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Biology subjects

van Hoef, V.

Publications and source records attributed to van Hoef, V..

3 recordsLinked to original sources

CD4 T cell surface architecture is associated with response to anti-PD-1 therapy in non-small cell lung cancer

Anti-PD-1 therapy has substantially improved outcomes for patients with advanced non-small cell lung cancer (NSCLC), but clinical responses remain highly heterogeneous and are difficult to predict. Current immune profiling approaches primarily characterize immune cell composition and protein abundance, whereas the spatial organization of proteins at the cell surface has remained largely unexplored. Here, we demonstrate for the first time that cell surface protein organization is associated with clinical response to immune checkpoint inhibition therapy. Using the Proximity Network Assay (PNA), we simultaneously quantified cell frequencies, protein abundance, and protein organization in pretreatment peripheral blood mononuclear cells from 62 patients with advanced NSCLC treated with anti-PD-1 agents. While most cell populations were unchanged between responders and non-responders, pronounced response-associated alterations were identified within the CD4 T-cell compartment. Responders exhibited elevated expression of adhesion-associated proteins, and remodeling of a CD5-containing membrane domain. Increased colocalization within this domain was associated with poor clinical outcome and reduced survival. Machine learning analysis further identified CD4 T cell features as the strongest predictors of treatment response and demonstrated that protein organization provided greater predictive power than protein abundance alone. Together, these findings identify cell surface protein organization as a previously unexplored source of biomarkers and highlight its potential to improve immune profiling and biomarker discovery in cancer immunotherapy.

immunology↗

Single-Cell Protein Interactomes by the Proximity Network Assay

Cellular functions depend on dynamic interactions of proteins and their spatial organisation. While transcriptomic and proteomic methods of molecular parts-lists have enabled single-cell profiling based on abundance, scalable technologies allowing high-resolution measurements of protein organization and interactions at scale are lacking. Here we present the Proximity Network Assay (PNA), a DNA-based method for constructing three-dimensional nanoscale maps of 155 plasma membrane proteins in single cells without the use of optics. PNA employs barcoded antibodies and in situ rolling circle amplification to generate >40,000 spatial nodes per cell, which are linked through proximity-dependent gap-fill ligation and decoded by DNA sequencing forming single cell Proximity Networks. PNA captures abundance, self-clustering, and [~]12,000 pairwise colocalization relationships per single-cell, validating established protein interactions. This new modality provides a framework to uncover novel spatial biomarkers, reveal functional mechanisms, and advance translational studies in immunology, oncology, and cell therapy.

bioengineering↗

Estrogen receptor alpha controls gene expression via translational offsetting

Estrogen receptor alpha (ER) activity is associated with increased cancer cell proliferation. Studies aiming to understand the impact of ER on cancer-associated phenotypes have largely been limited to its transcriptional activity. Herein, we demonstrate that ER coordinates its transcriptional output with selective modulation of mRNA translation. Importantly, translational perturbations caused by depletion of ER largely manifest as \"translational offsetting\" of the transcriptome, whereby amounts of translated mRNA and protein levels are maintained constant despite changes in mRNA abundance. Transcripts whose levels, but not polysome-association, are reduced following ER depletion lack features which limit translational efficiency including structured 5UTRs and miRNA target sites. In contrast, mRNAs induced upon ER depletion whose polysome-association remains unaltered are enriched in codons requiring U34-modified tRNAs for efficient decoding. Consistently, ER regulates levels of U34-modification enzymes, whereas altered expression of U34-modification enzymes disrupts ER dependent translational offsetting. Altogether, we unravel a hitherto unprecedented mechanism of ER-dependent orchestration of transcriptional and translational programs, and highlight that translational offsetting may be a pervasive mechanism of proteome maintenance in hormone-dependent cancers.

systems biology↗