Biology subjects

van der Heijden, M. S.

Publications and source records attributed to van der Heijden, M. S..

4 recordsLinked to original sources

bioRxiv2023

Spatial relationships in the urothelial and head and neck tumor microenvironment predict response to combination immune checkpoint inhibitors

Immune checkpoint inhibitors (ICI) currently achieve remarkable clinical results in urothelial cancer (UC). However, the relationship between the tumor microenvironment (TME), usually characterized by immune cell density, and response to ICI is unclear. We quantified the TME immune cell densities and spatial relationships (SRs) using the multiplex immunofluorescence data of 24 UC pre-treatment tumor resections. We described SRs by approximating the 1-NN distance distribution with a Weibull distribution and evaluated the association between TME metrics (spatial and density parameters) and ipilimumab+nivolumab response. Immune cell density did not discriminate between response groups. However, the Weibull SR metrics of CD8+ T-cells or macrophages to their closest cancer cell were positively associated with response. CD8+ T-cells close to B-cells were characteristic of non-response. The G- function, a threshold dependent alternative SR metric, yielded variable effect sizes and statistical power in association studies with response. We validated our SR response associations in a cohort of head and neck tumors with a comparable treatment design. Our data confirm that SRs, in contrast to density metrics, are strong biomarkers of response to ICIs, a finding with significant translational relevance.

cancer biology↗

bioRxiv2022

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↗

bioRxiv2021

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↗

bioRxiv2019

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↗