T-cell clonality assessment constitutes an essential part of the diagnostic evaluation of suspected T-cell neoplasms. Recent advances in flow cytometry-based analysis of TCR β chain constant region 1 (TRBC1) have introduced an accurate method of assessment of T-cell clonality. Its broader applicability is constrained due to the requirement of viable cells. Furthermore, the utility of the TRBC1 antibody in tissue immunohistochemistry (IHC) has not been comprehensively addressed. Herein, we validated an IHC-based approach to assess T-cell clonality using formalin-fixed, paraffin-embedded (FFPE) tissue. Utilizing DeepLIIF image analysis, we quantified TRBC1 positivity among CD3-positive cells in a training cohort comprising 34 cases of alpha/beta T-cell neoplasms and 29 cases of reactive lymphoid tissue as controls. In an independent validation cohort comprising 29 T-cell neoplasms and 20 controls, similar image quantification was conducted by a pathologist uninvolved in the analysis of the training cohort and blinded to the diagnoses. Receiver operating characteristic (ROC) analysis of the training cohort established the optimal cut-off points for monotypic TRBC1 expression-79.0% or higher indicating monotypic positivity and 36.3% or lower denoting negativity. These thresholds demonstrated robust metrics in both the training (sensitivity 88.2%, specificity 93.1%, positive predictive value 93.8%, negative predictive value 87.1%) and the validation cohorts (sensitivity 93.1%, specificity 95.0%, positive predictive value 96.4%, negative predictive value 90.5%). TRBC1 IHC was correlated with flow cytometry in 52 cases, which demonstrated a strong quantitative correlation of TRBC1 positivity (r = 0.78, p < 0.001) and a high categorical agreement (85.9%) in classifying monotypic versus polytypic staining. Discrepancies in categorization were associated with low tumor percentages. Furthermore, multiplex immunofluorescence (MIF) was performed in 15 cases for targeted quantification of TRBC1 expression in CD3-positive, PAX5-negative cells, achieving a concordance of 86.7% with IHC. In summary, TRBC1 IHC offers a reliable and practical complementary method for assessing T-cell clonality.
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http://dx.doi.org/10.1016/j.modpat.2025.100725 | DOI Listing |
Mod Pathol
January 2025
Hematopathology Service, Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Electronic address:
T-cell clonality assessment constitutes an essential part of the diagnostic evaluation of suspected T-cell neoplasms. Recent advances in flow cytometry-based analysis of TCR β chain constant region 1 (TRBC1) have introduced an accurate method of assessment of T-cell clonality. Its broader applicability is constrained due to the requirement of viable cells.
View Article and Find Full Text PDFNat Immunol
January 2025
Department of Cardiology, Renji Hospital, School of Medicine, State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Shanghai Jiao Tong University, Shanghai, China.
A comprehensive understanding of the evolution of the immune landscape in humans across the entire lifespan at single-cell transcriptional and protein levels, during development, maturation and senescence is currently lacking. We recruited a total of 220 healthy volunteers from the Shanghai Pudong Cohort (NCT05206643), spanning 13 age groups from 0 to over 90 years, and profiled their peripheral immune cells through single-cell RNA-sequencing coupled with single T cell and B cell receptor sequencing, high-throughput mass cytometry, bulk RNA-sequencing and flow cytometry validation experiments. We revealed that T cells were the most strongly affected by age and experienced the most intensive rewiring in cell-cell interactions during specific age.
View Article and Find Full Text PDFSci Data
January 2025
The Mina & Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
The distinctive characteristics of an individual's T cell receptor repertoire are crucial in recognizing and responding to a diverse array of antigens, contributing to immune specificity and adaptability. The repertoire, famously vast due to a series of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire of 85 women: ovarian cancer patients (OC) and healthy donors (HD), generating a dataset of T cell clones and their abundance.
View Article and Find Full Text PDFNat Commun
January 2025
Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, Nantes, France.
Autoimmune liver diseases (AILD) involve dysregulated CD4 T cell responses against liver self-antigens, but how these autoreactive T cells relate to liver tissue pathology remains unclear. Here we perform single-cell transcriptomic and T cell receptor analyses of circulating, self-antigen-specific CD4 T cells from patients with AILD and identify a subset of liver-autoreactive CD4 T cells with a distinct B-helper transcriptional profile characterized by PD-1, TIGIT and HLA-DR expression. These cells share clonal relationships with expanded intrahepatic T cells and exhibit transcriptional signatures overlapping with tissue-resident T cells in chronically inflamed environments.
View Article and Find Full Text PDFBioinformatics
January 2025
School of Computer Science and engineering, Central South University, Changsha, 410083, China.
Motivation: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer immunotherapy, vaccine design, and autoimmune disease management. Understanding the intricate binding patterns between TCRs and peptides is critical for advancing these clinical applications. While several computational tools have been developed, they neglect the directional semantics inherent in sequence data, which are essential for accurately characterizing TCR-peptide interactions.
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