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de Wit, R.

Publications and source records attributed to de Wit, R..

4 recordsLinked to original sources

Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers

While structural variants (SVs) are a clear sign of genomic instability, they have not been systematically quantified per patient. Therefore, the biological and clinical impact of high numbers of SVs in patients is unknown. We introduce tumor break load (TBL), defined as the sum of unbalanced SVs, as a measure for SV-associated genomic instability. Using pan-cancer data from TCGA, PCAWG, and CCLE, we show that a high TBL is associated with significant changes in gene expression in 26/31 cancer types that consistently involve upregulation of DNA damage repair and downregulation of immune response pathways. Patients with a high TBL show a higher risk of recurrence and shorter median survival times for 5/15 cancer types. Our data demonstrate that TBL is a biologically and clinically relevant feature of genomic instability that may aid patient prognostication and treatment stratification. For the datasets analyzed in this study, TBL has been made available in cBioPortal.

cancer biology↗

T Cell-to-Stroma Enrichment (TSE) score: a gene expression metric that predicts response to immune checkpoint inhibitors in patients with urothelial cancer

Immune checkpoint inhibitors (ICIs) improve overall survival in patients with metastatic urothelial cancer (mUC). To identify predictive markers of response, whole-genome DNA (n=70) and RNA-sequencing (n=41) were performed using fresh metastatic biopsies prior to treatment with pembrolizumab. PD-L1 combined positivity score did not, whereas tumor mutational burden and APOBEC mutagenesis modestly predicted response. Using gene expression analysis, we defined the T cell-to-stroma enrichment (TSE) score, a signature-based metric that captures the relative abundance of T cells and stromal cells. Patients with a positive and negative TSE score show progression-free survival rates at 6 months of 67 and 0%, respectively. The TSE score was captured by immunofluorescence in tumor tissue, and validated in two independent ICI-treated cohorts of patients with mUC (IMvigor210) and muscle-invasive UC (ABACUS). In conclusion, the TSE score represents a clinically applicable marker that potentially aids in prospectively selecting patients with mUC for ICI treatment.

cancer biology↗

Molecular characterization reveals genomic and transcriptomic subtypes of metastatic urothelial carcinoma

BackgroundMolecular characterization of primary urothelial carcinoma (UC) revealed molecular subtypes with different genomic, transcriptomic, and clinicopathological characteristics, which might guide therapeutic decision making. A comprehensive molecular characterization of metastatic UC (mUC), however, is currently lacking in the literature. Because of the lethality of mUC, with few therapeutic options available for patients, a multi-omics characterization of mUC could aid to improve patient selection for new and existing therapies. MethodsTo define the molecular landscape of mUC and to identify potential targets for therapy, we performed whole genome DNA sequencing on fresh-frozen metastatic tumor biopsies of 116 mUC patients, and mRNA sequencing on 90 matched biopsies. ResultsHierarchical clustering based on mutational signatures revealed two major genomic subtypes. The most prevalent subtype (67%) consisted almost exclusively of tumors with high APOBEC mutagenesis. APOBEC mutagenesis was detected in 91% of the samples, and appeared to be an ongoing process in mUC based on analysis of eight patients from whom serial biopsies were obtained during treatment. Contrary to the overall distribution of mutations, APOBEC associated mutations occurred throughout the genome, and independently of predicted accessible or transcribed genomic regions, suggesting that these mutations were generated during replication. Transcriptomic analysis revealed five mRNA-based subtypes: two luminal subtypes (40%), a stroma-rich (24%), basal/squamous (23%), and non-specified subtype (12%). The transcriptomic subtypes were different regarding driver gene alterations (e.g. ELF3 and TSC1), gene amplifications (NECTIN4 and PPARG), pathway activity, and immune cell infiltration. By integrating the genomic and transcriptomic data, potential therapeutic options per transcriptomic subtype and individual patient were proposed. ConclusionsThis study expands our knowledge on the molecular landscape of mUC, and serves as a reference for subtype-oriented and patient-specific research on the etiology of mUC, and for novel drug development. Trial registrationThe mUC cohort studied here is part of the Netherlands nationwide study of the center for personalized cancer treatment consortium (CPCT-02 Biopsy Protocol, NCT01855477), and the Drug Rediscovery Protocol (DRUP Trial, NCT02925234).

cancer biology↗

The genomic landscape of metastatic castration-resistant prostate cancers using whole genome sequencing reveals multiple distinct genotypes with potential clinical impact

Here we present whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 castration-resistant prostate cancer patients. Using hierarchical unsupervised clustering based on genomic aberrations only, we defined eight different clusters. We detected four distinct and potentially clinically relevant genotypes harboring unique genomic features, including: 1) Microsatellite Instability; 2) Homologous Recombination Deficiency (HRD) with enriched genomic deletions and BRCA2 aberrations; 3) tandem duplication phenotype associated with biallelic CDK12 mutations; and 4) a subgroup enriched for chromothripsis events. Our data suggest that classifying patients using WGS characteristics may improve classification of HRD patients. Moreover, we confirmed that important regulators of AR-mediated signaling are located in non-coding regions. Using ChIP sequencing data, we showed that the amplified AR and MYC promoter regions contain open chromatin and bind AR, suggesting a role in AR mediated biology. Thus, high-resolution WGS may be used to improve patient stratification.

cancer biology↗