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An open-label, multicenter phase I/IIa study evaluating the safety and clinical activity of clonal neoantigen reactive T cells in patients with advanced non-small cell lung cancer (CHIRON).

2021· article· en· W3170764582 on OpenAlexaff
Mariam Jamal‐Hanjani, Alastair Greystoke, Fiona Thistlethwaite, Yvonne Summers, Jennifer Allison, Judith Cave, Kim Orchard, Christian H. Ottensmeier, Gary Middleton, Leila Khoja, Michael Grant, Shreenal Patel, Jane Robertson, Karl S. Peggs, Martin Förster

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineLung cancerCancerOncologyChemotherapyImmunotherapyImmunologyCancer researchInternal medicine

Abstract

fetched live from OpenAlex

TPS9138 Background: Lung cancer is the most common cause of cancer-related death worldwide with over 1.6 million deaths per year. Non-small cell lung cancer (NSCLC) accounts for 80% of cases, the majority of which are adenocarcinomas. 75% of patients present with inoperable tumours and/or with distant metastatic spread, with 5-year survival for stage IV disease as low as 5%. Treatment options include chemotherapy, targeted therapies for specific mutations, and - increasingly - immune checkpoint inhibitors (CPI). Adoptive cell therapies (ACT) can produce durable responses in pre-treated NSCLC. Evidence also suggests potential benefit of combining ACT with CPIs, even after acquired resistance. Efforts to improve efficacy include the expansion of T cells able to recognise patient-specific clonal tumour neoantigens. Clonal tumour neoantigens arise early in cancer evolution and represent a subset of patient-specific mutations present in all cancer cells. Developing ACTs that target clonal neoantigens represents a personalised approach to treating all cancer cells concurrently, minimising the risk of tumour escape and reducing potential for off-target toxicities. Insights gained from applying the PELEUS bioinformatic platform (developed using UK TRACERx study data) to matched tumour and blood samples from NSCLC patients – as part of a tissue acquisition study (NCT03517917) – has enabled the manufacture of a personalized clonal neoantigen-reactive T cell (cNeT) product (ATL001), which is now in clinical development. Methods: The CHIRON Study (NCT04032847), is a first-in-human, open-label, multi-centre, phase I/IIa study to characterise the safety and clinical activity of ATL001 administered intravenously in up to 40 adults with advanced unresectable or metastatic NSCLC. Following consent and screening, patients enter the study for procurement of tumor tissue and blood to manufacture ATL001. Tissue may be procured during treatment with standard systemic therapies. Patients in Cohort A receive cyclophosphamide/fludarabine on days -6 to -4, followed by a single dose of ATL001 and 10 daily doses of subcutaneous IL-2; Patients in Cohort B will additionally receive one dose of pembrolizumab between days -13 and -6 before receiving ATL001, then restart pembrolizumab 2 weeks after receiving ATL001 and continue for up to 12 months. Key eligibility criteria include treatment with at least one prior systemic therapy (including a PD-1 inhibitor). Primary endpoints are the safety and tolerability of ATL001 as a monotherapy and in combination with pembrolizumab. Secondary endpoints include change in tumor size and response rate by RECIST 1.1 and imRECIST. Correlative studies will investigate the effects of cNeT dose and engraftment kinetics on clinical activity. The study began enrolling patients in Cohort A in August 2019. Clinical trial information: NCT04032847.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.159
GPT teacher head0.566
Teacher spread0.407 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations5
Published2021
Admission routes1
Has abstractyes

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