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Record W2909575449 · doi:10.1002/path.5232

The immunological consequences of radiation‐induced DNA damage

2019· review· en· W2909575449 on OpenAlexfundno aff
Anna Wilkins, Emmanuel C. Patin, Kevin J. Harrington, Alan Melcher

Bibliographic record

VenueThe Journal of Pathology · 2019
Typereview
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsnot available
FundersInstitute of Cancer ResearchCancer Research UKNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchRoyal Marsden NHS Foundation Trust
KeywordsImmune systemDNA damageCancer researchBiologyStromal cellGenome instabilityStimulator of interferon genesAbscopal effectContext (archaeology)Radiation therapyTumor microenvironmentDNA repairImmunosuppressionInterferonImmunologyProgrammed cell deathImmunotherapyInnate immune systemApoptosisMedicineDNAGenetics

Abstract

fetched live from OpenAlex

Historically, our understanding of the cytotoxicity of radiation has centred on tumour cell-autonomous mechanisms of cell death. Here, tumour cell death occurs when a threshold number of radiation-induced non-reparable double-stranded DNA breaks is exceeded. However, in recent years, the importance of immune mechanisms of cell death has been increasingly recognised, as well as the impact of radiotherapy on non-malignant cellular components of the tumour microenvironment. Conserved antiviral pathways that detect foreign nucleic acid in the cytosol and drive downstream interferon (IFN) responses via the cyclic guanosine monophosphate-adenosine monophosphate synthase/stimulator of IFN genes (cGAS/STING) pathway are key components of the immune response to radiation-induced DNA damage. In preclinical models, acute induction of a type 1 IFN response is important for both direct and abscopal tumour responses to radiation. Inhibitors of the DNA damage response show promise in augmenting this inflammatory IFN response. However, a substantial proportion of tumours show chronic IFN signalling prior to radiotherapy, which paradoxically drives immunosuppression. This chronic IFN signalling leads to treatment resistance, and heterotypic interactions between stromal fibroblasts and tumour cells contribute to an aggressive tumour phenotype. The effect of radiotherapy on myeloid cell populations, particularly tumour-associated macrophages, has an additional impact on the immune tumour microenvironment. It is not yet clear how the above preclinical findings translate into a human context. Human tumours show greater intratumoural genomic heterogeneity and more variable levels of chromosomal instability than experimental murine models. High-quality translational studies of immunological changes occurring during radiotherapy that incorporate intrinsic tumour biology will enable a better understanding of the immunological consequences of radiation-induced DNA damage in patients. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.066
GPT teacher head0.339
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2019
Admission routes1
Has abstractyes

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