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Identification of multifunctional cytotoxic T-cell subsets as immune correlates with clinical outcomes in a phase II study of AGS-003, an autologous dendritic cell-based therapy administered to patients with newly diagnosed, metastatic RCC.

2012· article· en· W2586740931 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMacrophage Migration Inhibitory Factor
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsCTL*MedicineCluster of differentiationCytotoxic T cellImmune systemCD8T cellImmunologyCellBiology

Abstract

fetched live from OpenAlex

80 Background: AGS-003 is an autologous dendritic cell (DC) immunotherapy prepared from matured monocyte-derived DC co-electroporated with the subject’s own amplified tumor RNA and synthetic CD40L RNA. The mechanism of action (MOA) of AGS-003 was evaluated in combination with sunitinib for treatment of advanced renal cell carcinoma (RCC) in AGS-003-006, an open label phase II trial including subjects with newly diagnosed, unfavorable-risk, metastatic clear cell RCC. The goal of the immune monitoring platform is to identify unique cytotoxic T-cell (CTL) signatures that correlate with clinical outcome in subjects receiving AGS-003 in combination with sunitinib. Methods: Multiparametric flow cytometry was used to identify tumor-reactive CTL subsets induced by AGS-003 based on combinatorial expression patterns of surface markers CD28, CD45RA, CD27 and CCR7. Moreover, further partitioning of each CTL subset identified combinatorial expression patterns of Markers of Immune Function (MIFs) defined as cytokines (IFN-γ TNF-α, IL-2), cytolytic markers (Granzyme b, CD107) and proliferation. Correlates of CTL signatures with clinical outcome were analyzed using an adaptation of a binary tree-structured vector quantization (BTSVQ) approach, originally developed to cluster and visualize large microarray data sets. The BTSVQ approach implements a two-way unsupervised clustering that allows a subject’s CTL signature to be mapped based on both surface marker and MIFs expression patterns to identify unique clustering patterns linked to clinical outcome. Results: Data analysis identified a unique CTL signature (CD28 + /CCR7 + /CD45RA - phenotype) displaying a broad MIFs profile as a statistically significant correlate to PFS and OS in patients treated with AGS-003. Conclusions: These results support the intended MOA of AGS-003 in vivo, as the induction of anti-tumor central and effector memory CTL responses. These data warrant further immunological evaluation of AGS-003 in the randomized phase III ADAPT study using AGS-003 in combination with standard treatment in RCC subjects.

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.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.406
Teacher spread0.343 · 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