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Record W4290739163 · doi:10.3389/fendo.2022.927390

Insulin-like growth factor-1 signaling in the tumor microenvironment: Carcinogenesis, cancer drug resistance, and therapeutic potential

2022· review· en· W4290739163 on OpenAlexaff
Armel Hervé Nwabo Kamdje, Paul F. Seke Etet, Maulilio J. Kipanyula, Lorella Vecchio, Richard Simo Tagne, Alfred K. Njamnshi, Kiven Erique Lukong, Patrice N. Mimche

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typereview
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTumor microenvironmentCarcinogenesisCancer researchMetastasisCancerMedicineBiologyPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

The tumor microenvironment fuels tumorigenesis and induces the development of resistance to anticancer drugs. A growing number of reports support that the tumor microenvironment mediates these deleterious effects partly by overexpressing insulin-like growth factor 1 (IGF-1). IGF-1 is known for its role to support cancer progression and metastasis through the promotion of neovascularization in transforming tissues, and the promotion of the proliferation, maintenance and migration of malignant cells. Anti-IGF therapies showed potent anticancer effects and the ability to suppress cancer resistance to various chemotherapy drugs in in vivo and in vitro preclinical studies. However, high toxicity and resistance to these agents are increasingly being reported in clinical trials. We review data supporting the notion that tumor microenvironment mediates tumorigenesis partly through IGF-1 signaling pathway. We also discuss the therapeutic potential of IGF-1 receptor targeting, with special emphasis on the ability of IGF-R silencing to overcome chemotherapy drug resistance, as well as the challenges for clinical use of anti-IGF-1R therapies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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
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

Citations52
Published2022
Admission routes1
Has abstractyes

Explore more

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