Biology subjects

Lukyanov, D. K.

Publications and source records attributed to Lukyanov, D. K..

5 recordsLinked to original sources

bioRxiv2025

Discovery of rare antigen-specific TCRs via replicate profiling

Development of effective vaccines and targeted immunotherapies for cancer, autoimmunity, allergy, and infectious diseases requires comprehensive understanding of functionality and antigenic specificity of involved T cell clones. A major technical challenge remains the high-throughput identification of antigen-specific T cells. Here, we present a rapid cost-efficient TCR discovery assay starting from PBMC that enables ultra-sensitive discovery of clonal alpha-beta paired TCRs responding to individual or pooled peptides. In a small-scale experiment with a single donor, assay identified over 90 SARS-CoV-2-specific CD4+ and CD8+ TCR{beta} clonotypes, validated by clonal tracking and comparison against known SARS-CoV-2-specific TCRs. Positioning within the scRNA-Seq map revealed distinct helper T cell subsets involved in primary and secondary response. Further validation in a cohort of five donors identified nearly 1,000 CD4+ and CD8+ TCR clonotypes specific to viral and fungal peptide antigens. The assay demonstrated exceptional sensitivity in capturing low-frequency clones and allowed accurate TCR/TCR{beta} pairing, validated using single-cell transcriptomics. The ability to capture low-frequency antigen-specific TCRs, combined with detailed scRNA-Seq annotation, establishes an integrated pipeline that links antigen-responsive clones to their precise functional phenotypes. This platform provides a robust foundation for dissecting T cell roles in health and disease and accelerates the development of vaccines and immunotherapies.

immunology↗

bioRxiv2024

FCRL4 and exhausted B cell signature in tumor infiltrating B cells from lung cancer

Advances in high-dimensional flow cytometry and single-cell RNA sequencing (scRNA-seq) have enhanced our understanding of the heterogeneity of tumor-infiltrating B cells (TIBs). Subpopulations of TIBs exhibit diverse, sometimes opposing roles in tumor control, influenced by surface molecule, cytokine, and transcription factor expression. IgA and IgG expression in tumors have shown predictive value in melanoma and KRAS-mutated, but not KRAS wild-type, lung adenocarcinoma (LUAD). To investigate the functional differences between B cells producing these isotypes, we performed bulk transcriptome analysis of tumor-infiltrating surface-IgA+ (sIgA+) and sIgG+ memory B cells in LUAD. In LUAD, sIgA+ B cells overexpressed FCRL4, PDCD1, and RUNX2, suggesting an atypical chronically antigen-stimulated phenotype with features of exhaustion. Public scRNA-seq data revealed FCRL4-expressing TIBs as a distinct cluster with upregulation of genes involved in IFN{gamma} and IFN responses. sIgG+ B cells from LUAD overexpressed IL5RA, indicating a role for IL-5 in class-switch recombination to IgG. TCGA LUAD cohort analysis showed that the FCRL4/CD20 expression ratio correlates with lower survival, reinforcing FCRL4 as a marker of dysfunctional TIBs. Additionally, in renal cancer, high IGHA1/IGHG1 ratios were linked to worse survival. These findings suggest that the IgA/IgG ratio in tumors reflects not only the TME cytokine environment, but also functional differences in B cell populations, providing insights into their diverse roles in tumor progression.

immunology↗

bioRxiv2024

Splicing-aware resolution of scRNA-Seq data

Single-cell RNA sequencing (scRNA-Seq) provides invaluable insights in cell biology. Current scRNA-Seq analytic approaches do not distinguish between spliced and unspliced mRNA. RNA velocity paradigm suggests that the presence of unspliced mRNA reflects transitional cell states, informative for studies of dynamic processes such as embryogenesis or tissue regeneration. Alternatively, stable cell subsets may also maintain unspliced mRNA reservoirs for prompt initiation of transcription-independent expression. Based on the latter paradigm, we have developed a method called SANSARA (Splicing-Aware scrNa-Seq AppRoAch) for the splicing-aware analysis of scRNA-Seq data. We employed SANSARA to characterize peripheral blood regulatory T cell (Treg) subsets, revealing the complex interplay between FoxP3 and Helios master transcription factors and other unexpected splicing-informed features. For Th1 and cytotoxic CD4+ T cell subsets, SANSARA also revealed substantial splicing heterogeneity across crucial subset-specific genes. SANSARA is straightforward to implement in current data analysis pipelines and opens new dimensions in scRNA-Seq-based discoveries.

immunology↗

bioRxiv2023

Sort-Seq: immune repertoire-based scRNA-Seq systematization

The functional programs selected by CD4+ helper (Th) T cell clones fundamentally determine the architecture of the immune response to distinct challenges. Advances in scRNA-Seq have enhanced our understanding of the diversity of these programs, yet the correspondence between scRNA-Seq clusters and previously characterized Th subsets remains unclear. In this study, we use immune repertoires to position phenotypically sorted Th subsets within scRNA-Seq data from three healthy donors. This approach, termed TCR-Track, and accurately maps Th1, Th1-17, Th17, Th22, Th2a, Th2, Tfh, and Treg subsets, outperforming CITE-Seq-based mapping. Remarkably, the mapping is tightly focused on specific scRNA-Seq clusters despite a four-year interval between the sorting of subsets and the effector CD4+ scRNA-Seq experiment. Thus, while transient T cell plasticity is commonly observed in functionally active T cell populations, TCR-Track reveals high intrinsic program sustainability of Th clones circulating in peripheral blood. Repertoire overlap analysis at the scRNA-Seq level confirms that circulating Th1, Th2, Th2a, Th17, Th22, and Treg subsets are clonally independent. However, a prominent clonal overlap between corresponding clusters indicates that cytotoxic CD4+ T cells differentiate from Th1 clones. More specifically, we demonstrate that sorted CCR10+ Th cells correspond to a specific Th22 scRNA-Seq cluster, while CCR10-CCR6+CXCR3-CCR4+ cells, traditionally sorted as the Th17 subset, represent a mixture of bona fide Th17 and clonally unrelated CCR10low Th22 cells, which may have confounded investigators in previous studies. This clear distinction of Th17 and Th22 subsets should influence vaccine and T cell based therapies development. Additionally, we show that SARS-CoV-2 infection is associated with transient IFN type 1 activation of naive CD4+ T cells, and an increased proportion of effector IFN- induced Th cells is associated with a moderate course of the disease but remains low in critical COVID-19 cases. Using integrated scRNA-Seq, TCR-Track, and CITE-Seq data from 122 donors, we provide a comprehensive Th scRNA-Seq reference that should facilitate further investigation of Th subsets in fundamental and clinical studies.

immunology↗

bioRxiv2021

Accounting for B cell behaviour and sampling bias yields a superior predictor of anti-PD-L1 response in bladder cancer

Tumor-infiltrating B cells and intratumorally-produced immunoglobulins (IG) play important roles in the tumor microenvironment and response to immunotherapy1-5. IgG antibodies produced by intratumoral B cells may drive antibody-dependent cellular cytotoxicity (ADCC) and enhance antigen presentation by dendritic cells6-8. Furthermore, B cells are efficient antigen-specific antigen presenters that can essentially modulate the behaviour of helper T cells9-11. Here we investigated the role of intratumoral IG isotype and clonality in bladder cancer. Our results show that the IgG1/IgA ratio offers a strong and independent prognostic indicator for the Basal squamous molecular subtype and for the whole ImVigor210 cohort in anti-PD-L1 immunotherapy. Our findings also indicate that effector B cell functions, rather than clonally-produced antibodies, are involved in the antitumor response. High IgG1/IgA ratio was associated with relative abundance of cytotoxic genes and prominence of the IL-21/IL-21R axis suggesting importance of T cell/B cell interaction. We integrated the B, NK, and T cell components, employing immFocus-like normalization to account for the stochastic nature of tumor tissue sampling. Using a random forest model with nested cross-validation, we developed a tumor RNA-Seq-based predictor of anti-PD-L1 therapy response in muscle-invasive urothelial carcinoma. The resulting PRIMUS (PRedIctive MolecUlar Signature) predictor achieves superior sensitivity compared to PD-L1 expression scores or existing gene signatures, allowing for reliable identification of responders even within the desert patient subcohort analyzed as a hold out set.

immunology↗