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Abstract A017: Multiple intratumoral sources of kit ligand promote oncogenic kit signaling in gastrointestinal stomal tumor

2022· article· en· W4295927922 on OpenAlexaboutno aff
Andrew Tieniber, Ferdinando Rossi, Andrew Hanna, Mengyuan Liu, Mark S. Etherington, Kevin Do, Laura Wang, Ronald P. DeMatteo

Bibliographic record

VenueClinical Cancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsGiSTCancer researchBiologyImatinibSarcomaReceptor tyrosine kinaseProto-Oncogene Proteins c-kitTyrosine kinaseStromal cellSignal transductionHaematopoiesisMedicinePathologyCell biologyStem cell factorStem cell

Abstract

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Abstract Introduction: Gastrointestinal stromal tumor (GIST) is the most common human sarcoma and is typically driven by a single mutation in the Kit receptor. While highly effective, tyrosine kinase inhibitors like imatinib are not curative. The natural ligand for the Kit receptor is Kit Ligand (KitL), which exists in both soluble and membrane-bound forms. We sought to determine the role of KitL in the oncogenic Kit signaling of GIST. Methods: KitV558Δ/+ mice, which spontaneously develop an intestinal GIST, were treated with imatinib or vehicle for 1 week, and sorted non-immune (CD45-) cells from tumors were submitted for single-cell RNA sequencing (n=3/group). GIST T1 cells were treated with KitL with or without imatinib and oncogenic Kit signaling was evaluated. KitV558Δ/+ mice were crossed with various KitL mutant and inducible models and tumor weights were measured (n=3-4/group). Human GISTs were stained for KitL expression by IHC, and an existing bulk RNA sequencing human GIST dataset with matched human serum was analyzed. Results: Unsupervised clustering revealed endothelial, smooth muscle, and tumor cells had high expression of KitL RNA in untreated tumors from KitV558Δ/+ mice. Imatinib therapy increased KitL RNA in all 3 cell types, suggesting that extra-tumoral KitL expression is dependent on oncogenic signaling (p<0.05). In GIST T1 cells, exogenous KitL increased Kit activation and reduced imatinib’s efficacy. Tumors from mice with homozygous KitL deletion (KitV558Δ/+;Etv1Cre-ERT2/+;KitLflox/flox) were smaller than tumors from littermates with heterozygous KitL deletion (KitV558Δ /+;Etv1Cre-ERT2/+;KitLflox/+), providing evidence that KitL contributes to GIST development in vivo despite the presence of mutated Kit (p<0.05). Furthermore, tumors from KitV558Δ/+;KitLKitL1Δ/KitL1Δ mice, which lack the proteolytic cleavage site for soluble KitL, were smaller than matched KitV558Δ/+ mice, indicating that soluble KitL is important for maximal tumor growth in vivo (p<0.05). Heterogeneous KitL expression was confirmed in human GISTs by IHC. Human serum contained more KitL in patients with tumors resistant to imatinib and in those with tumors expressing more KitL RNA(p<0.05). Conclusions: KitL is produced by multiple cell types within GIST and contributes to oncogenesis. Targeting KitL may be important for optimal tumor therapy. Citation Format: Andrew D. Tieniber, Ferdinando Rossi, Andrew Hanna, Mengyuan Liu, Mark Etherington, Kevin Do, Laura Wang, Ronald P. DeMatteo. Multiple intratumoral sources of kit ligand promote oncogenic kit signaling in gastrointestinal stomal tumor [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A017.

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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.179
GPT teacher head0.471
Teacher spread0.292 · 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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Citations0
Published2022
Admission routes1
Has abstractyes

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