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Record W4282940254 · doi:10.1158/1538-7445.am2022-819

Abstract 819: ERBB4 mediates IL10-induced growth of EGFR-independent colon tumors

2022· article· en· W4282940254 on OpenAlexaboutno aff
Michael P. McGill, Carolina Mantilla Rojas, David W. Threadgill

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsnot available
Fundersnot available
KeywordsERBB4Downregulation and upregulationErbBCancer researchColorectal cancerERBB3BiologyMedicineReceptorCancerInternal medicineEpidermal growth factor receptorReceptor tyrosine kinaseGeneGenetics

Abstract

fetched live from OpenAlex

Abstract ERBB4 is commonly over-expressed in human CRC, however the utility of ERBB4 as a target for colorectal cancer (CRC) therapeutics is largely unexplored. Our group recently identified a molecular subtype of CRC that arises independent of EGFR and displays a more aggressive growth phenotype than those dependent on EGFR. The robust growth phenotype of EGFR-independent tumors can be in part attributed to upregulation of IL10 signaling. In addition, EGFR-independent tumors display a significant upregulation of Erbb2 and Erbb4 transcripts in both spontaneous and sporadic CRC mouse models, perhaps compensating for the loss of EGFR. To investigate the importance of other ERBB receptors in EGFR-independent CRC tumor progression, we ablated Erbb4 to interrogate its influence on tumor development in vivo using a conditional allele of Erbb4tm1Fej (Erbb4f). ERBB4-deficient ApcMin/+ mice (ApcMin/+, ErbB4f/f, Tg(Vil1-Cre)) were established and used to show that ERBB4 ablation in the intestinal epithelia results in a significant decrease in the number of intestinal and colon tumors. Polyps lacking ERBB4 were also significantly reduced size, contrary to what is observed with loss of EGFR. We also recently developed ERBB2-deficient ApcMin/+ mice, and preliminary results suggest that Erbb2 ablation also results in a decrease in intestinal and colon tumor number and size. Consistent with data from EGFR-independent tumors, transcriptomic analysis of ERBB4-deficient intestinal tumors predicted down-regulation of IL10 signaling, which was validated through Il10 and Socs3 qPCR. To complement our findings, the observed down-regulation of Il10 and Socs3 at the transcript level corresponded with a significant decrease in IL10 levels in the serum of mice harboring ERBB4 deficient tumors when compared to mice without tumors. Furthermore, we found that transcript levels of Erbb4 significantly decreased after anti-IL10 treatment of EGFR-independent tumors in vivo. This illustrates a possible negative feedback loop whereby neutralizing IL10 also leads to a reduction of Erbb4 expression, further reducing IL10 signaling. Taken together, the data suggest that the absence of EGFR triggers Erbb4 upregulation, implicating an important role for ERBB4 in EGFR-independent colon tumor growth. These results suggest that therapeutic targeting of ERBB4 may lead to a reduction in IL10 signaling and reduced intestinal polyp multiplicity and size in EGFR-independent tumors and inform the development of novel approaches to treat CRC that exhibit aberrant expression of EGFR and ERBB4. Citation Format: Michael P. McGill, Carolina Mantilla Rojas, David W. Threadgill. ERBB4 mediates IL10-induced growth of EGFR-independent colon tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 819.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0040.002

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 head0.145
GPT teacher head0.460
Teacher spread0.315 · 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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