Biology subjects

Nicolet, B.

Publications and source records attributed to Nicolet, B..

7 recordsLinked to original sources

bioRxiv2026

PAIR-Scan: Single-step identification of highly potent TCR-neoantigen pairs through library-on-library screening

Tumors contain a mixture of T cells with bystander reactivities and reactivities towards different, frequently patient-specific, cancer (neo)antigens. The one-step identification of highly active TCR-antigen pairs in human tumors would be valuable, both as a monitoring tool and to boost T cell reactivities of interest. Here, we develop PAIR-Scan, an HLA-agnostic library-on-library screening technology that identifies functionally active TCR-neoantigen pairs among tens of thousands of candidate pairs in a single step. We demonstrate the value of PAIR-Scan on a range of tumor samples and for the direct identification of TCR-recognized minimal peptides. In addition, we demonstrate that PAIR-Scan correctly ranks TCRs reactive to the same antigen by their relative tumor-killing efficiency. Together, these data demonstrate the value of PAIR-Scan for both the dissection of T cell responses in clinical samples and to generate large-scale datasets for the development of predictive models of TCR reactivity.

immunology↗

bioRxiv2026

Decoding translational control by cis-regulatory elements and RNA binding proteins in human effector T cells

T cells are central players in killing virally infected and malignant cells. To achieve this, T cells depend on dynamic, tightly regulated alterations of the proteome. To decipher the rules instructing translation in T cells, we performed transcriptome and proteome analysis of polysome fractions from human effector CD8+ T cells. Transcriptome analysis informed on ribosomal occupancy of RNAs and uncovered the rapid and RNA-specific redistribution upon T cell activation. With machine learning, we identified RNA binding motifs that predict the RNA (re)distribution among the polysome fractions. Using matched proteome analysis, we identified polysome-associated RBPs and their swift shuttling across polysome fractions upon T cell activation. Integrating sequence feature analysis with polysome RBP localization uncovered PTBP1 as a positive translation regulator, through its interactions with cis-regulatory elements in 3'UTRs of target mRNAs. In conclusion, the multi-level analysis presented here identifies rules of selective translation control which shape the T cell proteome.

immunology↗

bioRxiv2024

Tertiary lymphoid structure-related immune infiltrates in NSCLC tumor lesions correlate with low tumor-reactivity of TIL products

Adoptive transfer of tumor infiltrating lymphocytes (TIL therapy) has shown great potential for the treatment of solid cancers, including non-small cell lung cancer (NSCLC). However, not all patients benefit from this therapy, and the parameters that define the likelihood of TIL products to be tumor reactive are to date unknown. Defining prognostic markers that correlate with high level of tumor-reactivity is key for achieving better tailored immunotherapies. To determine whether the composition of immune cell infiltrates correlates with the tumor-reactivity of expanded TIL products, we employed multi-parameter flow cytometry to characterize the immune cell infiltrates from 26 early-stage, and 20 late-stage NSCLC tumor lesions. Unbiased flow cytometry analysis with Cytotree and Spearmans Rank Correlation was used to correlate immune infiltrates with the expansion rate, immune cell activation and T cell differentiation state, and the anti-tumor response of TIL products generated from the same lesions. The composition of tumor immune infiltrates was highly variable between patients, irrespective of the disease stage. High percentages of B cell infiltrates positively correlated with the presence of conventional CD4+ T cells, and an overall increase of naive T cell infiltrates. In contrast, high B cell infiltrates negatively correlated with the tumor-reactivity of expanded TIL products, as defined by cytokine production upon exposure to autologous tumor digest. Tumors with high B cell infiltrates contained IgD+BCL6+ B cells and CXCR5+BLC6+ CD4+ T cell infiltrates and an increased percentage of naive CD8+ T cells, indicative of the presence of tertiary lymphoid structures (TLS) in tumors with high B cell infiltrates. This study reveals that the composition of immune cell infiltrates in NSCLC tumors associates with the functionality of expanded TIL products from NSCLC tumor lesions. Importantly, the tumor-responsiveness of TIL products negatively correlated with the presence of TLS-associated immune infiltrates in tumors. Our finding may thus help improve patient selection for TIL therapy.

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

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

bioinformatics↗

bioRxiv2022

The two enantiomers of 2-hydroxyglutarate differentially regulate cytotoxic T cell function

2-hydroxyglutarate (2HG) is a by-product of the TCA cycle, and is readily detected in the tissues of healthy individuals. 2HG is found in two enantiomeric forms: S-2HG and R-2HG. Here, we investigate the differential roles of these two enantiomers in CD8+ T cell biology, where we found they had highly divergent effects on proliferation, differentiation, and T cell function. We show here an analysis of structural determinants that likely underlie these differential effects on specific a-ketoglutarate (aKG)-dependent enzymes. Treatment of CD8+ T cells with exogenous S-2HG, but not R-2HG, increased CD8+ T cell fitness in vivo, and enhanced anti-tumour activity. These data show that S-2HG and R-2HG should be considered as two distinct and important actors in the regulation of T cell function.

immunology↗

bioRxiv2021

Time-dependent regulation of cytokine production by RNA binding proteins defines T cell effector function

Potent T cell responses against infections and malignancies depend on the release of effector molecules, such as pro-inflammatory cytokines. Because effector molecules can be toxic, their production is tightly regulated through post-transcriptional events at 3 Untranslated Regions (3UTRs). RNA binding proteins (RBPs) were shown to be key regulators herein. With an RNA aptamer-based capture assay from human T cells, we identified >130 RBPs interacting with the IFNG, TNF and IL2 3UTRs in human T cells. T cell activation altered RBP-RNA interactions, revealing that RBP-target mRNA interactions rapidly respond to stimulation. Furthermore, we uncovered the intricate and time-dependent regulation of cytokine production by RBPs: whereas HuR supports early cytokine production, ZFP36L1, ATXN2L and ZC3HAV1 dampen and shorten the production duration, each at different time points. Strikingly, even though ZFP36L1 deletion did not phenotypically rescue T cell dysfunction in tumors, the increased production of cytokines and cytotoxic molecules resulted in superior anti-tumoral T cell responses in vivo. Our findings thus show that identifying RBP-RNA interactions reveals key modulators of T cell responses in health and disease.

immunology↗