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Abstract B007: Phenotypic Signatures of Circulating Neoantigen-Reactive CD8+ T Cells in Patients with Metastatic Cancers

2023· article· en· W4389241392 on OpenAlexaboutno aff
Sri Krishna, Rami Yoseph, Sivasish Sindiri, Frank J. Lowery, Paul F. Robbins, Steven A. Rosenberg

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsCD8T-cell receptorCytotoxic T cellImmunotherapyT cellBiologyAntigenCancer immunotherapyImmunologyCirculating tumor cellCancer researchPhenotypeCancerImmune systemMetastasisGeneIn vitroGenetics

Abstract

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Abstract Background: Immunotherapies represent some of the most promising approaches to treat metastatic solid epithelial cancers, yet their response rates remain low. Identifying antitumor T cells, their antigenic specificities, and their cognate T cell receptors (TCRs) will provide crucial insights into the design of next-generation engineered cellular immunotherapies. Circulating T cells from the peripheral blood (PBL) can provide a rich and non-invasive source for identifying and studying antitumor T cells as an alternative to tumor-infiltrating lymphocytes (TIL). Yet, pre-immunotherapy pre-surgery antitumor T cell frequencies circulating in PBL of patients with metastatic cancer are often low, limiting the accurate definition of their phenotypic states. Methods: We employed single-cell phenotypic profiling of 36 experimentally defined neoantigen-specific T cell clones from 6 metastatic epithelial cancer patients to derive the transcriptional and cell surface protein signatures of pre-surgery PBL-resident antitumor CD8+ T cells (NeoTCRPBL). and compared T cell gene expression signatures neoantigen TCR clonotypes between the PBL and TIL compartments. We developed a NeoTCRPBL gene signature to assess its sensitivity and specificity in discovering new antitumor TCRs from PBL of prospective patients with different solid tumor types. Results: Circulating NeoTCRPBL T cells were clonally expanded, but low in frequency in the PBL (⇐0.001-0.005% per clone) necessitating prior-enrichment for studies. NeoTCRPBL T cells exhibited phenotypes distinct from common blood T cell subsets and bystander viral-reactive T cells displaying transcriptional programs of both dysfunctional as well as tissue-resident memory T cells. Within the same patient, intra-clonotype comparison of 24 TIL-and PBL-neoantigen-specific T cell clones revealed that relative to their TIL counterparts, circulating NeoTCRPBLT cells displayed less-dysfunctional immunotherapy-response associated progenitor phenotypic states. Combined analysis of 100 antitumor T cell clones revealed that circulating NeoTCRPBL T cells largely targeted the same clonal, subclonal neoantigens with comparable avidity as TIL (>79% shared), but their TCR-repertoire was only partially shared with TIL (47% shared). Finally, prediction and testing of 64 clonally expanded TCRs based on NeoTCRPBL gene expression signature-enrichment from prospective PBL samples discovered 20 neoantigen-TCR clonotypes suggesting that the NeoTCRPBL signature can successfully identify antitumor TCRs from very low circulating PBL frequencies(< 0.002%). Conclusions: Circulating PBL-resident antitumor T cells are low in frequency exhibiting distinct clonotypic repertoire and phenotypic states in patients with metastatic solid tumors. The NeoTCRPBL signature provides an alternative source for identifying antitumor T cells and their TCRs non-invasively from pre-surgery blood samples from cancer patients enabling immune monitoring and immunotherapies. Citation Format: Sri Krishna, Rami Yoseph, Sivasish Sindiri, Frank J Lowery, Paul F Robbins, Steven A Rosenberg. Phenotypic Signatures of Circulating Neoantigen-Reactive CD8+ T Cells in Patients with Metastatic Cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B007.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.065
GPT teacher head0.388
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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