular mechanism is poorly understood. We perform an integrative analysis of transcription factor (TF) and microRNA expression profiles and computationally identify three master TFs, AR, HOXC6 and NKX2-2, which induce the aberrant metastatic microRNA expression in a mutually exclusive fashion. Experimental validations confirm that the three TFs co-dysregulate a large number of metastasis-associated microRNAs. Moreover, their overexpression substantially enhances cell motility and is consistently associated with a poor clinical outcome. Finally, the mutually exclusive overexpression between AR, HOXC6 and NKX2-2 is preserved across various tissues and cancers, suggesting that mutual exclusivity may represent an intrinsic characteristic of driver TFs during tumorigenesis.
| S-EPMC5394245 | biostudies-literature
Project description:ObjectivesTo assess the cost-effectiveness of systemic treatments for metastatic castration-sensitive prostate cancer from the US healthcare sector perspective with a lifetime horizon.MethodsWe built a partitioned survival model based on a network meta-analysis of 7 clinical trials with 7287 patients aged 36 to 94 years between 2004 and 2018 to predict patient health trajectories by treatment. We tested parameter uncertainties with probabilistic sensitivity analyses. We estimated drug acquisition costs using the Federal Supply Schedule and adopted generic drug prices when available. We measured cost-effectiveness by an incremental cost-effectiveness ratio (ICER).ResultsThe mean costs were approximately $392 000 with androgen deprivation therapy (ADT) alone and approximately $415 000, $464 000, $597 000, and $959 000 with docetaxel, abiraterone acetate, enzalutamide, and apalutamide, added to ADT, respectively. The mean quality-adjusted life-years (QALYs) were 3.38 with ADT alone and 3.92, 4.76, 3.92, and 5.01 with docetaxel, abiraterone acetate, enzalutamide, and apalutamide, added to ADT, respectively. As add-on therapy to ADT, docetaxel had an ICER of $42 069 per QALY over ADT alone; abiraterone acetate had an ICER of $58 814 per QALY over docetaxel; apalutamide had an ICER of $1 979 676 per QALY over abiraterone acetate; enzalutamide was dominated. At a willingness to pay below $50 000 per QALY, docetaxel plus ADT is likely the most cost-effective treatment; at any willingness to pay between $50 000 and $200 000 per QALY, abiraterone acetate plus ADT is likely the most cost-effective treatment.ConclusionsThese findings underscore the value of abiraterone acetate plus ADT given its relative cost-effectiveness to other systemic treatments for metastatic castration-sensitive prostate cancer.
| S-EPMC9844549 | biostudies-literature
Project description:SummaryGene fusions are being discovered at an increasing rate using massively parallel sequencing technologies. Prioritization of cancer fusion drivers for validation cannot be performed using traditional single-gene based methods because fusions involve portions of two partner genes. To address this problem, we propose a novel network analysis method called fusion centrality that is specifically tailored for prioritizing gene fusions. We first propose a domain-based fusion model built on the theory of exon/domain shuffling. The model leads to a hypothesis that a fusion is more likely to be an oncogenic driver if its partner genes act like hubs in a network because the fusion mutation can deregulate normal functions of many other genes and their pathways. The hypothesis is supported by the observation that for most known cancer fusion genes, at least one of the fusion partners appears to be a hub in a network, and even for many fusions both partners appear to be hubs. Based on this model, we construct fusion centrality, a multi-gene-based network metric, and use it to score fusion drivers. We show that the fusion centrality outperforms other single gene-based methods. Specifically, the method successfully predicts most of 38 newly discovered fusions that had validated oncogenic importance. To our best knowledge, this is the first network-based approach for identifying fusion drivers.AvailabilityMatlab code implementing the fusion centrality method is available upon request from the corresponding authors.
| S-EPMC3634186 | biostudies-literature
Project description:BackgroundMetastatic castration-resistant prostate cancer (mCRPC) is the lethal form of the disease. Several recent studies have identified genomic alterations in mCRPC, but the clinical implications of these genomic alterations have not been fully elucidated.ObjectiveTo use whole-genome sequencing (WGS) to assess the association between key driver gene alterations and overall survival (OS), and to use whole-transcriptome RNA sequencing to identify genomic drivers of enzalutamide resistance.Design, setting, and participantsWe performed survival analyses and gene set enrichment analysis (GSEA) on WGS and RNA sequencing results for a cohort of 101 mCRPC patients.Outcome measurements and statistical analysisOS was the clinical endpoint for all univariate and multivariable survival analyses. Candidate drivers of enzalutamide resistance were identified in an unbiased manner, and mutations of the top candidate were further assessed for enrichment among enzalutamide-resistant patients using Fisher's exact test.Results and limitationsHarboring two DNA alterations in RB1 was independently predictive of poor OS (median 14.1 vs 42.0mo; p=0.007) for men with mCRPC. GSEA identified the Wnt/β-catenin pathway as the top differentially modulated pathway among enzalutamide-resistant patients. Furthermore, β-catenin mutations were exclusive to enzalutamide-resistant patients (p=0.01) and independently predictive of poor OS (median 13.6 vs 41.7mo; p=0.025).ConclusionsThe presence of two RB1 DNA alterations identified in our WGS analysis was independently associated with poor OS among men with mCRPC. The Wnt/β-catenin pathway plays an important role in enzalutamide resistance, with differential pathway expression and enrichment of β-catenin mutations in enzalutamide-resistant patients. Moreover, β-catenin mutations were predictive of poor OS in our cohort.Patient summaryWe observed a correlation between genomic findings for biopsy samples from metastases from men with metastatic castration-resistant prostate cancer (mCRPC) and clinical outcomes. This work sheds new light on clinically relevant genomic alterations in mCRPC and provides a roadmap for the development of new personalized treatment regimens in mCRPC.
| S-EPMC6764911 | biostudies-literature
Project description:MicroRNAs (miRNAs) have emerged as key regulators of numerous biological processes, and increasing evidence suggests that circulating miRNAs may be useful biomarkers of clinical disease. In this study, we sought to identify plasma miRNAs that differentiate patients with metastatic castration resistant prostate cancer (mCRPC) from those with localized prostate cancer (PCa). Pooled plasma samples from patients with localized PCa or mCRPC (25 per group) were assayed using the Exiqon miRNA qPCR panel, and the differential expression of selected candidates was validated using qRT-PCR. We identified 63 miRNAs upregulated in mCRPC versus localized PCa, while only four were downregulated. Pearson's correlation analysis revealed two highly correlated groups: one consisting of miR-141, miR375 and miR-200c and the other including miR151-3p, miR423-3p, miR-126, miR152 and miR-21. A third group, containing miR-16 and miR-205, showed less correlation. One miRNA from each group (miR-141, miR151-3p and miR-16) was used for logistic regression analysis and proved to increase the sensitivity of the prostate-specific antigen (PSA) test alone. While no miRNA alone differentiated localized PCa and mCRPC, combinations had greater sensitivity and specificity. The expression of these 10 candidates was assayed for association with clinical parameters of disease progression through the cBio portal. Our results demonstrate that plasma levels of selected miRNAs are potential biomarkers to differentiate localized PCa and mCRPC.
| S-EPMC3645714 | biostudies-other
Project description:The heterogeneity of cancer genomes in terms of acquired mutations complicates the identification of genes whose modification may exert a driver role in tumorigenesis. In this study, we present a novel method that integrates expression profiles, mutation effects, and systemic properties of mutated genes to identify novel cancer drivers. We applied our method to ovarian cancer samples and were able to identify putative drivers in the majority of carcinomas without mutations in known cancer genes, thus suggesting that it can be used as a complementary approach to find rare driver mutations that cannot be detected using frequency-based approaches.
| S-EPMC4054099 | biostudies-literature
Project description:Molecular profiling of prostate cancer with liquid biopsies, such as circulating tumor cells (CTCs) and cell-free nucleic acid analysis, yields informative yet distinct data sets. Additional insights may be gained by simultaneously interrogating multiple liquid biopsy components to construct a more comprehensive molecular disease profile. We conducted an initial proof-of-principle study aimed at piloting this multiparametric approach. Peripheral blood samples from men with metastatic castrate-resistant prostate cancer were analyzed simultaneously for CTC enumeration, single-cell copy number variations, CTC DNA and matched cell-free DNA mutations, and plasma cell-free RNA levels of androgen receptor (AR) and AR splice variant (ARV7). In addition, liquid biopsies were compared with matched tumor profiles when available, and a second liquid biopsy was drawn and analyzed at disease progression in a subset of patients. In this manner, multiparametric liquid biopsy profiles were successfully generated for each patient and time point, demonstrating the feasibility of this approach and highlighting shared as well as unique cancer-relevant alterations. With further refinement and validation in large cohorts, multiparametric liquid biopsies can optimally integrate disparate but clinically informative data sets and maximize their utility for molecularly directed, real-time patient management.
| S-EPMC6483502 | biostudies-literature