Biology subjects

Blanchette, C.

Publications and source records attributed to Blanchette, C..

5 recordsLinked to original sources

bioRxiv2025

Cross-competition shapes CD8+ T cell hierarchies and differentiation after RNA vaccination

Short SummaryImmunodominance is a universal feature of adaptive immunity that constrains T cell expansion, clonal diversity and breadth resulting in a narrowly focused T cell response. While observed across diverse priming settings and vaccine platforms, the influence of immunodominance on T cell phenotype remains unclear. Using an mRNA lipoplex vaccine encoding multiple antigens to study how immunodominance influences CD8+ T cell fate, we found that dominant CD8+ T cell responses alter the magnitude and phenotype of subdominant responses through peptide-MHC-I stability-mediated T cell cross-competition. Dominant CD8+ T cell responses preferentially acquired markers associated with terminal differentiation and cytotoxic function, while sub-dominant responses adopted memory-precursor and stem-like features. Removal of dominant responses allowed increased expansion of sub-dominant T cell responses and adoption of terminally differentiated effector phenotypes. These findings reveal that immunodominance dynamically shapes the magnitude, breadth and differentiation of CD8+ T cell responses and highlights opportunities to fine-tune T cell responses for therapeutic vaccination.

immunology↗

bioRxiv2022

HLApollo: A superior transformer model for pan-allelic peptide-MHC-I presentation prediction, with diverse negative coverage, deconvolution and protein language features.

Antigen presentation on MHC class I (MHC-I) is key to the adaptive immune response to cancerous cells. Computational prediction of peptide presentation by MHC-I has enabled individualized cancer immunotherapies. Here, we introduce HLApollo, a transformer-based approach with end-to-end modeling of MHC-I sequence, deconvolution, and flanking sequences. To achieve this, we develop a novel training strategy, negative set switching, which greatly reduces overfitting to falsely presumed negatives that are necessarily found in presentation datasets. HLApollo shows a meaningful improvement compared to recent MHC-I models on peptide presentation (20.19% average precision (AP)) and immunogenicity (4.1% AP). As expected, adding gene expression boosts the performance of HLApollo. More interestingly, we show that introduction of features from a protein language model, ESM 1b, remarkably recoups much of the benefits of gene expression in absence of true expression measurements. Finally, we demonstrate excellent pan-allelic generalization, and introduce a framework for estimating the expected accuracy of HLApollo for untrained alleles. This guides the use of HLApollo in a clinical setting, where rare alleles may be observed in some subjects, particularly for underrepresented minorities.

immunology↗

bioRxiv2022

Discovery of prevalent, clinically actionable tumor neoepitopes via integrated biochemical and cell-based platforms

Strategies for maximizing the potency and specificity of cancer immunotherapies have sparked efforts to identify recurrent epitopes presented in the context of defined tumor-associated neoantigens. Discovering these "neoepitopes" can be difficult owing to the limited number of peptides that arise from a single point mutation, a low number of copies presented on the cell surface, and variable binding specificity of the human leukocyte antigen (HLA) class I complex. Due to these limitations, many discovery efforts focus on identifying neoepitopes from a small number of cancer neoantigens in the context of few HLA alleles. Here we describe a systematic workflow to characterize binding and presentation of neoepitopes derived from 47 shared cancer neoantigens in the context of 15 HLA alleles. Through the development of a high-throughput neoepitope-HLA binding assay, we surveyed 24,149 candidate neoepitope-HLA combinations resulting in 587 stable complexes. These data were supplemented by computational prediction that identified an additional 257 neoepitope-HLA pairs, resulting in a total of 844 unique combinations. We used these results to build sensitive targeted mass spectrometry assays to validate neoepitope presentation on a panel of HLA-I monoallelic cell lines engineered to express neoantigens of interest as a single polypeptide. Altogether, our analyses detected 84 unique neoepitope-HLA pairs derived from 37 shared cancer neoantigens and presented across 12 HLA alleles. We subsequently identified multiple TCRs which specifically recognized two of these neoantigen-HLA combinations. Finally, these novel TCRs were utilized to elicit a T cell response suggesting that these neoepitopes are likely to be immunogenic. Together these data represent a validated, extensive resource of therapeutically relevant neoepitopes and the HLA context in which they can be targeted.

cancer biology↗

bioRxiv2020

Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

Advances in several key technologies, including MHC peptidomics, has helped fuel our understanding of basic immune regulatory mechanisms and identify T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. This multi-step analytical process remains challenging, and throughput and reproducibility are paramount for rapidly characterizing multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines, can be enriched in a semi-automated fashion on reusable, dry-storage, customized antibody cartridges. TOMAHAQ, a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation.

cancer biology↗

bioRxiv2018

Transposable Element Expression In Tumors Is Associated With Immune Infiltration And Increased Antigenicity

Profound loss of DNA methylation is a well-recognized hallmark of cancer. Given its role in silencing transposable elements (TEs), we hypothesized that extensive TE expression occurs in tumors with highly demethylated DNA. We developed REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observed increased expression of over 400 TE subfamilies, of which 262 appeared to result from a proximal loss of DNA methylation. The most recurrent TEs were among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent resulted in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing both inflammation and the display of potentially immunogenic neoantigens.\n\nOne Sentence SummaryTransposable element expression in tumors is associated with increased immune response and provides tumor-associated antigens

cancer biology↗