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Pro‐Resolving Lipid Mediators and Anti‐Angiogenic Therapy Exhibit Synergistic Anti‐Tumor Activity via Resolvin Receptor Activation

2020· article· en· W3017210831 on OpenAlexaff
Victoria M. Hallisey, Franciele Kipper, Justin M. Moore, Allison Gartung, Diane R. Bielenberg, Jim Petrik, Jack Lawler, Dipak Panigrahy, Charles N. Serhan

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAngiogenesisCancer researchInflammationTumor microenvironmentReceptorCancerCancer cellChemistryBiologyImmunologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Inflammation and angiogenesis are interdependent hallmarks of cancer. Tumor growth is angiogenesis‐dependent and inflammation is a risk factor for many cancers. Inflammation is regulated by endogenous specialized pro‐resolving lipid‐autacoid mediators (SPMs), including resolvins, protectins, and maresins, which are present in multiple tissues. Unlike the majority of anti‐inflammatory agents, SPMs are non‐immunosuppressive, and non‐toxic. These lipid autacoids inhibit angiogenesis and clear cellular debris by macrophages resulting in reduced localized inflammatory cytokines. SPMs mediate their pro‐resolution and anti‐inflammatory activity through at least five known human G‐coupled protein receptors (GPR32, GPR18, ChemR23, GPR37, and LGR6) for resolvin (Rv) D1, RvD2, RvE1, protectin D1, and maresin 1, respectively, as well as a murine RvD1 receptor ALX/FPR2. We show that stimulating resolution of inflammation (RvD4 or RvD5) and anti‐angiogenic therapy (e.g. the thrombospondin (TSP)‐1 peptide 3TSR or anti‐VEGF via DC101) induced synergistic antitumor activity in human xenograft models including ovarian cancer (e.g. 36M2) compared with either treatment alone. The triple therapy 3TSR, anti‐VEGF, and resolvins displayed additive anti‐tumor activity. As the role of SPM receptors in cancer is unknown, we screened various stromal cells in the tumor microenvironment (e.g. macrophages, pericytes, fibroblasts, and neutrophils) for expression of SPM receptors. SPM receptors were expressed in various clinical specimens including breast cancer, head and neck cancer (e.g. oral squamous cell carcinoma), and brain cancer. Flow cytometry and double immunohistochemistry staining confirmed that SPM receptors were expressed in non‐tumor cells in the tumor microenvironment (e.g. macrophages, fibroblasts, pericytes and blood vessels) in vivo. Accordingly, SPMs inhibited tumor cell proliferation in vivo. Thus, SPMs exhibit anti‐tumor activity via the tumor stroma. Loss of SPM receptor expression may be associated with cancer progression in clinical cancer specimens. Notably, resolvins (RvD4 or RvD5) inhibited tumor growth at doses 10,000 times lower than anti‐inflammatory agents such as aspirin and NSAIDs. Thus, stimulating the expression or activity of SPM receptors may enhance current anti‐angiogenic therapy for various cancers.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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 designBench or experimental
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".

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Citations4
Published2020
Admission routes1
Has abstractyes

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