Abstract A008: Adaptive immune receptor repertoire characterization highlights the importance of interplay between B and T cells in disease progression
Bibliographic record
Abstract
Abstract Understanding the adaptive immune system is integral to disease progression studies, development of diagnostic biomarkers, identification of therapeutic targets, and discerning varied treatment responses. Despite growing interest in profiling B and T cells in cancer research, the interaction between these cells and also the crucial roles of γδ T cells often go overlooked. In this research project, we explored the role of crucial yet frequently ignored γδ T cells in cancer research, using immune repertoire data from bladder cancer patients. We also studied the synergy between B and T cells in the immune repertoires of COVID-19 patients.Roche has developed immunoPETE (immune repertoire Primer Extension Target Enrichment), a DNA- based target enrichment assay to capture adaptive immune repertoire data*. immunoPETE efficiently identifies the heavy chains of B cells, alongside αβ and γδ T cells in one reaction, facilitating normalized clone counts across the adaptive immune system. To explore the significance of γδ T cells, we profiled the immune repertoires of 24 Non-Muscle Invasive Bladder Cancer patients treated with Bacillus Calmette-Guerin (BCG). Additionally, we evaluated the interplay between B and T cells in 117 peripheral blood immune repertoire from healthy and COVID-19 afflicted individuals, ranging from mild to severe cases.Immune repertoire data analysis indicates that underrepresentation of T cell receptor delta locus (TRD) is associated with higher risk of bladder cancer recurrence or progress. Urine pellet DNA was available for a subset of the patients in this study. Comparing immune repertoires from PBMC and urine revealed that urine repertoires represent the tumor repertoire more accurately than PBMC. Analysis of the immune repertoires from the COVID-19 patients linked disease severity with immune repertoire measures across all three cell types, highlighting the importance of multiple lymphocyte classes in disease progression. Using immunoPETE technology, which is capable of capturing the heavy chain of multiple immune cell types simultaneously in a single reaction, we have demonstrated that both B cell and T cell compartments provide distinct and valuable information in cancer and infectious diseases, each responding uniquely to the disease. Additionally, we emphasized the significance of γδ T cells in predicting cancer prognosis. Note: immunoPETE is for Research Use Only. Not for use in diagnostic procedures. Citation Format: Hossein Asgharian, Hamid Mirebrahim, Dilduz Telman, Hahn Zhao, Ulrich Schlecht, Sylvie McNamara, Rajiv Dua, Jan Berka, Patrick Bogard, Dinesh Kumar. Adaptive immune receptor repertoire characterization highlights the importance of interplay between B and T cells in disease progression [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A008.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".