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Abstract PR10: Disruption of IL6-mediated paracrine signaling to prevent pulmonary metastasis

2020· article· en· W3047029284 on OpenAlexaboutno aff
John Hinckley, Amy C. Gross, Ryan D. Roberts

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsParacrine signallingAutocrine signallingLungCancer researchInterleukin 8BiologyMetastasisCellCell biologyMedicineReceptorImmunologyCytokineInternal medicineCancer

Abstract

fetched live from OpenAlex

Abstract Outcomes for patients diagnosed with osteosarcoma (OS) hinge primarily on whether or not they develop pulmonary metastasis. Looking to identify novel opportunities for therapeutic intervention, we have sought mechanisms that facilitate colonization of lung tissues by osteosarcoma cells. We have shown that metastatic colonization of lung by OS cells requires their IL6 and CXCL8 production, which is elicited upon the interaction of OS cells with lung tissues. The lung-derived signals that trigger this behavior and the effector mechanisms by which IL6 and CXCL8 facilitate metastatic colonization remain unknown. Here, we hypothesized that the interaction of OS cells lung epithelium triggers production of cytokines that establish paracrine signal amplification loops. We postulated that OS cell-derived IL6 and CXCL8 stimulate lung-resident cells to produce secondary signaling molecules that are, in turn, capable of stimulating OS cells. If our paracrine loop hypothesis is correct, we would expect that these lung cell-derived factors elicit further production of IL6 and CXCL8, resulting in a feed-forward paracrine signaling. Our lab has shown that soluble factors produced by lung epithelium profoundly increase IL6 and CXCL8 production by OS cells. In order to identify the specific factors responsible for this effect, we used RNA-seq to identify soluble ligands produced by lung epithelial cells that could activate cognate receptors produced by OS cells. Epithelial cell production of a subset of these soluble ligands increased when cells were exposed to supernatants from OS cells. We then performed a similar analysis using single-cell RNA-seq in mouse lungs bearing metastatic OS tumors, which identified many of the same ligands and receptors. Eleven candidate epithelial-to-tumor ligand-receptor interactions were identified in both the in vitro and the in vivo analysis. Interpreting these results in the context of prior known biology, one of these factors, IL-1, stood out as a prime candidate for a lung-to-tumor signal that would elicit IL6 and CXCL8 production in disseminated OS cells. We have since shown that IL-1 is upregulated in lung cells upon interaction with OS cells, that the cognate receptor IL1R1 is increased on OS cells following exposure to lung cell conditioned media, and that stimulation of OS cells with IL-1β drastically increases production of both IL6 and CXCL8. We have also verified production of IL-1α/β in lung epithelial cells and are working to confirm these findings in additional human-derived lung cell models. Our results suggest that this lung cell-tumor cell paracrine loop may play a mechanistic role in the colonization of lung tissue by OS. If true, the therapeutic effects of inhibiting this imminently targetable pathway on OS lung metastasis should be explored. Such studies are currently under way. This abstract is also being presented as Poster A61. Citation Format: John Hinckley, Amy Gross, Ryan Roberts. Disruption of IL6-mediated paracrine signaling to prevent pulmonary metastasis [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr PR10.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.028
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.175
GPT teacher head0.445
Teacher spread0.270 · 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 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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Citations0
Published2020
Admission routes1
Has abstractyes

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