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Record W2943155654 · doi:10.1186/s40425-019-0542-z

Radiotherapy enhances responses of lung cancer to CTLA-4 blockade

2019· letter· en· W2943155654 on OpenAlexaff
Anna Wilkins, Fiona McDonald, Kevin J. Harrington, Alan Melcher

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2019
Typeletter
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsInstitute of Cancer Research
FundersNational Institute for Health and Care ResearchCancer Research UK
KeywordsAbscopal effectIpilimumabMedicineRadiation therapyImmunotherapyCTLA-4Immune systemLung cancerOncologyClinical trialBlockadeImmune checkpointBiological response modifiersImmunologyInternal medicineT cellReceptor

Abstract

fetched live from OpenAlex

Formenti et al. have recently reported the clinical outcomes and translational readouts of a trial of the anti-CTLA-4 inhibitor, ipilimumab, in combination with palliative radiotherapy in 39 patients with non-small cell lung cancer. A radiological response was seen in 18% of patients and 31% of patients experienced disease control. These clinical outcomes appear to be superior to historical studies using ipilimumab alone and suggest that radiation may have triggered systemic, so-called abscopal, immune responses in some patients. Induction of interferon-beta (IFN-β) and maximal expansion and contraction of distinct T cell receptor clones were the most significant factors predicting response. Importantly, established predictive biomarkers of response to immunotherapy alone, including the expression of PD-L1 in diagnostic biopsies and tumour mutational burden, did not predict response. The report provides important human qualification of pre-clinical mechanistic insights indicating that abscopal responses can be generated with optimised radiotherapy fractionation schedules and anti-CTLA-4 inhibition. Additionally, an intriguing mechanism by which radiation can be immunogenic is described, namely radiation-induced transcriptional upregulation of neo-antigens.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.366
Teacher spread0.346 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations26
Published2019
Admission routes1
Has abstractyes

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