Biology subjects

Bresser, K.

Publications and source records attributed to Bresser, K..

6 recordsLinked to original sources

bioRxiv2026

Proteomics of human cancer-associated T cells identifies regulators of T cell functionality

CD8+ T cells in solid cancers progressively lose anti-tumor activity, yet the cell-intrinsic mechanisms driving this loss of function remain incompletely defined. Here, we performed matched proteomic and transcriptomic profiling of dysfunctional and bystander CD8+ tumor-infiltrating T cells isolated from primary tumors of treatment-naive non-small cell lung cancer patients. Proteomic analysis revealed widespread discordance with mRNA expression, with 8% of all quantified proteins displaying differential expression exclusively at the protein level. Genetic perturbation of such differentially expressed proteins identified the chromatin remodeler CHD4 and fatty acid synthase (FASN) as cell-intrinsic regulators of T cell function. CHD4 deletion resulted in altered gene-regulatory networks that promoted effector differentiation and enhanced cytokine production. In contrast, FASN deletion preserved mitochondrial fitness and sustained T cell functionality under chronic T cell receptor stimulation. Together, these findings demonstrate that proteomic profiling uncovers regulators of T cell functionality that are not apparent from transcriptomic analyses alone, highlighting an additional layer of regulatory control.

immunology↗

bioRxiv2026

An early mTOR-dependent window during human T cell activation programs T cell state

T cell activation results in profound proteome remodeling that programs T cells into distinct cellular states. The mechanistic target of rapamycin (mTOR) biases T cell differentiation toward a cytotoxic fate at the expense of memory-precursor formation, making mTOR inhibition an attractive strategy to boost T cell memory during vaccination. Here, we used matched time-resolved mRNA sequencing and quantitative mass spectrometry to define how the human T cell proteome is remodeled during the first 24 hours of activation. We found that human T cells rapidly remodel their proteome in distinct, temporally ordered modules that drive translation and proliferation while promoting a cytotoxic T cell state. Notably, mTOR inhibition during the first 24 hours of T cell activation perturbed these protein modules. Strikingly, transient mTOR inhibition limited to the first 16 hours of T cell priming was sufficient to imprint a memory-like T cell state, while preserving the capacity to produce inflammatory cytokines and mediate target cell killing. Together, these findings indicate that mTOR activity dictates stable functional trajectories during early T cell activation, revealing a therapeutic window to refine vaccination responses.

immunology↗

bioRxiv2025

Mapping the dynamic RNA binding proteome in human effector T 1 cells identifies differentiation and cytotoxicity regulators

RNA-binding proteins (RBPs) are key regulators of T cell function by controlling (m)RNA fate and fine-tuning protein expression dynamics. Dysregulated RBPs can drive immune diseases and malignancies, highlighting their potential as therapeutic targets. To achieve this, a systematic analysis of the dynamic RBP-RNA interactions is required. Here, we mapped the RNA-binding proteome in human T cells and measured its alterations upon T cell activation using orthogonal organic phase separation (OOPS), analysed with PROMOGEB, a Bayesian linear regression model. This approach uncovered the intricate RNA-binding dynamics of the RBProteome. Gene-editing of such dynamic RNA binders revealed that TUT1 (Star-PAP) maintains the integrity of the T cell differentiation program, and that mutating SF3A1 enhanced the cytotoxic molecule expression and thus target cell killing. Our work provides the most comprehensive analysis of the effector T cell RBProteome to date and shows the potential of identifying RBPs and their binding dynamics as therapeutic agents. TeaserOOPS analysed with PROMOGEB maps RBP dynamics in human Teff cells, identifying TUT1 and SF3A1 as regulators of T cell fidelity.

immunology↗

bioRxiv2023

Gene and protein sequence features augment HLA class I ligand predictions

The sensitivity of malignant tissues to T cell-based cancer immunotherapies is dependent on the presence of targetable HLA class I ligands on the tumor cell surface. Peptide intrinsic factors, such as HLA class I affinity, likelihood of proteasomal processing, and transport into the ER lumen have all been established as determinants of HLA ligand presentation. However, the role of sequence features at the gene and protein level as determinants of epitope presentation has not been systematically evaluated. To address this, we performed HLA ligandome mass spectrometry on patient-derived melanoma lines and used this data-set to evaluate the contribution of 7,124 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turn-over, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of gene and protein sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as predictive models that include experimental measures of gene expression. Our study highlights the value of gene and protein features to HLA ligand predictions.

immunology↗

bioRxiv2023

Learning the sequence code for mRNA and protein abundance in human immune cells

Accurate protein expression in human immune cells is essential for appropriate cellular function. The mechanisms that define protein abundance are complex and executed on transcriptional, post-transcriptional and post-translational level. Here, we present SONAR, a machine learning pipeline that learns the endogenous sequence code and that defines protein abundance in human cells. SONAR uses thousands of sequence features (SFs) to predict up to 63% of the protein abundance independently of promoter or enhancer information. SONAR uncovered the cell type-specific and activation-dependent usage of SFs. The deep knowledge of SONAR provides a map of biologically active SFs, which can be leveraged to manipulate the amplitude, timing, and cell type-specificity of protein expression. SONAR informed on the design of enhancer sequences to boost T cell receptor expression and to potentiate T cell function. Beyond providing fundamental insights in the regulation of protein expression, our study thus offers novel means to improve therapeutic and biotechnology applications. One Sentence SummarySONAR informs the design of cell type-specific protein expression in human cells

cell biology↗

bioRxiv2023

A fluorescence-based sensor screen identifies MED12 as a potential microsatellite instability regulator in colon cancer

Inactivation of the DNA mismatch repair (MMR) system, due to (epi)genetic alterations of MMR genes, increases the frequency of mutations across the genome, creating a phenotype known as microsatellite instability (MSI). Cancers with this phenotype have been associated with a better prognosis for some time, but only since recently it has been recognised as a predictive biomarker of response to immunotherapy. Because MSI tumours accumulate more insertions and/or deletions in coding regions of the genome containing microsatellites, there is an increase in neoantigens resulting from reading frame shifts, which promotes immunogenicity. To investigate if additional genes exist that can cause an MSI phenotype, we developed a fluorescence-based sensor to identify genes whose inactivation increases the rate of frameshift mutations on microsatellite sequences in cancer cells. Using genome-scale CRISPR/Cas9 screens, we identified MED12 as a potential new regulator of microsatellite instability. Consistent with this, we found that MED12 mutant colon cancers that lack mutations in the known MMR genes are more likely to be of the MSI phenotype.

cancer biology↗