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Record W2755822411 · doi:10.1530/erc-17-0316

Immune responses in the thyroid cancer microenvironment: making immunotherapy a possible mission

2017· review· en· W2755822411 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEndocrine Related Cancer · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Guelph
FundersOVC Pet TrustCanadian Institutes of Health ResearchTerry Fox Research InstituteMinistry of Agriculture, Food and Rural AffairsNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsImmunotherapyImmune systemTumor microenvironmentCancer immunotherapyThyroid cancerCancerMedicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

The incidence of thyroid cancers has been steadily increasing worldwide over the past few decades. Although five-year survival rates for differentiated thyroid cancers are upwards of 90%, clinical outcomes for patients with undifferentiated, recurrent and/or metastatic disease are often dismal despite conventional interventions. As such, there is a demand for novel treatment options. Cancer immunotherapy represents the ultimate form of personalized medicine by leveraging the specificity and potency of a patient's immune system to kill their tumor. The thyroid cancer microenvironment is rich in immunological cells, making it a reasonable candidate for immunotherapy. This review maps out the immunological features of thyroid cancers and how these can be modulated. There are surprising immunological consequences of conventional therapies that demand attention. Also, hormonal modulation of the immune system is highlighted as a unique and confounding feature of thyroid cancers. A variety of cutting-edge immune-based therapies are discussed, with an emphasis placed on how these can be integrated with the current standard of care. Several high priority areas in need of research are also highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.371
Teacher spread0.321 · 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